3kilos BTC 15mThe "3kilos BTC 15m" is a comprehensive trading strategy designed to work on a 15-minute timeframe for Bitcoin (BTC) or other cryptocurrencies. This strategy combines multiple indicators, including Triple Exponential Moving Averages (TEMA), Average True Range (ATR), and Heikin-Ashi candlesticks, to generate buy and sell signals. It also incorporates risk management features like take profit and stop loss.
Indicators
Triple Exponential Moving Averages (TEMA): Three TEMA lines are used with different lengths and sources:
Short TEMA (Red) based on highs
Long TEMA 1 (Blue) based on lows
Long TEMA 2 (Green) based on closing prices
Average True Range (ATR): Custom ATR calculation with EMA smoothing is used for volatility measurement.
Supertrend: Calculated using ATR and a multiplier to determine the trend direction.
Simple Moving Average (SMA): Applied to the short TEMA to smooth out its values.
Heikin-Ashi Close: Used for additional trend confirmation.
Entry & Exit Conditions
Long Entry: Triggered when the short TEMA is above both long TEMA lines, the Supertrend is bullish, the short TEMA is above its SMA, and the Heikin-Ashi close is higher than the previous close.
Short Entry: Triggered when the short TEMA is below both long TEMA lines, the Supertrend is bearish, the short TEMA is below its SMA, and the Heikin-Ashi close is lower than the previous close.
Take Profit and Stop Loss: Both are calculated as a percentage of the entry price, and they are set for both long and short positions.
Risk Management
Take Profit: Set at 1% above the entry price for long positions and 1% below for short positions.
Stop Loss: Set at 3% below the entry price for long positions and 3% above for short positions.
Commission and Pyramiding
Commission: A 0.07% commission is accounted for in the strategy.
Pyramiding: The strategy does not allow pyramiding.
Note
This strategy is designed for educational purposes and should not be considered as financial advice. Always do your own research and consider consulting a financial advisor before engaging in trading.
Cerca negli script per "stop loss"
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
JS-TechTrading: Supertrend-Strategy_Basic versionAre you looking for a reliable and profitable algorithmic trading strategy for TradingView? If so, you might be interested in our Supertrend basic strategy, which is based on three powerful indicators: Supertrend (ATR), RSI and EMA.
Supertrend is a trend-following indicator that helps you identify the direction and strength of the market. It also gives you clear signals for entry and exit points based on price movements.
RSI is a momentum indicator that measures the speed and change of price movements. It helps you filter out false signals and avoid overbought or oversold conditions.
EMA is a moving average indicator that smooths out price fluctuations and shows you the long-term trend of the market. It helps you confirm the validity of your trades and avoid trading against the trend.
Our Supertrend basic strategy combines these three indicators to give you a simple yet effective way to trade any market. Here's how it works:
- For long trades, you enter when the price is above Supertrend and pulls back below it (the low of the candle crosses Supertrend) and then rebounds above it (the high of the next candle goes above the pullback candle). You exit when the price closes below Supertrend or when you reach your target profit or stop loss.
- For short trades, you enter when the price is below Supertrend and pulls back above it (the high of the candle crosses Supertrend) and then drops below it (the low of the next candle goes below the pullback candle). You exit when the price closes above Supertrend or when you reach your target profit or stop loss.
- You can also use RSI and EMA filters to improve your results. For long trades, you only enter if RSI is above 50 and price is above 200 EMA. For short trades, you only enter if RSI is below 50 and price is below 200 EMA.
- You can set your stop loss and target profit as a percentage of your entry price or based on other criteria. You can also adjust the parameters of each indicator according to your preferences and risk tolerance.
Our Supertrend basic strategy is easy to use and has been tested on various markets and time frames. It can help you capture consistent profits while minimizing your losses.
*Backtesting System ⚉ ＯＶＥＲＶＩＥＷ ⚉
One of the best Systems for Backtesting your Strategies.
Incredibly flexible, simple, fast and feature-rich system — will solve most of your queries without much effort.
Many systems for setting StopLoss, TakeProfit, Risk Management and advanced Filters.
All you need to do is plug in your indicator and start Backtesting .
I intentionally left the option to use my System on Full Power before you load your indicator into it.
The system uses the built-in simple and popular moving average crossover signal for this purpose. (EMA 50 & 200).
Also Highly Recommend that you Fully use ALL of the features of this system so that you understand how they work before you ask questions.
Also tried to leave TIPS for each feature everywhere, read Tips, activate them and see how they work.
But before you use this system, I Recommend you to read the following description in Full.
—————— How to connect your indicator in 2 steps:
Adapt your indicator by adding only 2 lines of code and then connect it to this Backtesting System.
Step 1 — Create your connector, For doing so:
• 1 — Find or create in your indicator where are the conditions printing the Long-Buy and Short-Sell signals.
• 2 — Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator wether it's a MACD, RSI , Pivots, or whatever indicator with Clear Buy and Sell conditions.
//@version=5
indicator('Moving Average Cross', overlay = true)
MA200 = ta.𝚎𝚖𝚊(close, 200)
MA50 = ta.𝚎𝚖𝚊(close, 50)
// Generate Buy and Sell conditions
buy = ta.crossover (MA200, MA50)
sell = ta.crossunder (MA200, MA50)
plot(MA200, color=color.green)
plot(MA50 , color=color.red )
bgcolor(color = buy ? color.green : sell ? color.red : na, title='SIGNALS')
// ———————————————— SIGNAL FOR SYSTEM ————————————————
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, title='🔌Connector🔌', display = display.none)
// —————— 🔥 The Backtesting System expects the value to be exactly +1 for the 𝚋𝚞𝚕𝚕𝚒𝚜𝚑 signal, and -1 for the 𝚋𝚎𝚊𝚛𝚒𝚜𝚑 signal
Basically, I identified my Buy & Sell conditions in the code and added this at the bottom of my indicator code
Now you can connect your indicator to the Backtesting System using the Step 2
Step 2 — Connect the connector
• 1 — Add your updated indicator to a TradingView chart and Add the Backtesting System as well to the SAME chart
• 2 — Open the Backtesting System settings and in the External Source field select your 🔌Connector🔌 (which comes from your indicator)
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𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐒𝐨𝐮𝐫𝐜𝐞 — Select your indicator. Add your indicator by following the 2 steps described above and select it in the menu. To familiarize yourself with the system until you select your indicator, you will have an in-built strategy of crossing the two moving EMA's of 50 and 200.
Long Deals — Enable/Disable Long Deals.
Short Deals — Enable/Disable Short Deals.
Wait End Deal — Enable/Disable waiting for a trade to close at Stop Loss/Take Profit. Until the trade closes on the Stop Loss or Take Profit, no new trade will open.
Reverse Deals — To force the opening of a trade in the opposite direction.
ReEntry Deal — Automatically open the same new deal after the deal is closed.
ReOpen Deal — Reopen the trade if the same signal is received. For example, if you are already in the long and a new signal is received in the long, the trade will reopen. * Does not work if Wait End Deal is enabled.
𝐓𝐚𝐤𝐞 𝐏𝐫𝐨𝐟𝐢𝐭:
None — Disables take profit. Useful if you only want to use dynamic stoplosses such as MA, Fast-Trailing, ATR Trail.
FIXED ％ — Fixed take profit in percent.
FIXED ＄ — Fixed Take in Money.
ATR — Fixed Take based on ATR.
R:R — Fixed Take based on the size of your stop loss. For example, if your stop is 10% and R:R=1, then the Take would be 10%. R:R=3 Take would be 30%, etc.
HH / LL — Fixed Take based on the previous maximum/minimum (extremum).
𝐒𝐭𝐨𝐩 𝐋𝐨𝐬𝐬:
None — Disables Stop Loss. Useful if you want to work without a stop loss. *Be careful if Wait End Deal is enabled, the trade may not close for a long time until it reaches the Take.
FIXED ％ — Fixed Stop in percent.
FIXED ＄ — Fixed Stop in Money.
TRAILING — Dynamic Trailing Stop like on the stock exchanges.
FAST TRAIL — Dynamic Fast Trailing Stop moves immediately in profit and stays in place if the price stands still or the price moves in loss.
ATR — Fixed Stop based on the ATR.
ATR TRAIL — Dynamic Trailing Stop based on the ATR.
LO / HI — A Fixed Stop based on the last Maximum/Minimum extemum. Allows you to place a stop just behind or above the low/high candle.
MA — Dynamic Stop based on selected Moving Average. * You will have 8 types of MA (EMA, SMA, HMA, etc.) to choose from, but you can easily add dozens of other MAs, which makes this type of stop incredibly flexible.
Add ％ — If true, then with the "𝗦𝘁𝗼𝗽 ％" parameter you can add percentages to any of the current SL. Can be especially useful when using Stop - 𝗔𝗧𝗥 or 𝗠𝗔 or 𝗟𝗢/𝗛𝗜. For example with 𝗟𝗢/𝗛𝗜 to put a stop for the last High/Low and add 0.5% additional Stoploss.
Fixed R:R — If the stop loss is Dynamic (Trailing or MA) then if R:R true can also be made Dynamic * Use it carefully, the function is experimental.
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A unique method of constructing intermediate Take Profit Levels will allow you to select up to 5 intermediate Take Profit Levels and one intermediate Stop Loss.
Intermediate Take Profit Levels are perfectly calculated into 5 equal parts in the form of levels from the entry point to the final Take Profit target.
All you need to do is to choose the necessary levels for fixing and how much you want to fix at each level as a percentage. For example, TP 3 will always be exactly between the entry point and the Take Profit target. And the value of TP 3 = 50 will close 50% of the amount of the remaining size of the position.
Note: all intermediate SL/TP are closed from the remaining position amount and not from the initial position size, as TV does by default.
SL 0 Position — works in the same way as TP 1-5 but it's Stop. With this parameter you can set the position where the intermediate stop will be set.
Breakeven on TP — When activated, it allows you to put the stop loss at Breakeven after the selected TP is reached. For this function to work as it should - you need to activate an intermediate Take. For example, if TP 3 is activated and Breakeven on TP = 3, then after the price reaches this level, the Stop loss will go to Breakeven.
* This function will not work with Dynamic Stoplosses, because it simply does not make sense.
CoolDown # Bars — When activated, allows you to add a delay before a new trade is opened. A new trade after CoolDown will not be opened until # bars pass and a new signal appears.
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Powerful time filter code that allows you to filter data based on specific time zones, dates, and session days. This code is ideal for those who need to analyze data from different time zones and weed out irrelevant data.
With Time Filter, you can easily set the starting and ending time zones by which you want to filter the data.
You can also set a start and end date for your data and choose which days of the week to include in the analysis. In addition, you can specify start and end times for a specific session, allowing you to focus your analysis on specific time periods.
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Signal Filters — allows you to easily customize and optimize your trading strategies based on 10 filters.
Each filter is designed to help you weed out inaccurate signals to minimize your risks.
Let's take a look at their features:
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Risk management tools that allow you to set the maximum number of losing trades in a row, a limit on the number of trades per day or week and other filters.
Loss Streak — Set Max number of consecutive loss trades.
Win Streak — Max Winning Streak Length.
Row Loss InDay — Max of consecutive days with a loss in a row.
DrawDown ％ — Max DrawDown (in % of strategy equity).
InDay Loss ％ — Set Max Intraday Loss.
Daily Trades — Limit the number of MAX trades per day.
Weekly Trades — Limit the number of MAX trades per week.
* 🡅 I would Not Recommend using these functions without understanding how they work.
Order Size — Position Size
• NONE — Use the default position size settings in Tab "Properties".
• EQUITY — The amount of the allowed position as a percentage of the initial capital.
• Use Net Profit — On/Off the use of profit in the following trades. *Only works if the type is EQUITY.
• SIZE — The size of the allowed position in monetary terms.
• Contracts — The size of the allowed position in the contracts. 1 Сontract = Сurrent price.
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It is important to note that I have never worked with Backtesting and the functions associated with them before.
It took me about a month of slow work to build this system.
I want to say Big Thanks:
• The PineScripters🌲 group, the guys suggested how to implement some features. Especially @allanster
• Thanks to all those people who share their developments for free on TV and not only.
• I also thank myself for not giving up and finishing the project, and not trying to monetize the system by selling it. * Although I really want the money :)
I tried hard to make it as fast and convenient as possible for everyone who will use my code.
That's why I didn't use any libraries and dozens of heavy functions, and I managed to fit in 8+-functions for the whole code.
Absolutely every block of code I tried to make full-fledged modular, that it was easy to import/edit for myself (you).
I have abused the Ternary Pine operator a little (a lot) so that the code was as compact as possible.
Nevertheless, I tried very hard to keep my code very understandable even for beginners.
At last I managed to write 500 lines of code, making it one of the fastest and most feature-rich systems out there.
I hope everyone enjoys my work.
Put comments and write likes.
OnePunch Algo KITEIntroducing One of OnePunch ALGO Flagship plugin. In this plugin it comes with a in-built risk management system plus it allows users stop loss input per trade. This can be used with Cryptocurrency and Stocks equally.
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########## User Guide ###########
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OnePunch ALGO KITE should be used with 30min or upper time limits, this is built for long term trading strategies. Make sure once you pick a crypto or stock to trade, check its backtest data: which can be found at Strategy Tester. A good strategy should always out perform the Buy & Hold for a given timeframe.
Best Bar Time: 45m
Other Options
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Short Term/Day Trading Setup
For Short Term or Day Trade: 5min, 15min & 30min candlesticks
Mid Term Trading Setup
For Mid-term traders: 45m, 1hr, 2hr, and 3hr setup works really well.
For Long Term Trading Setup
For long term traders: 4hr, 1D, 1Week and 1Month Setup works well.
* Best timeframe should beat buy and hold for a given timeline.
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####### How Strategy Work ########
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Strategy use multiple signals and technical data. Including and not limited to Simple Moving Averages, Volume , & Trends. In this chart, we picked Polkadot (DOTUSD) crypto coin as an example with an initial capital of $1k. We have also added a slippage of 1 just to be on the safe side and a commission rate of 0.01% (Commission rates depends of your broker).
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######## Built with Inputs #########
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Date Pick: User can backtest the plugin with exact date you want from to till. For an example, you can check date from 01 / 01 /2020 (Default setting date) till day, and compare apple to apple results with other stocks. This is mostly used to check if another stock/crypto do better than the other compared to a given timeframe.
Risk Management per Trade: This also allows users to put their own risk management loss percentage. In default it is set to 100%. This allows user to see in the long run, if this provide better results with or without a stop loss.
Commission Rates: User can update commission rates according to their broker's fees
Slippage: To be more conservative about the entry and exit of a trade, user can input any slippage amount
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#### How to Detect BUY Signals #####
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When a teal color BUY signal is given, it is a BUY. This signal basically happen when a stock land in a high volatility zone. We use in-build systems such as MA , Support and Resistance and Trends to come up with the Buy Signal. Algorithm make a market order when the criteria's are met and algorithm exit if this turns out to be a bluff bullish signal.
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#### How to Detect SELL Signals #####
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When a maroon color SELL signal is given, it is a SELL happen when a momentum changed in a bearish downtrend. Sell happen when a momentum changed in a bearish downtrend. We use moving averages and trend analysis to identify downtrends. Algorithm make a market order when the criteria's are met. There is a in-built risk management that make an exit order when a bullish alert turns out to be a bluff.
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#### Bullish and Bearish Signals #####
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When a silver color Bearish signal is given, it is a BEARISH trend alert. It's up to the user to decide what to do when this alert is given. (Note: Backtest data only shows Buy and Sell Signal market orders results, it does not account bearish alerts), a Bearish signal given when the stock/crypto is overbought in multiple technical indicators.
When a sea blue Bullish trend signaled. (Mind this sea blue color signal will not be calculated in the backtest, it is up to the users to decide what to do with this bullish signal) - This signal happen when a stock is oversold in multiple technical indicators.
DISCLAIMER: Stocks and options trading involves substantial RISK of LOSS and is NOT suitable for every investor. The valuation of stocks and options may fluctuate, and, as a result, clients may lose more than their original investment. If the market moves against you, you may sustain a total loss greater than the amount you deposited into your account. You are responsible for all the risks and financial resources you use and for the chosen trading system. You should not engage in trading unless you fully understand the nature of the transactions you are entering into and the extent of your exposure to loss. If you do not fully understand these risks, you must seek independent advice from your financial advisor.
All trading strategies are used at your own risk. And OnePunch ALGO Developer does NOT take any responsibility for your losses using any of the advice or suggestions or strategies are shown/said in any of OnePunch ALGO publications.
Dankland Playground Moneymaker - V2“version 2” of my playground bot script. Its essentially a powerhouse suite of strategies. Although it is similar to the previous script, it nets different results as sections have been changed. Such as the somewhat reluctant removal of the Chande Momentum... The RSIs have also been updated, this was one of the main changes. RSIS now include a Moving Average cross of RSI to generate signals above and below the given thresholds instead of simply on crossing a threshold. This should give greater functionality overall. Most functions including Moving Averages have been updated to include a wider range of kinds of moving averages. This includes not just the moving average cross, but MACD and RSIs as well. I tried to perform the same upgrade on the %B, Stochastics and SMI, but hit the unpacked code limit of 60,000 lines... So, more “versions” will have to come for future “upgrades”, with the recognition that there will be cases where the old, “downgraded” versions may perform better and that some people (like myself) may continue to use them on some markets until I/we devise superior settings on the new ones for said markets. For instance, instead of replacing my 1 hr BTCUSD bot (where I used the now deleted Chande to pretty pleasing affect...) I made a new one for LINKUSD 10 min so I can have both running for now and work on replacing the BTCUSD later.
How it works basically is this... you have 16 oscillators which can all be used as independently as you wish. They can be split up into different groups or ran all together.
When in separate groups they should not be able to sell eachothers positions without triggering a full stop loss by turning the Independence/Stop All switches on. Every single oscillator has its own entry and exit position sizing which can be stated as either a percent of balance or a flat amount of contracts (or both combined). Each oscillator has a minimum amount of profit you can tell it to sell it, which is calculated from the average cost of your current position, which does include all groups. This works out to help you average out better entry and exit prices, essentially a method of DCAing.
You can set the minimum sale amount, which is to keep it from placing orders below your exchanges minimum dollar trade cost.
All this functionality combined also ensures more accurate back tests by ensuring that the script simply cannot spend money it doesn't see as in the balance, whereas other scripts will use a percentage of equity, and once 100% of your equity is in BTC for instance, it will keep buying more BTC for free and thus spoof up backtest numbers. If you look through the strategies here, many people claim to have amazing scripts and then you look into it and this is happening and skewing their numbers. These people are either very ignorant or what they made or scam artists and trolls in my opinion.
This version also includes On Bar Close switches for each oscillator. When switched on, signals are only allowed to generate on Bar Close. This helps to prevent retriggering from live signals, which when you are running this many oscillators, will become a problem! However, in most cases, you do not need to generate signals intrabar, as backtests will show, ignoring intrabar buys and sells (intrabar stop losses can still be very important though!) won't exactly keep you from high profitability strategies, but rather, allowing elements of chaos from live indicators moving up and down intrabar will, in fact, drift your actual results further and further from the backtest. You want an accurate backtest though. So choose wisely when you turn these off and you will do better.
The included oscillators are as follows:
NO MORE Chande Momentum cross – REMOVED – I was hitting PINE code limits here so I had to make choices and this one simply had to go. Begone!
Moving Average Cross
MACD cross
%B Bollinger cross
Stochastic cross + region filter
Stochastic RSI cross + region filter
SMII cross and region filter
Three RMIs
Know-Sure-Thing line-cross
Coppock Curve line-cross
TRIX line-cross
RSI of MA w/ MA cross
RSI of MA of KST w/ MA cross
RSI of MA of Coppock Curve w/ MA cross
RSI of MA of Trix w/ MA cross
So the idea is that this is essentially multiple strategies combined into one backtestable house. Balance is calculated for all position sizes in order to try to prevent false entries that plague so many scripts (IE, you set pyramiding to 2, each buy $1000, initial balance $1000, and yet it buys two orders off the bat for $2000 total and nets 400% profit because the second was considered free, happens on 90+% of scripts on Tradingview if you aren't very very careful!)
You tune each indicator and position size them so that they work together as well as you can and in doing so you are able to create a single backtest that is capable of running a bot, essentially, between multiple strategies - you can run a slower Moving Average cross, a faster SMI cross or MACD , or Bollinger that grabs big moves only, all the while having MACD trade small bonuses along the way. This way you can weight the Risk to Reward of each against eachother.
I will not try to claim this is something you can open and with no work have the best bot on the planet. This scripts intention is to take a lot of relatively common trading strategies and combine them under on roof with some risk management and the ability to weigh each against eachother.
If you are looking for a super advanced singular algorithm that tries to capture every peak and valley exactly on the dot, this is not for you. If you are looking for a tool with a high level of customizability, with a publisher who intends to update it to the best of his ability in accordance to seeking to make the best product that I personally can make for both myself and the community (because I will be using this myself of course!) that was specifically designed with the intention of performing well in spot markets by averaging low entry costs and high exit costs, this is for you! That is the exact intention here. It can certainly work with margin, but you will have to take extra care in setting your stop losses. I intend to make a version capable of going short which will be included as part of the package. It may take some work to keep all of the risk management working as well for shorts though. There will be more scripts added to the “package” as I hit the limit on this one a few times and have had to keep some ideas out already.
The current backtest shown is hand-optimized by myself for Link /USD 10min market (Binance US – shouldn't need much work to fit to other exchange markets) with multiple stop losses.
(IK) Base Break BuyThis strategy first calculates areas of support (bases), and then enters trades if that support is broken. The idea is to profit off of retracement. Dollar-cost-averaging safety orders are key here. This strategy takes into account a .1% commission, and tests are done with an initial capital of 100.00 USD. This only goes long.
The strategy is highly customizable. I've set the default values to suit ETH/USD 15m. If you're trading this on another ticker or timeframe, make sure to play around with the settings. There is an explanation of each input in the script comments. I found this to be profitable across most 'common sense' values for settings, but tweaking led to some pretty promising results. I leaned more towards high risk/high trade volume.
Always remember though: historical performance is no guarantee of future behavior . Keep settings within your personal risk tolerance, even if it promises better profit. Anyone can write a 100% profitable script if they assume price always eventually goes up.
Check the script comments for more details, but, briefly, you can customize:
-How many bases to keep track of at once
-How those bases are calculated
-What defines a 'base break'
-Order amounts
-Safety order count
-Stop loss
Here's the basic algorithm:
-Identify support.
--Have previous candles found bottoms in the same area of the current candle bottom?
--Is this support unique enough from other areas of support?
-Determine if support is broken.
--Has the price crossed under support quickly and with certainty?
-Enter trade with a percentage of initial capital.
-Execute safety orders if price continues to drop.
-Exit trade at profit target or stop loss.
Take profit is dynamic and calculated on order entry. The bigger the 'break', the higher your take profit percentage. This target percentage is based on average position size, so as safety orders are filled, and average position size comes down, the target profit becomes easier to reach.
Stop loss can be calculated one of two ways, either a static level based on initial entry, or a dynamic level based on average position size. If you use the latter (default), be aware, your real losses will be greater than your stated stop loss percentage . For example:
-stop loss = 15%, capital = 100.00, safety order threshold = 10%
-you buy $50 worth of shares at $1 - price average is $1
-you safety $25 worth of shares at $0.9 - price average is $0.966
-you safety $25 worth of shares at $0.8. - price average is $0.925
-you get stopped out at 0.925 * (1-.15) = $0.78625, and you're left with $78.62.
This is a realized loss of ~21.4% with a stop loss set to 15%. The larger your safety order threshold, the larger your real loss in comparison to your stop loss percentage, and vice versa.
Indicator plots show the calculated bases in white. The closest base below price is yellow. If that base is broken, it turns purple. Once a trade is entered, profit target is shown in silver and stop loss in red.
BBofVWAP with entry at Pivot PointThis strategy uses BB of VWAP and Pivot point to enter and exit the Long position.
settings
BB length 50
BB Source VWAP
Entry
When VWAP crossing up BB midline and price/close is above weekly PivotPoint ( you can also use Daily pivot point )
Exit
When VWAP is crossing down BB lower band
Stop Loss
Stop loss defaulted to 5%
Note : Long will position will be exited on either VWAP crossing down BB lower band or stop loss is hit - whichever comes first . Being said that some time your stop loss exit is less than 5% which saves from more losses.
Entry is based on weekly Pivot point , so any time frame below weekly will work perfect. I have tested t on 30 min , 1 HR , 4 Hr , Daily charts. Even weekly setting shows good results , that will work for long term investing style.
if you change Pivot period to Daily , chose time frames below Daily.
I also noticed this strategy mostly do not enter Long position in a down trend. Even it finds one , it will be exited with minimal loss.
Warning
For the use of educational purposes only
Bitcoin (BTC) Scalp / Short-term Short IndicatorThe purpose of this scalping Indicator is to help identifying Sell signals for short term trades on Bitcoin (Spot, Features, etc.) .
This script is working with more indicators and everything is balanced by hard work on (back)testing.
Result for users is a simple signal to SELL.
You can use it as easy indicator in your graph or create alerts.
I have the best results on 1min graph, with leverage and stop-loss feature.
This is my own version of scalping Sell Script / Indicator, which is a combination of few indicators, for example RSI , BB and price levels (actual and average) and works on standard candles.
SELL signal paints above the candle and you can set your target / trailing / stop-loss in the settings and check how it works in Strategy Tester.
Settings of this Indicator:
Take Profit
Stop Loss
Trailing Stop Loss
Trailing Stop Loss Offset
Initial Capital
Base Currency
Order size
Pyramiding
Commissions
Slippage
Average price lines (colors and visibility)
Plot background
These signals can be often observed at the beginning of a strong move, but there is a significant probability that these price levels will be revisited at a later point in time again.
Therefore these are interesting levels to place limit orders.
A Sell signal is defined as the last up candle before a sequence of down candles.
In my trading settings I have more but small positions, one safety limit order (for price averaging = better entry - easier close in profit) and stop-loss.
Sometimes trailing-profit feature have very nice profits.
Settings depends on your own money-management and free capital.
Don't ignore UP / DOWN trend. For UP trend I have an Indicator too (check my profile).
In addition to the upper/lower limits of each line, also average value is marked as this is an interesting area for price interaction and better view.
PM me to obtain access, more informations or support.
NOTICE: By requesting access to this script you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script.
Bitcoin (BTC) Scalp / Short-term Long IndicatorThe purpose of this scalping Indicator is to help identifying Buy signals for short term trades on Bitcoin (Spot, Features, etc.) .
This script is working with more indicators and everything is balanced by hard work on (back)testing.
Result for users is a simple signal to BUY .
You can use it as easy indicator in your graph or create alerts.
I have the best results on 1min graph, with leverage and stop-loss feature.
This is my own version of scalping Buy Script / Indicator, which is a combination of few indicators, for example RSI, BB and price levels (actual and average) and works on standard candles .
LONG signal paints below the candle and you can set your target / trailing / stop-loss in the settings and check how it works in Strategy Tester .
Settings of this Indicator:
Take Profit
Stop Loss
Trailing Stop Loss
Trailing Stop Loss Offset
Initial Capital
Base Currency
Order size
Pyramiding
Commissions
Slippage
Average price lines (colors and visibility)
Plot background
These signals can be often observed at the beginning of a strong move, but there is a significant probability that these price levels will be revisited at a later point in time again.
Therefore these are interesting levels to place limit orders.
A Buy signal is defined as the last down candle before a sequence of up candles.
In my trading settings I have more but small positions, one safety limit order (for price averaging = better entry - easier close in profit) and stop-loss.
Sometimes trailing-profit feature have very nice profits.
Settings depends on your own money-management and free capital.
In addition to the upper/lower limits of each line, also average value is marked as this is an interesting area for price interaction and better view.
PM me to obtain access, more informations or support.
NOTICE: By requesting access to this script you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script.
- Trading Bot – Dynamic RSI (Professional) - Robot Strategy -1. General Concept and Philosophy
This strategy was designed for systematic traders and work especially well on short timeframes (1 to 5 minutes), who seek to capture trend reversal movements with a high degree of confirmation. The goal is not to follow the trend, but to identify precise entry points in oversold or overbought zones, and then to exit the position dynamically to adapt to changing market conditions.
The originality of Trading Bot Dynamic RSI lies not in a single indicator, but in the intelligent fusion of several concepts:
Dynamic RSI bands for both entries and exits .
A triple confirmation filter to secure trade entries.
A fully parameterizable design ready for automation .
2. Originality at the Core of the Strategy: Key Features
Dynamic Exits on RSI Bands: This is a main original feature of this script. Unlike traditional strategies that use fixed Take-Profits and Stop-Losses, this one uses an exit RSI band, calculated with parameters independent of the entry ones. This allows the strategy to:
Adapt to Volatility: In a volatile market, the exit band will move further away, allowing for the capture of larger moves. In a ranging market, it will tighten to secure smaller gains.
Optimize Profits: The exit occurs when momentum genuinely fades, not at an arbitrary price level, thus maximizing the potential of each trade.
Triple Confirmation Filter for Precise Entries: To avoid false signals, each entry is validated by the convergence of three distinct conditions:
The base signal is generated when the price reaches an overbought or oversold zone, materialized by an RSI band calculated directly on the chart.
The WaveTrend oscillator must also be in an extreme zone, confirming that the short-term momentum is ready for a reversal.
Finally, the StochRSI must validate that the RSI itself is in an overbought or oversold condition, adding an extra layer of security.
"Automation Ready" Design: The strategy was developed with automation in mind.
Customizable Alert Messages: All messages for entries and exits (Long/Short) can be formatted to be compatible with automated trade execution platforms.
Precise Capital Management: The position size calculation can be set as a fixed amount (e.g., 100 USDT), a percentage of the total capital, or of the available capital, and includes leverage. These parameters are crucial for a trading bot.
3. Detailed Operation
Entry Logic: A position is opened only if the following three conditions are met:
The market price touches (or closes below/above) the entry RSI band (lower for a buy, upper for a sell).
The WaveTrend indicator is in the oversold zone (for a buy) or overbought zone (for a sell).
The Stochastic RSI indicator is also in the oversold zone (for a buy) or overbought zone (for a sell).
The order is placed as a limit order on the RSI band, allowing for execution at the best possible price.
Exit Logic: The primary exit is dynamic.
For a Long position, the trade is closed when the price reaches the upper exit RSI band.
For a Short position, the trade is closed when the price reaches the lower exit RSI band.
Optionally, a percentage-based Stop-Loss and Take-Profit can be activated for more traditional risk management, although the dynamic exit is the recommended default mechanism.
4. Ease of Use and Customization
Despite its internal complexity, the strategy is designed to be user-friendly :
Clear Settings Panel: Parameters are grouped by function (Long Entry, Long Exit, Quantity, etc.), and each option comes with an explanatory tooltip.
Integrated Display: All key information (performance, current settings) is displayed in clean and discreet tables directly on the chart, allowing you to see at a glance how the strategy is configured.
Total Flexibility: Although default settings are provided, every parameter (RSI lengths, levels, filters) can be adjusted to optimize the strategy on any asset (cryptocurrencies, Forex, indices...) and any timeframe.
5. Detailed Guide to User Settings
A comprehensive set of parameters
To offer you complete control and maximum flexibility, the strategy exposes a comprehensive set of parameters. Here is an overview of what you can customize:
Trading Mode and Display
Trading Mode: Choose to enable only long positions ("Long Only"), only short positions ("Short Only"), or both simultaneously ("Long and Short").
Display: Manage the information panels on the chart. You can opt for a full display, a minimal window showing the profit, or hide all information for a clean chart.
Filters Smoothing (StochRSI K)
Filters Smoothing: This key parameter adjusts the smoothing of the Stochastic RSI. A lower value will make the filter more responsive, generating more signals. A higher value will make it smoother, generating fewer but potentially more reliable signals.
LONG Position Settings
Long Only mode
Entry: Define the RSI length and Oversold level that draw the lower band for long position entries.
Exit: Independently configure the RSI length and Overbought level that draw the upper band for the dynamic position exit.
Options: Optionally enable a percentage-based Take-Profit and/or Stop-Loss.
SHORT Position Settings
Short Only Mode
Entry: Define the RSI length and Overbought level for the upper entry band for short positions.
Exit: Independently configure the RSI length and Oversold level for the lower dynamic exit band.
Options: Just like for long positions, you can enable a percentage-based Take-Profit and/or Stop-Loss.
Quantity and Leverage
Quantity Type: Calculate your position size in three ways: as a fixed cash amount, as a percentage of available capital, or as a percentage of the total account balance.
Amount: Specify the dollar amount or percentage to commit per trade.
Leverage: Set the leverage to be applied. This is crucial for automation.
Backtest Period
Backtest Period: Enable this option to limit the strategy's calculations to a specific time period. This is a powerful tool for testing performance under particular market conditions.
Bot Alert Messages
Bot Alert Messages: This section is dedicated to automation. Customize the exact text messages that will be sent by TradingView alerts for each event (enter long, exit long, etc.).
Other Settings (Advanced - Optional)
Other Settings: This section allows experienced users to fine-tune the confirmation engine. You can adjust the parameters of the WaveTrend and Stochastic RSI oscillators in detail.
Spread Calculator (Informative Only)
Spread Calculator: This handy tool helps you estimate the actual fees of your exchange to run a much more realistic backtest. This panel has no impact on the trading logic itself.
Disclaimer
This strategy provides signals based on past market conditions. Past performance is not indicative of future results. Trading involves risk, and it is the responsibility of each user to manage their risk appropriately. It is strongly recommended to conduct thorough backtests and to understand the functioning of each parameter before using this strategy in live conditions or automating it. Take into account transaction fees, spread, and slippage, which can impact real results.
PHANTOM STRIKE Z-4 [ApexLegion]Phantom Strike Z-4
STRATEGY OVERVIEW
This strategy represents an analytical framework using 6 detection systems that analyze distinct market dimensions through adaptive timeframe optimization. Each system targets specific market inefficiencies - automated parameter adjustment, market condition filtering, phantom strike pattern detection, SR exit management, order block identification, and volatility-aware risk management - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions.
SYSTEM ARCHITECTURE PHILOSOPHY
Phantom Strike Z-4 operates through 12 distinct parameter groups encompassing individual settings that allow detailed customization for different trading environments. The strategy employs modular design principles where each analytical component functions independently while contributing to unified decision-making protocols. This architecture enables traders to engage with structured market analysis through intuitive configuration options while the underlying algorithms handle complex computational processes.
The framework approaches certain aspects differently from static trading approaches by implementing real-time parameter adjustment based on timeframe characteristics, market volatility conditions, news event detection, and weekend gap analysis. During low-volatility periods where traditional strategies struggle to generate meaningful returns, Z-4's adaptive systems identify micro-opportunities through formation analysis and systematic patience protocols.
🔍WHY THESE CUSTOM SYSTEMS WERE INDEPENDENTLY DEVELOPED
The strategy approaches certain aspects differently from traditional indicator combinations through systematic development of original analytical approaches:
# 1. Auto Timeframe Optimization Module (ATOM)
Problem Identification: Standard strategies use fixed parameters regardless of timeframe characteristics, leading to over-optimization on specific timeframes and reduced effectiveness when market conditions change between different time intervals. Most retail traders manually adjust parameters when switching timeframes, creating inconsistency and suboptimal results. Traditional approaches may not account for how market noise, signal frequency, and intended holding periods differ substantially between 1-minute scalping and 4-hour swing trading environments.
Custom Solution Development: The ATOM system addresses these limitations through systematic parameter matrices developed specifically for each timeframe environment. During development, analysis indicated that 1-minute charts require aggressive profit-taking approaches due to rapid price reversals, while 15-minute charts benefit from patient position holding during trend development. The system automatically detects chart timeframe through TradingView's built-in functions and applies predefined parameter configurations without user intervention.
Timeframe-Specific Adaptations:
For ultra-short timeframe trading (1-minute charts), the system recognizes that market noise dominates price action, requiring tight stop losses (1.0%) and rapid profit realization (25% at TP1, 35% at TP2, 40% at TP3). Position sizes automatically reduce to 3% of equity to accommodate the higher trading frequency while mission duration limits to 20 bars prevent extended exposure during unsuitable conditions.
Medium timeframe configurations (5-minute and 15-minute charts) balance signal quality with execution frequency. The 15-minute configuration aims to provide a favorable combination of signal characteristics and practical execution for most retail traders. Formation thresholds increase to 2.0% for both stealth and strike ready levels, requiring stronger momentum confirmation before signal activation.
Longer timeframe adaptations (1-hour and 4-hour charts) accommodate swing trading approaches where positions may develop over multiple trading sessions. Position sizing increases to 10% of equity reflecting the reduced signal frequency and higher validation requirements typical of swing trading. Take profit targets extend considerably (TP1: 2.0%, TP2: 4.0%, TP3: 8.0%) to capture larger price movements characteristic of these timeframes.
# 2. Market Condition Filtering System (MCFS)
Problem Identification: Existing volatility filters use simple ATR calculations that may not distinguish between trending volatility and chaotic noise, potentially affecting signal quality during news events, market transitions, and unusual trading sessions. Traditional volatility measurements treat all price movement equally, whether it represents genuine trend development or random market noise caused by low liquidity or algorithmic trading activities.
Custom Solution Architecture: The MCFS addresses these limitations through multi-dimensional market analysis that examines volatility characteristics, external market influences, and temporal factors affecting trading conditions. Rather than relying solely on price-based volatility measurements, the system incorporates news event detection, weekend gap analysis, and session transition monitoring to provide systematic market state assessment.
Volatility Classification and Response Framework:
• EXTREME Volatility Conditions (>2.5x average ATR): When current volatility exceeds 250% of the recent average, the system recognizes potentially chaotic market conditions that often occur during major news events, market crashes, or significant fundamental developments. During these periods, position sizing automatically reduces by 70% while exit sensitivity increases by 50%.
• HIGH Volatility Conditions (1.8-2.5x average ATR): High volatility environments often represent strong trending conditions or elevated market activity that still maintains some predictability. Position sizing reduces by 40% while maintaining standard signal generation processes.
• NORMAL Volatility Conditions (1.2-1.8x average ATR): Normal volatility represents favorable trading conditions where technical analysis may provide reliable signals and market behavior tends to follow predictable patterns. All strategy parameters operate at standard settings.
• LOW Volatility Conditions (0.8-1.2x average ATR): Low volatility environments may present opportunities for increased position sizing due to reduced risk and improved signal characteristics. Position sizing increases by 30% while profit targets extend to capture larger movements when they occur.
• DEAD Volatility Conditions (<0.8x average ATR): When volatility falls below 80% of recent averages, the system suspends trading activity to avoid choppy, directionless market conditions that may produce unfavorable risk-adjusted returns.
# 3. Phantom Strike Detection Engine (PSDE)
Problem Identification: Traditional momentum indicators may lag market reversals by 2-4 bars and can generate signals during consolidation periods. Existing oscillator combinations may lack precision in identifying high-probability momentum shifts with adequate filtering mechanisms. Most trading systems rely on single-indicator signals or simple two-indicator confirmations that may not distinguish between genuine momentum changes and temporary market fluctuations.
Multi-Indicator Convergence System: The PSDE addresses these limitations through structured multi-indicator convergence requiring simultaneous confirmation across four independent momentum systems: SuperTrend directional analysis, MACD histogram acceleration, Parabolic SAR momentum validation, and CCI buffer zone detection. This approach recognizes that each indicator provides unique market insights, and their convergence may create different trading opportunity characteristics compared to individual signals.
Enhanced vs Phantom Mode Operation:
Enhanced mode activates when at least three of the four primary indicators align with directional bias while meeting minimum validation criteria. Enhanced mode provides more frequent signals while Phantom mode offers more selective signal generation with stricter confirmation requirements.
Phantom mode requires complete alignment across all four indicators plus additional momentum validation. All Enhanced mode criteria must be met, plus additional confirmation requirements. This stricter requirement set reduces signal frequency to 5-8 monthly but aims for higher signal quality through comprehensive multi-indicator alignment and additional momentum validation.
# 4. Smart Resistance Exit Grid (SR Exit Grid)
Problem Identification: Static take-profit levels may not account for changing market conditions and momentum strength. Traditional trailing stops may exit during strong moves or during reversals, while not distinguishing between profitable and losing position characteristics.
Systematic Holding Evaluation Framework: The SR Exit Grid operates through continuous evaluation of position viability rather than predetermined price targets through a structured 4-stage priority hierarchy:
🎯 1st Priority: Standard Take Profit processing (Highest Priority)
🔄 2nd Priority: SMART EXIT (Only when TP not executed)
⛔ 3rd Priority: SL/Emergency/Timeout Exit
🛡️ 4th Priority: Smart Low Logic (Separate Safety Safeguard)
The system employs a tpExecuted flag mechanism ensuring that only one exit type activates per bar, preventing conflicting orders and maintaining execution priority. Each stage operates independently with specific trigger conditions and risk management protocols.
Fast danger scoring evaluates immediate threats including SAR distance deterioration, momentum reversals, extreme CCI readings, volatility spikes, and price action intensity. When combined scores exceed specified thresholds (8.0+ danger with <2.0 confidence), the system triggers protective exits regardless of current profitability.
# 5. Order Block Tracking System (OBTS)
Problem Identification: Standard support/resistance levels are static and may not account for institutional order flow patterns. Traditional approaches may use horizontal lines without considering market structure evolution or mathematical price relationships.
Dynamic Channel Projection Logic: The OBTS creates dynamic order block identification using pivot point analysis with parallel channel projection based on mathematical price geometry. The system identifies significant turning points through configurable swing length parameters while maintaining historical context through consecutive pivot tracking for trend analysis.
Rather than drawing static horizontal lines, the system calculates slope relationships between consecutive pivot points and projects future support/resistance levels based on mathematical progression. This approach recognizes that institutional order flow may follow geometric patterns that can be mathematically modeled and projected forward.
# 6. Volatility-Aware Risk Management (VARM)
Problem Identification: Fixed percentage risk management may not adapt optimally during varying market volatility regimes, potentially creating conservative exits in low volatility and limited protection during high volatility periods. Traditional approaches may not scale dynamically with market conditions.
Dual-Mode Adaptive Framework: The VARM provides systematic risk scaling through dual-mode architecture offering both ATR-based dynamic adjustment and fixed percentage modes. Dynamic mode automatically scales all TP/SL levels based on current market volatility while maintaining proportional risk-reward relationships. Fixed mode provides predictable percentage-based levels regardless of volatility conditions.
Emergency protection protocols operate independently from standard risk management, providing enhanced safeguards against significant moves that exceed normal volatility expectations. The emergency system cannot be disabled and triggers at wider levels than normal stops, providing final protection when standard risk management may be insufficient during extreme market events.
## Technical Formation Analysis System
The foundation of Z-4's analytical framework rests on a structured EMA system utilizing 8, 21, and 50-period exponential moving averages that create formation structure analysis. This system differs from simple crossover signals by evaluating market geometry and momentum alignment.
Formation Gap Analysis: The formation gap measurement calculates the percentage separation between Recon Scout EMA (8-period) and Technical Support EMA (21-period) to determine market state classification. When gap percentage falls below the Stealth Mode Threshold (default 1.5%), the market enters consolidation phase requiring enhanced patience. When gap exceeds Strike Ready Threshold (1.5%), conditions become favorable for momentum-based entries.
This mathematical approach to formation analysis provides structured measurement of market transition states. During stealth mode periods, the strategy reduces entry frequency while maintaining monitoring protocols. Strike ready conditions activate increased signal sensitivity and quicker entry evaluation processes.
The Command Base EMA (50-period) provides strategic context for overall market direction and trend strength measurement. Position decisions incorporate not only immediate formation geometry but also alignment with longer-term directional bias represented by Command Base positioning relative to current price action.
🎯CORE SYSTEMS TECHNICAL IMPLEMENTATION
# SuperTrend Foundation Analysis Implementation
SuperTrend calculation provides the directional foundation through volatility-adjusted bands that adapt to current market conditions rather than using fixed parameters. The system employs configurable ATR length (default 10) and multiplier (default 3.0) to create dynamic support/resistance levels that respond to both trending and ranging market environments.
Volatility-Adjusted Band Calculation:
st_atr = ta.atr(stal)
st_hl2 = (high + low) / 2
st_ub = st_hl2 + stm * st_atr
st_lb = st_hl2 - stm * st_atr
stb = close > st and ta.rising(st, 3)
The HL2 methodology (high+low)/2 aims to provide stable price reference compared to closing prices alone, reducing sensitivity to intraday price spikes that can distort traditional SuperTrend calculations. ATR multiplication creates bands that expand during volatile periods and contract during consolidation, aiming for suitable signal sensitivity across different market conditions.
Rising/Falling Trend Confirmation: The key feature involves requiring rising/falling trend confirmation over multiple periods rather than simple price-above-band validation. This requirement screens signals that occur during SuperTrend whipsaw periods common in sideways markets. SuperTrend signals with 3-period rising confirmation help reduce false signals that occur during sideways market conditions compared to simple crossover signals.
Band Distance Validation: The system measures the distance between current price and SuperTrend level as a percentage of current price, requiring minimum separation thresholds to identify meaningful momentum rather than marginal directional changes. This validation aims to reduce signal generation during periods where price oscillates closely around SuperTrend levels, indicating indecision rather than clear directional bias.
# MACD Histogram Acceleration System - Momentum Detection
MACD analysis focuses exclusively on histogram acceleration rather than traditional line crossovers, aiming to provide earlier momentum detection. This approach recognizes that histogram acceleration may precede price acceleration by 1-2 bars, potentially offering timing benefits compared to conventional MACD applications.
Acceleration-Based Signal Generation:
mf = ta.ema(close, mfl)
ms = ta.ema(close, msl)
ml = mf - ms
msg = ta.ema(ml, msgl)
mh = ml - msg
mb = mh > 0 and mh > mh and mh > mh
The requirement for positive histogram values that increase over two consecutive periods aims to identify genuine momentum expansion rather than temporary fluctuations. This filtering approach aims to reduce false signals while maintaining signal quality.
Fast/Slow EMA Optimization: The default 12/26 EMA combination aims for intended balance between responsiveness and stability for most trading timeframes. However, the system allows customization for specific market characteristics or trading styles. Shorter settings (8/21) increase sensitivity for scalping approaches, while longer settings (16/32) provide smoother signals for swing trading applications.
Signal Line Smoothing Effects: The 9-period signal line smoothing creates histogram values that screen high-frequency noise while preserving essential momentum information. This smoothing level aims to balance signal latency and accuracy across multiple market conditions.
# Parabolic SAR Validation Framework - Momentum Verification
Parabolic SAR provides momentum validation through price separation analysis and inflection detection that may precede significant trend changes. The system requires minimum separation thresholds while monitoring SAR behavior for early reversal signals.
Separation-Based Validation:
sar = ta.sar(ss, si, sm)
sarb = close > sar and (close - sar) / close > 0.005
sardp = math.abs(close - sar) / close * 100
sariu = sarm > 0 and sarm < 0 and math.abs(sarmc) > saris
The 0.5% minimum separation requirement screens marginal directional changes that may reverse within 1-3 bars. The 0.5% minimum separation requirement helps filter out marginal directional changes.
SAR Inflection Detection: SAR inflection identification examines rate-of-change over 5-period lookback periods to detect momentum direction changes before they appear in price action. Inflection sensitivity (default 1.5) determines the magnitude of momentum change required for classification. These inflection points may precede significant price reversals by 1-2 bars, potentially providing early signals for position protection or entry timing.
Strength Classification Framework: The system categorizes SAR momentum into weak/moderate/strong classifications based on distance percentage relative to strength range thresholds. Strong momentum periods (>75% of range) receive enhanced weighting in composite calculations, while weak periods (<25%) trigger additional confirmation requirements. This classification aims to distinguish between genuine momentum moves and temporary price fluctuations.
# CCI SMART Buffer Zone System - Oscillator Analysis
The CCI SMART system represents a detailed component of the PSDE, combining multiple mathematical techniques to create modified momentum detection compared to conventional CCI applications. The system employs ALMA preprocessing, TANH normalization, and dynamic buffer zone analysis for market timing.
ALMA Preprocessing Benefits: Arnaud Legoux Moving Average preprocessing aims to provide phase-neutral smoothing that reduces high-frequency noise while preserving essential momentum information. The configurable offset (0.85) and sigma (6.0) parameters create Gaussian filter characteristics that aim to maintain signal timing while reducing unwanted signals caused by random price fluctuations.
TANH Normalization Advantages: The rational TANH approximation creates bounded output (-100 to +100) that aims to prevent extreme readings from distorting analysis while maintaining sensitivity to normal market conditions. This normalization is designed to provide consistent behavior across different volatility regimes and market conditions, addressing an aspect found in traditional CCI applications.
Rational TANH Approximation Implementation:
rational_tanh(x) =>
abs_x = math.abs(x)
if abs_x >= 4.0
x >= 0 ? 1.0 : -1.0
else
x2 = x * x
numerator = x * (135135 + x2 * (17325 + x2 * (378 + x2)))
denominator = 135135 + x2 * (62370 + x2 * (3150 + x2 * 28))
numerator / denominator
cci_smart = rational_tanh(cci / 150) * 100
The rational approximation uses polynomial coefficients that provide mathematical precision equivalent to native TANH functions while maintaining computational efficiency. The 4.0 absolute value threshold creates complete saturation at extreme values, while the polynomial series delivers smooth S-curve transformation for intermediate values.
Dynamic Buffer Zone Analysis: Unlike static support/resistance levels, the CCI buffer system creates zones that adapt to current market volatility through ALMA-calculated true range measurements. Upper and lower boundaries expand during volatile periods and contract during consolidation, providing context-appropriate entry and exit levels.
CCI Buffer System Implementation:
cci = ta.cci(close, ccil)
cci_atr = ta.alma(ta.tr, al, ao, asig)
cci_bu = low - ccim * cci_atr
cci_bd = high + ccim * cci_atr
ccitu = cci > 50 and cci > cci
CCI buffer analysis creates dynamic support/resistance zones using ALMA-smoothed true range calculations rather than fixed levels. Buffer upper and lower boundaries adapt to current market volatility through ALMA calculation with configurable offset (default 0.85) and sigma (default 6.0) parameters.
The CCI trending requirements (>50 and rising) provide directional confirmation while buffer zone analysis offers price level validation. This dual-component approach identifies both momentum direction and suitable entry/exit price levels relative to current market volatility.
# Momentum Gathering and Assessment Framework
The strategy incorporates a dual-component momentum system combining RSI and MFI calculations into unified momentum assessment with configurable suppression and elevation thresholds.
Composite Momentum Calculation:
ri = ta.rsi(close, mgp)
mi = ta.mfi(close, mip)
ci = (ri + mi) / 2
us = ci < sl // Undersupported conditions
ed = ci > dl // Elevated conditions
The composite momentum score averages RSI and MFI over configurable periods (default 14) to create unified momentum measurement that incorporates both price momentum and volume-weighted momentum. This dual-factor approach provides different momentum assessment compared to single-indicator analysis.
Suppression level identification (default 35) indicates oversold conditions where counter-trend opportunities may develop. These conditions often coincide with formation analysis showing bullish progression potential, creating enhanced-validation long entry scenarios. Elevation level detection (default 65) identifies overbought conditions suitable for either short entries or long position exits depending on overall market context.
The momentum assessment operates continuously, providing real-time context for all entry and exit decisions. Rather than using fixed thresholds, the system evaluates momentum levels relative to formation geometry and volatility conditions to determine suitable response protocols.
Composite Signal Generation Architecture:
The strategy employs a systematic scoring framework that aggregates signals from independent analytical modules into unified decision matrices through mathematical validation protocols rather than simple indicator combinations.
Multi-Group Signal Analysis Structure:
The scoring architecture operates through three analytical timeframe groups, each targeting different market characteristics and response requirements:
✅Fast Group Analysis (Immediate Response): Fast group scoring evaluates immediate market conditions requiring rapid assessment and response. SAR distance analysis measures price separation from parabolic SAR as percentage of close price, with distance ratios exceeding 120% of strength range indicating momentum exhaustion (3.0 points). SAR momentum detection captures rate-of-change over 5-period lookback, with absolute momentum exceeding 2.0% indicating notable acceleration or deceleration (1.0 point).
✅Medium Group Analysis (Signal Development): Medium group scoring focuses on signal development and confirmation through momentum indicator progression. Phantom Strike detection operates in two modes: Enhanced mode requiring 4-component confirmation awards 3.0 base points, while Phantom mode requiring complete alignment plus additional criteria awards 4.0 base points.
✅Slow Group Analysis (Strategic Context): Slow group analysis provides strategic market context through trend regime classification and structural assessment. Trend classification scoring awards top points (3.5) for optimal conditions: major trend bullish with strong trend strength (>2.0% EMA spread), 2.8 points for normal strength major trends, and proportional scoring for various trend states.
Signal Integration and Quality Assessment: The integration process combines medium group tactical scoring with 30% weighting from slow group strategic assessment, recognizing that immediate signal development should receive primary emphasis while strategic context provides important validation. Fast group danger levels operate as filtering mechanisms rather than additive scoring components.
Score normalization converts raw calculations to 10-point scales through division by total possible score (19.6) and multiplication by 10. This standardization enables consistent threshold application regardless of underlying calculation complexity while maintaining proportional relationships between different signal strength levels.
Conflict Resolution and Priority Logic:
sc = math.abs(cs_les - cs_ses) < 1.5
hqls = sql and not sc and (cs_les > cs_ses * 1.15)
hqss = sqs and not sc and (cs_ses > cs_les * 1.15)
Signal conflict detection identifies situations where competing long/short signals occur simultaneously within 1.5-point differential. During conflict periods, the system requires 15% threshold margin plus absence of conflict conditions for signal activation, screening trades during uncertain market conditions.
🧠CONFIGURATION SETTINGS & USAGE GUIDE
Understanding Parameter Categories and Their Impact
The Phantom Strike Z-4 strategy organizes its numerous parameters into 12 logical groups, each controlling specific aspects of market analysis and position management. Understanding these parameter relationships enables users to customize the strategy for different trading styles, market conditions, and risk preferences without compromising the underlying analytical framework.
Parameter Group Overview and Interaction: Parameters within the strategy do not operate in isolation. Changes to formation thresholds affect signal generation frequency, which in turn impacts intended position sizing and risk management settings. Similarly, timeframe optimization automatically adjusts multiple parameter groups simultaneously, creating coordinated system behavior rather than piecemeal modifications.
Safe Modification Ranges: Each parameter includes minimum and maximum values that prevent system instability or illogical configurations. These ranges are designed to maintain strategy behavior stability and functional operation. Operating outside these ranges may result in either excessive conservatism (missed opportunities) or excessive aggression (increased risk without proportional reward).
# Tactical Formation Parameters (Group 1) - Foundation Configuration
**EMA Period Settings and Market Response**
Recon Scout EMA (Default: 8 periods): The fastest moving average in the system, providing immediate price action response and early momentum detection. This parameter influences signal sensitivity and entry timing characteristics. Values between 5-12 periods may work across most market conditions, with specific adjustment based on trading style and timeframe preferences.
-Conservative Setting (10-12 periods): Reduces signal frequency by approximately 25% while potentially improving accuracy by 8-12%. Suitable for traders preferring fewer, higher-quality signals with reduced monitoring requirements.
-Standard Setting (8 periods): Provides balanced performance with moderate signal frequency and reasonable accuracy. Represents intended configuration for most users based on backtesting across multiple market conditions.
-Aggressive Setting (5-6 periods): Increases signal frequency by 35-40% while accepting 5-8% accuracy reduction. Appropriate for active traders comfortable with increased position monitoring and faster decision-making requirements.
Technical Support EMA (Default: 21 periods): Creates medium-term trend reference and formation gap calculations that determine market state classification. This parameter establishes the baseline for consolidation detection and momentum confirmation, influencing the strategy's approach to distinguish between trending and ranging market conditions.
Command Base EMA (Default: 50 periods): Provides strategic context and long-term trend classification that influences overall market bias and position sizing decisions. This slower moving average acts as a filter for trade direction, helping support alignment with broader market trends rather than counter-trend trading against major market movements.
**Formation Threshold Configuration**
Stealth Mode Threshold (Default: 1.5%): Defines the maximum percentage gap between Recon Scout and Technical Support EMAs that indicates market consolidation. When the gap falls below this threshold, the market enters "stealth mode" requiring enhanced patience and reduced entry frequency. This parameter influences how the strategy behaves during sideways market conditions.
-Tight Threshold (0.8-1.2%): Creates more restrictive consolidation detection, reducing entry frequency during marginal trending conditions but potentially improving accuracy by avoiding low-momentum signals.
-Standard Threshold (1.5%): Provides balanced consolidation detection suitable for most market conditions and trading styles.
-Loose Threshold (2.0-3.0%): Permits trading during moderate consolidation periods, increasing opportunity capture but accepting some reduction in signal quality during transitional market phases.
-Strike Ready Threshold (Default: 1.5%): Establishes minimum EMA separation required for momentum-based entries. When the gap exceeds this threshold, conditions become favorable for signal generation and position entry. This parameter works inversely to Stealth Mode, determining when market conditions support active trading.
# Momentum System Configuration (Group 2) - Momentum Assessment
**Oscillator Period Settings**
Momentum Gathering Period (Default: 14): Controls RSI calculation length, influencing momentum detection sensitivity and signal timing. This parameter determines how quickly the momentum system responds to price momentum changes versus how stable the momentum readings remain during normal market fluctuations.
-Fast Response (7-10 periods): Aims for rapid momentum detection suitable for scalping approaches but may generate more unwanted signals during choppy market conditions.
-Standard Response (14 periods): Provides balanced momentum measurement appropriate for most trading styles and timeframes.
-Smooth Response (18-25 periods): Creates more stable momentum readings suitable for swing trading but with delayed response to momentum changes.
-Mission Indicator Period (Default: 14): Determines MFI (Money Flow Index) calculation length, incorporating volume-weighted momentum analysis alongside price-based RSI measurements. The relationship between RSI and MFI periods affects how the composite momentum score behaves during different market conditions.
**Momentum Threshold Configuration**
-Suppression Level (Default: 35): Identifies oversold conditions indicating potential bullish reversal opportunities. This threshold determines when the momentum system signals that selling pressure may be exhausted and buying interest could emerge. Lower values create more restrictive oversold identification, while higher values increase sensitivity to potential reversal conditions.
-Dominance Level (Default: 65): Establishes overbought thresholds for potential bearish reversals or long position exit consideration. The separation between Suppression and Dominance levels creates a neutral zone where momentum conditions don't strongly favor either direction.
# Phantom Strike System Configuration (Group 3) - Core Signal Generation
**System Activation and Mode Selection**
Phantom Strike System Enable (Default: True): Activates the core signal generation methodology combining SuperTrend, MACD, SAR, and CCI confirmation requirements. Disabling this system converts the strategy to basic formation analysis without advanced momentum confirmation, substantially affecting signal characteristics while increasing frequency.
Phantom Strike Mode (Default: PHANTOM): Determines signal generation strictness through different confirmation requirements. This setting fundamentally affects trading frequency, signal accuracy, and required monitoring intensity.
ENHANCED Mode: Requires 4-component confirmation with moderate validation criteria. Suitable for active trading approaches where signal frequency balances with accuracy requirements.
PHANTOM Mode: Requires complete alignment across all indicators plus additional momentum criteria. Appropriate for selective trading approaches where signal quality takes priority over frequency.
**SuperTrend Configuration**
SuperTrend ATR Length (Default: 10): Determines volatility measurement period for dynamic band calculation. This parameter affects how quickly SuperTrend bands adapt to changing market conditions and how sensitive the trend detection becomes to short-term price movements.
SuperTrend Multiplier (Default: 3.0): Controls band width relative to ATR measurements, influencing trend change sensitivity and signal frequency. This parameter determines how much price movement is required to trigger trend direction changes.
**MACD System Parameters**
MACD Fast Length (Default: 12): Establishes responsive EMA for MACD line calculation, influencing histogram acceleration detection timing and signal sensitivity.
MACD Slow Length (Default: 26): Creates baseline EMA for MACD calculations, establishing the reference for momentum measurement.
MACD Signal Length (Default: 9): Smooths MACD line to generate histogram values used for acceleration detection.
**Parabolic SAR Settings**
SAR Start (Default: 0.02): Determines initial acceleration factor affecting early SAR behavior after trend initiation.
SAR Increment (Default: 0.02): Controls acceleration factor increases as trends develop, affecting how quickly SAR approaches price during sustained moves.
SAR Maximum (Default: 0.2): Establishes upper limit for acceleration factor, preventing rapid SAR approach speed during extended trends.
**CCI Buffer System Configuration**
CCI Length (Default: 20): Determines period for CCI calculation, affecting oscillator sensitivity and signal timing.
CCI ATR Length (Default: 5): Controls period for ALMA-smoothed true range calculations used in dynamic buffer zone creation.
CCI Multiplier (Default: 1.0): Determines buffer zone width relative to ATR calculations, affecting entry requirements and signal frequency.
⭐HOW TO USE THE STRATEGY
# Step 1: Core Parameter Setup
Technical Formation Group (g1) - Foundation Settings: The Technical Formation group provides the foundational analytical framework through 7 key parameters that influence signal generation and timeframe optimization.
Auto Optimization Controls:
enable_auto_tf = input.bool(false, "🎯 Enable Auto Timeframe Optimization")
enable_market_filters = input.bool(true, "🌪️ Enable Market Condition Filters")
Auto Timeframe Optimization activation automatically detects chart timeframe and applies configured parameter matrices developed for each time interval. When enabled, the system overrides manual settings with backtested suggested values for 1M/5M/15M/1H configurations.
Market Condition Filters enable real-time parameter adjustment based on volatility classification, news event detection, and weekend gap analysis. This system provides adaptive behavior during unusual market conditions, automatically reducing position sizes during extreme volatility and increasing exit sensitivity during news events.
# Step 2: The Momentum System Configuration
Momentum Gathering Parameters (g2): The Momentum System combines RSI and MFI calculations into unified momentum assessment with configurable thresholds for market state classification.
# Step 3: Phantom Strike System Setup
Core Detection Parameters (g3): The Phantom Strike System represents the strategy's primary signal generation engine through multi-indicator convergence analysis requiring detailed configuration for intended performance.
Phantom Strike Mode selection determines signal generation strictness. Enhanced mode requires 4-component confirmation (SuperTrend + MACD + SAR + CCI) with base scoring of 3.0 points, structured for active trading with moderate confirmation requirements. Phantom mode requires complete alignment across all indicators plus additional momentum criteria with 4.0 base scoring, creating enhanced validation signals for selective trading approaches
# Step 4: SR Exit Grid Configuration
Position Management Framework (g6): The SR Exit Grid system manages position lifecycle through progressive profit-taking and adaptive holding evaluation based on market condition analysis.
esr = input.bool(true, "Enable SR Exit Grid")
ept = input.bool(true, "Enable Partial Take Profit")
ets = input.bool(true, "Enable Technical Trailing Stop")
📊MULTI-TIMEFRAME SYSTEM & ADAPTIVE FEATURES
Auto Timeframe Optimization Architecture: The Auto Timeframe Optimization system provides automated parameter adaptation that automatically configures strategy behavior based on chart timeframe characteristics with reduced need for manual adjustment.
1-Minute Ultra Scalping Configuration:
get_1M_params() =>
StrategyParams.new(
smt = 0.8, srt = 1.0, mcb = 2, mmd = 20,
smartThreshold = 0.1, consecutiveLimit = 20,
positionSize = 3.0, enableQuickEntry = true,
ptp1 = 25, ptp2 = 35, ptp3 = 40,
tm1 = 1.5, tm2 = 3.0, tm3 = 4.5, tmf = 6.0,
isl = 1.0, esl = 2.0, tsd = 0.5, dsm = 1.5)
15-Minute Swing Trading Configuration:
get_15M_params() =>
StrategyParams.new(
smt = 2.0, srt = 2.0, mcb = 8, mmd = 100,
smartThreshold = 0.3, consecutiveLimit = 12,
positionSize = 7.0, enableQuickEntry = false,
ptp1 = 15, ptp2 = 25, ptp3 = 35,
tm1 = 4.0, tm2 = 8.0, tm3 = 12.0, tmf = 18.0,
isl = 2.0, esl = 3.5, tsd = 1.2, dsm = 2.5)
Market Condition Filter Integration:
if enable_market_filters
vol_condition = get_volatility_condition()
is_news = is_news_time()
is_gap = is_weekend_gap()
step1 = adjust_for_volatility(base_params, vol_condition)
step2 = adjust_for_news(step1, is_news)
final_params = adjust_for_gap(step2, is_gap)
Market condition filters operate in conjunction with timeframe optimization to provide systematic parameter adaptation based on both temporal and market state characteristics. The system applies cascading adjustments where each filter modifies parameters before subsequent filter application.
Volatility Classification Thresholds:
- EXTREME: >2.5x average ATR (70% position reduction, 50% exit sensitivity increase)
- HIGH: 1.8-2.5x average (40% position reduction, increased monitoring)
- NORMAL: 1.2-1.8x average (standard operations)
- LOW: 0.8-1.2x average (30% position increase, extended targets)
- DEAD: <0.8x average (trading suspension)
The volatility classification system compares current 14-period ATR against a 50-period moving average to establish baseline market activity levels. This approach aims to provide stable volatility assessment compared to simple ATR readings, which can be distorted by single large price movements or temporary market disruptions.
🖥️TACTICAL HUD INTERPRETATION GUIDE
Overview of the 21-Component Real-Time Information System
The Tactical HUD Display represents the strategy's systematic information center, providing real-time analysis through 21 distinct data points organized into 6 logical categories. This system converts complex market analysis into actionable insights, enabling traders to make informed decisions based on systematic market assessment supporting informed decision-making processes.
The HUD activates through the "Show Tactical HUD" parameter and displays continuously in the top-right corner during live trading and backtesting sessions. The organized 3-column layout presents Item, Value, and Status for each component, creating efficient information density while maintaining clear readability under varying market conditions.
# Row 1: Mission Status - Advanced Position State Management
Display Format: "LONG MISSION" | "SHORT MISSION" | "STANDBY"
Color Coding: Green (Long Active) | Red (Short Active) | Gray (Standby)
Status Indicator: ✓ (Mission Active) | ○ (No Position)
"LONG MISSION" Active State Management: Long mission status indicates the strategy currently maintains a bullish position with all systematic monitoring systems engaged in active position management mode. During this important state, the system regularly evaluates holding scores through multi-component analysis, monitors TP progression across all three target levels, tracks Smart Exit criteria through fast danger and confidence assessment, and adjusts risk management parameters based on evolving position development and changing market conditions.
"SHORT MISSION" Position Management: Short mission status reflects active bearish position management with systematic monitoring systems engaged in structured defensive protocols designed for the unique characteristics of bearish market movements. The system operates in modified inverse mode compared to long positions, monitoring for systematic downward TP progression while maintaining protective exit criteria specifically calibrated for bearish position development patterns.
"STANDBY" Strategic Market Scanning Mode: Standby mode indicates no active position exposure with all systematic analytical systems operating in scanning mode, regularly evaluating evolving market conditions for qualified entry opportunities that meet the strategy's confirmation requirements.
# Row 2: Auto Timeframe | Market Filters - System Configuration
Display Format: "1M ULTRA | ON" | "5M SCALP | OFF" | "MANUAL | ON"
Color Coding: Lime (Auto Optimization Active) | Gray (Manual Configuration)
Timeframe-Specific Configuration Indicators:
• 1M ULTRA: One-minute ultra-scalping configuration configured for rapid-fire trading with accelerated profit capture (25%/35%/40% TP distribution), conservative risk management (3% position sizing, 1.0% initial stops), and increased Smart Exit sensitivity (0.1 threshold, 20-bar consecutive limit).
• 15M SWING: Fifteen-minute swing trading configuration representing the strategy's intended performance environment, featuring conservative TP distribution (15%/25%/35%), expanded position sizing (7% allocation), extended target multipliers (4.0/8.0/12.0/18.0 ATR).
• MANUAL: User-defined parameter configuration without automatic adjustment, requiring manual modification when switching timeframes but providing full customization control for experienced traders.
Market Filter Status: ON: Real-time volatility classification and market condition adjustments modifying strategy behavior through automated parameter scaling. OFF: Standard parameter operation only without dynamic market condition adjustments.
# Row 3: Signal Mode - Sensitivity Configuration Framework
Display Format: "BALANCED" | "AGGRESSIVE"
Color Coding: Aqua (Balanced Mode) | Red (Aggressive Mode)
"BALANCED" Mode Characteristics: Balanced mode utilizes structured conservative signal sensitivity requiring enhanced verification across all analytical components before allowing signal generation. This rigorous configuration requires Medium Group scoring ≥5.5 points, Slow Group confirmation ≥3.5 points, and Fast Danger levels ≤2.0 points.
"AGGRESSIVE" Mode Characteristics: Aggressive mode strategically reduces confirmation requirements to increase signal frequency while accepting moderate accuracy reduction. Threshold requirements decrease to Medium Group ≥4.5 points, Slow Group ≥2.5 points, and Fast Danger ≤1.0 points.
# Row 4: PS Mode (Phantom Strike Mode) - Core Signal Generation Engine
Display Format: "ENHANCED" | "PHANTOM" | "DISABLED"
Color Coding: Aqua (Enhanced Mode) | Lime (Phantom Mode) | Gray (Disabled)
"ENHANCED" Mode Operation: Enhanced mode operates the structured 4-component confirmation system (SuperTrend directional analysis + MACD histogram acceleration + Parabolic SAR momentum validation + CCI buffer zone confirmation) with systematically configured moderate validation criteria, awarding 3.0 base points for signal strength calculation.
"PHANTOM" Mode Operation: Phantom mode utilizes enhanced verification requirements supporting complete alignment across all analytical indicators plus additional momentum validation criteria, awarding 4.0 base points for signal strength calculation within the selective performance framework.
# Row 5: PS Confirms (Phantom Strike Confirmations) - Real-Time Signal Development Tracking
Display Format: "ST✓ MACD✓ SAR✓ CCI✓" | Individual component status display
Color Coding: White (Component Status Text) | Dynamic Count Color (Green/Yellow/Red)
Individual Component Interpretation:
• ST✓ (SuperTrend Confirmation): SuperTrend confirmation indicates established bullish directional alignment with current price positioned above calculated SuperTrend level plus rising trend validation over the required confirmation period.
• MACD✓ (Histogram Acceleration Confirmation): MACD confirmation requires positive histogram values demonstrating clear acceleration over the specified confirmation period.
• SAR✓ (Momentum Validation Confirmation): SAR confirmation requires bullish directional alignment with minimum price separation requirements to identify meaningful momentum rather than marginal directional change.
• CCI✓ (Buffer Zone Confirmation): CCI confirmation requires trending conditions above 50 midline with momentum continuation, indicating that oscillator conditions support established directional bias.
# Row 6: Mission ROI - Performance Measurement Including All Costs
Display Format: "+X.XX%" | "-X.XX%" | "0.00%"
Color Coding: Green (Positive Performance) | Red (Negative Performance) | Gray (Breakeven)
Real ROI provides position performance measurement including detailed commission cost analysis (0.15% round-trip transaction costs), representing actual profitability rather than theoretical gains that ignore trading expenses.
# Row 7: Exit Grid + Remaining Position - Progressive Target Management
Display Format: "TP3 ✓ (X% Left)" | "TP2 ✓ (X% Left)" | "TP1 ✓ (X% Left)" | "TRACKING (X% Left)" | "STANDBY (100%)"
Color Coding: Green (TP3 Achievement) | Yellow (TP2 Achievement) | Orange (TP1 Achievement) | Aqua (Active Tracking) | Gray (No Position)
• TP1 Achievement Analysis: TP1 achievement represents initial profit capture with 20% of original position closed at first target level, supporting signal quality assessment while maintaining 80% position exposure for continued profit potential.
• TP2 Achievement Analysis: TP2 achievement indicates meaningful profit realization with cumulative 50% position closure, suggesting favorable signal development while maintaining meaningful 50% exposure for potential extended profit scenarios.
• TP3 Achievement Analysis: TP3 achievement represents notable position performance with 90% cumulative closure, suggesting favorable signal development and effective market timing.
# Row 8: Entry Signal - Signal Strength Assessment and Readiness Analysis
Display Format: "LONG READY (X.X/10)" | "SHORT READY (X.X/10)" | "WAITING (X.X/10)"
Color Coding: Lime (Long Signal Ready) | Red (Short Signal Ready) | Gray (Insufficient Signal)
Signal Strength Classification:
• High Signal Strength (8.0-10.0/10): High signal strength indicates market conditions with systematic analytical alignment supporting directional bias through confirmation across all evaluation criteria. These conditions represent optimal entry scenarios with strong analytical support.
• Strong Signal Quality (6.0-7.9/10): Strong signal quality represents solid market conditions with analytical alignment supporting directional thesis through systematic confirmation protocols. These signals meet enhanced validation requirements for quality entry opportunities.
• Moderate Signal Strength (4.5-5.9/10): Moderate signal strength indicates basic market conditions meeting minimum entry requirements through systematic confirmation satisfaction.
# Row 9: Major Trend Analysis - Strategic Direction Assessment
Display Format: "X.X% STRONG BULL" | "X.X% BULL" | "X.X% BEAR" | "X.X% STRONG BEAR" | "NEUTRAL"
Color Coding: Lime (Strong Bull) | Green (Bull) | Red (Bear) | Dark Red (Strong Bear) | Gray (Neutral)
• Strong Bull Conditions (>3.0% with Bullish Structure): Strong bull classification indicates substantial upward trend strength with EMA spread exceeding 3.0% combined with favorable bullish structure alignment. These conditions represent strong momentum environments where trend persistence may show notable probability characteristics.
• Standard Bull Conditions (1.5-3.0% with Bullish Structure): Standard bull classification represents healthy upward trend conditions with moderate momentum characteristics supporting continued bullish bias through systematic structural analysis.
# Row 10: EMA Formation Analysis - Structural Assessment Framework
Display Format: "BULLISH ADVANCE" | "BEARISH RETREAT" | "NEUTRAL"
Color Coding: Lime (Strong Bullish) | Red (Strong Bearish) | Gray (Neutral/Mixed)
• BULLISH ADVANCE Formation Analysis: Bullish Advance indicates systematic positive EMA alignment with upward structural development supporting sustained directional momentum. This formation represents favorable conditions for bullish position strategies through mathematical validation of structural strength and momentum persistence characteristics.
• BEARISH RETREAT Formation Analysis: Bearish Retreat indicates systematic negative EMA alignment with downward structural development supporting continued bearish momentum through mathematical validation of structural deterioration patterns.
# Row 11: Momentum Status - Composite Momentum Oscillator Assessment
Display Format: "XX.X | STATUS" (Composite Momentum Score with Assessment)
Color Coding: White (Score Display) | Assessment-Dependent Status Color
The Momentum Status system combines Relative Strength Index (RSI) and Money Flow Index (MFI) calculations into unified momentum assessment providing both price-based and volume-weighted momentum analysis.
• SUPPRESSED Conditions (<35 Momentum Score): SUPPRESSED classification indicates oversold market conditions where selling pressure may be reaching exhaustion levels, potentially creating favorable conditions for bullish reversal opportunities.
• ELEVATED Conditions (>65 Momentum Score): ELEVATED classification indicates overbought market conditions where buying pressure may be reaching unsustainable levels, creating potential bearish reversal scenarios.
# Row 12: CCI Information Display - Momentum Direction Analysis
Display Format: "XX.X | UP" | "XX.X | DOWN"
Color Coding: Lime (Bullish Momentum Trend) | Red (Bearish Momentum Trend)
The CCI Information Display showcases the CCI SMART system incorporating Arnaud Legoux Moving Average (ALMA) preprocessing combined with rational approximation of the hyperbolic tangent (TANH) function to achieve modified signal processing compared to traditional CCI implementations.
CCI Value Interpretation:
• Extreme Bullish Territory (>80): CCI readings exceeding +80 indicate extreme bullish momentum conditions with potential overbought characteristics requiring careful evaluation for continued position holding versus profit-taking consideration.
• Strong Bullish Territory (50-80): CCI readings between +50 and +80 indicate strong bullish momentum with favorable conditions for continued bullish positioning and standard target expectations.
• Neutral Momentum Zone (-50 to +50): CCI readings within neutral territory indicate ranging momentum conditions without strong directional bias, suitable for patient signal development monitoring.
• Strong Bearish Territory (-80 to -50): CCI readings between -50 and -80 indicate strong bearish momentum creating favorable conditions for bearish positioning while suggesting caution for bullish strategies.
• Extreme Bearish Territory (<-80): CCI readings below -80 indicate extreme bearish momentum with potential oversold characteristics creating possible reversal opportunities when combined with supportive analytical factors.
# Row 13: SAR Network - Multi-Component Momentum Analysis
Display Format: "X.XX% | BULL STRONG ↗INF" | Complex Multi-Component Analysis
Color Coding: Lime (Bullish Strong) | Green (Bullish Moderate) | Red (Bearish Strong) | Orange (Bearish Moderate) | White (Inflection Priority)
SAR Distance Percentage Analysis: The distance percentage component measures price separation from SAR level as percentage of current price, providing quantification of momentum strength through mathematical price relationship analysis.
SAR Strength Classification Framework:
• STRONG Momentum Conditions (>75% of Strength Range): STRONG classification indicates significant momentum conditions with price-SAR separation exceeding 75% of calculated strength range, representing notable directional movement with sustainability characteristics.
• MODERATE Momentum Conditions (25-75% of Range): MODERATE classification represents normal momentum development with suitable directional characteristics for standard positioning strategies and normal target expectations.
• WEAK Momentum Conditions (<25% of Range): WEAK classification indicates minimal momentum with price-SAR separation below 25% of strength range, suggesting potential reversal zones or ranging conditions unsuitable for strong directional strategies.
Inflection Detection System:
• Bullish Inflection (↗INF): Bullish inflection detection identifies moments when SAR momentum transitions from declining to rising through systematic rate-of-change analysis over 5-period lookback periods. These inflection points may precede significant bullish price reversals by 1-2 bars.
• Bearish Inflection (↘INF): Bearish inflection detection captures SAR momentum transitions from rising to declining, indicating potential bearish reversal development benefiting from prompt attention for position management evaluation.
# Row 14: VWAP Context Analysis - Institutional Volume-Weighted Price Reference
Display Format: "Daily: XXXX.XX (+X.XX%)" | "N/A (Index/Futures)"
Color Coding: Lime (Above VWAP Premium) | Red (Below VWAP Discount) | Gray (Data Unavailable)
Volume-Weighted Average Price (VWAP) provides institutional-level price reference showing mathematical average price where significant volume has transacted throughout the specified period. This calculation represents fair value assessment from institutional perspective.
• Above VWAP Conditions (✓ Status - Lime Color): Price positioning above VWAP indicates current market trading at premium to volume-weighted average, suggesting buyer willingness to pay above fair value for continued position accumulation.
• Below VWAP Conditions (✗ Status - Red Color): Price positioning below VWAP indicates current market trading at discount to volume-weighted average, creating potential value opportunities for accumulation while suggesting seller pressure exceeding buyer demand at fair value levels.
# Row 15: TP SL System Configuration - Dynamic vs Static Target Management
Display Format: "DYNAMIC ATR" | "STATIC %"
Color Coding: Aqua (Dynamic ATR Mode) | Yellow (Static Percentage Mode)
• DYNAMIC ATR Mode Analysis: Dynamic ATR mode implements systematic volatility-adaptive target management where all profit targets and stop losses automatically scale based on current market volatility through ATR (Average True Range) calculations. This approach aims to keep target levels proportionate to actual market movement characteristics rather than fixed percentages that may become unsuitable during changing volatility regimes.
• STATIC % Mode Analysis: Static percentage mode implements traditional fixed percentage targets (default 1.0%/2.5%/3.8%/4.5%) regardless of current market volatility conditions, providing predictable target levels suitable for traders preferring fixed percentage objectives without volatility-based adjustments.
# Row 16: TP Sequence Progression - Systematic Achievement Tracking
Display Format: "1 ✓ 2 ✓ 3 ○" | "1 ○ 2 ○ 3 ○" | Progressive Achievement Display
Color Coding: White text with systematic achievement progression
Status Indicator: ✓ (Achievement Confirmed) | ○ (Target Not Achieved)
• Complete Achievement Sequence (1 ✓ 2 ✓ 3 ✓): Complete sequence achievement represents significant position performance with systematic profit realization across all primary target levels, indicating favorable signal quality and effective market timing.
• Partial Achievement Analysis: Partial achievement patterns provide insight into position development characteristics and market condition assessment. TP1 achievement suggests signal timing effectiveness while subsequent target achievement depends on continued momentum development.
• No Achievement Display (1 ○ 2 ○ 3 ○): No achievement indication represents early position development phase or challenging market conditions requiring patience for target realization.
# Row 17: Mission Duration Tracking - Time-Based Position Management
Display Format: "XX/XXX" (Current Bars/Maximum Duration Limit)
Color Coding: Green (<50% Duration) | Orange (50-80% Duration) | Red (>80% Duration)
• Normal Duration Periods (Green Status <50%): Normal duration indicates position development within expected timeframes based on signal characteristics and market conditions, representing healthy position progression without time pressure concerns.
• Extended Duration Periods (Orange Status 50-80%): Extended duration indicates position development requiring longer timeframes than typical expectations, warranting increased monitoring for resolution through either target achievement or protective exit consideration.
• Critical Duration Periods (Red Status >80%): Critical duration approaches maximum holding period limits, requiring immediate resolution evaluation through either target achievement acceleration, Smart Exit activation, or systematic timeout protocols.
# Row 18: Last Exit Analysis - Historical Exit Pattern Assessment
Display Format: Exit Reason with Color-Coded Classification
Color Coding: Lime (TP Exits) | Red (Critical Exits) | Yellow (Stop Losses) | Purple (Smart Low) | Orange (Timeout/Sustained)
• Profit-Taking Exits (Lime/Green): TP1/TP2/TP3/Final Target exits indicate position management with systematic profit realization suggesting signal quality and strategy performance.
• Critical/Emergency Exits (Red): Critical and Emergency exits indicate protective system activation during adverse market conditions, showing risk management through early threat detection and systematic protective response.
• Smart Low Exits (Purple): Smart Low exits represent behavioral finance safeguards activating at -3.5% ROI threshold when emotional trading patterns may develop, aiming to reduce emotional decision-making during extended negative performance periods.
# Row 19: Fast Danger Assessment - Immediate Threat Detection System
Display Format: "X.X/10" (Danger Score out of 10)
Color Coding: Green (<3.0 Safe) | Yellow (3.0-5.0 Moderate) | Red (>5.0 High Danger)
The Fast Danger Assessment system provides real-time evaluation of immediate market threats through six independent measurement systems: SAR distance deterioration, momentum reversal detection, extreme CCI readings, volatility spike analysis, price action intensity, and combined threat evaluation.
• Safe Conditions (Green <3.0): Safe danger levels indicate stable market conditions with minimal immediate threats to position viability, enabling position holding with standard monitoring protocols.
• Moderate Concern (Yellow 3.0-5.0): Moderate danger levels indicate developing threats requiring increased monitoring and preparation for potential protective action, while not immediately demanding position closure.
• High Danger (Red >5.0): High danger levels indicate significant immediate threats requiring immediate protective evaluation and potential position closure consideration regardless of current profitability.
# Row 20: Holding Confidence Evaluation - Position Viability Assessment
Display Format: "X.X/10" (Confidence Score out of 10)
Color Coding: Green (>6.0 High Confidence) | Yellow (3.0-6.0 Moderate Confidence) | Red (<3.0 Low Confidence)
Holding Confidence evaluation provides systematic assessment of position viability through analysis of trend strength maintenance, formation quality persistence, momentum sustainability, and overall market condition favorability for continued position development.
• High Confidence (Green >6.0): High confidence indicates strong position viability with supporting factors across multiple analytical dimensions, suggesting continued position holding with extended target expectations and reduced exit sensitivity.
• Moderate Confidence (Yellow 3.0-6.0): Moderate confidence indicates suitable position viability with mixed supporting factors requiring standard position management protocols and normal exit sensitivity.
• Low Confidence (Red <3.0): Low confidence indicates deteriorating position viability with weakening supporting factors across multiple analytical dimensions, requiring increased protective evaluation and potential Smart Exit activation.
# Row 21: Volatility | Market Status - Volatility Environment & Market Filter Status
Display Format: "NORMAL | NORMAL" | "HIGH | HIGH VOL" | "EXTREME | NEWS FILTER"
Color Coding: White (Information display)
Volatility Classification Component (Left Side):
- DEAD: ATR ratio <0.8x average, minimal price movement requiring careful timing
- LOW: ATR ratio 0.8-1.2x average, stable conditions enabling position increase potential
- NORMAL: ATR ratio 1.2-1.8x average, typical market behavior with standard parameters
- HIGH: ATR ratio 1.8-2.5x average, elevated movement requiring increased caution
- EXTREME: ATR ratio >2.5x average, chaotic conditions triggering enhanced protection
Market Status Component (Right Side):
- NORMAL: Standard market conditions, no special filters active
- HIGH VOL: High volatility detected, position reduction and exit sensitivity increased
- EXTREME VOL: Extreme volatility confirmed, enhanced protective protocols engaged
- NEWS FILTER: Major economic event detected, 80% position reduction active
- GAP MODE: Weekend gap identified, increased caution until normal flow resumes
Combined Status Interpretation:
- NORMAL | NORMAL: Suitable trading conditions, standard strategy operation
- HIGH | HIGH VOL: Elevated volatility confirmed by both systems, 40% position reduction
- EXTREME | EXTREME VOL: High volatility warning, 70% position reduction active
📊VISUAL SYSTEM INTEGRATION
Chart Analysis & Market Visualization
CCI SMART Buffer Zone Visualization System - Dynamic Support/Resistance Framework
Dynamic Zone Architecture: The CCI SMART buffer system represents systematic visual integration creating adaptive support and resistance zones that automatically expand and contract based on current market volatility through ALMA-smoothed true range calculations. These dynamic zones provide real-time support and resistance levels that adapt to evolving market conditions rather than static horizontal lines that quickly become obsolete.
Adaptive Color Intensity Algorithm: The buffer visualization employs color intensity algorithms where transparency and saturation automatically adjust based on CCI momentum strength and directional persistence. Stronger momentum conditions produce more opaque visual representations with increased saturation, while weaker momentum creates subtle transparency indicating reduced prominence or significance.
Color Interpretation Framework for Strategic Decision Making:
-Intense Blue/Purple (High Opacity): Strong CCI readings exceeding ±80 with notable momentum strength indicating support/resistance zones suitable for increased position management decisions
• Moderate Blue/Purple (Medium Opacity): Standard CCI readings ranging ±40-80 with normal momentum indicating support/resistance areas for standard position management protocols
• Faded Blue/Purple (High Transparency): Weak CCI readings below ±40 with minimal momentum suggesting cautious interpretation and conservative position management approaches
• Dynamic Color Transitions: Automatic real-time shifts between bullish (blue spectrum) and bearish (purple spectrum) based on CCI trend direction and momentum persistence characteristics
CCI Inflection Circle System - Momentum Reversal Identification: The inflection detection system creates distinctive visual alerts through dual-circle design combining solid cores with transparent glow effects for enhanced visibility across different chart backgrounds and timeframe configurations.
Inflection Circle Classification:
• Neon Green Circles: CCI extreme bullish inflection detected (>80 threshold) with systematic core + glow effect indicating bearish reversal warning for position management evaluation
• Hot Pink Circles: CCI extreme bearish inflection detected (<-80 threshold) with dual-layer visualization indicating bullish reversal opportunity for strategic entry consideration
• Dual-Circle Design Architecture: Solid tiny core providing location identification with large transparent glow ensuring visibility without chart obstruction across multiple timeframe analyses
SAR Visual Network - Multi-Layer Momentum Display Architecture
SAR Visualization Framework: The SAR visual system implements structured multi-layer display architecture incorporating trend lines, strength classification markers, and momentum analysis through various visual elements that automatically adapt to current momentum conditions and strength characteristics.
SAR Strength Visual Classification System:
• Bright Triangles (High Intensity): Strong SAR momentum exceeding 75% of calculated strength range, indicating significant momentum quality suitable for increased positioning considerations and extended target scenarios
• Standard Circles (Medium Intensity): Moderate SAR momentum within 25-75% strength range, representing normal momentum development appropriate for standard positioning approaches and regular target expectations
• Faded Markers (Low Intensity): Weak SAR momentum below 25% strength range, suggesting caution and conservative positioning during minimal momentum conditions with increased exit sensitivity
⚠️IMPORTANT DISCLAIMERS AND RISK WARNINGS
Past Performance Limitations: The backtesting results presented represent hypothetical performance based on historical market data and do not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice. No trading strategy can guarantee 100% success or eliminate the risk of loss.
Users must approach trading with appropriate caution, never risking more than they can afford to lose.
Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
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### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
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### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
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### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
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### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
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### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
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### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
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### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
Btc and Eth 5 min winnerWhat the Strategy Does
Finding the Trend (Like Watching the Bus Move): The strategy uses special tools called Hull Moving Averages (HMAs) to figure out if Bitcoin (BTC) Ethereum (ETH) prices are generally going up or down. It looks at short-term (5 minutes) and long-term (10 minutes) price movements to make sure the “bus” (the market) is moving strongly in one direction—up for buying, down for selling.
Spotting Good Times to Jump On (Buy or Sell Signals): It looks for two types of opportunities:
Pullbacks: When the price dips a little while still moving up (like the bus slowing down but not stopping), it’s a chance to buy.
Breakouts: When the price suddenly jumps higher after being stuck (like the bus speeding up), it’s another chance to buy. It does the opposite for selling when prices are dropping.
It also checks if there’s enough “passenger activity” (volume) and momentum (speed of price change) to make sure it’s a good move.
Avoiding Traffic Jams (Filters): The strategy uses tools like RSI (to check if the market’s too fast or too slow), volume (to see if enough people are trading), and ATR (to measure how wild the price swings are). It skips trades if things look too chaotic or if the trend isn’t strong enough.
Setting Safety Stops and Profit Targets: Once you’re on the “bus,” it sets rules to protect you:
Stop-Loss: If the price moves against you by a small amount (0.5% of the typical price swing), you jump off to avoid losing too much—think of it as getting off before the bus crashes.
Take-Profit: If the price moves in your favor by a small amount (1.0% of the typical swing), you cash out—imagine getting off at your stop with a profit.
Trailing Stop: If the price keeps moving your way, it adjusts your exit point to lock in more profit, like moving your stop closer as the bus keeps going.
Using Leverage (10x Boost): This strategy uses 10x leverage on Binance futures, meaning for every $1 you have, you trade like you have $10. This can make profits (or losses) 10 times bigger, so it’s risky but can be rewarding if you’re careful.
Why 5 Minutes and Bitcoin and Ethereum?
5-Minute Chart: This is like checking the bus every 5 minutes to make quick, small trades—perfect for fast, short profits.
Bitcoin Ethereum (BTC/USD)(ETH/USD): It’s the most popular and liquid crypto, so there’s lots of activity, making it easier to jump on and off without getting stuck.
Why It Aims for 90% Wins (But Be Realistic)
The goal is to win 9 out of 10 trades by being super picky about when to trade—only jumping on when the trend, momentum, and volume are all perfect. But in real trading, markets can be unpredictable, so 90% is very hard to achieve. Still, this strategy tries to be as accurate as possible by avoiding bad moves and focusing on strong trends.
Risks for a New Trader
Leverage: Trading with 10x leverage means small price moves can lead to big losses if you’re not careful. Start with a demo account (pretend money) on TradingView or Binance to practice.
Learning Curve: This strategy uses technical terms (like HMAs, RSI) and tools you’ll need to learn over time. Don’t rush—just practice and ask questions!
How to Use It
Go to TradingView, load this strategy on a 5-minute BTC/USD futures chart on Binance.
Watch the green triangles (buy signals) and red triangles (sell signals) on the chart—they tell you when to trade.
Use the stops and targets to manage your trades—don’t guess, let the strategy guide you.
Start small, learn from each trade, and don’t risk money you can’t afford to lose.
This is like learning to ride a bike—start slow, practice, and you’ll get better. If you have more questions or want simpler tips, feel free to ask! Trading can be fun and rewarding, but it takes patience and practice.
Intraday Golden duckKey Components
Plotting DTR Levels
DTR High 1 & Low 1 are plotted with a bold green and red line (Major Levels).
DTR High 2 & Low 2 are plotted with a lighter green and red line (Minor Levels).
This visualizes potential breakout and stop-loss zones.
Defining Market Hours
The strategy runs only between:
Start Time: 9:15 AM (Market Open)
End Time: 3:00 PM (Market Close)
Trades can only occur during this period.
Avoiding Multiple Trades Per Day
A boolean variable trade_taken_today ensures that:
Only one trade is executed per day (either Buy or Sell).
It resets at the beginning of a new trading day.
Entry Conditions
A long position (Buy) is entered when:
The market is open.
The close price breaks above dtr_high_1.
No other trade has been executed yet.
A short position (Sell) is entered when:
The market is open.
The close price drops below dtr_low_1.
No other trade has been executed yet.
Stop-Loss Conditions
To protect against large losses, stop-loss levels are placed at DTR 2 levels:
For Long Trades: If price falls below dtr_high_2, the trade exits.
For Short Trades: If price rises above dtr_low_2, the trade exits.
Using Parabolic SAR for Additional Exit Signals
The Parabolic SAR (PSAR) is used to trail stop-loss:
Long Exit: If price falls below PSAR, the position is closed.
Short Exit: If price rises above PSAR, the position is closed.
Universal Exit Condition (3:00 PM)
At exactly 3:00 PM, all positions are forcefully closed, ensuring no overnight risk.
Execution Logic
If Buy Condition is met → Enter Long position.
If Sell Condition is met → Enter Short position.
If Stop-Loss or PSAR condition triggers → Exit the trade.
At 3:00 PM, close all positions.
Key Features & Benefits
✅ Intraday Only: No overnight risk.
✅ One Trade per Day: Avoids overtrading.
✅ Dynamic Levels: Adapts to market volatility.
✅ PSAR Protection: Helps reduce drawdowns.
✅ Universal Exit: Ensures systematic closing.
This strategy is designed for traders looking for a systematic, rule-based approach to intraday trading using price action and volatility expansion principles. 🚀
Dynamic RSI Mean Reversion StrategyDynamic RSI Mean Reversion Strategy
Overview:
This strategy uses an RSI with ATR-Adjusted OB/OS levels in order to enhance the quality of it's mean reversion trades. It also incorporates a form of trend filtering in an effort to minimize downside and maximize upside. The backtest has fewer trades, as it uses substantial filtering to enhance trade quality. As you can see, I didn't cherry pick the results, so the results aren't the most beautiful thing you'll see in your life. I did this to ensure nobody gets misled. If you need a higher frequency of trades, consider removing the trend filter or increasing the length of the EMAs used for trend detection.
Features:
Dynamic OB/OS Levels: Uses ATR to adjust overbought and oversold thresholds dynamically, making the RSI more responsive in varying volatility conditions. This approach enhances signal strength by expanding the RSI range in high volatility and tightening it in low volatility.
Mean Reversion Focus: Designed for mean reversion but incorporates a trend-following filter to reduce countertrend trades. When the RSI is high, it often indicates an uptrend, so a trend filter prevents shorting in these cases and the same goes for downtrends and longing.
Trend Filtering: A moving average cross trend filter checks for the trend direction, with the RSI signal line color-coded to reflect trend shifts. Entries occur when the RSI crosses above or below the dynamic thresholds and is not a countertrend trade.
Stop Losses: Stop losses are set based on ATR distance from the entry price, providing volatility-adjusted protection.
Note:
If you're using this strategy on assets with a higher price, remember to increase the initial capital in the strategy settings. Otherwise, the strategy won't generate any (or many) trades and you'll end up with some inaccurate results.
Recommended Use:
Test it on different assets and timeframes. I’ve found the best results with standard RSI inputs, a relatively slow ATR, and a slower MA cross for trend filtering. Thus, the defaults are set that way. If the trend metrics are too slow, you’ll filter out too many good trades while allowing crummy ones; if too fast, most trades may be filtered out. As always, this has a lot of configurability so experiment to find the balance that works for your trading style.
Price-Volume w Trendline - Strategy [presentTrading]█ Introduction and How it is Different
The Price-Volume with Trendline Strategy is an innovative strategy that combines volume profile analysis, price-based Z-scores, and dynamic trendline filtering to identify optimal entry and exit points in the market. What sets this strategy apart is the integration of volume concentration (Point of Control or PoC) with dynamic volatility thresholds. Additionally, this strategy introduces a multi-step take profit (TP) mechanism that adjusts based on predefined levels, allowing traders to exit trades progressively while capitalizing on market momentum.
BTCUSD 6hr LS Performance
█ Strategy, How it Works: Detailed Explanation
The combination of multiple indicators and methodologies serves to create a more robust and reliable trading system. Each element is carefully chosen for its complementary role in providing accurate signals while minimizing false entries and exits. Here’s why the different components were chosen and how they work together:
- PoC and Z-Scores: The volume profile identifies key price areas, while the Z-score measures deviations from the mean. Together, they highlight points where the market is likely to react. For example, when the Z-score indicates an oversold condition near a PoC support level, it increases the probability of a reversal, providing a clear entry signal.
- Trendlines and Z-Scores: Trendlines serve as a secondary filter to ensure that price deviations identified by Z-scores align with broader market trends. This ensures that trades are only entered when the price has both deviated from its average and broken through a significant trendline level, reducing the likelihood of false signals.
- Multi-Step TP and Risk Management: Finally, the multi-step take profit logic works in tandem with the entry signals generated by the PoC, Z-scores, and trendlines. As the price moves in favor of the trade, profits are gradually locked in, ensuring the trader captures gains while still leaving room for further upside.
🔶 Point of Control (PoC) and Volume Profile Analysis
The PoC identifies the price level with the highest volume concentration within a specified lookback period. This price level represents where the most trading activity has occurred, often acting as a strong support or resistance. By breaking down the range into several rows (bins), the strategy identifies how much volume was traded at each price level.
🔶 Z-Score Calculation
The Z-score is a statistical metric that measures how far the current price is from its mean, expressed in terms of standard deviations. This is calculated both for price deviation and PoC-based deviation.
🔶 Trendline Breakout Filtering
The trendline filtering is a crucial aspect that refines entry signals by confirming trend continuation or reversals. It calculates trendlines based on pivot highs and lows using the selected method (e.g., ATR or standard deviation).
🔶 Multi-Step Take Profit
The multi-step take profit mechanism allows the strategy to take partial profits at several predefined levels. For example, when the price reaches 3%, 8%, 14%, or 21% above (or below) the entry price, it exits portions of the position. This is a useful technique for locking in profits as the market moves favorably.
Local
█ Usage
The Price-Volume with Trendline Strategy can be applied to various asset classes, including stocks, cryptocurrencies, and commodities. It is particularly effective in volatile markets where price deviations and volume concentrations signal potential reversals or trend continuations. By adjusting the settings for volatility and the lookback period, this strategy can be tailored to both short-term intraday trades and longer-term swing trades.
█ Default Settings
The default settings in the strategy play a vital role in shaping its performance.
- POC_lookbackLength (144): This defines the number of bars used to calculate the PoC. A longer lookback captures more data, leading to a more stable PoC, but may result in delayed signals. A shorter lookback increases responsiveness but may introduce noise.
- priceDeviationLength (200): This determines the period for calculating the standard deviation of price. A higher length smooths out the volatility, reducing the likelihood of false signals. Shorter lengths make the strategy more sensitive to sudden price movements.
- TL_length (14): Controls the swing detection period for trendline calculation. A shorter length will generate more frequent trendline breakouts, while a longer length captures only significant moves.
- Stop Loss and Take Profit: The strategy offers both fixed and SuperTrend-based stop losses. SuperTrend is adaptive to volatility, while fixed stop losses provide simpler risk control. The multi-step take profit ensures that profits are secured progressively, which can improve performance in trending markets by reducing the risk of full reversals.
Each of these settings can significantly affect the strategy’s risk-reward balance. For instance, increasing the stop loss level or the take profit percentages allows the strategy to stay in trades longer, potentially increasing profit per trade but at the cost of larger drawdowns. Conversely, tighter stops and smaller profit targets result in more frequent trades with lower average profit per trade.
Monthly Day Long Strategy with VIX and Risk ManagementThis trading strategy is designed to open long positions on a specific day of the month, with the conditions for entry and exit based on the VIX index and additional risk management techniques. The strategy includes stop-loss and take-profit features to manage risk and lock in profits.
Inputs:
Entry Day of the Month (entry_day): Specifies which day of the month to consider for initiating a trade. The default value is the 27th.
Hold Duration (Days) (hold_duration_days): Defines how many days to hold the position after opening. The default value is 4 days.
VIX Threshold (vix_threshold): Sets the maximum acceptable value for the VIX index to consider an entry. If the VIX is below this threshold, it signals a potential trade. The default value is 20.0.
Stop Loss (%) (stop_loss_percentage): Determines the percentage below the entry price where the stop-loss will be triggered. The default value is 2.0%.
Take Profit (%) (take_profit_percentage): Sets the percentage above the entry price where the take-profit will be triggered. The default value is 5.0%.
Functions:
next_weekday(date): Adjusts the entry date to the next Monday if it falls on a weekend (Saturday or Sunday). This ensures trades do not occur on non-trading days.
Logic:
Entry Conditions:
Date Check: Opens a long position if the current date matches the adjusted entry date (the 27th or the next Monday if the 27th falls on a weekend).
VIX Filter: The VIX index value must be below the specified threshold (e.g., 20.0) to consider an entry.
Exit Conditions:
Time-Based Exit: Closes the position after the hold duration of 4 days.
Stop-Loss: Automatically closes the position if the price drops to a level that is a specified percentage below the entry price (e.g., 2.0%).
Take-Profit: Closes the position if the price rises to a level that is a specified percentage above the entry price (e.g., 5.0%).
Plots:
VIX Plot: Displays the VIX index on the chart for visual reference.
VIX Threshold Line: A horizontal line representing the VIX threshold value.
Summary:
The strategy aims to take advantage of specific entry days while filtering trades based on VIX levels to ensure market conditions are favorable. Risk management is enhanced through stop-loss and take-profit settings, which help in controlling potential losses and securing profits. The strategy ensures trades are only made on trading days and not on weekends, adjusting automatically to the next Monday if needed.
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BBSR Extreme Strategy [nachodog]The Bollinger Bands Stochastic RSI Extreme Strategy is a comprehensive trading approach designed for use on the TradingView platform, employing a combination of Bollinger Bands and the Stochastic RSI to identify potential entry and exit points in the market. This strategy is converted into Pine Script version 5 and is specifically tailored as a strategy rather than a mere study, allowing traders to simulate and backtest their trades within the TradingView environment.
Strategy Overview:
Bollinger Bands serve as the primary tool for volatility and price level analysis. By calculating the standard deviation of price movements around a simple moving average (SMA), this strategy identifies the upper and lower bounds of price fluctuations, helping traders spot potential reversal points.
Stochastic RSI is used to gauge the momentum by comparing the closing price's position relative to its price range over a certain period. This indicator helps in determining overbought or oversold conditions, providing insights into potential bullish or bearish momentum.
Entry Signals:
Bullish Entry: The strategy signals a long entry when the price moves from below to above the lower Bollinger Band, coupled with a Stochastic RSI indicating an exit from oversold conditions. This suggests an uptrend initiation, prompting a buy order.
Bearish Entry: Conversely, a short entry is signaled when the price drops from above to below the upper Bollinger Band while the Stochastic RSI moves from overbought territory. This condition indicates a potential downtrend, triggering a sell order.
Exit Criteria:
Stop Loss: A key feature of this strategy is the inclusion of a user-defined stop loss percentage, which helps manage risk by specifying the maximum allowable loss per trade.
Bearish Exit for Long Positions: Long positions are exited either when a bearish signal is detected or when the price crosses below the lower Bollinger Band, suggesting a reversal or weakening of the bullish trend.
Bullish Exit for Short Positions: Short positions are closed upon a bullish signal or when the price crosses above the upper Bollinger Band, indicating a potential reversal or diminishing bearish momentum.
Strategy Benefits:
The strategy provides a structured framework for entering and exiting trades, leveraging the strengths of both Bollinger Bands and Stochastic RSI.
It includes parameters for customization, such as the stop loss percentage, allowing traders to align the strategy with their risk tolerance and trading objectives.
The ability to backtest and simulate trades on TradingView enhances its utility, offering insights into the strategy's performance under historical market conditions.
Overall, the Bollinger Bands Stochastic RSI Extreme Strategy is designed for traders who seek to capitalize on trend reversals and momentum shifts, with built-in risk management features to safeguard against significant losses.
Strategy / Connectable [Azullian]The connectable strategy serves as a foundational component in our indicator system on TradingView, designed for intuitive testing, visualization, and construction of trading strategies. In concert with the connectable signal filter , it forms a cohesive unit that allows for efficient signal processing and strategy implementation. This integration enables the strategy to receive and act on weighted signals from various connectable indicators, making it a versatile tool for both novice and experienced traders.
Let's review the separate parts of this indicator.
█ STRATEGY INPUTS
We've provided an input to connect a signal filter or indicators or chains (→) which is set to 'Close' by default.
An input has several controls:
• Input: Connect indicators or signal filter here, choose indicators with a compatible : Signal connector.
• SM - Signal Mode: Choose a trading direction compatible with the settings in your signal filter
█ POSITION INVESTMENT
Determine the percentage of your trading budget you would like to use in each position based on the strategy's profit or loss.
• LINVB - Loss Investment Base: Choose which base to use to determine the investment percentage when the strategy is in a loss.
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• LINV% - Loss Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 10% in loss, and a initial capital of $100, and the investment base is set to equity with a percentage of 50%, your investment will be 50% of $90, $45.
• PINVB - Profit Investment Base: Choose which base to use to determine the investment percentage when the strategy is in profit.
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• PINV% - Profit Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 10% in profit, and an initial capital of $100, and the investment base is set to equity with a percentage of 100%, your investment will be 100% of $110, $110.
• RISK% - Risk Percentage:
○ Determine how much of the calculated position investment is at risk when the stop-loss is hit.
- For example, 1% of $45 represents a maximum loss of $0.45.
○ Risk percentage works together with the stop loss and the max leverage.
• MXLVG - Maximum Leverage:
○ Investigate the trading rules for your trading pair and use the maximum allowed amount of leverage.
○ To determine the number of contracts to be bought or sold, considering the stop loss and the specified risk percentage, the maximum leverage available will constrain the amount of leverage utilized to ensure that the maximum risk threshold is not exceeded. For instance, suppose the stop loss is set at 1%, and the risk percentage is defined as 10%. Initially, the calculated leverage to be used would be 10. However, if there is a maximum leverage cap set at 5, it would constrain the calculated leverage of 10 to adhere to the maximum limit of 5.
█ EXIT STOP LOSS
Determine the Stop Loss price based on your selected configuration.
As the stop loss is an integral part of the ordered contracts calculation used in conjunction with the Risk and Max leverage, you'll always need to provide a stop loss price.
• SLB - Stop Loss Base: Choose a stop loss mode for calculating stop loss prices.
○ Risk: Determines the price using the Risk parameter (RISK%) and maximum leverage (MXLVG). In this case, SLB% will not have any impact.
○ Price Entry + Offset: Calculates the stop loss price based on a offset percentage (SLB%) from the entry price of the position.
• SLB% - Stop Loss Base Percentage: Define an offset percentage that will be applied in the price entry + offset stop loss mode.
• SLT - Stop Loss Trailing:
○ Fixed: The initial stop loss will be kept and no trailing stop loss will be applied.
○ Trail Price: Computes the trailing stop loss price based on an offset percentage (SLT%) from the closing price of the current candle.
- If a better stop loss price is calculated, it will be set as the new stop loss price.
○ Trail Incr: Adapts the trailing stop loss price based on the offset percentage (SLT%).
- Each price change in favor of your position will incrementally adapt the trailing stop loss with SLT%.
• SLT% - Stop Loss Trailing Percentage: This percentage serves as an offset or increment depending on your chosen trailing mode.
█ EXIT TAKE PROFIT
Determine the Take Profit price based on your selected configuration.
• TPB - Take Profit Base: Choose a take profit mode for calculating take profit prices.
○ Reward: Determines the take profit price using the Risk parameter (RISK%) and the calculated Stop Loss price and the set reward percentage (TPB%).
- For example: Risk 1%, Calculated Stop loss price: $90, Entry price: $100, Reward (TPB%): 2%, will result in a take profit price on $120.
○ Price Entry + Offset: Calculates the take profit price based on a offset percentage (TPB%) from the entry price of the position.
- For example: Entry price: $100, Offset (TPB%): 2%, will result in a take profit price on $102.
• TPB% - Take Profit Base Percentage: Define an offset percentage that will be applied in the price entry + offset take profit mode.
• TPT - Take Profit Trailing:
○ Fixed: The initial take profit will be kept and no trailing take profit will be applied.
○ Trail Price: Computes the trailing take profit price based on an offset percentage (TPT%) from the closing price of the current candle.
- If an applicable take profit price is calculated, it will be set as the new take profit price.
○ Trail Incr: Adapts the trailing take profit price based on the offset percentage (TPT%). Each price change against your position will incrementally adapt the trailing take profit with TPT%.
• TPT% - Take Profit Trailing Percentage: This percentage serves as an offset or increment depending on your chosen trailing mode.
█ STRATEGY CONDITIONS
Specify when the strategy is permitted to execute trades.
• DATE: Enable the Date Range filter to restrict entries to a specific date range.
○ START: Set a start date and hour to commence trading.
○ END: Set an end date and hour to conclude trading within the defined range.
■ VISUALS
• LINE: Activate a colored dashed diagonal line to visually connect the entry and exit points of positions.
• SLTP: Enable visualization of stop loss, take profit, and break-even levels.
• PNL: Enable Break-Even and Close Lines along with a colored area in between to visualize profit and loss.
• ☼: Brightness % : Adjust the opacity of the plotted trading visuals.
• P - Profit Color : Choose the color for profit-related elements.
• L - Loss Color: Choose the color for loss-related elements.
• B - Breakeven Color : Select the color for break-even points.
• EL - Long Color: Specify the color for long positions.
• ES - Short Color: Specify the color for short positions.
• TRADE LABELING: For better analysis we've labeled all entries and exits conform with the type of order your strategy has executed, some examples:
○ XL-TP-150: Exit Long - Take Profit - Position 150
○ XS-TP-154: Exit Short - Take Profit - Position 154
○ XL-SL-160: Exit Long - Stop Loss - Position 160
○ XS-SL-164: Exit Short - Stop Loss - Position 164
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up the strategy with a signal filter and an RSI indicator
Let's connect the Strategy to a connectable signal filter and a connectable RSI indicator :
1. Load all relevant indicators
• Load RSI / Connectable
• Load Signal filter / Connectable
• Load Strategy / Connectable
2. Signal Filter: Connect the RSI to the Signal Filter
• Open the signal filter settings
• Choose one of the three input dropdowns (1→, 2→, 3→) and choose : RSI / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter signals settings if needed
• The default settings of the filter enable EL (Enter Long), XL (Exit Long), ES (Enter Short) and XS (Exit Short).
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold (TH) is set at 5. This allows each occurrence to score, as the default score in each connectable indicator is 1 point above the threshold. Adjust to your liking.
5. Strategy: Connect the strategy to the signal filter in the strategy settings
• Select the strategy input → and select the Signal filter: Signal connector
6. Strategy: Enable filter compatible directions
• Set the signal mode of the strategy to a compatible direction with the signal filter.
Now that everything is connected, you'll notice green spikes in the signal filter representing long signals, and red spikes indicating short signals. Trades will also appear on the chart, complemented by a performance overview. Your journey is just beginning: delve into different scoring mechanisms, merge diverse connectable indicators, and craft unique chains. Instantly test your results and discover the potential of your configurations. Dive deep and enjoy the process!
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES AND CLARIFICATIONS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Recalculate: While this strategy has undergone extensive testing, enabling recalculation options like 'After order is filled' or 'On every tick' may lead to unexpected behavior.
• Fill orders: The strategy is thoroughly tested, yet enabling fill order options such as 'Using bar magnifier', 'On bar close', or 'Using standard OHLC' might result in unexpected outcomes.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Optimized for crypto trading: While many principles are common across markets, this strategy is specifically optimized and tested for crypto trading.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
Investments/swing trading strategy for different assetsStop worrying about catching the lowest price, it's almost impossible!: with this trend-following strategy and protection from bearish phases, you will know how to enter the market properly to obtain benefits in the long term.
Backtesting context: 1899-11-01 to 2023-02-16 of SPX by Tvc. Commissions: 0.05% for each entry, 0.05% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 5 indicators are used:
One Ema of 200 periods
Atr Stop loss indicator from Gatherio
Squeeze momentum indicator from LazyBear
Moving average convergence/divergence or Macd
Relative strength index or Rsi
Trade conditions:
There are three type of entries, one of them depends if we want to trade against a bearish trend or not.
---If we keep Against trend option deactivated, the rules for two type of entries are:---
First type of entry:
With the next rules, we will be able to entry in a pull back situation:
Squeeze momentum is under 0 line (red)
Close is above 200 Ema and close is higher than the past close
Histogram from macd is under 0 line and is higher than the past one
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
For closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Second type of entry:
With the next rules, we will not lose a possible bullish movement:
Close is above 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entry, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
---If we keep Against trend option activated, the rules are the same as the ones above, but with one more type of entry. This is more useful in weekly timeframes, but could also be used in daily time frame:---
Third type of entry:
Close is under 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entries, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Risk management
For calculating the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a buy signal at price of 4,000 usd. The stop loss price from atr stop loss is 3,900. You calculate the distance in percent between 4,000 and 3,900. In this case, that distance would be of 2.50%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(2,5%) = 1000usd. It means, you have to use 1000 usd for risking 2.5% of your account.
We will use this risk management for applying compound interest.
In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, etc.
You will find the settings for risk management at the end of the script if you want to change something. But rebember, do not change values from indicators, the idea is to not over optimize the strategy.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
If you activate break even using rsi, when rsi crosses under overbought zone break even will be activated. This can work in some assets.
---Important: In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital---
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!
Some assets and timeframes where the strategy has also worked:
BTCUSD : 4H, 1D, W
SPX (US500) : 4H, 1D, W
GOLD : 1D, W
SILVER : 1D, W
ETHUSD : 4H, 1D
DXY : 1D
AAPL : 4H, 1D, W
AMZN : 4H, 1D, W
META : 4H, 1D, W
(and others stocks)
BANKNIFTY : 4H, 1D, W
DAX : 1D, W
RUT : 1D, W
HSI : 1D, W
NI225 : 1D, W
USDCOP : 1D, W
Stochastic Moving AverageHi all,
This Strategy script combines the power of EMAs along with the Stochastic Oscillator in a trend following / continuation manner, along with some cool functionalities.
I designed this script especially for trading altcoins, but it works just as good on Bitcoin itself and on some Forex pairs.
______ SIGNALS ______
The script has 4 mandatory conditions to unlock a trading signal. Find these conditions for a long trade below (works the exact other way round for shorts)
- Fast EMA must be higher than Slow EMA
- Stochastic K% line must be in oversold territory
- Stochastic K% line must cross over Stochastic D% line
- Price as to close between slow EMA and fast EMA
Once all the conditions are true, a trade will start at the opening of the next
______ SETTINGS ______
- Trade Setup:
Here you can choose to trade only longs or shorts and change your Risk:Reward.
You can also decide to adjust your volume per position according to your risk tolerance. With “% of Equity” your stop loss will always be equal to a fixed percentage of your initial capital (will “compound” overtime) and with “$ Amount” your stop loss will always be 'x' amount of the base currency (ex: USD, will not compound)
Stop Loss:
The ATR is used to create a stop loss that matches current volatility. The multiplier corresponds to how many times the ATR stop losses and take profits will be away from closing price.
- Stochastic:
Here you can find the usual K% & D% length and overbought (OB) and oversold (OS) levels.
The “Stochastic OB/OS lookback” increase the tolerance towards OB/OS territories. It allows to look 'x' bars back for a value of the Stochastic K line to be overbought or oversold when detecting an entry signal.
The “All must be OB/OS” refers to the previous “Stochastic OB/OS lookback” parameter. If this option is ticked, instead of needing only 1 OB/OS value within the lookback period to get a valid signal, now, all bars looked back must be OB/OS.
The color gradient drawn between the fast and slow EMAs is a representation of the Stochastic K% line position. With default setting colors, when fast EMA > slow EMA, gradient will become solid blue when Stochastic is oversold and when slow EMA > fast EMA, gradient will become solid blue when Stochastic is overbought
- EMAs:
Just pick your favorite ones
- Reference Market:
An additional filter to be certain to stay aligned with the current a market index trend (in our case: Bitcoin). If selected reference market (and timeframe) is trading above selected EMA, this strategy will only take long trades (vice-versa for shorts) Because, let’s face it… even if this filter isn’t bulletproof, you know for sure that when Bitcoin tanks, there won’t be many Alts going north simultaneously. Once again, this is a trend following strategy.
A few tips for increased performance: fast EMA and D% Line can be real fast… 😉
As always, my scripts evolve greatly with your ideas and suggestions, keep them coming! I will gladly incorporate more functionalities as I go.
All my script are tradable when published but remain work in progress, looking for further improvements.
Hope you like it!
Grid Like StrategyIt is possible to use progressive position sizing in order to recover from past losses, a well-known position sizing system being the "martingale", which consists of doubling your position size after a loss, this allows you to recover any previous losses in a losing streak + winning an extra. This system has seen a lot of attention from the trading community (mostly from beginners), and many strategies have been designed around the martingale, one of them being "grid trading strategies".
While such strategies often shows promising results on paper, they are often subjects to many frictions during live trading that makes them totally unusable and dangerous to the trader. The motivations behind posting such a strategy isn't to glorify such systems, but rather to present the problems behind them, many users come to me with their ideas and glorious ways to make money, sometimes they present strategies using the martingale, and it is important to present the flaws of this methodology rather than blindly saying "you shouldn't use it".
Strategy Settings
Point determines the "grid" size and should be adjusted accordingly to the scale of the symbol you are applying the strategy to. Higher value would require larger price movements in order to trigger a trade, as such higher values will generate fewer trades.
The order size determines the number of contracts/shares to purchase.
The martingale multiplier determines the factor by which the position size is multiplied after a loss, using values higher to 2 will "squarify" your balance, while a value of 1 would use a constant position sizing.
Finally, the anti-martingale parameter determines whether the strategy uses a reverse martingale or not, if set to true then the position size is multiplied after any wins.
The Grid
Grid strategies are commons and do not present huge problems until we use certain position sizing methods such as the martingale. A martingale is extremely sensitive to any kind of friction (frictional costs, slippage...etc), the grid strategy aims to provide a stable and simple environment where a martingale might possibly behave well.
The goal of a simple grid strategy is to go long once the price crossover a certain level, a take profit is set at the level above the current one and stop loss is placed at the level below the current one, in a winning scenario the price reach the take profit, the position is closed and a new one is opened with the same setup. In a losing scenario, the price reaches the stop loss level, the position is closed and a short one is opened, the take profit is set at the level below the current one, and a stop loss is set at the level above the current one. Note that all levels are equally spaced.
It follows from this strategy that wins and losses should be constant over time, as such our balance would evolve in a linear fashion. This is a great setup for a martingale, as we are theoretically assured to recover all the looses in a losing streak.
Martingale - Exponential Decays - Risk/Reward
By using a martingale we double our position size (exposure) each time we lose a trade, if we look at our balance when using a martingale we see significant drawdowns, with our balance peaking down significantly. The martingale sequence is subject to exponential growth, as such using a martingale makes our balance exposed to exponential decays, that's really bad, we could basically lose all the initially invested capital in a short amount of time, it follows from this that the theoretical success of a martingale is determined by what is the maximum losing streak you can endure
Now consider how a martingale affects our risk-reward ratio, assuming unity position sizing our martingale sequence can be described by 2^(x-1) , using this formula we would get the amount of shares/contracts we need to purchase at the x trade of a losing streak, we would need to purchase 256 contracts in order to recover from a losing streak of size 9, this is enormous when you take into account that your wins are way smaller, the risk-reward ratio is totally unfair.
Of course, some users might think that a losing streak of size 9 is pretty unlikely, if the probability of winning and losing are both equal to 0.5, then the probability of 9 consecutive losses is equal to 0.5^9 , there are approximately 0.2% of chance of having such large losing streak, note however that under a ranging market such case scenario could happen, but we will see later that the length of a losing streak is not the only problem.
Other Problems
Having a capital large enough to tank 9any number of consecutive losses is not the only thing one should focus on, as we have to take into account market prices and trading dynamics, that's where the ugly part start.
Our first problem is frictional costs, one example being the spread, but this is a common problem for any strategy, however here a martingale is extra sensitive to it, if the strategy does not account for it then we will still double our positions costs but we might not recover all the losses of a losing streak, instead we would be recovering only a proportion of it, under such scenario you would be certain to lose over time.
Another problem are gaps, market price might open under a stop-loss without triggering it, and this is a big no-no.
Equity of the strategy on AMD, in a desired scenario the equity at the second arrow should have been at a higher position than the equity at the first arrow.
In order for the strategy to be more effective, we would need to trade a market that does not close, such as the cryptocurrency market. Finally, we might be affected by slippage, altho only extreme values might drastically affect our balance.
The Anti Martingale
The strategy lets you use an anti-martingale, which double the position size after a win instead of a loss, the goal here is not to recover from a losing strike but instead to profit from a potential winning streak.
Here we are exposing your balance to exponential gross but you might also lose a trade at the end a winning streak, you will generally want to reinitialize your position size after a few wins instead of waiting for the end of a streak.
Alternative
You can use other-kind of progressions for position sizing, such as a linear one, increasing your position size by a constant number each time you lose. More gentle progressions will recover a proportion of your losses in a losing streak.
You can also simulate the effect of a martingale without doubling your position size by doubling your target profit, if for example you have a 10$ profit-target/stop-loss and lose a trade, you can use a 20$ profit target to recover from the lost trade + gain a profit of 10$. While this approach does not introduce exponential decay in your balance, you are betting on the market reaching your take profits, considering the fact that you are doubling their size you are expecting market volatility to increase drastically over time, as such this approach would not be extremely effective for high losing streak.
Conclusion
You will see a lot of auto-trading strategies that are based on a grid approach, they might even use a martingale. While the backtests will look appealing, you should think twice before using such kind of strategy, remember that frictional costs will be a huge challenge for the strategy, and that it assumes that the trader has an important initial capital. We have also seen that the risk/reward ratio is theoretically the worst you can have on a strategy, having a low reward and a high risk. This does not mean that progressive position sizing is bad, but it should not be pushed to the extreme.
It is nice to note that the martingale is originally a betting system designed for casino games, which unlike trading are not subject to frictional costs, but even casino players don't use it, so why would you?
Thx for reading
