Price change scalping short and long strategyPrice change scalping Short and Long strategy uses a rate of change momentum oscillator to calculate the percent change in price between a period of time. Rate of change calculation takes the current price and compares it to a price of "n" periods while the period of time can be defined by a user. The calculated rate of change value is then compared to the upper threshold and the lower threshold values to determine if a position should be opened. If the threshold is crossed and filtering conditions are met a strategy position will be triggered. Entry, take profit, and stop loss prices are calculated and displayed on the chart as well as positions directions. Once the entry price is crossed, a long or short position is created and once the take profit price is crossed, the stop loss price will begin to trail behind the price action using the close of the previous bar. Once the trailing stop price is crossed, the position is closed. If the entry price is not crossed and the price action crosses the stop level, the trade setup is cancelled. The strategy is enhanced by DCA algorithm which allows to average entry price with safety orders. The script also allows to use Martingale coefficient to increase averaging power
Advantages of this script:
Strategy has high net profit of 293% at backtests
Backtests show high accuracy around 71%
High frequency and low duration of trades
Can be used with short-term timeframes ranging from 5 to 60 minutes
Strategy is sustainable to market slumps due to DCA implementation
Can be used for short and long positions (can be adjusted to long only, short only or both)
Can be applied to any market and quote currency
Easy to configure user interface settings
Built in detailed statistic menu
How to use?
1. Apply the strategy to a trading pair your are interested in using 5 to 60 minutes timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Cerca negli script per "the script"
Bitfinex Shorts StratOverview
This strat applies the data from BITFINEX:USDSHORTS to the RSI indicator in order to provide SHORT/LONG entries as the number of contracts goes up and down. Although Bitfinex has lost relevance over the years its generally considered an exchange dominated by smart money rather than retail. I'd like to see if any insights can be gained by following their trading behaviour.
How to use
Select the underlying security you wish to trade and load the indicator. Select the appropriate short security by searching in the Bitfinex Short Symbol. RSI settings apply to short symbol not the actual asset. Strategy shorts the underlying asset when shorts rise and longs when they drop. The shorts symbol will follow the value of the loaded chart. Works best on 4 hour chart.
Why use shorts only rather than both long/shorts?
Bitfinex longs seem to be on a long-term uptrend accounting for 25x the number of shorts. Might be enormous confidence on part of the whales, but more likely reflects selling spot and buying perp. Given the size disparity and price action I don't think longs info is adding much.
Problems with script:
a) We don't really know the intentions of short players (e.g. speculation or hedging spot)
b) The script uses a decline in shorts as a long signal
c) RSI is a blunt tool there are probably better options for calculating high/lows in shorts
d) Shorts are accumulated both at highs and also when BTC price is already heavily trending down. This suggests some are speculative (at the highs) or protective/hedging during a decline
Takeaways:
Based on this strat Bitfinex whales are more wrong than right.
Results don't carry across well into altcoins using the accompanying short symbol. However, what is interesting is that applying the BITFINEX:BTCUSDSHORTS to altcoin charts does work pretty well.
Strat needs some refinement to control for entries under different circumstances.
Probably not a great idea to use this as a strategy in isolation, but highlights how Bitfinex whale behaviour is a good gauge to follow.
VIDYA Trend StrategyOne of the most common messages I get is people reaching out asking for quantitative strategies that trade cryptocurrency. This has compelled me to write this script and article, to help provide a quantitative/technical perspective on why I believe most strategies people write for crypto fail catastrophically, and how one might build measures within their strategies that help reduce the risk of that happening. For those that don't trade crypto, know that these approaches are applicable to any market.
I will start off by qualifying up that I mainly trade stocks and ETFs, and I believe that if you trade crypto, you should only be playing with money you are okay with losing. Most published crypto strategies I have seen "work" when the market is going up, and fail catastrophically when it is not. There are far more people trying to sell you a strategy than there are people providing 5-10+ year backtest results on their strategies, with slippage and commissions included, showing how they generated alpha and beat buy/hold. I understand that this community has some really talented people that can create some really awesome things, but I am saying that the vast majority of what you find on the internet will not be strategies that create alpha over the long term.
So, why do so many of these strategies fail?
There is an assumption many people make that cryptocurrency will act just like stocks and ETFs, and it does not. ETF returns have more of a Gaussian probability distribution. Because of this, ETFs have a short term mean reverting behavior that can be capitalized on consistently. Many technical indicators are built to take advantage of this on the equities market. Many people apply them to crypto. Many of those people are drawn down 60-70% right now while there are mean reversion strategies up YTD on equities, even though the equities market is down. Crypto has many more "tail events" that occur 3-4+ standard deviations from the mean.
There is a correlation in many equities and ETF markets for how long an asset continues to do well when it is currently doing well. This is known as momentum, and that correlation and time-horizon is different for different assets. Many technical indicators are built based on this behavior, and then people apply them to cryptocurrency with little risk management assuming they behave the same and and on the same time horizon, without pulling in the statistics to verify if that is actually the case. They do not.
People do not take into account the brokerage commissions and slippage. Brokerage commissions are particularly high with cryptocurrency. The irony here isn't lost to me. When you factor in trading costs, it blows up most short-term trading strategies that might otherwise look profitable.
There is an assumption that it will "always come back" and that you "HODL" through the crash and "buy more." This is why Three Arrows Capital, a $10 billion dollar crypto hedge fund is now in bankruptcy, and no one can find the owners. This is also why many that trade crypto are drawn down 60-70% right now. There are bad risk practices in place, like thinking the martingale gambling strategy is the same as dollar cost averaging while also using those terms interchangeably. They are not the same. The 1st will blow up your trade account, and the 2nd will reduce timing risk. Many people are systematically blowing up their trade accounts/strategies by using martingale and calling it dollar cost averaging. The more risk you are exposing yourself too, the more important your risk management strategy is.
There is an odd assumption some have that you can buy anything and win with technical/quantitative analysis. Technical analysis does not tell you what you should buy, it just tells you when. If you are running a strategy that is going long on an asset that lost 80% of its value in the last year, then your strategy is probably down. That same strategy might be up on a different asset. One might consider a different methodology on choosing assets to trade.
Lastly, most strategies are over-fit, or curve-fit. The more complicated and more parameters/settings you have in your model, the more likely it is just fit to historical data and will not perform similar in live trading. This is one of the reasons why I like simple models with few parameters. They are less likely to be over-fit to historical data. If the strategy only works with 1 set of parameters, and there isn't a range of parameters around it that create alpha, then your strategy is over-fit and is probably not suitable for live trading.
So, what can I do about all of this!?
I created the VIDYA Trend Strategy to provide an example of how one might create a basic model with a basic risk management strategy that might generate long term alpha on a volatile asset, like cryptocurrency. This is one (of many) risk management strategies that can reduce the volatility of your returns when trading any asset. I chose the Variable Index Dynamic Average (VIDYA) for this example because it's calculation filters out some market noise by taking into account the volatility of the underlying asset. I chose a trend following strategy because regressions are capturing behaviors that are not just specific to the equities market.
The more volatile an asset, the more you have to back-off the short term price movement to effectively trend-follow it. Otherwise, you are constantly buying into short term trends that don't represent the trend of the asset, then they reverse and loose money. This is why I am applying a trend following strategy to a 4 hour chart and not a 4 minute chart. It is also important to note that following these long term trends on a volatile asset exposes you to additional risk. So, how might one mitigate some of that risk?
One of the ways of reducing timing risk is scaling into a trade. This is different from "doubling down" or "trippling down." It is really a basic application of dollar cost averaging to reduce timing risk, although DCA would typically happen over a longer time period. If it is really a trend you are following, it will probably still be a trend tomorrow. Trend following strategies have lower win rates because the beginning of a trend often reverses. The more volatile the asset, the more likely that is to happen. However, we can reduce risk of buying into a reversal by slowly scaling into the trend with a small % of equity per trade.
Our example "VIDYA Trend Strategy" executes this by looking at a medium-term, volatility adjusted trend on a 4 hour chart. The script scales into it with 4% of the account equity every 4-hours that the trend is still up. This means you become fully invested after 25 trades/bars. It also means that early in the trade, when you might be more likely to experience a reversal, most of your account equity is not invested and those losses are much smaller. The script sells 100% of the position when it detects a trend reversal. The slower you scale into a trade, the less volatile your equity curve will be. This model also includes slippage and commissions that you can adjust under the "settings" menu.
This fundamental concept of reducing timing risk by scaling into a trade can be applied to any market.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTESTSmoothed Heikin Ashi Trend on chart - Backtest
This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a Heikin Ashi trend from red to green and vice versa. The original indicator can be found in the scripts section of my profile.
This particular back test uses this indicator with a Trend following paradigm with a percentage-based stop loss.
Note, that backtesting performance is not always indicative of future performance, but it does provide some basis for further development and walk-forward / live testing.
Testing was performed on Bitcoin , as this is a primary target market for me to use this kind of strategy.
Sample Backtesting results as of 10th June 2022:
Backtesting parameters:
Position size: 10% of equity
Long stop: 1% below entry
Short stop: 1% above entry
Repainting: Off
Smoothing: SMA
Period: 10
8 Hour:
Number of Trades: 1046
Gross Return: 249.27 %
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 28.01 %
Profit Factor (Expectancy): 2.019
Average Loss: 0.33 %
Average Win: 1.69 %
Average Time for Loss: 1 day
Average Time for Win: 5.33 days
1 Day:
Number of Trades: 429
Gross Return: 458.4 %
CAGR Return: 15.76 %
Max Drawdown: 6.37 %
Profit Factor (Expectancy): 2.804
Average Loss: 0.8 %
Average Win: 7.2 %
Average Time for Loss: 3 days
Average Time for Win: 16 days
5 Day:
Number of Trades: 69
Gross Return: 1614.9 %
CAGR Return: 26.7 %
Max Drawdown: 5.7 %
Profit Factor (Expectancy): 10.451
Average Loss: 3.64 %
Average Win: 81.17 %
Average Time for Loss: 15 days
Average Time for Win: 85 days
Analysis:
The strategy is typical amongst trend following strategies with a less regular win rate, but where profits are more significant than losses. Most of the losses are in sideways, low volatility markets. This strategy performs better on higher timeframes, where it shows a positive expectancy of the strategy.
The average win was positively impacted by Bitcoin’s earlier smaller market cap, as the percentage wins earlier were higher.
Overall the strategy shows potential for further development and may be suitable for walk-forward testing and out of sample analysis to be considered for a demo trading account.
Note in an actual trading setup, you may wish to use this with volatility filters, combined with support resistance zones for a better setup.
As always, this post/indicator/strategy is not financial advice, and please do your due diligence before trading this live.
Original indicator links:
On chart version -
Oscillator version -
Update - 27/06/2022
Unfortunately, It appears that the original script had been taken down due to auto-moderation because of concerns with no slippage / commission. I have since adjusted the backtest, and re-uploaded to include the following to address these concerns, and show that I am genuinely trying to give back to the community and not mislead anyone:
1) Include commission of 0.1% - to match Binance's maker fees prior to moving to a fee-less model.
2) Include slippage of 10 ticks (This is a realistic slippage figure from searching online for most crypto exchanges)
3) Adjust account balance to 10,000 - since most of us are not millionaires.
The rest of the backtesting parameters are comparable to previous results:
Backtesting parameters:
Initial capital: 10000 dollars
Position size: 10% of equity
Long stop: 2% below entry
Short stop: 2% above entry
Repainting: Off
Smoothing: SMA
Period: 10
Slippage: 10 ticks
Commission: 0.1%
This script still remains to shows viability / profitablity on higher term timeframes (with slightly higher drawdown), and I have included the backtest report below to document my findings:
8 Hour:
Number of Trades: 1082
Gross Return: 233.02%
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 25.6%
Profit Factor (Expectancy): 1.627
Average Loss: 0.46 %
Average Win: 2.18 %
Average Time for Loss: 1.33 day
Average Time for Win: 7.33 days
Once again, please do your own research and due dillegence before trading this live. This post is for education and information purposes only, and should not be taken as financial advice.
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!
Godtrix's Crypto HA+RSI+EMA+ATH+DCA Strategy 3.0New Updates is here! Upgrade from previous version 2.0 (Please avoid using v2.0 as it's outdated.)
Great stability, Repaint bug fixes, and New features!
==================
| Introduction: |
==================
This is a Long Term Strategy, using compounding profit method, it can generate high returns, but it also risk for losses, this can be overcome if you set Stop Loss to over 25% for bitcoin & 60% for Altcoins.
Best profit plan with this strategy is you trade on Future leverage while you hold on to your coin, so that when price goes up, your coin value goes up, and at the same time, you trade with your leverage to earn even more, easily doubling up your total profit.
Benefits:
Fully customizable and you can easily personalized it and FINE TUNE it according to the market or coin you trading on.
The strategy is based on REAL PRACTICAL trading skills, so it works in real-world.
I fixed the "repainting" issue so the backtest it shows you IS ACCURATE when you run for real-time.
We all know one indicator is not going to help you win your trades, so this strategy combines ALL three: EMA for long+short term trend, HA for short term trend, RSI for entry/exit
This strategy is designed for LONG trade (Buy low, Sell high), not for SHORT trade.
This is not day trading, it is more to mid-term trading, where there's only few trades per month
Mainly is coded to work with 3Commas bot auto trading, so you only need to key in your Bot ID & Email Token.
Bot trading NOTE:
- You need to replace the Alert Message with this: {{strategy.order.alert_message}}
- And you'll need the Bot's webhook Url set with the Alert too.
- One Alert will work for both Buy and Sell Order
- If you using other Bot service, you can enter Custom Command in Input Settings too, it works on any bot service.
Lastly,
regarding the setting advice, I would say you try playing with different settings and your objective is to achieve a backtest result that has:
1) Profitable is > 80%
2) Losing trades is nearly 0 or below 25% of your winning trades. Trick is using far stop loss %
3) Net Profit be almost same or more than "Buy & Hold Profit"
==================
| Latest Updates: |
==================
=| Tidy Up Codings |=
- Group input fields so it'll be easier to understand and find the settings
- Upgrade code for obsolete 'transp' options
=| Repaint Issues |=
- Previous v2.0's RSI has repaint issue, creating false result against real-time data. I've fixed this.
- Also done fine-tuning other parts of the codes to prevent possible repaint issues.
=| Bot System |=
- Improved Custom Bot system, so that you're able to set dynamic order size/quantity with my custom keyword: and
Base Order Example:
{ 'message_type': 'bot', 'bot_id': 1234567, 'email_token': 'abcdefgh-1234-1234-1234', 'base_order': , 'delay_seconds': 0, 'pair': 'USDT_BTC'}
=| EMA Downtrend Exit |=
- Added option for you to decide whether to close position when detected EMA Long term downtrend.
=| EMA 2 (short term) is removed |=
- After several test, I've decided to remove this because it doesn't contribute to improving the results.
=| Heikin Ashi System |=
- Improved the chart display, now you'll see the HA candle 'shadowed' behind, so you'll see both actual price candle and HA candle at same time.
- Added the system that detect the HA candle sizes to decide specifically when it's suitable for Entry and Exit.
>> For "Entry/Exit Range"
- This means after HA is valid for Entry or Exit, how many following bars are allowed to stay valid so it will match other requirements to be completely fulfilled for Entry or Exit.
>> For "Crossing Interval"
- This means after detected HA line crossover, how many HA intervals is allow to Entry or Exit
>> For "Reversed Exit"
- This function let's you decide whether to close position if after HA bull (green candle) changed into HA Bear (red candle)
=| RSI A Entry |=
- Added option to avoid Entry during NTZ (No trade Zone)
- Also added the option to avoid next same condition RSI A entry too soon
=| RSI B Entry |=
- This function is for Entry if RSI is going very low, mostly due to bigger price drops in short time, it's good for buying DIP, however we'll never be able to know when a DIP ends, so do more test on this settings before put into real use.
- Added "avoid" options to help avoid getting Entry at "false" DIP, more like a short & fast pullback which causes RSI to drop very low but actually the price is near ATH or Recent High.
- Added option for Entry with Trailing Price Lower Buy combine with a limit order that grabs low price, so whichever it fulfill first.
=| New: Avoid Entry |=
- Well, it's a pain if you bought at the top, so I've added two options that will avoid buying near ATH and Recent High.
=| Time-limit Removed |=
- Sorry that I've missed look on the script policy which I'm not allowed to put a time-limit for public scripts.
=| System Improvements |=
- HA condition detection is optimized and bug fixed
- RSI values now reads accurately on each bar despite using higher timeframe, especially when moving to next interval
=| New: Dollar Cost Averaging (DCA) Orders |=
- Although DCA strategy is not appealing for Long term strategy, but I've added it for your extra options and flexibilities.
- The settings are quite straight-forward and standard, so I won't be explaining here.
=| New: Backtest Start & End Date |=
- This is very good function when you need more accurate result starting at specific date & time.
- Also if you set the date & time for your real trading starts, it'll much result the same as your actual trading records, which helps you to see clearer and make future decisions.
Any found bugs or flaws, please feel free to PM me, I can't get notifications from comments here below, so I'll not able to reply you the soonest possible, still not sure how to turn on notification for comments, anyone who knows can PM and teach me, lol... Thanks in advance!
Well, this is free version, hope it helps! Feedbacks are all welcome :)
(To Moderators: I've fully use the "f_security()" guideline, but instead of creating a separate function, I apply directly on all security() function. Please don't ban my script before fully check if I've truly fixed repaint. Thank you.)
BITSTAMP:BTCUSD COINBASE:BTCUSD COINBASE:ETHUSD BINANCE:BNBUSDT
Pyramiding BTC 5 minThe pyramide based on this script with his concent
the strategy is the same as BTC 15 script (look at my open scripts) there it without pyramide
you can use the filter if you wish
one trick if you want it to be more accurate (not mean more profit is to reverse the long and short in the filter ' just it will lose less)
about the strategy of pyrimde you can read in detail from the script of Coinrule
i modify only to have 5 step in the pyramide scheme on 20% of equity (seems more logical)
so let me me know what you think:)
T3-CCI Strategy [SystemAlpha]This is a strategy based on FX Sniper's T3-CCI indicator. Instead of using just the normal buy and sell signal, we added an option to use trend filters, trailing stop loss and take profit targets.
In this strategy you have a choice of:
Trend Filters:
- Average Directional Index ( ADX ) – buy when price is trend is up and sell when trend is down.
- Moving Average (MA) – buy when price close above the defined moving average and sell when price close below moving average
- Parabolic SAR – buy when SAR is above price is above price and sell when SAR is below price.
- All - Use ADX , MA and SAR as filters
For MA Filter , you can use the “TF MA Type” and "TF MA Period" parameter to select Simple or Exponential Moving Average and length.
Stop Loss:
- Average True Range (ATR) – ATR % stop as trailing stop loss.
- Parabolic SAR ( SAR ) – Parabolic SAR adapted as trailing stop loss.
For ATR , you can use the “ATR Trailing Stop Multiplier” parameter to set an initial offset for trailing stop loss.
Take Profit Target:
- Average True Range (ATR) – ATR % stop as trailing stop loss.
- Standard % – Percent as target profit
For ATR , you can use the “ATR Take Profit Multiplier” parameter to set an initial offset for trailing stop loss.
Additional feature include:
- Show Bar Colors
STRATEGY ONLY:
- Set back test date range
- Set trade direction - Long, Short or Both
- Use timed exit - Select method and bars
- Method 1: Exit after specified number of bars.
- Method 2: Exit after specified number of bars, ONLY if position is currently profitable.
- Method 3: Exit after specified number of bars, ONLY if position is currently losing.
TradingView Links:
Alerts:
T3-CCI Indicator:
Advance ADX:
How to use:
1. Apply the script by browsing through Indicators --> Invite-Only scripts and select the indicator
2. Once loaded, click the gear (settings) button to select/adjust the parameters based on your preference.
3. Wait for the next BUY or SELL signal to enter the trade!
Disclaimer:
The indicator and signals generated do not constitute investment advice; are provided solely for informational purposes and therefore is not an offer to buy or sell a security; are not warranted to be correct, complete or accurate; and are subject to change without notice.
Smooth Moving Average Ribbon [STRATEGY] @PuppyTherapyThe Smooth moving average ribbon script is an enhancement of the script I posted yesterday. But will help you also create a very simple trend-following strategy or a simple trend-following filter.
You are able to select from a large variety of moving averages add Heikin Ashi Candles as a source and also add additional smoothing to every single of the moving averages.
The Strategy is using the basic backtesting engine.
It is a showcase that a simple strategy like buy when we going up and sell when we going down actually works especially on a bigger timeframe.
Thanks to all supporters and everget for some of the moving average scripts.
Cyatophilum Bands Pro Trader [BACKTEST]A Multi Timeframe Indicator for trading cryptocurrency and other assets
Presentation Page
HOW IT WORKS
The indicator mainly consists of what I call "Cyatophilum Bands", who can be used as either Trend lines or Support/Resistance. The color indicates the current Trend. Buy and Sell signals trigger upon Trend Reversal Breakouts.
These alerts can be used with automated trading systems. They correspond to the big green and red triangles.
For daytraders, there is an option to activate Long and Short signals during a Trend. It can also be used as re-entry points if you missed a major breakout. They correspond to the small triangles.
If you trade BTCUSD, I created an option that will allow you to configure your script on any timeframe from 5M to 1D in one click.
If you do not trade BTCUSD, you can use a custom setup (See the Presentation Page )
This indicators also works on other assets such as Oil Futures or other cryptocurrency pairs such as ETH/BTC.
The script comes with two versions:
The alert Setup is used creating automated alerts
The Backtest Version that will help you see the results on past data. You can choose to enable or disable shorts results.
HOW TO USE
Once I granted you access, you will receive a notification. Add both indicators to the chart. Use the Backtest version to find the best configuration (BTCUSD is already pre-configured. I post configurations on my Discord Server, and you can ask me for help). Then apply this configuration to the Alert Setup script. Finally, create the alerts.
Before you ask, the script does not repaint. I made sure to not use the security function which I know is bugged right now.
Get the indicator today !
Purchase on my website
NOTE
If you purchase the Indicator you will get access to my past indicators as well!
Profit Trailer Tester v0.2This script combines all buy and sell strategies of the Profit Trailer bot for research, backtesting (simulation) and teaching those strategies. Due to several reasons, the script cannot emulate the Profit Trailer strategies 100%. It is more to visualize the strategies and support you in your decisions.
It is an early version and still under heavy development and testing. Currently, 'DCA' and trailing are not implemented yet.
Please send a PM to get access to the script.
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!
Chandelier Exit Strategy with 200 EMA FilterStrategy Name and Purpose
Chandelier Exit Strategy with 200EMA Filter
This strategy uses the Chandelier Exit indicator in combination with a 200-period Exponential Moving Average (EMA) to generate trend-based trading signals. The main purpose of this strategy is to help traders identify high-probability entry points by leveraging the Chandelier Exit for stop loss levels and the EMA for trend confirmation. This strategy aims to provide clear rules for entries and exits, improving overall trading discipline and performance.
Originality and Usefulness
This script integrates two powerful indicators to create a cohesive and effective trading strategy:
Chandelier Exit : This indicator is based on the Average True Range (ATR) and identifies potential stop loss levels. The Chandelier Exit helps manage risk by setting stop loss levels at a distance from the highest high or lowest low over a specified period, multiplied by the ATR. This ensures that the stop loss adapts to market volatility.
200-period Exponential Moving Average (EMA) : The EMA acts as a trend filter. By ensuring trades are only taken in the direction of the overall trend, the strategy improves the probability of success. For long entries, the close price must be above the 200 EMA, indicating a bullish trend. For short entries, the close price must be below the 200 EMA, indicating a bearish trend.
Combining these indicators adds layers of confirmation and risk management, enhancing the strategy's effectiveness. The Chandelier Exit provides dynamic stop loss levels based on market volatility, while the EMA ensures trades align with the prevailing trend.
Entry Conditions
Long Entry
A buy signal is generated by the Chandelier Exit.
The close price is above the 200 EMA, indicating a strong bullish trend.
Short Entry
A sell signal is generated by the Chandelier Exit.
The close price is below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions: The position is closed when a sell signal is generated by the Chandelier Exit.
For short positions: The position is closed when a buy signal is generated by the Chandelier Exit.
Risk Management
Account Size: 1,000,00 yen
Commission and Slippage: 17 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
Stop Loss: For long trades, the stop loss is placed slightly below the candle that generated the buy signal. For short trades, the stop loss is placed slightly above the candle that generated the sell signal. The stop loss levels are dynamically adjusted based on the ATR.
Settings Options
ATR Period: Set the period for calculating the ATR to determine the Chandelier Exit levels.
ATR Multiplier: Set the multiplier for ATR to define the distance of stop loss levels from the highest high or lowest low.
Use Close Price for Extremums: Choose whether to use the close price for calculating the extremums.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show Buy/Sell Labels: Choose whether to display buy and sell labels on the chart for visual confirmation.
Highlight State: Choose whether to highlight the bullish or bearish state on the chart.
Sufficient Sample Size
The strategy has been backtested with a sufficient sample size to evaluate its performance accurately. This ensures that the strategy's results are statistically significant and reliable.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the Chandelier Exit indicator. Special thanks to the original contributors for their work on the Chandelier Exit concept.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
FVG Positioning Average with 200EMA Auto Trading [Pakun]Description
Strategy Name and Purpose
FVG Positioning Average with 200EMA Auto Trading
This strategy uses Fair Value Gaps (FVG) combined with a 200-period Exponential Moving Average (EMA) and Average True Range (ATR) to generate trend-based trading signals. It is designed to help traders identify high-probability entry points by leveraging the gaps between fair value prices and current market prices.
Originality and Usefulness
This script combines multiple indicators to create a cohesive trading strategy that is greater than the sum of its parts. While FVG is a powerful tool on its own, combining it with the EMA and ATR adds layers of confirmation and risk management, enhancing its effectiveness. Here’s how the components work together:
Fair Value Gap (FVG): Identifies gaps in the market where price action has not fully filled, indicating potential reversal or continuation points.
200-period Exponential Moving Average (EMA): Acts as a trend filter to ensure trades are taken in the direction of the overall trend, improving the probability of success.
Average True Range (ATR): Used to filter out insignificant gaps and set dynamic stop-loss levels based on market volatility, enhancing risk management.
Entry Conditions
Long Entry
The close price crosses above the downtrend FVG.
The close price, FVG up average, and down average are all above the 200 EMA, indicating a strong bullish trend.
Short Entry
The close price crosses below the uptrend FVG.
The close price, FVG up average, and down average are all below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions, the stop loss is set at the recent low, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
For short positions, the stop loss is set at the recent high, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
Risk Management
Account Size: 1,000,000 yen
Commission and Slippage: 2 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
The stop loss is based on the recent low or recent high, ensuring trades are exited when the market moves against the position.
Settings Options
FVG Lookback: Set the lookback period for calculating FVGs.
Lookback Type: Choose the type of lookback (Bar Count or FVG Count).
ATR Multiplier: Set the multiplier for ATR to filter significant gaps.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show FVGs on Chart: Choose whether to display FVGs on the chart for visual confirmation.
Bullish/Bearish Color: Set the color for bullish and bearish FVGs to distinguish them easily.
Show Gradient Areas: Choose whether to display gradient areas to highlight the zones of interest.
Sufficient Sample Size
The strategy has been backtested with 113 trades, providing a sufficient sample size to evaluate its performance.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the FVG Positioning Average Strategy indicator. Thanks to for their contribution.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
VAWSI and Trend Persistance Reversal Strategy SL/TPThis is a completely revamped version of my "RSI and ATR Trend Reversal Strategy."
What's New?
The RSI has been replaced with an original indicator of mine, the "VAWSI," as I've elected to call it.
The standard RSI measures a change in an RMA to determine the strength of a movement.
The VAWSI performs very similarly, except it uses another original indicator of mine, the VAWMA.
VAWMA stands for "Volume (and) ATR Weight Moving Average." It takes an average of the volume and ATR and uses the ratio of each bar to weigh a moving average of the source.
It has the same formula as an RSI, but uses the VAWMA instead of an RMA.
Next we have the Trend Persistence indicator, which is an index on how long a trend has been persisting for. It is another original indicator. It takes the max deviation the source has from lowest/highest of a specified length. It then takes a cumulative measure of that amount, measures the change, then creates a strength index with that amount.
The VAWSI is a measure of an emerging trend, and the Trend Persistence indicator is a measure of how long a trend has persisted.
Finally, the 3rd main indicator, is a slight variation of an ATR. Rather than taking the max of source - low or high- source and source - source , it instead takes the max of high-low and the absolute value of source - the previous source. It then takes the absolute value of the change of this, and normalizes it with the source.
Inputs
Minimum SL/TP ensures that the Stop Loss and Take Profit still exist in untrendy markets. This is the minimum Amount that will always be applied.
VAWSI Weight is a divided by 100 multiplier for the VAWSI. So value of 200 means it is multiplied by 2. Think of it like a percentage.
Trend Persistence weight and ATR Weight are applied the same. Higher the number, the more impactful on the final calculation it is.
Combination Mult is an outright multiplier to the final calculation. So a 2.0 = * 2.0
Trend Persistence Smoothing Length is the length of the weighted moving average applied to the Trend Persistence Strength index.
Length Cycle Decimal is a replacement of length for the script.
Here we used BlackCat1402's Dynamic Length Calculation, which can be found on his page. With his permission we have implemented it into this script. Big shout out to them for not only creating, but allowing us to use it here.
The Length Cycle Decimal is used to calculate the dynamic length. Because TradingView only allows series int for their built-in library, a lot of the baseline indicators we use have to be manually recreated as functions in the following section.
The Strategy
As usual, we use Heiken Ashi values for calculations.
We begin by establishing the minimum SL/TP for use later.
Next we determine the amount of bars back since the last crossup or crossdown of our threshold line.
We then perform some normalization of our multipliers. We want a larger trend or larger VAWSI amount to narrow the threshold, so we have 1 divide them. This way, a higher reading outputs a smaller number and vice versa. We do this for both Trend Persistence, and the VAWSI.
The VAWSI we also normalize, where rather than it being a 0-100 reading of trend direction and strength, we absolute it so that as long as a trend is strong, regardless of direction, it will have a higher reading. With these normalized values, we add them together and simply subtract the ATR measurement rather than having 1 divide it.
Here you can see how the different measurements add up. A lower final number suggests imminent reversal, and a higher final number suggests an untrendy or choppy market.
ATR is in orange, the Trend Persistence is blue, the VAWSI is purple, and the final amount is green.
We take this final number and depending on the current trend direction, we multiply it by either the Highest or Lowest source since the last crossup or crossdown. We then take the highest or lowest of this calculation, and have it be our Stop Loss or Take Profit. This number cannot be higher/lower than the previous source to ensure a rapid spike doesn't immediately close your position on a still continuing trend. As well, the threshold cannot be higher/ lower than the the specified Stop Loss and Take Profit
Only after the source has fully crossed these lines do we consider it a crossup or crossdown. We confirm this with a barstate.isconfirmed to prevent repainting. Next, each time there is a crossup or crossdown we enter a long or a short respectively and plot accordingly.
I have the strategy configured to "process on order close" to ensure an accurate backtesting result. You could also set this to false and add a 1 bar delay to the "if crossup" and "if crossdown" lines under strategy so that it is calculated based on the open of the next bar.
Final Notes
The amounts have been preconfigured for performance on RIOT 5 Minute timeframe. Other timeframes are viable as well. With a few changes to the parameters, this strategy has backtested well on NVDA, AAPL, TSLA, and AMD. I recommend before altering settings to try other timeframes first.
This script does not seem to perform nearly as well in typically untrendy and choppy markets such as crypto and forex. With some setting changes, I have seen okay results with crypto, but overfitting could be the cause there.
Thank you very much, and please enjoy.
Advanced EMA Cross with Normalized ATR Filter, Controlling ADX
Description:
This strategy is based on EMA cross strategy and additional filters are used to get better results, a normalized ATR filter, and ADX control...
It aims to provide traders with a code base that generates signals for long positions based on market conditions defined by various indicators.
How it Works:
1. EMA: Uses short (8 periods) and long (20 periods) EMAs to identify crossovers.
2. ATR: Uses a 14-period ATR, normalized to its 20-period historical range, to filter out noise.
3. ADX: Uses a 14-period RMA to identify strong trends.
4. Volume: Filters trades based on a 14-period SMA of volume.
5. Super Trend: Uses a Super Trend indicator to identify the market direction.
How to Use:
- Buy Signal: Generated when EMA short crosses above EMA long, and other conditions like ATR and market direction are met.
- Sell Signal: Generated based on EMA crossunder and high ADX value.
Originality and Usefulness:
This script combines EMA, ATR, ADX, and Super Trend indicators to filter out false signals and identify more reliable trading opportunities.
USD Strength in the code is not working, just simulated it as PSEUDO CODE:
Strategy Results:
- Account Size: $1000
- Commission: Not considered
- Slippage: Not considered
- Risk: Manageable through parameters, now less than 5% per trade
- Dataset: Aim for more than 100 trades for a sufficient sample size
- Test Conditions: Test in 30 min chart for BTCUSDT
IMPORTANT NOTE: This script should be used for educational purposes and should not be considered as financial advice.
Chart:
- The script's output is plotted as Buy and Sell signals on the chart.
- No other scripts are included for clarity.
- Have tested with 30mins period
- You are encouraged to play with parameters, let me know if it helps you and/or if you can upgrade the code to a better level.
WHY DID I USE ATR AND ADX?
ATR filter is usually used for the following purposes.
Market Volatility: ATR measures how volatile the market is. High ATR values indicate that the price is experiencing significant fluctuations.
Filtering: Crossing a certain ATR threshold may indicate that the market is active enough to present trading opportunities.
Risk Management: ATR can also be used to set stop-loss and take-profit levels, helping to manage risk effectively.
And ADX is usually used for;
Trend Strength: ADX measures the strength of a trend. High ADX values indicate a strong trend.
Filtering: An ADX value above a certain level suggests that the trend is strong and it might be safer to trade.
Versatility: ADX does not indicate the direction of the trend, only its strength. This makes it useful in both bullish and bearish markets.
Using these indicators together can help filter out false signals and produce more reliable trading signals. While ATR helps to determine if the market is active enough, ADX measures the strength of the trend. Combined, they can create a more complex and effective trading strategy.
I've used ADX data to support generating a buy signal after a golden cross (bullish trend) and waiting until this is a strong trend. It sounds good to check for different trend strengths for bullish and bearish markets to decide a buy signal. Additionally I used ATR to check if the market has enough fluctuations.
Advanced VWAP_Pullback Strategy_Trend-Template QualifierGeneral Description and Unique Features of this Script
Introducing the Advanced VWAP Momentum-Pullback Strategy (long-only) that offers several unique features:
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends. Mark Minervini, a 2x US Investment Champion, developed the Trend-Template, which covers eight different and independent characteristics that can be adjusted and optimized in this trend-following strategy to ensure the best results. The strategy will only trigger buy-signals in case the optimized qualifiers are being met.
2. Our strategy is based on the supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you are day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We have also integrated technical indicators such as the RSI and the MA / VWAP crossover into this strategy to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available in TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
This strategy can be applied to all timeframes from 5 min to daily.
The VWAP Momentum-Pullback Strategy
For the JS-TechTrading VWAP Momentum-Pullback Strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are recommended for algorithmic trading with this startegy.
A further prerequisite for generating a buy signals is that the individual value is in a short-term oversold state (RSI).
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MA / VWAP crossover after reaching a price low, a buy signal is issued by this strategy.
Stop-loss limits and profit targets can be set variably. You also have the option to make use of the trailing stop exit strategy.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
The MA / VWAP Crossover Trading Strategy
This strategy combines two popular technical indicators: the Moving Average (MA) and the Volume Weighted Average Price (VWAP). The MA VWAP crossover strategy is used to identify potential trend reversals and entry/exit points in the market.
The VWAP is calculated by taking the average price of an asset for a given period, weighted by the volume traded at each price level. The MA, on the other hand, is calculated by taking the average price of an asset over a specified number of periods. When the MA crosses above the VWAP, it suggests that buying pressure is increasing, and it may be a good time to enter a long position. When the MA crosses below the VWAP, it suggests that selling pressure is increasing, and it may be a good time to exit a long position or enter a short position.
Traders typically use the MA VWAP crossover strategy in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions. As with any trading strategy, it is important to carefully consider the risks and potential rewards before making any trades.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MA/VWAP) can be adjusted and optimized as needed.
Backtesting
Backtesting gives outstanding results on all timeframes and drawdowns can be reduced to a minimum level. In this example, the hourly chart for MCFT has been used.
Settings for backtesting are:
- Period from Jan 2020 until March 2023
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
- Slippage = 2 ticks
Other comments
- This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
- The combination of the Trend-Template and the RSI qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
- Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
3Commas Bot DCA Backtester & Signals FREEThis is a DCA Strategy backtester + signals, built to emulate the 3Commas DCA bots. It uses your choice of 4 different buy signals, 2 of which can be adjusted in the settings. Everything is customizable so you can backtest specific settings with different buy signals and find the best performing strategy for your risk tolerance and capital. It can be used to backtest strategies on stocks as well, but just make sure your base order is larger than the share price for the entire backtesting range or it will not calculate properly.
You can use this template to code your own buy signals and then backtest them as a DCA strategy if you know some basic pine script.
The indicator shows all of your backtesting orders on the chart. The red line is your take profit level, the blue line is your average price level, the white line is your first order and the green lines are your average down orders. If you enable a stop loss in the settings your stop loss will be shown as an orange line once all of your average down orders have been hit, it will not be set until price has dipped below your covered trading range.
These levels update when things change during backtesting so you can visualize your strategy and how it would perform as well as see if your percentage deviation is large enough to cover dips. When backtesting trades are taken, the chart will show where they were taken(in backtesting) along with info on those trades such as the number each order is, the size of that order and the percentage deviation that order is from the initial buy.
SENDING SIGNALS TO 3COMMAS
Tradingview cannot sync this backtester to 3Commas and with the way alerts are setup for strategies on Tradingview, the best option for you to give signals to your bot would be to use this backtester to figure out what trigger you want to use and then setup that indicator separately to send alerts to your bot. All of the indicators used for signals in this backtester are available for free and can be configured to match this backtester and send alerts to 3Commas for you. Just make sure you set your alerts to once per bar close and don’t use less than a 15 second timeframe because then you could trigger the Tradingview threshold for alerts and get your alerts shut off.
You can also use this backtester with your own buy triggers if you know a little pine script. Just make copy of the script and code in your own buy signals and see how it backtests.
INFO PANEL FOR ANALYZING YOUR STRATEGY
The right hand side of the screen will show an info panel that shows a lot of different information so you can quickly see your bot settings and how it performed right on the screen.
In the top right corner you will see in purple your bot settings. These include your stoploss % if turned on, take profit %, average down order %, average down order % multiplier, volume multiplier, max number of orders allowed and size of your base order.
The top section of the first column “Current Trade” shows these stats: the open trade’s average price, the open trade’s take profit price, the open trade’s PNL, how far price is from your open tarde’s take profit level in percentage, your open position size and number of open orders.
The bottom section of the first column “Overall Performance” shows these stats: total number of trades taken during backtesting range, the largest amount of trades that were open at one time during backtesting, the max drawdown, the average number of bars per trade, gross profit, net profit, percent profit from your initial capital, current portfolio value and your initial capital.
CUSTOMIZABLE OPTIONS TO FIND THE PERFECT STRATEGY
Stoploss On/Off
This will turn your stoploss on or off. By default it is set to off and will not affect anything unless turned on.
Stoploss Percentage
This is the percentage below your final average down order price that will be set as a stoploss to keep your account from going too far in the red on big dips.
Take Profit Percentage - This is the percentage of profit you want the trade to hit before taking profit on your entire DCA trade. This level updates everytime you average down.
Average Down Percentage - This is the percentage that price has to drop from your initial order to initiate your first safety order. If the Average Down Percent Multiplier is set to 1 then this percentage will be the same for every average down order.
Average Down Percentage Multiplier - This multiplies your Average Down Percentage so each safety order needs a larger percentage deviation than the previous one. This keeps your buys closer together at the beginning and further apart when you hit more orders so you can extend your trading range but still be aggressive when price is going sideways.
Volume Multiplier Per New Order - This multiplies the size of each trade based on your base order. If you set it to a 2x multiplier then each average down order will be 2 times the size of the last one. So for example, a $100 base order with a 2x multiplier would have these values for the first 3 average down orders: 200, 400, 800.
Size Of Base Order - This is the size of your first position entry and will be used as a starting point for the volume multiplier. If your base order is $100 then it will buy $100 worth of whatever crypto you are backtesting this on. If you are looking at stock charts, you need to make sure your base order is higher than the share price across the entire backtesting range or it will not perform correctly.
Max Number Of Orders - This is the maximum number of orders the bot can take, including your base order. Adjust this to suit the amount of capital you are willing to allocate to your bot based on how much money it will require to run according to your bot settings.
TIPS ON HOW TO USE FOR BEST RESULTS
If you don’t have a lot of capital to work with, then use longer timeframes with a reasonable take profit percentage so that you don’t need a lot of average down orders. You can also try keeping the volume multiplier close to 1.
You can use the 3Commas dca bot settings page to see how much capital you will need for your strategy if you match it to the settings you have on this indicator. You can also check to see how much of a percentage deviation your bot is covering to make sure you have a reasonable range to trade in and orders to cover big dips. You can also check your coverage by seeing how far down the chart the green lines cover, which are your average down orders.
Make sure the initial capital in the properties tab of the settings has enough to cover all of your orders otherwise you will get unrealistic backtesting results. Also, make sure you leave the order size in the properties tab on contracts so it calculates your trades correctly. The only settings you need to touch in the properties tab is the initial capital. Unless you are trading somewhere that has lower commission fees, then you can change that to match, but leave all the other settings as is for it to function properly.
Increasing the volume multiplier will make your average price and take profit target follow the price action a lot closer as price falls, but it can also lead to having very large orders very quickly once you get into the 1.5-3x multiple range. Try using a high volume multiplier with less safety orders and you will get better results, however you need to have money on the sidelines to add on major dips to keep your bot turning a profit. Be very careful with this as greed and impatience will hurt your overall performance. This bot is meant to make money with lots of small wins so don’t get greedy and make sure you have enough money to cover large dips. If you are being aggressive with your bot, then I recommend only using 25% or less of your portfolio to trade aggressively and then use the smart trade feature on 3commas to add chunks of funds to your trades when price dips below your last safety order. Or if you want it to run without any supervision, then use lower volume multipliers and have lots of safety orders that can cover entire bear markets and still keep buying lower.
It’s a good idea to have some capital on the sidelines that you can add in when price dips quickly. This will help lower your average price and allow your bot to get out in profit quicker. 3Commas bot has a smart trade feature that will allow you to track your average price when adding extra funds and it will automatically update your other orders which is very convenient. Look at the longer timeframes when price dips and only add chunks at major areas where price is very likely to bounce. Or you can be aggressive when trading and add to your position when price dips and is at a likely bounce zone to maximize profits.
Only trade coins that have a good amount of liquidity as the larger your orders get, the harder it will be to sell if there isn’t much liquidity. Also, beware of how large your first order is as it will usually be a market order and can move the market if there is not much liquidity.
Since this bot takes a lot of trades and performs best when taking small profits consistently, you will need to factor in exchange fees. The bot is set to .5% commission(you can change this) on the buy and sell orders as most exchanges charge that amount. Some exchanges offer no fee trading on certain coins so be sure to look around for those so you can keep the commissions and maximize profits.
I strongly encourage you to try out a lot of different setting combinations across multiple different coins and do it across a few months to see how it would have performed under various market conditions. This will help you get a better idea of how much of a percentage deviation you’ll need to be able to cover to keep your bot running and making constant profits. You can also use the deep backtesting feature of the strategy panel to see how it would have done, but just beware that the info panel of the indicator will not reflect deep backtesting results, only the normal backtesting range.
MARKETS
This backtester can be used on any market including crypto, stocks, forex & futures. You just need to make sure your base order is larger than the share price when using this on things besides crypto.
TIMEFRAMES
This backtester can be used on all timeframes.
Multi Trend Cross Strategy TemplateToday I am sharing with the community trend cross strategy template that incorporates any combination of over 20 built in indicators. Some of these indicators are in the Pine library, and some have been custom coded and contributed over time by the beloved Pine Coder community. Identifying a trend cross is a common trend following strategy and a common custom-code request from the community. Using this template, users can now select from over 400 different potential trend combinations and setup alerts without any custom coding required. This Multi-Trend cross template has a very inclusive library of trend calculations/indicators built-in, and will plot any of the 20+ indicators/trends that you can select in the settings.
How it works : Simple trend cross strategies go long when the fast trend crosses over the slow trend, and/or go short when the fast trend crosses under the slow trend. Options for either trend direction are built-in to this strategy template. The script is also coded in a way that allows you to enable/modify pyramid settings and scale into a position over time after a trend has crossed.
Use cases : These types of strategies can reduce the volatility of returns and can help avoid large market downswings. For instance, those running a longer term trend-cross strategy may have not realized half the down swing of the bear markets or crashes in 02', 08', 20', etc. However, in other years, they may have exited the market from time to time at unfavorable points that didn't end up being a down turn, or at times the market was ranging sideways. Some also use them to reduce volatility and then add leverage to attempt to beat buy/hold of the underlying asset within an acceptable drawdown threshold.
Special thanks to @Duyck, @everget, @KivancOzbilgic and @LazyBear for coding and contributing earlier versions of some of these custom indicators in Pine.
This script incorporates all of the following indicators. Each of them can be selected and modified from within the indicator settings:
ALMA - Arnaud Legoux Moving Average
DEMA - Double Exponential Moving Average
DSMA - Deviation Scaled Moving Average - Contributed by Everget
EMA - Exponential Moving Average
HMA - Hull Moving Average
JMA - Jurik Moving Average - Contributed by Everget
KAMA - Kaufman's Adaptive Moving Average - Contributed by Everget
LSMA - Linear Regression , Least Squares Moving Average
RMA - Relative Moving Average
SMA - Simple Moving Average
SMMA - Smoothed Moving Average
Price Source - Plotted based on source selection
TEMA - Triple Exponential Moving Average
TMA - Triangular Moving Average
VAMA - Volume Adjusted Moving Average - Contributed by Duyck
VIDYA - Variable Index Dynamic Average - Contributed by KivancOzbilgic
VMA - Variable Moving Average - Contributed by LazyBear
VWMA - Volume Weighted Moving Average
WMA - Weighted Moving Average
WWMA - Welles Wilder's Moving Average
ZLEMA - Zero Lag Exponential Moving Average - Contributed by KivancOzbilgic
Disclaimer : This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
TradeIQ - Crazy Scalping Trading Strategy [Kaspricci]This strategy script is a combination of two indicators developed by LuxAlgo:
Triangular Momentum Oscillator & Real Time Divergences ( TMO )
Adjustable MA & Alternating Extremities (AMA)
The script combines the BUY and SELL signals from the TMO indicator with the BUY and SELL extremities shown by the AMA script and waits for the smoothed candles to grow in size. It places a SHORT or LONG order and sets a stop loss at the latest swing high or low (highes high or lowest low for a defined number of recent bars). A new LONG trade is highlighted by a green background. A new SHORT trade is highlighted by red background.
The trades will be closed once a new TMO indicator BUY or SELL signal appears or the color of the AMA extremities is switching from green to red and vice versa.
All parameters of TOM and AMA indicators are added as well and work the same way as in the original scripts provided by LuxAlgo.
The idea to combine these two indicators has been provided to me by TradIQ in his youtube video.
Please leave a comment in case you find a bug. In case you find a combination of parameters with a high win rat and high PnL I would be interested as well.
COT + ema + aux tickerPurpose: Create a script for backtesting the idea that COT can steer weekly Bias on Forex Market.
How does it works: the script use Commercials Delta Conctract, EMA of the selected ticker, EMA of 2 auxiliary tickers (e.g. correlated ticker) to generates buy and sell signals, it allows to include or not each of these.
If you use all the indicator, The buy or sell signals are generated following that rules:
(Example for buy signals on GBPCAD)
1) Commercials add net contract to GBP futures + remove net contract to CAD
2) EMA of GBPCAD is rising
3) EMA of 1st aux ticker is rising (or decline if select inv option)
4) EMA of 2nd aux ticker is rising (or decline if select inv option)
The scripts set the stop at low of the week for long orders and high of the week for shorts.
The exit strategy is to exit at first week of profit
How could you use it:
1) Choose your FX Ticker e.g. GBPCAD and set 1W TimeFrame
2) Select ticker in the strategy setting, remember to select the currency in right order, if you want to study GBP CAD 1st currency is GBP and 2nd CAD
3) Choose if you want to use EMA (and its period of calculation)
4) Choose if you want to use a aux ticker, the direction, and the relative ema period
What could be better;
1) you can just buy on begin of the week.
2) the exit strategy isn't best you can do
3) No level of delta contract is consider, its generate a buy signial also for 1 contract in the right direction
For any question, suggestion of improvemet, ideas, insult:) write to me
It all started from a script i find here on tradingview that extract COT data. Don't remember the name of that guy but Thanks a lot.
My English isn't perfect but i hope you can understand as well.
Backtest EngineThis is a simple backtest engine for your trading strategies. The idea behind this script is to make testing new strategies as easy as possible. Parameters such as take profit/stop loss and time period are built into the script and are customisable by the user via the settings interface. The only coding is to set the entry and exit conditions. Users need not touch any code beyond line 30.
For this post, I have used a 50/200 SMA crossover to demonstrate the ease of use for this script.
The features of this script include:
Backtest period start
Number of days until backtest period end
Take profit and stop loss % (via settings)
Programmable long and short entry/exit
Anti duplicate system (for entry conditions that are continuously satisfied, the engine will only make 1 trade until the is exit condition is satisfied).
DISCLAIMER: The strategy in this post is only a placeholder. The TP/SL levels are set to showcase the functionality of the engine and are in no means optimal settings.
Hope this helps! Feel free to ask any questions about the engine and happy coding!
"Golden buy" for cryptofutures (alerts for 3 commas/finandy)This script is a blend of open source cipher B indicator by VuManChu and Hammers & Stars strategy made by ZenAndTheArtOfTrading.
"Golden buy" is based on divergencies and was considered as one of the top strategies for cryptotrading. So I used it for entrance point in this script.
You can turn on opening short positions which are based on divergencies as well.
SL/TP, based on ATR 14, can be tuned, so does Risk/reward ratio.
VuManChu's parameters can be tuned too, but honestly, I don't know how it can help you.
And, finally, you can fully automate your trading with alerts templates presented in the script. (strategy.entry (...//comments= ) - for 3commas and 'alert' function under if conditions for finandy)
Thank you for your attention.
Monthly Returns in Strategies with Market BenchmarkThis is a modified version of this excellent script Monthly Returns in PineScript Strategues by QuantNomad
I liked and used the script but wanted to see how strategy performed vs market on each month/year. So I am sharing back.
The modification consists in adding Market or Buy & Hold performance between parenthesis inside each cell to better see how strategy performed vs market.
Also, 3 red levels and 3 green levels have been used :
For green :
1/ Light when strategy pnl > 0 but < market
2/ medium when strategy pnl > 0 and > market
3/ Dark when strategy pnl > 0 and market < 0 or pnl > market x 2
Same logic in the opposite direction for red.
The strategy provided here is just a showcase of how to use the table in pine script.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
