Day Trading Booster by DGTTiming when day trading can be everything
In Stock markets typically more volatility (or price activity) occurs at market opening and closings
When it comes to Forex (foreign exchange market), the world’s most traded market, unlike other financial markets, there is no centralized marketplace, currencies trade over the counter in whatever market is open at that time, where time becomes of more importance and key to get better trading opportunities. There are four major forex trading sessions, which are Sydney , Tokyo , London and New York sessions
Forex market is traded 24 hours a day, 5 days a week across by banks, institutions and individual traders worldwide, but that doesn’t mean it’s always active the entire day. It may be very difficult time trying to make money when the market doesn’t move at all. The busiest times with highest trading volume occurs during the overlap of the London and New York trading sessions, because U.S. dollar (USD) and the Euro (EUR) are the two most popular currencies traded. Typically most of the trading activity for a specific currency pair will occur when the trading sessions of the individual currencies overlap. For example, Australian Dollar (AUD) and Japanese Yen (JPY) will experience a higher trading volume when both Sydney and Tokyo sessions are open
There is one influence that impacts Forex matkets and should not be forgotten : the release of the significant news and reports. When a major announcement is made regarding economic data, currency can lose or gain value within a matter of seconds
Cryptocurrency markets on the other hand remain open 24/7, even during public holidays
Until 2021, the Asian impact was so significant in Cryptocurrency markets but recent reasearch reports shows that those patterns have changed and the correlation with the U.S. trading hours is becoming a clear evolving trend.
Unlike any other market Crypto doesn’t rest on weekends, there’s a drop-off in participation and yet algorithmic trading bots and market makers (or liquidity providers) can create a high volume of activity. Never trust the weekend’ is a good thing to remind yourself
One more factor that needs to be taken into accout is Blockchain transaction fees, which are responsive to network congestion and can change dramatically from one hour to the next
In general, Cryptocurrency markets are highly volatile, which means that the price of a coin can change dramatically over a short time period in either direction
The Bottom Line
The more traders trading, the higher the trading volume, and the more active the market. The more active the market, the higher the liquidity (availability of counterparties at any given time to exit or enter a trade), hence the tighter the spreads (the difference between ask and bid price) and the less slippage (the difference between the expected fill price and the actual fill price) - in a nutshell, yield to many good trading opportunities and better order execution (a process of filling the requested buy or sell order)
The best time to trade is when the market is the most active and therefore has the largest trading volume, trading all day long will not only deplete a trader's reserves quickly, but it can burn out even the most persistent trader. Knowing when the markets are more active will give traders peace of mind, that opportunities are not slipping away when they take their eyes off the markets or need to get a few hours of sleep
What does the Day Trading Booster do?
Day Trading Booster is designed ;
- to assist in determining market peak times, the times where better trading opportunities may arise
- to assist in determining the probable trading opportunities
- to help traders create their own strategies. An example strategy of when to trade or not is presented below
For Forex markets specifically includes
- Opening channel of Asian session, Europien session or both
- Opening price, opening range (5m or 15m) and day (session) range of the major trading center sessions, including Frankfurt
- A tabular view of the major forex markets oppening/closing hours, with a countdown timer
- A graphical presentation of typically traded volume and various forext markets oppening/clossing events (not only the major markets but many other around the world)
For All type of markets Day Trading Booster plots
- Day (Session) Open, 5m, 15m or 1h Opening Range
- Day (Session) Referance Levels, based on Average True Range (ATR) or Previous Day (Session) Range (PH - PL)
- Week and Month Open
Day Trading Booster also includes some of the day trader's preffered indicaotrs, such as ;
- VWAP - A custom interpretaion of VWAP is presented here with Auto, Interactive and Manual anchoring options.
- Pivot High/Low detection - Another custom interpretation of Pivot Points High Low indicator.
- A Moving Average with option to choose among SMA, EMA, WMA and HMA
An example strategy - Channel Bearkout Strategy
When day trading a trader usually monitors/analyzes lower timeframe charts and from time to time may loose insight of what really happens on the market from higher time porspective. Do not to forget to look at the larger time frame (than the one chosen to trade with) which gives the bigger picture of market price movements and thus helps to clearly define the trend
Disclaimer : Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Cerca negli script per "TAKE"
[ChasinAlts]Top-Wicked Good S/R LinesHello Tradeurs, as per usual, I hope everyone is having a FAN-FRIGGIN-TASTIC day. With the soon incoming bull market approaching fast(Nov 7, 2022), there are a few ideas that I've really been trying to push out to help nail a few coins as they are near their bottom peak of this closing Bear Market. This one may seem very similar to the last one I posted but I think this one takes the cake...esp when you see the next script from my 'Market Overview' series that I will be publishing shortly after this one as it is utilizing this new script for a market scanner that will be SUPER legit and profitable. Though it is alway nice to be noticed, I'm glad that I'm relatively unpopular so the few people that are now following me can have some time to make some money with some of these scripts I'm trying to pump out for the benefit of the community. I will rarely give my full analysis of how I take in and utilize these scripts but I can tell you, QUITE A FEW of them are money in the bank. Esp these last few I've done/am doing and even more-so the ones that are soon to come (I'm speaking of about the next 3-4 that I will be attempting to pump out in this next VERY IMPORTANT week.). One more thing I'll add before going to the script is a little alpha(Im pretty certain this is the way it is going but NOTHING is EVERY 100% in life). What I believe should be realized is the bottoming out of MANY of the crypto coins at the VERY bottom of a LONG TERM Cup and Handle (so it seems but shat can still change in the blink of an eye). Thus there are quite a few coins that I believe have already bottomed and wont be returning to said bottom for a few years or so but there are also quite a few still at the brink of the bottomest part before the real market breakout occurs. My goal with these scripts coming out this week to help you all find those coins that have yet to hit their very bottom (thus the ATH/ATL script recently published). Going back in history looking for the lowest points of long term Cup & Handles I will point out 2 key things. Near the center/bottomest part of these historical CnH you will see either Double Bottoms OR a Huge dump and then its V-shaped recovery. After these print the point of no return has occurred where only a few coins will be going lower than these Double Bottoms/V-Shaped recoveries. So the time is at hand. Now that many coins are seemingly pumping after this long consolidation, I believe we need to keep a keen eye out for THE FINAL RUG PULL (as soon as enough degenerates are leveraging Long their entire savings.). What Im saying is be ready for this final rug pull to finally be seeing these Double Bottoms/V-Shaped recoveries VERY soon. DO NOT waste all your capital yet and MAKE SURE to use stop losses or else rather than stop losses you will be burdened with MUCH WORSE losses. Im currently not even in the market bc I am waiting on said rug pull. Ok for the Script now.
This script is similar to the last one but with the previous one, one general set of settings can produce VASTLY different results (might have 2 S/R lines on one coin and 80 on another). I wanted to fix that with this script, turn it into a "Market Overview" Scanner and create alerts for the MO Scanner to be able to get alerted any time a coin is passing its largest wick S/R levels bc DULY NOTE...it is VERY rare that a coin will blow past it if it hasn't approached it recently. That means that a small retrace of 3-5%(or more) is EASY to acquire (with leverage that can really add up with how many coins are in the Kucoin Margin Coin list that I have in my scanners). Now, once price does shoot through a level you best be sure to be looking down the line for a retest of the S/R level it blew past before as they are MANY times the retest level and price will be coming back to it before continuing
in the direction it was going. Depending on the TF your using this could be a few hours to a few days to a few weeks...you get it. With this script you can choose to draw S/R lines 2 ways: 1) by having it plot S/R lines on the end of the largest 2(3,4,5..however many you choose) wicks that the chart has access to. For the scanner ill just be putting the largest 2-3 wicks and set alerts when coming up to them/crossing them & 2) having it draw S/R lines on the ends of the largest X% of wicks. it will be erasing the lines and drawing new ones on each new candle occurrence so the same general settings will no longer be producing VASTLY diff amounts of S/R lines and will be way more consistent amongst the coins for better utilization with the scanner (when I publish it). There is also a Wick Max Cutoff % so for those coins that had it's first few hours printing 100% sized wicks...you can choose to ignore them so they are not taking up one of your top spots for the S/R lines. There is similarly a Wick % min Size that can be selected so if you’re using the top % setting, it will help decrease those coins that can be still plotting 30 lines even though the top 3% of the largest wicks are set in the settings. Hope Im being clear but it's easy enough. I believe in you and your capabilities of comprehending it all and getting it all figured out. So this script is for a visualization for the scanner that I will be uploading soon-after. It's always nice to get a few comments if my ideas/scripts have been helpful to you and please don't hold back if you have something to tell me that I screwed up on (I am still rather new to this coding thing but I like to think I at least have some fresh ideas that aren’t out there in the public library). Talk to you soon and may the force be with your trades. Peace and love people...peace and love. -ChasinAlts out.
Stochastic Moving Average Delta Oscillator (SMADO)This is an interesting take on the stochastic oscillator. What I have done here is I've taken the cumulative sum of the deltas of all the simple moving averages from 1 to 200 and summed them. Next I transform this into a stochastic oscillator with ta.stoch. The point of this is to show you trends, tops and bottoms. I hope you find this indicator as interesting as I did. Please enjoy!
The Feature include: Stochastic Window, Number of MA's to check, General Smoothing, and Direction Indication.
Sw1tchFX - Average Daily RangeDESCRIPTION AND OVERVIEW
The Average Daily Range is a measure of volatility (typically across 5 days for the FX markets). I originally saw this being used in a trading system called ANTSSYS by Daryll Guppy and some other developers. I couldn't find it anywhere so I decided to build it from scratch.
What this does is allow you to measure volatility across various FX assets (I will apply other asset classes in the future that this is applicable to i.e. Crypto, Commodities, Blue Chip Stocks), and set realistic targets based off that volatility. Overall, this makes much more sense to me in the FX markets rather than support and resistance lines because it's based off the actual movement of the asset class. Market research shows that an asset class has a 80-85% chance to reach 75% of it's Average Daily Range (ADR).
Let's take a look at the daily ADR on the GBPNZD 15m chart. Notice how the values of the ADR act as real support and resistance based off the volatility of the asset. In this case, price did not quite reach the 75% ADR target.
Let's take a look at another example on EURNZD 15m chart. In this case, price hit the 75% target.
It's important to note that these levels do not bound the price. The probability that price exceeds it's 75% ADR is fairly low, but not impossible. Especially during important news events. Let's look at the recent USDCHF 15m chart for example.
Additionally, you can use these values to measure longer term movements (Weekly, and Monthly)
Here is a weekly view:
And a monthly view:
HOW I USE THIS
I use this in conjunction with some other indicators I've developed. Typically, I use range bars since I only care about price, not time. Additionally, averages are smoother when time is not taken into account and only price.
HOW THE CANDLE OPEN AND CLOSE IS CALCULATED
This is done based off of your own specific time zone and from the daily candle. So for me on PST, the daily candle will close at 1400. Once closed, a new ADR value is automatically calculated and added to the chart. There is an option to show past ADR values if you would like to see them or conduct additional research.
AJ's Position Size Calculator for Forex and StocksThis position size/ stop loss and take profit calculator is designed to make entering positions more efficient. In the settings enter your account size and currency. Stop loss and profit levels can be calculated from the ATR or manually. To manually choose stop and profit price, choose manual from the SL or TP Value Type, then enter your price in the boxes below. Lot size or shares will be calculated and displayed on the table to the right of the chart. Position size calculation takes into account any currency exchange rates between your account currency and the quoted currency of the selected ticker. For forex lot sizes the exchange rate for the quoted currency relative to account currency is also built in to get an accurate position size. Enter your brokers leverage and your used margin will be displayed as well. The position size calculator is currently only configured for stocks and forex, I will try to add updates, in the future to other tickers like crypto , precious metals and crude oil CFD's. profit target and stop loss calculator should work for all symbols. I can't guarantee that the output of this calculator is correct. Use at your own risk!
Limited MACDwhat is "Limited MACD"?
it is macd but it has some useful additional features.
what it does?
it takes limited values ??just like rsi. The highest value it can take is 100 and the lowest value is -100. this way it gets the same highs and lows for different symbols and time slots. which means we can set overbought and oversold values ??with it. he also paints candles according to their values. The closer the price is to the oversold values, the more red, and the closer to the overbought values, the greener.
how it does it?
macd values ??are limited by dividing by extreme values. The macd value is used as the variable for the color.rgb function, this is used to get a different color for each macd value.
how to use it?
The variables in the settings section are the same as standard macd.
Use the colors to identify overbought and oversold zones and to predict possible price reversal points. also the indicator will mark possible turning points. other than that, its use is similar to standard macd and its limits are up to your imagination.
four hour:
one hour:
five minute:
AM's SRTAM SRT In a year, there are around 248 to 252 trading days .
On dividing the same by 2 we get 124. Even 125 / 126 can be taken.
We get SRT value by dividing Nifty Spot with 124 SMA value & SRT is applicable on Nifty in a Day Chart.
This value ranges in between 0.6 (Low) to 1.38/1.4/1.45/1.5 (High).
Ideal Entry in a stock will be at 0.6, which is very rare. You tend to buy at 0.7/0.8/0.9/1.10.
Exit from a stock will be at 1.3 - 1.5.
However generally we get a value of 0.8/0.9 and we should start investing 20 % of our capital that we have planned to invest. For every 0.1 decrease in SRT Value, we should add 20% to the stock portfolio.
Start Booking Profit if SRT value above 1.35 & book 50 % of the portfolio when SRT value is 1.45.
For Traders, as an when SRT value comes to 0.8/ 0.9. Buy when Hilega Milega gives us a clear BUY signal on Monthly Time Frame.
Stock bought at SRT value of 0.6 tend to double in a year. It generally quite rare to see a SRT Value of 0.6.
Didi ATR HybridThis is a hybrid indicator that combines the Didi Index with the Average True Range.
It acts as both an ATR and a Confirmation indicator, based on the No-Nonsense Forex (NNFX) trade rules.
The Didi Index takes three moving averages to build a fast line (MA1 and MA2) and a slow line (MA2 and MA3). You can use it several different ways (2 lines cross, zero-cross); in this setup, we only use the slow line with the zero-cross to produce a signal (source code is set up to take advantage of the fast line - you just need to plot it yourself).
ATR is a measure of candle volatility.
The plotted value is equal to the ATR, which then gets colored based on:
Black : Didi Index is below 0 - do not enter trade
Red : Didi Index is above 1, but the previous candle closed >1x ATR - do not enter trade (too volatile)
Green : Didi Index is above 1, and the previous candle closed <1x ATR - a possible trend is confirmed and you may enter the trade (use other indicators too)
The provided chart does not look exciting - as with NNFX, I am posting it with the OANDA:EURUSD , which is one of the harder FX pairs to trade.
NIFTY IT volumeKEY TAKEAWAYS
-Uses NIFTY IT Index Stocks Volume .
-NIFTY IT Volume Indicator is created by adding all 10 NIFTY IT Stocks Volume together.
-NIFTY IT Volume will be an important indicator in NIFTY IT Index technical analysis because it is used to measure the relative significance of a market move.
-The higher the volume during a NIFTY IT index price move, the more significant the move and the lower the volume during a NIFTY IT index price move, the less significant the move.
-Moving Average is also added.
FinNifty VolumesKEY TAKEAWAYS
-Uses FinNifty Index Stocks Volume .
-FinNifty Volume Indicator is created by adding all 20 FinNifty Stocks Volume together.
-FinNifty Volume will be an important indicator in FinNifty Index technical analysis because it is used to measure the relative significance of a market move.
-The higher the volume during a FinNiftyy index price move, the more significant the move and the lower the volume during a FinNifty index price move, the less significant the move.
-Moving Average is also added.
Buy the dips - sell the topsThis script is a merge of the RSI and the Williams %R.
I've observed that in strong uptrends, we go from RSI overbought to RSI overbought, but it hardly gets oversold. (the same in the opposite direction)
To find a better entry point, Williams %R is used to find oversold conditions in an uptrend or overbought in a downtrend.
=> When W%R returns from oversold/overbought to normal, a triangle will be plotted and this is the point of entry to add to your position. (there's an option to mark all candles in the overbought/oversold region, by default it is off)
=> When RSI goes from overbought back to normal it will tell you to buy the dip. In a downtrend it will tell you to sell the tops.
=> When the RSI gets oversold and the previous RSI was overbought, it will mark to exit the position
I did backtest this one with a risk to reward of 2 and exit when target is reached.
Trading EUR/USD on the daily would return 28% after 10 years of trading with a success ratio of 43%.
Trading BTC/USD on the daily would lose 12% after 7 years and a success rate of 28%.
Trading it this way is not the best idea ;-) 2 Interesting observations however:
- Once you get the entry right, in 80% of the cases, you do reach the next RSI oversold/overbought level. Keeping your position open until you reach that level can be an option to maximize profits.
- When a triangle is plotted and it is the low compared to the previous more or less 5 candles (same for the high), chances are high it will be taken out a few candles later, so don't take a trade yet.
Using classic technical analysis might improve more your entry and exit positions.
Feel free to comment your best strategy using this indicator ;-)
Happy trading!
Calculate target by Range [Wyckoff,PnF]First of all, I would like to thank the author @LonesomeTheBlue.
This indicator developed on the source code "Point and Figure (PnF)" by author @LonesomeTheBlue.
This indicator calculate the range (Cause) of Phase accumulation or distribution to calculate the taget (Effect) based on the Wyckoff Method.
Formula for calculate move value target : Col * BoxSize * Reversal
Col -> Number of Column (PnF) in the range (Cause)
BoxSize -> Value in one Box (PnF)
Reversal -> Reversal (PnF)
FrostyBotLibrary "FrostyBot"
JSON Alert Builder for FrostyBot.js Binance Futures and FTX orders
github.com
More Complete Version Soon.
TODO: Comment Functions and annotations from command reference ^^
TODO: Add additional whitelist and symbol mappings.
leverage()
buy()
sell()
cancelall()
closelong()
closeshort()
traillong()
trailshort()
long()
short()
takeprofit()
stoploss()
Open High Low StrategyThis is a very simple, yet effective and to some extend widely followed scalping strategy to capture the underling sentiments of the counter whether it will go up or down.
What is it?
This is Open-High-Low (OLH) strategy.
As you already aware of Candlestick patterns, there is patterns called as Marubozu patterns where the sell wick or buy wick either ceases to exists (or very small). This is exactly in the same principle.
In OLH strategy: The buy signal appears when the Open Price is the Low Price. It means if you draw the candlestick, there is no bottom wick. So after the opening of the candle, the demand drives the price up to the level, some selling may or may not come and closes in green. This indicates a strong upward biasness of the underlying counter.
Similarly, a sell signal appears when the Open price is the High Price. It means there is no upper wick. So there is no buying pressure, since the opening of the candle, sellers are in force and pulls down the price to a closing.
This strategy generates the signal at the close of the candle (technically barstate.isconfirmed). Because until the bar is real-time there is no option to know the final closing or high. So you will see the bar on which it generates the buy or sell signal is actually indicates the previous bar as OLH bar.
To determine the Stop-Loss, it uses the most widely known SL calculation of:
For buy signal, it takes the low of the last 7 candles and substract the ATR (Average True Range) of 14-period.
For sell signal, it takes the high of the last 7 candles and add it to the ATR (Average True Range) of 14-period.
One can plot the SL lines as dotted green and red lines as well to see visually.
Default Risk:Reward is 1:2, Can be customizable.
What is Unique?
Of course the utter simplistic nature of this strategy is it's key point. Very easy and intuitive to understand.
There are awesome strategies in this forum that talks about the various indicators combinations and what not.
Instead of all this, in a 15m NSE:NIFTY chart, it generates a good ~ 47% profit-factor with 1:2 Risk Reward ratio. Means if you loose a trade you will loose 1% of account and if you win you will gain 2%. Means 3 trades (2 profits and 1 loss) in a trading session result 3% overall gain for the day. (Assuming you are ready with 1% draw down of your account per trade, at max).
Disclaimer:
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
Barndorff-Nielsen and Shephard Jump Statistic [Loxx]The following comments and descriptions are from from "Problems in the Application of Jump Detection Tests to Stock Price Data" by Michael William Schwert; Professor George Tauchen, Faculty Advisor.
This indicator applies several jump detection tests to intraday stock price data sampled at various frequencies. It finds that the choice of sampling frequency has an effect on both the amount of jumps detected by these tests, as well as the timing of those jumps. Furthermore, although these tests are designed to identify the same phenomenon, they find different amounts and timing of jumps when performed on the same data. These results suggest that these jump detection tests are probably identifying different types of jump behavior in stock price data, so they are not really substitutes for one another.
In recent years there has been a great deal of interest in studying jumps in asset price movements. Reasons why it is important to know when and how frequently jumps occur include risk management and the pricing and hedging of derivative contracts. Investors would benefit greatly from knowing the properties of jumps, since large instantaneous drops in asset prices result in large instantaneous losses. The effect of jumps on derivative pricing is equally significant, especially considering the important role derivatives play in modern financial markets. When asset price movements are continuous, investors can perfectly hedge derivative contracts such as options, but when jumps occur, they cause a change in the derivative price that is non-linear to the change in the price of the underlying asset. Thus, jumps introduce an unhedgeable risk to the holders of derivative contracts.
The ability to identify realized jumps in the financial markets could provide helpful information such as how frequently jumps occur, how large the jumps are, and whether they tend to occur in clusters. With this goal in mind, several authors have developed tests to determine whether or not an asset price movement is a statistically significant jump. These tests take advantage of the high-frequency intraday price data available today through electronic sources. Barndorff-Nielsen and Shephard (2004, 2006) use the difference between an estimate of variance and a jump-robust measure of variance to detect jumps over the course of a day. Approaching the problem differently, Jiang and Oomen (2007) exploit high order sample moments of returns to identify days that include jumps. Aїt-Sahalia and Jacod (2008) also exploit high order sample moments of returns to detect jumps by comparing price data sampled at two different frequencies. Lee and Mykland (2007) test for jumps at individual price observations by scaling returns by a local volatility measure. While these tests employ different strategies for detecting jumps, they are all designed to identify the same phenomenon.
For this indicator we are focused on the Barndorff-Nielsen and Shephard jump statistic.
Barndorff-Nielsen and Shephard (2004, 2006) developed a test that uses high-frequency price data to determine whether there is a jump over the course of a day. Their test compares two measures of variance: Realized Variance, which converges to the integrated variance plus a jump component as the time between observations approaches zero; and Bipower Variation, which converges to the integrated variance as the time between observations approaches zero, and is robust to jumps in the price path, an important fact for this application. The integrated variance of a price process is the integral of the square of the σ(t) term in (2.2.2), taken over the course of a day. Since prices cannot be observed continuously, one cannot calculate integrated variance exactly, and must estimate it instead.
For our purposes here, this is calculated as:
r = log(p /p )
This the geometric return from time ti-1 to time ti.
Then, Realized Variance and Bipower Variation are described by the following functions (see code for details)
realizedVariance(float src, int per)
and
bipowerVariance(float src, int per)
Huang and Tauchen (2005) also consider Relative Jump, a measure that approximates the percentage of total variance attributable to jumps:
RJ = (RV - BV) / RV
This statistic approximates the ratio of the sum of squared jumps to the total variance and is useful because it scales out long-term trends in volatility so one can compare the relative contribution of jumps to the variance of two price series with different volatilities.
To develop a statistical test to determine whether there is a significant difference between RV and BV, one needs an estimate of integrated quarticity. Andersen, Bollerslev, and Diebold (2004) recommend using a jump-robust realized Tri-Power Quarticity, I've included commentary in code to better explain how this indicator is collocated. See code for details.
How to use this indicator
When the bars turn gray, it's an indication that a jump has occurred in the market. It serves a warning that price jumped. I've included a percent point function (or inverse cumulative distribution function) to cutoff Z-score values depicted by histogram values. The top line at 3 is the empirical maximum Z-score value a serves merely as a point of reference. The Red line is the cutoff line calculated using PPF. When the histogram is green, no jumps have been detected. This indicator also includes alerts, signals, and bar coloring. I've also expanded the possible source types using my own Expanded Source Types library so you can test different log return methods as inputs. It is recommended to use window sizes of 7, 16, 78, 110, 156, and 270 returns for sampling intervals of 1 week, 1 day, 1 hour, 30 minutes, 15 minutes, and 5 minutes, respectively.
If you'ed like to better understand PPF, see here: Distributions in python
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Coral Trend Pullback Strategy (TradeIQ)Description:
Strategy is taken from the TradeIQ YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto".
Check out the full video for further details/clarification on strategy entry/exit conditions.
The default settings are exactly as TradeIQ described in his video.
However I found some better results by some tweaking settings, increasing R:R ratio and by turning off confirmation indicators.
This would suggest that perhaps the current confirmation indicators are not the best options. I'm happy to try add some other optional confirmation indicators if they look to be more effective.
Recommended timeframe: 1H
Strategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: Coral Trend is bullish
C2: At least 1 candle where low is above Coral Trend since last cross above Coral Trend
C3: Pullback happens and price closes below Coral Trend
C4: Coral Trend colour remains bullish for duration of pullback
C5: After valid pullback, price then closes above Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Green line is above red line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is blue
C6.2.2: HawkEye Volume Indicator colour is green
SHORT
C1: Coral Trend is bearish
C2: At least 1 candle where high is below Coral Trend since last cross below Coral Trend
C3: Pullback happens and price closes above Coral Trend
C4: Coral Trend colour remains bearish for duration of pullback
C5: After valid pullback, price then closes below Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Red line is above green line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is red
C6.2.2: HawkEye Volume Indicator colour is red
NOTE: All the optional confirmation indicators cannot be overlayed with Coral Trend so feel free to add each separately to the chart for visual purposes
Trade exit:
Stop Loss: Calculated by recent swing low over previous X candles (configurable with "Local High/Low Lookback")
Take Profit: Calculated from R:R multiplier * Stop Loss size
Credits
Strategy origin: TradeIQ's YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto"
It combines the following indicators for trade entry conditions:
Coral Trend Indicator by @LazyBear (Main indicator)
Absolute Strength Histogram | jh by @jiehonglim (Optional confirmation indicator)
Indicator: HawkEye Volume Indicator by @LazyBear (Optional confirmation indicator)
ADX and DI by @BeikabuOyaji (Optional confirmation indicator)
STD/C-Filtered, N-Order Power-of-Cosine FIR Filter [Loxx]STD/C-Filtered, N-Order Power-of-Cosine FIR Filter is a Discrete-Time, FIR Digital Filter that uses Power-of-Cosine Family of FIR filters. This is an N-order algorithm that turns the following indicator from a static max 16 orders to a N orders, but limited to 50 in code. You can change the top end value if you with to higher orders than 50, but the signal is likely too noisy at that level. This indicator also includes a clutter and standard deviation filter.
See the static order version of this indicator here:
STD/C-Filtered, Power-of-Cosine FIR Filter
Amplitudes for STD/C-Filtered, N-Order Power-of-Cosine FIR Filter:
What are FIR Filters?
In discrete-time signal processing, windowing is a preliminary signal shaping technique, usually applied to improve the appearance and usefulness of a subsequent Discrete Fourier Transform. Several window functions can be defined, based on a constant (rectangular window), B-splines, other polynomials, sinusoids, cosine-sums, adjustable, hybrid, and other types. The windowing operation consists of multipying the given sampled signal by the window function. For trading purposes, these FIR filters act as advanced weighted moving averages.
What is Power-of-Sine Digital FIR Filter?
Also called Cos^alpha Window Family. In this family of windows, changing the value of the parameter alpha generates different windows.
f(n) = math.cos(alpha) * (math.pi * n / N) , 0 ≤ |n| ≤ N/2
where alpha takes on integer values and N is a even number
General expanded form:
alpha0 - alpha1 * math.cos(2 * math.pi * n / N)
+ alpha2 * math.cos(4 * math.pi * n / N)
- alpha3 * math.cos(4 * math.pi * n / N)
+ alpha4 * math.cos(6 * math.pi * n / N)
- ...
Special Cases for alpha:
alpha = 0: Rectangular window, this is also just the SMA (not included here)
alpha = 1: MLT sine window (not included here)
alpha = 2: Hann window (raised cosine = cos^2)
alpha = 4: Alternative Blackman (maximized roll-off rate)
This indicator contains a binomial expansion algorithm to handle N orders of a cosine power series. You can read about how this is done here: The Binomial Theorem
What is Pascal's Triangle and how was it used here?
In mathematics, Pascal's triangle is a triangular array of the binomial coefficients that arises in probability theory, combinatorics, and algebra. In much of the Western world, it is named after the French mathematician Blaise Pascal, although other mathematicians studied it centuries before him in India, Persia, China, Germany, and Italy.
The rows of Pascal's triangle are conventionally enumerated starting with row n = 0 at the top (the 0th row). The entries in each row are numbered from the left beginning with k=0 and are usually staggered relative to the numbers in the adjacent rows. The triangle may be constructed in the following manner: In row 0 (the topmost row), there is a unique nonzero entry 1. Each entry of each subsequent row is constructed by adding the number above and to the left with the number above and to the right, treating blank entries as 0. For example, the initial number in the first (or any other) row is 1 (the sum of 0 and 1), whereas the numbers 1 and 3 in the third row are added to produce the number 4 in the fourth row.
Rows of Pascal's Triangle
0 Order: 1
1 Order: 1 1
2 Order: 1 2 1
3 Order: 1 3 3 1
4 Order: 1 4 6 4 1
5 Order: 1 5 10 10 5 1
6 Order: 1 6 15 20 15 6 1
7 Order: 1 7 21 35 35 21 7 1
8 Order: 1 8 28 56 70 56 28 8 1
9 Order: 1 9 36 34 84 126 126 84 36 9 1
10 Order: 1 10 45 120 210 252 210 120 45 10 1
11 Order: 1 11 55 165 330 462 462 330 165 55 11 1
12 Order: 1 12 66 220 495 792 924 792 495 220 66 12 1
13 Order: 1 13 78 286 715 1287 1716 1716 1287 715 286 78 13 1
For a 12th order Power-of-Cosine FIR Filter
1. We take the coefficients from the Left side of the 12th row
1 13 78 286 715 1287 1716 1716 1287 715 286 78 13 1
2. We slice those in half to
1 13 78 286 715 1287 1716
3. We reverse the array
1716 1287 715 286 78 13 1
This is our array of alphas: alpha1, alpha2, ... alphaN
4. We then pull alpha one from the previous order, order 11, the middle value
11 Order: 1 11 55 165 330 462 462 330 165 55 11 1
The middle value is 462, this value becomes our alpha0 in the calculation
5. We apply these alphas to the cosine calculations
example: + alpha4 * math.cos(6 * math.pi * n / N)
6. We then divide by the sum of the alphas to derive our final coefficient weighting kernel
**This is only useful for orders that are EVEN, if you use odd ordering, the following are the coefficient outputs and these aren't useful since they cancel each other out and result in a value of zero. See below for an odd numbered oder and compare with the amplitude of the graphic posted above of the even order amplitude:
What is a Standard Deviation Filter?
If price or output or both don't move more than the (standard deviation) * multiplier then the trend stays the previous bar trend. This will appear on the chart as "stepping" of the moving average line. This works similar to Super Trend or Parabolic SAR but is a more naive technique of filtering.
What is a Clutter Filter?
For our purposes here, this is a filter that compares the slope of the trading filter output to a threshold to determine whether to shift trends. If the slope is up but the slope doesn't exceed the threshold, then the color is gray and this indicates a chop zone. If the slope is down but the slope doesn't exceed the threshold, then the color is gray and this indicates a chop zone. Alternatively if either up or down slope exceeds the threshold then the trend turns green for up and red for down. Fro demonstration purposes, an EMA is used as the moving average. This acts to reduce the noise in the signal.
Included
Bar coloring
Loxx's Expanded Source Types
Signals
Alerts
MACD x SuperTrend with trailing stoplossThis trading strategy is based on MACD crossover and crossunder. It uses the supertrend to identify the trend it is trading on and takes trades accordingly. You can use the built in risk to reward ratio parameter through the settings of the indicator for your desired R/R
My goal in creating this indicator was to learn about risk management. This indicator will put up a stop-loss and take profit target according to the entry point it shows.
This indicator showed me the best results on BTC at 5min price chart. I'm new to trading so, do your own due diligence
SBS AlgoHello traders, I am here again with a new and improved indicator.
This indicator is based on a pivot breakout algorithm which gives buy and sell signals according to the breakout of trendline. This is an advanced version of another script. It also takes price action into consideration along with some basic indicators like MACD and ADX to give good entry signals.
NOTE: This indicator is not designed to take entries completely based on signals it gives. Please use it along with your trading strategy to add more confluence to your trading system and maximize your profits.
I hope you guys will like this one too .Enjoy 👍
In case you find any bug, please do report in comment section .Thank you.
NNFX Exposure UtilityOVERVIEW
This tool allows the user to manually keep track of how much of their account is currently exposed to each currency, and keep that information handy and organized on the chart as a table.
It is specialized for NNFX traders who are trading all the pairs among the 9 major currency crosses: AUD, CAD, CHF, EUR, GBP, JPY, NZD, SGD, USD.
HOW DO I USE THIS INDICATOR?
Before you take a trade, you should open the indicator settings for this indicator and check off which currencies you are about to go long and short on. Here are 3 trades taken as examples:
If you go long on EUR/USD with 2% risk, your exposure is 2% long on EUR and 2% short on USD.
Then if you go short on GBP/SGD with 2% risk, your exposure is 2% short on GBP and 2% long on SGD.
But if you go long on SGD/JPY with 2% risk, your exposure would now be 4% long on SGD and 2% short on JPY. This is against your rules if you are trading the NNFX way. So this tool allows you to see when you are about to accidentally overexpose yourself to any currency pair.
Ehlers Linear Extrapolation Predictor [Loxx]Ehlers Linear Extrapolation Predictor is a new indicator by John Ehlers. The translation of this indicator into PineScript™ is a collaborative effort between @cheatcountry and I.
The following is an excerpt from "PREDICTION" , by John Ehlers
Niels Bohr said “Prediction is very difficult, especially if it’s about the future.”. Actually, prediction is pretty easy in the context of technical analysis. All you have to do is to assume the market will behave in the immediate future just as it has behaved in the immediate past. In this article we will explore several different techniques that put the philosophy into practice.
LINEAR EXTRAPOLATION
Linear extrapolation takes the philosophical approach quite literally. Linear extrapolation simply takes the difference of the last two bars and adds that difference to the value of the last bar to form the prediction for the next bar. The prediction is extended further into the future by taking the last predicted value as real data and repeating the process of adding the most recent difference to it. The process can be repeated over and over to extend the prediction even further.
Linear extrapolation is an FIR filter, meaning it depends only on the data input rather than on a previously computed value. Since the output of an FIR filter depends only on delayed input data, the resulting lag is somewhat like the delay of water coming out the end of a hose after it supplied at the input. Linear extrapolation has a negative group delay at the longer cycle periods of the spectrum, which means water comes out the end of the hose before it is applied at the input. Of course the analogy breaks down, but it is fun to think of it that way. As shown in Figure 1, the actual group delay varies across the spectrum. For frequency components less than .167 (i.e. a period of 6 bars) the group delay is negative, meaning the filter is predictive. However, the filter has a positive group delay for cycle components whose periods are shorter than 6 bars.
Figure 1
Here’s the practical ramification of the group delay: Suppose we are projecting the prediction 5 bars into the future. This is fine as long as the market is continued to trend up in the same direction. But, when we get a reversal, the prediction continues upward for 5 bars after the reversal. That is, the prediction fails just when you need it the most. An interesting phenomenon is that, regardless of how far the extrapolation extends into the future, the prediction will always cross the signal at the same spot along the time axis. The result is that the prediction will have an overshoot. The amplitude of the overshoot is a function of how far the extrapolation has been carried into the future.
But the overshoot gives us an opportunity to make a useful prediction at the cyclic turning point of band limited signals (i.e. oscillators having a zero mean). If we reduce the overshoot by reducing the gain of the prediction, we then also move the crossing of the prediction and the original signal into the future. Since the group delay varies across the spectrum, the effect will be less effective for the shorter cycles in the data. Nonetheless, the technique is effective for both discretionary trading and automated trading in the majority of cases.
EXPLORING THE CODE
Before we predict, we need to create a band limited indicator from which to make the prediction. I have selected a “roofing filter” consisting of a High Pass Filter followed by a Low Pass Filter. The tunable parameter of the High Pass Filter is HPPeriod. Think of it as a “stone wall filter” where cycle period components longer than HPPeriod are completely rejected and cycle period components shorter than HPPeriod are passed without attenuation. If HPPeriod is set to be a large number (e.g. 250) the indicator will tend to look more like a trending indicator. If HPPeriod is set to be a smaller number (e.g. 20) the indicator will look more like a cycling indicator. The Low Pass Filter is a Hann Windowed FIR filter whose tunable parameter is LPPeriod. Think of it as a “stone wall filter” where cycle period components shorter than LPPeriod are completely rejected and cycle period components longer than LPPeriod are passed without attenuation. The purpose of the Low Pass filter is to smooth the signal. Thus, the combination of these two filters forms a “roofing filter”, named Filt, that passes spectrum components between LPPeriod and HPPeriod.
Since working into the future is not allowed in EasyLanguage variables, we need to convert the Filt variable to the data array XX . The data array is first filled with real data out to “Length”. I selected Length = 10 simply to have a convenient starting point for the prediction. The next block of code is the prediction into the future. It is easiest to understand if we consider the case where count = 0. Then, in English, the next value of the data array is equal to the current value of the data array plus the difference between the current value and the previous value. That makes the prediction one bar into the future. The process is repeated for each value of count until predictions up to 10 bars in the future are contained in the data array. Next, the selected prediction is converted from the data array to the variable “Prediction”. Filt is plotted in Red and Prediction is plotted in yellow.
The Predict Extrapolation indicator is shown above for the Emini S&P Futures contract using the default input parameters. Filt is plotted in red and Predict is plotted in yellow. The crossings of the Predict and Filt lines provide reliable buy and sell timing signals. There is some overshoot for the shorter cycle periods, for example in February and March 2021, but the only effect is a late timing signal. Further reducing the gain and/or reducing the BarsFwd inputs would provide better timing signals during this period.
ADDITIONS
Loxx's Expanded source types:
Library for expanded source types:
Explanation for expanded source types:
Three different signal types: 1) Prediction/Filter crosses; 2) Prediction middle crosses; and, 3) Filter middle crosses.
Bar coloring to color trend.
Signals, both Long and Short.
Alerts, both Long and Short.
Mark StructureMark Structure is building the market swing structure, minor and sub structure and marks all possible insignificant pivots
Building such structure is really complex task to do, that has a lot of obstacles and challenges. I'm doing my best to develop this indicator behaving in absolutely expectable and right way. Fill free to leave any comments or bug reports.
it supports:
- Marking all pivots with labels or join them continuously with trend lines.
- Marking minor and sub structured swings with labels or join them continuously with trend lines. Marking BOS or SMS BOS, which are mbos. Minor and substructure are structures inside swing structure and it can differ from the structure of lower timeframe
- Marking swings of swing structure with labels or join them continuously with trend lines. Marking BOS or SMS BOS of swing structure
- Changing bullish and bearish colors of each kind of structures
- Changing pivot labelings
- Changing colors of BOSs
Remarks:
- As I told you guys before, it has a lot of challenging cases. eg we have swing low and high on the same candle and in order to decide which pivot goes first I take lower time frame data to figure out what pivot is the first, but it happens that on lower time frame the same issue takes place, due to limitation of TradingView I can't go infinitely to lower timeframes to solve this issue, so I mark those cases with labels
- Another issue is very beginning of the trend its hard to detect swing structure there due to missing historical data. so skip a few waves in the very beginning
- Don't expect to have minor and sub structure in each swing waves, its totally fine when you don't have them at all
- Swing structure is the most significant structure and shows real price direction. Trend change is confirmed when for bull->bear the last HLbull LH>HH and HH-HL-HH are confirmed. You can change labelling for unconfirmed swing trend in the settings. By default its already done
TriexDev - SuperBuySellTrend (PLUS+)Minimal but powerful.
Have been using this for myself, so thought it would be nice to share publicly. Of course no script is correct 100% of the time, but this is one of if not the best in my basic tools. (This is the expanded/PLUS version)
Github Link for latest/most detailed + tidier documentation
Base Indicator - Script Link
TriexDev - SuperBuySellTrend (SBST+) TradingView Trend Indicator
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SBST Plus+
Using the "plus" version is optional, if you only want the buy/sell signals - use the "base" version.
## What are vector candles?
Vector Candles (inspired to add from TradersReality/MT4) are candles that are colour coded to indicate higher volumes, and likely flip points / direction changes, or confirmations.
These are based off of PVSRA (Price, Volume, Support, Resistance Analysis).
You can also override the currency that this runs off of, including multiple ones - however adding more may slow things down.
PVSRA - From MT4 source:
Situation "Climax"
Bars with volume >= 200% of the average volume of the 10 previous chart TFs, and bars
where the product of candle spread x candle volume is >= the highest for the 10 previous
chart time TFs.
Default Colours: Bull bars are green and bear bars are red.
Situation "Volume Rising Above Average"
Bars with volume >= 150% of the average volume of the 10 previous chart TFs.
Default Colours: Bull bars are blue and bear are blue-violet.
A blue or purple bar can mean the chart has reached a top or bottom.
High volume bars during a movement can indicate a big movement is coming - or a top/bottom if bulls/bears are unable to break that point - or the volume direction has flipped.
This can also just be a healthy short term movement in the opposite direction - but at times sets obvious trend shifts.
## Volume Tracking
You can shift-click any candle to get the volume of that candle (in the pair token/stock), if you click and drag - you will see the volume for that range.
## Bollinger Bands
Bollinger Bands can be enabled in the settings via the toggle.
Bollinger Bands are designed to discover opportunities that give investors a higher probability of properly identifying when an asset is oversold (bottom lines) or overbought (top lines).
>There are three lines that compose Bollinger Bands: A simple moving average (middle band) and an upper and lower band.
>The upper and lower bands are typically 2 standard deviations +/- from a 20-day simple moving average, but they can be modified.
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Base Indicator
## What is ATR?
The average true range (ATR) is a technical analysis indicator, which measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following:
- current high - the current low;
- the absolute value of the current high - the previous close;
- and the absolute value of the current low - the previous close.
The ATR is then a moving average, generally using 10/14 days, of the true ranges.
## What does this indicator do?
Uses the ATR and multipliers to help you predict price volatility, ranges and trend direction.
> The buy and sell signals are generated when the indicator starts
plotting either on top of the closing price or below the closing price. A buy signal is generated when the ‘Supertrend’ closes above the price and a sell signal is generated when it closes below the closing price.
> It also suggests that the trend is shifting from descending mode to ascending mode. Contrary to this, when a ‘Supertrend’ closes above the price, it generates a sell signal as the colour of the indicator changes into red.
> A ‘Supertrend’ indicator can be used on equities, futures or forex, or even crypto markets and also on daily, weekly and hourly charts as well, but generally, it will be less effective in a sideways-moving market.
Thanks to KivancOzbilgic who made the original SuperTrend Indicator this was based off
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## Usage Notes
Two indicators will appear, the default ATR multipliers are already set for what I believe to be perfect for this particular (double indicator) strategy.
If you want to break it yourself (I couldn't find anything that tested more accurately myself), you can do so in the settings once you have added the indicator.
Basic rundown:
- A single Buy/Sell indicator in the dim colour; may be setting a direction change, or just healthy movement.
- When the brighter Buy/Sell indicator appears; it often means that a change in direction (uptrend or downtrend) is confirmed.
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You can see here, there was a (brighter) green indicator which flipped down then up into a (brighter) red sell indicator which set the downtrend. At the end it looks like it may be starting to break the downtrend - as the price is hitting the trend line. (Would watch for whether it holds above or drops below at that point)
Another example, showing how sometimes it can still be correct but take some time to play out - with some arrow indicators.
Typically I would also look at oscillators, RSI and other things to confirm - but here it held above the trend lines nicely, so it appeared to be rather obvious.
It's worth paying attention to the trend lines and where the candles are sitting.
Once you understand/get a feel for the basics of how it works - it can become a very useful tool in your trading arsenal.
Also works for traditional markets & commodities etc in the same way / using the same ATR multipliers, however of course crypto generally has bigger moves.
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You can use this and other indicators to confirm likeliness of a direction change prior to the brighter/confirmation one appearing - but just going by the 2nd(brighter) indicators, I have found it to be surprisingly accurate.
Tends to work well on virtually all timeframes, but personally prefer to use it on 5min,15min,1hr, 4hr, daily, weekly. Will still work for shorter/other timeframes, but may be more accurate on mid ones.
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This will likely be updated as I go / find useful additions that don't convolute things. The base indicator may be updated with some limited / toggle-able features in future also.