SPY - SPX - S&P --- DAILY MODELThis model is optimized for SPY on a daily time-frame.
Even though it is still profitable (Profit factor > 1) on other time-frames, such as 1h or weekly, I strongly advise you to NOT consider these signals.
You might also get positive returns on other assets, and time-frames, and I also strongly advise you to NOT consider them for your trades. For example:
AAPL-1h
GOOGL-D-W
TSLA-D-W
PYPL-D
INTC-W
MSFT-D-W
FDN-D-W
And so on …
This model is an optimization (parameters tuning) of a meta-model (generic model) for the SPY. It is mainly based on a conjunction of price & volume personal indicators for both entry and exit signals.
The relative portability of the model to other assets and time-frames, coupled with a "Development set -> Validation set" approach, confers it a stronger reliability, and a better warranty of not being « over-optimized ». The meta-model has also served for other model buildings, about 100 as of today.
Be advised that this model applied to real data will get much lower profit factors. During high-volatility periods (such as current times), the model might also be less accurate, as "News streams", more than "prices and volumes", make the market.
As always, this model is for an educational purpose only, and should never be considered as a single decision tool. So, study it, and make sure your decisions are still your own choice.
Объем
Coinbase_3-MIN_HFT-StrategyThis conceptual strategy trades against the short-term trend. The first position can be either long or short.
In the short-term, prices fluctuate up and down on wide spread exchanges.
And if the price moves to one side, the price tends to return to its original position momentarily.
This strategy set stop order. Stop price is calculated with upper and lower shadows.
Only CPR StrategyHello Everyone This Strategy Base on CPR
By Default 1 Percentage TP AND 0.5 Percentage Sl & quantity 500
By Default Backtesting Starting Time 1 Jan 2020 and end time 31 Dec 2020
You Can also change everything.
In future, I will Enhance this Strategy
if you have any suggestion Mention here
Thank you so much
Dominator StrategyThis is the Strategy Version Of Dominator you can choose your take profit level and dates for backtesting calculates fee as well
Do investors appreciate a good animal mascot? It seems like it. Bull and bear markets are key investing lingo and symbols, capturing positive feelings (bull) or negative ones (bear). There’s no official rule, but a bull market tends to refer to a 20% increase in a market over time from its bottom, while a bear represents a 20% decrease from its top. In general, “bull” positivity or “bear” negativity can refer to upward or downward movements of almost anything, like individual stocks. And you’ll even notice investors saying they’re “bullish” on an industry with growth potential or “bearish” on a stock they think will drop .
Dominator will give you the calculation of the wave between Bull&bear
How to use :
Long Alert signal = Bull Wave on the market
Short Alert signal = Bear wave on the market
Apply these fundamentals to any time frame and you will be able to read the correction into the trend or even the trend reversals.
VWAP Bands BacktestThis is a backtest for evaluating the profitability of a vwap offsets strategy over time.
I took part of the code to create the script from Noro
So there is a link for its code
Trends and volume“Trends and volume” is a pair of ZigZag and Volume indicators. If in the ZigZag indicator a trend has changed from descending to ascending, and in the Volume indicator the volume of purchases (accumulation) exceeds the volume of sales (distribution), a signal to open a long position occurs.
Accordingly, the opening of a short position occurs with opposite indicators of trend and volume. The strategy has Volume smoothing settings and a ZigZag filter for selecting optimal settings on other instruments.
With default settings, the strategy allows you to make 2-4 successful trades per month, ideally shows the direction of the trades on the BINANCE:BTCUSDT , timeframe 1 hour.
Together with the “Trends and volume” backtest, you get the “Trends and volume alerts” indicator in which the alert function is built-in, you can set an alert for events: long entry and short entry.
Pay attention when you set alerts in the tradingview in the indicator, the true signal comes at the close of the hourly candle.
I can open demo access to the Trends and volume strategy for 15 days, for this write me.
Amrullah Deep Liquidity for S&P 500Amrullah Deep Liquidity (ADL)
Amrullah Deep Liquidity (ADL) is a high profit factor strategy based on models designed by Muhd Amrullah.
Choosing your trading pair that you are planning to backtest
Check that you have been given access to Amrullah Deep Liquidity (ADL). Select SPX500USD with the default 4H time frame. Once done, open Indicators > Invite-Only Scripts > Amrullah Deep Liquidity %.
Choosing your initial capital that you want to begin backtesting
Go to Settings > Properties > Initial Capital and type in the amount of capital you're starting with. For the SPX500USD trading pair, the initial capital is denominated in USD.
Adjusting your equity at risk until the trades match your risk profile and comfort level
Go to Inputs > Equity Risk and adjust the value you are comfortable with. To analyse performance, you also want to choose the Start Year, Start Month and Start Date. Select lower equity risk for trades that you intend to take without the use of leverage. You can select an equity risk from 0.001 to 0.05 or all the way to 1.
Finding the time frame with the highest profit factor
Profit factor is defined as the gross profit a strategy makes across a defined period of time divided by its gross loss. You may choose to scroll through other time frames to find better models. You can select a different time frame from 1 min to 1H or all the way to 1M. Once you find the model you desire, you are encouraged to check that the model has a backtested profit factor of >3.5. You can then begin looking through the Performance Summary to find other detailed statistics.
Analysing the equity curve from the Amrullah Deep Liquidity (ADL) strategy
A green equity curve indicates that the trades are accumulating profits. A red equity curve indicates that the trades are accumulating losses. A healthy equity curve is one that is green and grows steadily to the right and upward direction.
Analysing the display arrows on the chart
Amrullah Deep Liquidity (ADL) tells you when to take a trade and how much to put in a trade. ADL can do this as the model identifies inventory risk in traders and market makers in the chosen market. On your Tradingview chart, ADL will display an arrow that tells you when to enter a trade. You can also see the amount to trade beside the arrow.
Opting for a trial
Yes you may opt for a trial which has limited availability.
The author's background and experience
My career in software and deep learning development spans across more than 5 years. At work, I lead a team to solve core computer vision tasks for large companies. I continually read all kinds of computer science books and papers, and follows progress on tools used in financial markets.
Amrullah Deep Liquidity for ETHUSDAmrullah Deep Liquidity (ADL)
Amrullah Deep Liquidity (ADL) is a high profit factor strategy based on models designed by Muhd Amrullah.
Choosing your trading pair that you are planning to backtest
Check that you have been given access to Amrullah Deep Liquidity (ADL). Select ETHUSD with the default 4H time frame. Once done, open Indicators > Invite-Only Scripts > Amrullah Deep Liquidity %.
Choosing your initial capital that you want to begin backtesting
Go to Settings > Properties > Initial Capital and type in the amount of capital you're starting with. For the ETHUSD trading pair, the initial capital is denominated in USD.
Adjusting your equity at risk until the trades match your risk profile and comfort level
Go to Inputs > Equity Risk and adjust the value you are comfortable with. To analyse performance, you also want to choose the Start Year, Start Month and Start Date. Select lower equity risk for trades that you intend to take without the use of leverage. You can select an equity risk from 0.001 to 0.05 or all the way to 1.
Finding the time frame with the highest profit factor
Profit factor is defined as the gross profit a strategy makes across a defined period of time divided by its gross loss. You may choose to scroll through other time frames to find better models. You can select a different time frame from 1 min to 1H or all the way to 1M. Once you find the model you desire, you are encouraged to check that the model has a backtested profit factor of >3.5. You can then begin looking through the Performance Summary to find other detailed statistics.
Analysing the equity curve from the Amrullah Deep Liquidity (ADL) strategy
A green equity curve indicates that the trades are accumulating profits. A red equity curve indicates that the trades are accumulating losses. A healthy equity curve is one that is green and grows steadily to the right and upward direction.
Analysing the display arrows on the chart
Amrullah Deep Liquidity (ADL) tells you when to take a trade and how much to put in a trade. ADL can do this as the model identifies inventory risk in traders and market makers in the chosen market. On your Tradingview chart, ADL will display an arrow that tells you when to enter a trade. You can also see the amount to trade beside the arrow.
Opting for a trial
Yes you may opt for a trial which has limited availability.
The author's background and experience
My career in software and deep learning development spans across more than 5 years. At work, I lead a team to solve core computer vision tasks for large companies. I continually read all kinds of computer science books and papers, and follows progress on tools used in financial markets.
Amrullah Deep Liquidity for BTCUSDAmrullah Deep Liquidity (ADL)
Amrullah Deep Liquidity (ADL) is a high profit factor strategy based on models designed by Muhd Amrullah.
Choosing your trading pair that you are planning to backtest
Check that you have been given access to Amrullah Deep Liquidity (ADL). Select BTCUSD with the default 4H time frame. Once done, open Indicators > Invite-Only Scripts > Amrullah Deep Liquidity %.
Choosing your initial capital that you want to begin backtesting
Go to Settings > Properties > Initial Capital and type in the amount of capital you're starting with. For the BTCUSD trading pair, the initial capital is denominated in USD.
Adjusting your equity at risk until the trades match your risk profile and comfort level
Go to Inputs > Equity Risk and adjust the value you are comfortable with. To analyse performance, you also want to choose the Start Year, Start Month and Start Date. Select lower equity risk for trades that you intend to take without the use of leverage. You can select an equity risk from 0.001 to 0.05 or all the way to 1.
Finding the time frame with the highest profit factor
Profit factor is defined as the gross profit a strategy makes across a defined period of time divided by its gross loss. You may choose to scroll through other time frames to find better models. You can select a different time frame from 1 min to 1H or all the way to 1M. Once you find the model you desire, you are encouraged to check that the model has a backtested profit factor of >3.5. You can then begin looking through the Performance Summary to find other detailed statistics.
Analysing the equity curve from the Amrullah Deep Liquidity (ADL) strategy
A green equity curve indicates that the trades are accumulating profits. A red equity curve indicates that the trades are accumulating losses. A healthy equity curve is one that is green and grows steadily to the right and upward direction.
Analysing the display arrows on the chart
Amrullah Deep Liquidity (ADL) tells you when to take a trade and how much to put in a trade. ADL can do this as the model identifies inventory risk in traders and market makers in the chosen market. On your Tradingview chart, ADL will display an arrow that tells you when to enter a trade. You can also see the amount to trade beside the arrow.
Opting for a trial
Yes you may opt for a trial which has limited availability.
The author's background and experience
My career in software and deep learning development spans across more than 5 years. At work, I lead a team to solve core computer vision tasks for large companies. I continually read all kinds of computer science books and papers, and follows progress on tools used in financial markets.
Amrullah Deep Liquidity for ETHBTCAmrullah Deep Liquidity (ADL)
Amrullah Deep Liquidity (ADL) is a high profit factor strategy based on models designed by Muhd Amrullah.
Choosing your trading pair that you are planning to backtest
Check that you have been given access to Amrullah Deep Liquidity (ADL). Select ETHBTC with the default 2H time frame. Once done, open Indicators > Invite-Only Scripts > Amrullah Deep Liquidity %.
Choosing your initial capital that you want to begin backtesting
Go to Settings > Properties > Initial Capital and type in the amount of capital you're starting with. For the ETHBTC trading pair, the initial capital is denominated in BTC.
Adjusting your equity at risk until the trades match your risk profile and comfort level
Go to Inputs > Equity Risk and adjust the value you are comfortable with. To analyse performance, you also want to choose the Start Year, Start Month and Start Date. Select lower equity risk for trades that you intend to take without the use of leverage. You can select an equity risk from 0.001 to 0.05 or all the way to 1.
Finding the time frame with the highest profit factor
Profit factor is defined as the gross profit a strategy makes across a defined period of time divided by its gross loss. You may choose to scroll through other time frames to find better models. You can select a different time frame from 1 min to 1H or all the way to 1M. Once you find the model you desire, you are encouraged to check that the model has a backtested profit factor of >3.5. You can then begin looking through the Performance Summary to find other detailed statistics.
Analysing the equity curve from the Amrullah Deep Liquidity (ADL) strategy
A green equity curve indicates that the trades are accumulating profits. A red equity curve indicates that the trades are accumulating losses. A healthy equity curve is one that is green and grows steadily to the right and upward direction.
Analysing the display arrows on the chart
Amrullah Deep Liquidity (ADL) tells you when to take a trade and how much to put in a trade. ADL can do this as the model identifies inventory risk in traders and market makers in the chosen market. On your Tradingview chart, ADL will display an arrow that tells you when to enter a trade. You can also see the amount to trade beside the arrow.
Opting for a trial
Yes you may opt for a trial which has limited availability.
The author's background and experience
My career in software and deep learning development spans across more than 5 years. At work, I lead a team to solve core computer vision tasks for large companies. I continually read all kinds of computer science books and papers, and follows progress on tools used in financial markets.
Bio's LRL Straty
Its a strategy, in contrast with the last study I posted.
You have a FAST/SLOW Ma/Emas, and a LRL which is made of 2 different lenghts aswell.
Its backtested on Daily frames, and I advice to not blindy trust the signals, but consider using the buy signals as spot price opportunity for buy and hold.
LRL gives you the dominating trend.
SLOW EMA66 a LIME/RED signal, which you have to interpret in function of the LRL line.
The fast MA33 is useful as a moving Support/Resistance line.
Im still optimizing it, so you might find updates to this script.
I also made a strategy, which Im perfecting so I will give u an even easier tool if I find the holy grail :P
If you have any doubt, please consider asking.
Otherwise you will be helping me by leaving a feedback.
Forex Daily Trading - NNFX StyleHere is my implementation of the No Nonsense Forex way of trading.
I've tried to apply most of VP's rules to the best of my coding abilities. As of now, with default settings, the strategy does not perform exceptionally well - however I'm pretty confident there is a combination of settings that will make it profitable across all pairs, and maybe even commodities.
If anyone can find some good performing settings for this strategy please let me know and I'll provide the full logic and all indicators within the strategy. Also, if you have any suggestions of any indicators you feel could improve this strategy let me know and I'll update.
If anything doesn't make sense/doesn't work, or if you just need some more information please just let me know. Enjoy!
Trend Following or Mean RevertingThe strategy checks nature of the instruments. It Buys if the close is greater than yesterday's high, reverse the position if the close is lower than yesterday's low and repeat the process.
1. If it is trend following then the equity curve will be in uptrend
2. If it is mean reverting then the equity curve will be downtrend
Thanks to Rayner Teo.
Hancock - Filtered Volume OBV OSC [Strategy]Trading strategy based on Donchain channel price breakouts confirmed by an optionally configurable volume filtered OBV oscillator.
Colored diamonds on charts represent signals where top side is buy side and bot side is sell side - green indicates open and red indicates close.
Pretty simple but nicely demonstrates the volume filtered OBV oscillator found here .
Happy trading
Hancock
Hermes v1.0Hello
Today, I'm releasing Hermès my Eth Trading Script.
Hermès is a variation of my BTCUSDT Script Hadès.
It's looking for specific money/price patterns and compares the results with the "retails sentiment" then, the potential signals are filtered out with an advance/exclusive trend detector. ("Apóllôn" module).
Because this script is expected to be used with Bitmex, you should have a solid trading knowledge(money/Risk Management) .
On the last 4 Months:
* High Profits (~242% fees included)
* Extreme Accuracy (~92.86%)
* Very Low drawdown (-6%)
* About 4-5 Trades a month.
This indicator has been developed for BITMEX:ETHUSD /15Mins/Candles only.
As usual with my scripts:
- No repaint.
- Two Weeks of trial. (Minimum 1 Full trade/nothing to lose!)
Don't hesitate to claim your trial to check on its performance.
More information in my signature.(again don't hesitate to send me a message if you have questions)
Have a Good Day!
FearsAndHopesA strategy based on the assumption that if you buy in a panic and sell on the euphoria of the crowd, then in the long run you get a profit. The strategy is symmetrical, that is, we assume that FOMO and FUD have an equal impact on the crowd. Never make different paired parameters. Do not try to get a perfect result on the backtest. The setup is symmetrical, the program does not use EMA, requests to larger timeframes, and other things that can cause repaintings. However, if you use the value 1 in the Fast Sma Length field, repaintings is possible, use with caution. This algorithm makes me profit 2600% profit per year, which, of course, does not mean that the next year will bring the same. API history on Bitmex on request in PM. Use it as an indicator with pleasure. Access to the script and help in setting up costs 0.5 btc
All Instrument Swing Trader with Pyramids, DCA and Leverage
Introduction
This is my most advanced Pine 4 script so far. It combines my range trader algorithms with my trend following pyramids all on a single interval. This script includes my beta tested DCA feature along with simulated leverage and buying power calculations. It has a twin study with several alerts. The features in this script allow you to experiment with different risk strategies and evaluate the approximate impact on your account capital. The script is flexible enough to run on instruments from different markets and at various bar intervals. This strategy can be run in three different modes: long, short and bidirectional. The bidirectional mode has two split modes (Ping Pong and BiDir). It also generates a summary report label with information not available in the TradingView Performance report such as Rate Of Return Standard Deviation and other Sharpe Ratio input values. Notable features include the following:
- Swing Trading Paradigm
- Uni or Bidirectional trading modes
- Calculation presets for Crypto, Stocks and Forex
- Conditional Minimum Profit
- Hard stop loss field
- Two types of DCA (Positive and Negative)
- Discretionary Pyramid levels with threshold adjustment and limiter
- Consecutive loss counter with preset and label
- Reentry loss limiter and trade entry caution fields
- Simulated Leverage and margin call warning label (approximation only)
- Buying power report labels (approximation only)
- Rate Of Return report with input values for Sharpe Ratio, Sortino and others
- Summary report label with real-time status indicators
- Trend follow bias modes (Its still range trading)
- Six anti-chop settings
- Single interval strategy to reduce repaint occurrence
This is a swing trading strategy so the behavior of this script is to buy on weakness and sell on strength. As such trade orders are placed in a counter direction to price pressure. What you will see on the chart is a short position on peaks and a long position on valleys. Just to be clear, the range as well as trends are merely illusions as the chart only receives prices. However, this script attempts to calculate pivot points from the price stream. Rising pivots are shorts and falling pivots are longs. I refer to pivots as a vertex in this script which adds structural components to the chart formation (point, sides and a base). When trading in “Ping Pong” mode long and short positions are intermingled continuously as long as there exists a detectable vertex. Unfortunately, this can work against your backtest profitability on long duration trends where prices continue in a single direction without pullback. I have designed various features in the script to compensate for this event. A well configured script should perform in a range bound market and minimize losses in a trend. For a range trader the trend is most certainly not your friend. I also have a trend following version of this script for those not interested in trading the range.
This script makes use of the TradingView pyramid feature accessible from the properties tab. Additional trades can be placed in the draw-down space increasing the position size and thereby increasing the profit or loss when the position finally closes. Each individual add on trade increases its order size as a multiple of its pyramid level. This makes it easy to comply with NFA FIFO Rule 2-43(b) if the trades are executed here in America. The inputs dialog box contains various settings to adjust where the add on trades show up, under what circumstances and how frequent if at all. Please be advised that pyramiding is an advanced feature and can wipe out your account capital if your not careful. You can use the “Performance Bond Leverage” feature to stress test your account capital with varying pyramid levels during the backtest. Use modest settings with realistic capital until you discover what you think you can handle. See the“Performance Bond Leverage” description for more information.
In addition to pyramiding this script employs DCA which enables users to experiment with loss recovery techniques. This is another advanced feature which can increase the order size on new trades in response to stopped out or winning streak trades. The script keeps track of debt incurred from losing trades. When the debt is recovered the order size returns to the base amount specified in the TV properties tab. The inputs for this feature include a limiter to prevent your account from depleting capital during runaway markets. The main difference between DCA and pyramids is that this implementation of DCA applies to new trades while pyramids affect open positions. DCA is a popular feature in crypto trading but can leave you with large “bags” if your not careful. In other markets, especially margin trading, you’ll need a well funded account and much experience.
To be sure pyramiding and dollar cost averaging is as close to gambling as you can get in respectable trading exchanges. However, if you are looking to compete in a Forex contest or want to add excitement to your trading life style those features could find a place in your strategies. Although your backtest may show spectacular gains don’t expect your live trading account to do the same. Every backtest has some measure to data mining bias. Please remember that.
This script is equipped with a consecutive loss counter. A limit field is provided in the report section of the input dialog box. This is a whole number value that, when specified, will generate a label on the chart when consecutive losses exceed the threshold. Every stop hit beyond this limit will be reported on a version 4 label above the bar where the stop is hit. Use the location of the labels along with the summary report tally to improve the adaptability of system. Don’t simply fit the chart. A good trading system should adapt to ever changing market conditions. On the study version the consecutive loss limit can be used to halt live trading on the broker side (managed manually).
This script can simulate leverage applied to your account capital. Basically, you want to know if the account capital you specified in the properties tab is sufficient to trade this script with the order size, pyramid and DCA parameters needed. TradingView does not halt trading when the account capital is depleted nor do you receive notification of such an event. Input the leverage you intend to trade with and simulate the stress on your account capital. When the check box labeled “Report Margin Call” is enabled a marker will plot on the chart at the location where the threshold was breached. Additionally, the Summary Report will indicated such a breach has occurred during the backtest. Please note that the margin calculation uses a performance bond contract model which is the same type of leverage applied to Forex accounts. This is not the same leverage as stock margin accounts since shares are not actually borrowed. It is also not applicable to futures contracts since we do not calculate maintenance margin. Also note that the account margin and buying power are calculated using the U.S. Dollar as a funding currency. Margin rules across the globe vary considerably so use this feature as an approximation. The “Report Margin Call” plot only appears on negative buying power which is well beyond the NFA enforced margin closeout price. Vary the order size and account capital and activate the buying power plot to get as close as you can to the desired margin call threshold. Also keep in mind that rollover fees, commissions, spreads, etc affect the margin call in actual live trading. This feature does not include any of those costs.
Inputs
The script input dialog box is divided into five sections. The last section, Section 5, contains all of the script reporting options. Notable reporting options are the inputs which provide support for calculating actual Sharpe Ratios and other risk / performance metrics. The TradingView performance report does not produce a scalable Sharpe Ratio which is unfortunate considering the limited data supplied to the backtest. Three report fields made available in this section are intended to enable users to measure the performance of this script using various industry standard risk metrics. In particular, The Sharpe Ratio, Sortino Ratio, Alpha Calculation, Beta Calculation, R-Squared and Monthly Standard Deviation. The following fields are dedicated to this effort:
– ROR Sample Period - Integer number which specifies the rate of return period. This number is a component of the Sharpe Ratio and determines the number of sample periods divisible in the chart data. The number specified here is the length of the period measured in bar intervals. Since the quantity of TradingView historical data is limited this number should reflect the scalar value applied to your Sharpe calculation. When the checkbox “Report Period ROR” is enabled red boxes plot on the dates corresponding to the ROR sample period. The red boxes display information useful in calculating various risk and performance models. Ongoing buying power is included in the period report which is especially useful in assessing the DCA stress on account capital. Important: When the “ROR Sample Period” is specified the script computes the ROR mean value and displays the result in the summary report label on the live end of the chart. Use this number to calculate the historical standard deviation of period returns.
– Return Mean Value - This is the ROR mean value which is displayed in the summary report field “ROR Mean”. Enter the value shown in the summary report here in order to calculate the standard deviation of returns. Once calculated the result is displayed in the summary report field “Standard Dev”. Please note that ROR and standard deviation are calculated on the quote currency of the chart and not the account currency. If you intend to calculate risk metrics based on other denominated returns use the period calculations in a spreadsheet. Important: Do not change the account denomination on the properties tab simply to force a dollar calculation. It will alter the backtest itself since the minimum profit, stop-loss and other variables are always measured in the quote currency of the chart.
– Report Period ROR - This checkbox is used to display the ROR period report which plots a red label above the bars corresponding to the ROR sample period. The sample period is defined by the value entered into the “ROR Sample Period” field. This checkbox only determines if the period labels plot on the chart. It does not enable or disable the ROR calculation itself. Please see input description“ROR Sample Period” for a detailed description of this feature.
Design
This script uses twelve indicators on a single time frame. The original trading algorithms are a port from a much larger program on another trading platform. I’ve converted some of the statistical functions to use standard indicators available on TradingView. The setups make heavy use of the Hull Moving Average in conjunction with EMAs that form the Bill Williams Alligator as described in his book “New Trading Dimensions” Chapter 3. Lag between the Hull and the EMAs form the basis of the entry and exit points. The vertices are calculated using one of five featured indicators. Each indicator is actually a composite of calculations which produce a distinct mean. This mathematical distinction enables the script to be useful on various instruments which belong to entirely different markets. In other words, at least one of these indicators should be able generate pivots on an arbitrarily selected instrument. Try each one to find the best fit.
The entire script is around 2200 lines of Pine code which pushes the limits of what can be created on this platform given the TradingView maximums for: local scopes, run-time duration and compile time. This script incorporates code from both my range trader and trend following published programs. Both have been in development for nearly two years and have been in beta test for the last several months. During the beta test of the range trading script it was discovered that by widening the stop and delaying the entry, add on trading opportunities appeared on the chart. I determined that by sacrificing a few minor features code space could be made available for pyramiding capability in the range trader. The module has been through several refactoring passes and makes extensive use of ternary statements. As such, It takes a full three minutes to compile after adding it to a chart. Please wait for the hovering dots to disappear before attempting to bring up the input dialog box. For the most part the same configuration settings for the range script can be applied to this script.
Inputs to the script use cone centric measurements in effort to avoid exposing adjustments to the various internal indicators. The goal was to keep the inputs relevant to the actual trade entry and exit locations as opposed to a series of MA input values and the like. As a result the strategy exposes over 70 inputs grouped into long or short sections. Inputs are available for the usual minimum profit and stop-loss as well as safeguards, trade frequency, pyramids, DCA, modes, presets, reports and lots of calibrations. The inputs are numerous, I know. Unfortunately, at this time, TradingView does not offer any other method to get data in the script. The usual initialization files such as cnf, cfg, ini, json and xml files are currently unsupported.
I have several example configuration settings that I use for my own trading. They include cryptocurrencies and forex instruments on various time frames.
Indicator Repainting and Anomalies
Indicator repainting is an industry wide problem which mainly occurs when you mix backtest data with real-time data. It doesn't matter which platform you use some form of this condition will manifest itself on your chart over time. The critical aspect being whether live trades on your broker’s account continue to match your TradingView study.
Based on my experience with Pine, most of the problems stem from TradingView’s implementation of multiple interval access. Whereas most platforms provide a separate bar series for each interval requested, the Pine language interleaves higher time frames with the primary chart interval. The problem is exacerbated by allowing a look-ahead parameter to the Security function. The goal of my repaint prevention is simply to ensure that my signal trading bias remains consistent between the strategy, study and broker. That being said this is what I’ve done address this issue in this script:
1. This script uses only 1 time frame. The chart interval.
2. Every entry and exit condition is evaluated on closed bars only.
3. No security functions are called to avoid a look-ahead possibility.
4. Every contributing factor specified in the TradingView wiki regarding this issue has been addressed.
5. Entry and exit setups are not reliant on crossover conditions.
6. I’ve run a 10 minute chart live for a week and compared it to the same chart periodically reloaded. The two charts were highly correlated with no instances of completely opposite real-time signals. I do have to say that there were differences in the location of some trades between the backtest and the study. But, I think mostly those differences are attributable to trading off closed bars in the study and the use of strategy functions in the backtest.
The study does indeed bring up the TV warning dialog. The only reason for this is because the script uses an EMA indicator which according to TradingView is due to “peculiarities of the algorithm”. I use the EMA for the Bill Williams Alligator so there is no way to remove it.
One issue that comes up when comparing the strategy with the study is that the strategy trades show on the chart one bar later than the study. This problem is due to the fact that “strategy.entry()” and “strategy_exit()” do not execute on the same bar called. The study, on the other hand, has no such limitation since there are no position routines.
Please be aware that the data source matters. Cryptocurrency has no central tick repository so each exchange supplies TradingView its feed. Even though it is the same symbol the quality of the data and subsequently the bars that are supplied to the chart varies with the exchange. This script will absolutely produce different results on different data feeds of the same symbol. Be sure to backtest this script on the same data you intend to receive alerts for. Any example settings I share with you will always have the exchange name used to generate the test results.
Usage
The following steps provide a very brief set of instructions that will get you started but will most certainly not produce the best backtest. A trading system that you are willing to risk your hard earned capital will require a well crafted configuration that involves time, expertise and clearly defined goals. As previously mentioned, I have several example configs that I use for my own trading that I can share with you. To get hands on experience in setting up your own symbol from scratch please follow the steps below.
The input dialog box contains over 70 inputs separated into five sections. Each section is identified as such with a makeshift separator input. There are three main areas that must to be configured: long side, short side and settings that apply to both. The rest of the inputs apply to pyramids, DCA, reporting and calibrations. The following steps address these three main areas only. You will need to get your backtest in the black before moving on to the more advanced features.
Step 1. Setup the Base currency and order size in the properties tab.
Step 2. Select the calculation presets in the Instrument Type field.
Step 3. Select “No Trade” in the Trading Mode field.
Step 4. Select the Histogram indicator from Section 2. You will be experimenting with different ones so it doesn’t matter which one you try first.
Step 5. Turn on Show Markers in Section 2.
Step 6. Go to the chart and checkout where the markers show up. Blue is up and red is down. Long trades show up along the red markers and short trades on the blue.
Step 7. Make adjustments to “Base To Vertex” and “Vertex To Base” net change and roc in Section 3. Use these fields to move the markers to where you want trades to be.
Step 8. Try a different indicator from Section 2 and repeat Step 7 until you find the best match for this instrument on this interval. This step is complete when the Vertex settings and indicator combination produce the most favorable results.
Step 9. Go to Section 3 and enable “Apply Red Base To Base Margin”.
Step 10. Go to Section 4 and enable “Apply Blue Base To Base Margin”.
Step 11. Go to Section 2 and adjust “Minimum Base To Base Blue” and “Minimum Base To Base Red”. Observe the chart and note where the markers move relative to each other. Markers further apart will produce less trades but will reduce cutoffs in “Ping Pong” mode.
Step 12. Return to Section 3 and 4 and turn off “Base To Base Margin” which was enabled in steps 9 and 10.
Step 13. Turn off Show Markers in Section 2.
Step 14. Put in your Minimum Profit and Stop Loss in the first section. This is in pips or currency basis points (chart right side scale). Percentage is not currently supported. This is a fixed value minimum profit and stop loss. Also note that the profit is taken as a conditional exit on a market order not a fixed limit. The actual profit taken will almost always be greater than the amount specified (due to the exit condition). The stop loss, on the other hand, is indeed a hard number which is executed by the TradingView broker simulator when the threshold is breached. On the study version, the stop is executed at the close of the bar.
Step 15. Return to step 3 and select a Trading Mode (Long, Short, BiDir, Ping Pong). If you are planning to trade bidirectionally its best to configure long first then short. Combine them with “BiDir” or “Ping Pong” after setting up both sides of the trade individually. The difference between “BiDir” and “Ping Pong” is that “Ping Pong” uses position reversal and can cut off opposing trades less than the specified minimum profit. As a result “Ping Pong” mode produces the greatest number of trades.
Step 16. Take a look at the chart. Trades should be showing along the markers plotted earlier.
Step 17. Make adjustments to the Vertex fields in Section 2 until the TradingView performance report is showing a profit. This includes the “Minimum Base To Base” fields. If a profit cannot be achieved move on to Step 18. Other adjustments may make a crucial difference.
Step 18. Improve the backtest profitability by adjusting the “Entry Net Change” and “Entry ROC” in Section 3 and 4.
Step 19. Enable the “Mandatory Snap” checkbox in Section 3 and 4 and adjust the “Snap Candle Delta” and “Snap Fractal Delta” in Section 2. This should reduce some chop producing unprofitable reversals.
Step 20. Increase the distance between opposing trades by adding an “Interleave Delta” in Sections 3 and 4. This is a floating point value which starts at 0.01 and typically does not exceed 2.0.
Step 21. Increase the distance between opposing trades even further by adding a “Decay Minimum Span” in Sections 3 and 4. This is an absolute value specified in the symbol’s quote currency (right side scale of the chart). This value is similar to the minimum profit and stop loss fields in Section 1.
Step 22. Improve the backtest profitability by adjusting the “Sparse Delta” in Section 3 and 4.
Step 23. Improve the backtest profitability by adjusting the “Chase Delta” in Section 3 and 4.
Step 24. Improve the backtest profitability by adjusting the “Adherence Delta” in Section 3 and 4. This field requires the “Adhere to Rising Trend” checkbox to be enabled.
Step 25. Try each checkbox in Section 3 and 4. See if it improves the backtest profitability. The “Caution Lackluster” checkbox only works when “Caution Mode” is enabled.
Step 26. Enable the reporting conditions in Section 5. Look for long runs of consecutive losses or high debt sequences. These are indications that your trading system cannot withstand sudden changes in market sentiment.
Step 27. Examine the chart and see that trades are being placed in accordance with your desired trading goals. This is an important step. If your desired model requires multiple trades per day then you should be seeing hundreds of trades on the chart. Alternatively, you may be looking to trade fewer steep peaks and deep valleys in which case you should see trades at major turning points. Don’t simply settle for what the backtest serves you. Work your configuration until the system aligns with your desired model. Try changing indicators and even intervals if you cannot reach your simulation goals. Generally speaking, the histogram and Candle indicators produce the most trades. The Macro indicator captures the tallest peaks and valleys.
Step 28. Apply the backtest settings to the study version and perform forward testing.
This script is open for beta testing. After successful beta test it will become a commercial application available by subscription only. I’ve invested quite a lot of time and effort into making this the best possible signal generator for all of the instruments I intend to trade. I certainly welcome any suggestions for improvements. Thank you all in advance.
One final note. I'm not a fan of having the Performance Overview (blue wedge) automatically show up at the end of the publish page since it could be misleading. On the EUR/USD backtest showing here I used a minimum profit of 65 pips, a stop of 120 pips, the candle indicator and a 5 pyramid max value. Also Mark Pyramid Levels (blue triangles) are enabled along with a 720 ROR Sample Period (red labels).
Ploutos v1.0 (MedRsk)Hi everyone!
Today I'm gently releasing an alternative version of my other BINANCE:BTCUSDT accumulator: Hadès .
Ploũtos is a "Med-risk/Med reward" script, it's more conservative than Hadès but also less rewarding.
Ploũtos is carefully looking for specific money/price patterns and compares the results with the "retails sentiment" then, the potential signals are filtered out with an advance/exclusive trend detector. ("Apóllôn" module)
- High Profits (~13211% in about 2.5y compounding and fees included)
- High accuracy (~76%)
- Low Drawdown (~-10.5%)
This indicator has been developed for BINANCE:BTCUSDT /Binance/2H/Candles only.
As usual with my scripts:
- No repaint.
- Two Weeks of trial. (Minimum 1 Full trade/nothing to lose!)
Don't hesitate to claim your trial to check on its performance.
More information in my signature.(again don't hesitate to send me a message if you have questions)
Have a Good Day!
Strategy Death To The Bear Simple strategy for the indicator "Death To The Bear".
Simple rules:
- Entry according to the selected weapons.
- Take profit 1 (TP1) in% of daily ATR (can be set, default 20%)
- Active Stop in Breakeven when I take profit in TP1.
- Take profit 2 (TP1) in% of daily ATR (can be set, default 30%)
* Pyramidization can be changed from the configuration (maximum number of tickets to average your price)
* Many do not like to pyramid, but I can assure you that with good management, and good choice of the instrument and time frame, you will get good money.
Note: at the request of some people who cannot see the EMOJI in the configuration you can choose TEXT.
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VuManChu/Noski B Backtester (Gold Dot)This is a backtest version of Vumanchu's original script Market Cipher-B. All credit goes to his original coding.
This has been coded to backtest "Gold dot" entries only, so please keep that in mind when using.
Hope this is helpful!
VuManChu/Noski B Backtester (Divergence Green/Red Dot)This is a backtest version of Vumanchu's original script Market Cipher-B. All credit goes to his original coding.
This has been coded to backtest the alert conditions "Buy (Big green circle +div) and Sell (Big red circle + div)" entries only from the original Cipher B script, so please keep that in mind when using.
Hope this is helpful!
VuManChu/Noski B Backtester (Small Green/Red Dot)This is a backtest version of Vumanchu's original script Market Cipher-B. All credit goes to his original coding.
This has been coded to backtest Small Red/Green dot entries only, so please keep that in mind when using.
Hope this is helpful!
