Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
Cerca negli script per "profit"
Strategy Chameleon [theUltimator5]Have you ever looked at an indicator and wondered to yourself "Is this indicator actually profitable?" Well now you can test it out for yourself with the Strategy Chameleon!
Strategy Chameleon is a versatile, signal-agnostic trading strategy designed to adapt to any external indicator or trading system. Like a chameleon changes colors to match its environment, this strategy adapts to match any buy/sell signals you provide, making it the ultimate backtesting and automation tool for traders who want to test multiple strategies without rewriting code.
🎯 Key Features
1) Connects ANY external indicator's buy/sell signals
Works with RSI, MACD, moving averages, custom indicators, or any Pine Script output
Simply connect your indicator's signal output to the strategy inputs
2) Multiple Stop Loss Types:
Percentage-based stops
ATR (Average True Range) dynamic stops
Fixed point stops
3) Advanced Trailing Stop System:
Percentage trailing
ATR-based trailing
Fixed point trailing
4) Flexible Take Profit Options:
Risk:Reward ratio targeting
Percentage-based profits
ATR-based profits
Fixed point profits
5) Trading Direction Control
Long Only - Bull market strategies
Short Only - Bear market strategies
Both - Full market strategies
6) Time-Based Filtering
Optional trading session restrictions
Customize active trading hours
Perfect for day trading strategies
📈 How It Works
Signal Detection: The strategy monitors your connected buy/sell signals
Entry Logic: Executes trades when signals trigger during valid time periods
Risk Management: Automatically applies your chosen stop loss and take profit levels
Trailing System: Dynamically adjusts stops to lock in profits
Performance Tracking: Real-time statistics table showing win rate and performance
⚙️ Setup Instructions
0) Add indicator you want to test, then add the Strategy to your chart
Connect Your Signals:
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Go to strategy settings → Signal Sources
1) Set "Buy Signal Source" to your indicator's buy output
2) Set "Sell Signal Source" to your indicator's sell output
3) Choose table position - This simply changes the table location on the screen
4) Set trading direction preference - Buy only? Sell only? Both directions?
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5) Set your preferred stop loss type and level
You can set the stop loss to be either percentage based or ATR and fully configurable.
6) Enable trailing stops if desired
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7) Configure take profit settings
8) Toggle time filter to only consider specific time windows or trading sessions.
🚀 Use Cases
Test various indicators to determine feasibility and/or profitability.
Compare different signal sources quickly
Validate trading ideas with consistent risk management
Portfolio Management
Apply uniform risk management across different strategies
Standardize stop loss and take profit rules
Monitor performance consistently
Automation Ready
Built-in alert conditions for automated trading
Compatible with trading bots and webhooks
Easy integration with external systems
⚠️ Important Notes
This strategy requires external signals to function
Default settings use 10% of equity per trade
Pyramiding is disabled (one position at a time)
Strategy calculates on bar close, not every tick
🔗 Integration Examples
Works perfectly with:
RSI strategies (connect RSI > 70 for sells, RSI < 30 for buys)
Moving average crossovers
MACD signal line crosses
Bollinger Band strategies
Custom oscillators and indicators
Multi-timeframe strategies
📋 Default Settings
Position Size: 10% of equity
Stop Loss: 2% percentage-based
Trailing Stop: 1.5% percentage-based (enabled)
Take Profit: Disabled (optional)
Trade Direction: Both long and short
Time Filter: Disabled
Big Candle Identifier with RSI Divergence and Advanced Stops1. Strategy Objective
The main goal of this strategy is to:
Identify significant price momentum (big candles).
Enter trades at opportune moments based on market signals (candlestick patterns and RSI divergence).
Limit initial risk through a fixed stop loss.
Maximize profits by using a trailing stop that activates only after the trade moves a specified distance in the profitable direction.
2. Components of the Strategy
A. Big Candle Identification
The strategy identifies big candles as indicators of strong momentum.
A big candle is defined as:
The body (absolute difference between close and open) of the current candle (body0) is larger than the bodies of the last five candles.
The candle is:
Bullish Big Candle: If close > open.
Bearish Big Candle: If open > close.
Purpose: Big candles signal potential continuation or reversal of trends, serving as the primary entry trigger.
B. RSI Divergence
Relative Strength Index (RSI): A momentum oscillator used to detect overbought/oversold conditions and divergence.
Fast RSI: A 5-period RSI, which is more sensitive to short-term price movements.
Slow RSI: A 14-period RSI, which smoothens fluctuations over a longer timeframe.
Divergence: The difference between the fast and slow RSIs.
Positive divergence (divergence > 0): Bullish momentum.
Negative divergence (divergence < 0): Bearish momentum.
Visualization: The divergence is plotted on the chart, helping traders confirm momentum shifts.
C. Stop Loss
Initial Stop Loss:
When entering a trade, an immediate stop loss of 200 points is applied.
This stop loss ensures the maximum risk is capped at a predefined level.
Implementation:
Long Trades: Stop loss is set below the entry price at low - 200 points.
Short Trades: Stop loss is set above the entry price at high + 200 points.
Purpose:
Prevents significant losses if the price moves against the trade immediately after entry.
D. Trailing Stop
The trailing stop is a dynamic risk management tool that adjusts with price movements to lock in profits. Here’s how it works:
Activation Condition:
The trailing stop only starts trailing when the trade moves 200 ticks (profit) in the right direction:
Long Position: close - entry_price >= 200 ticks.
Short Position: entry_price - close >= 200 ticks.
Trailing Logic:
Once activated, the trailing stop:
For Long Positions: Trails behind the price by 150 ticks (trail_stop = close - 150 ticks).
For Short Positions: Trails above the price by 150 ticks (trail_stop = close + 150 ticks).
Exit Condition:
The trade exits automatically if the price touches the trailing stop level.
Purpose:
Ensures profits are locked in as the trade progresses while still allowing room for price fluctuations.
E. Trade Entry Logic
Long Entry:
Triggered when a bullish big candle is identified.
Stop loss is set at low - 200 points.
Short Entry:
Triggered when a bearish big candle is identified.
Stop loss is set at high + 200 points.
F. Trade Exit Logic
Trailing Stop: Automatically exits the trade if the price touches the trailing stop level.
Fixed Stop Loss: Exits the trade if the price hits the predefined stop loss level.
G. 21 EMA
The strategy includes a 21-period Exponential Moving Average (EMA), which acts as a trend filter.
EMA helps visualize the overall market direction:
Price above EMA: Indicates an uptrend.
Price below EMA: Indicates a downtrend.
H. Visualization
Big Candle Identification:
The open and close prices of big candles are plotted for easy reference.
Trailing Stop:
Plotted on the chart to visualize its progression during the trade.
Green Line: Indicates the trailing stop for long positions.
Red Line: Indicates the trailing stop for short positions.
RSI Divergence:
Positive divergence is shown in green.
Negative divergence is shown in red.
3. Key Parameters
trail_start_ticks: The number of ticks required before the trailing stop activates (default: 200 ticks).
trail_distance_ticks: The distance between the trailing stop and price once the trailing stop starts (default: 150 ticks).
initial_stop_loss_points: The fixed stop loss in points applied at entry (default: 200 points).
tick_size: Automatically calculates the minimum tick size for the trading instrument.
4. Workflow of the Strategy
Step 1: Entry Signal
The strategy identifies a big candle (bullish or bearish).
If conditions are met, a trade is entered with a fixed stop loss.
Step 2: Initial Risk Management
The trade starts with an initial stop loss of 200 points.
Step 3: Trailing Stop Activation
If the trade moves 200 ticks in the profitable direction:
The trailing stop is activated and follows the price at a distance of 150 ticks.
Step 4: Exit the Trade
The trade is exited if:
The price hits the trailing stop.
The price hits the initial stop loss.
5. Advantages of the Strategy
Risk Management:
The fixed stop loss ensures that losses are capped.
The trailing stop locks in profits after the trade becomes profitable.
Momentum-Based Entries:
The strategy uses big candles as entry triggers, which often indicate strong price momentum.
Divergence Confirmation:
RSI divergence helps validate momentum and avoid false signals.
Dynamic Profit Protection:
The trailing stop adjusts dynamically, allowing the trade to capture larger moves while protecting gains.
6. Ideal Market Conditions
This strategy performs best in:
Trending Markets:
Big candles and momentum signals are more effective in capturing directional moves.
High Volatility:
Larger price swings improve the probability of reaching the trailing stop activation level (200 ticks).
Stock Rating [TrendX_]# OVERVIEW
This Stock Rating indicator provides a thorough evaluation of a company (NON-FINANCIAL ONLY) ranging from 0 to 5. The rating is the average of six core financial metrics: efficiency, profitability, liquidity, solvency, valuation, and technical ratings. Each metric encompasses several financial measurements to ensure a robust and holistic evaluation of the stock.
## EFFICIENCY METRICS
1. Asset-to-Liability Ratio : Measures a company's ability to cover its liabilities with its assets.
2. Equity-to-Liability Ratio : Indicates the proportion of equity used to finance the company relative to liabilities.
3. Net Margin : Shows the percentage of revenue that translates into profit.
4. Operating Expense : Reflects the costs required for normal business operations.
5. Operating Expense Ratio : Compares operating expenses to total revenue.
6. Operating Profit Ratio : Measures operating profit as a percentage of revenue.
7. PE to Industry Relative PE/PB : Compares the company's PE ratio to the industry average.
## PROFITABILITY METRICS
1. ROA : Indicates how efficiently a company uses its assets to generate profit.
2. ROE : Measures profitability relative to shareholders' equity.
3. EBITDA : Reflects a company's operational profitability.
4. Free Cash Flow Margin : Shows the percentage of revenue that remains as free cash flow.
5. Revenue Growth : Measures the percentage increase in revenue over a period.
6. Gross Margin : Reflects the percentage of revenue exceeding the cost of goods sold.
7. Net Margin : Percentage of revenue that is net profit.
8. Operating Margin : Measures the percentage of revenue that is operating profit.
## LIQUIDITY METRICS
1. Current Ratio : Indicates the ability to cover short-term obligations with short-term assets.
2. Interest Coverage Ratio : Measures the ability to pay interest on outstanding debt.
3. Debt-to-EBITDA : Compares total debt to EBITDA.
4. Debt-to-Equity Ratio : Indicates the relative proportion of debt and equity financing.
## SOLVENCY METRICS
1. Altman Z-score : Predicts bankruptcy risk
2. Beneish M-score : Detects earnings manipulation.
3. Fulmer H-factor : Predicts business failure risk.
## VALUATION METRICS
1. Industry Relative PE/PB Comparison : Compares the company's PE and PB ratios to industry averages.
2. Momentum of PE, PB, and EV/EBITDA Multiples : Tracks the trends of PE, PB, and EV/EBITDA ratios over time.
## TECHNICAL METRICS
1. Relative Strength Index (RSI) : Measures the speed and change of price movements.
2. Supertrend : Trend-following indicator that identifies market trends.
3. Moving Average Golden-Cross : Occurs when a short-term MA crosses above mid-term and long-term MA which are determined by half-PI increment in smoothing period.
4. On-Balance Volume Golden-Cross : Measures cumulative buying and selling pressure.
Customizable OCC Non Repainting Scalper Bot v7.0bThis strategy is intended to be used on an automated trading platform and should be run on a one minute chart for fastest confirmations and signal relay to crypto automation platform. The strategy has been modded to only go long at this time to focus on profitability for one direction. The open long and close long text fields allow you to use your own webhook message for this purpose.
I have spent quite a bit of time and I figured I would put it out to the community to share the work and also get some feedback.
Ok, so let me say that I have done absolutely everything I can to make the strategy not repaint while still maintaining it's profitability. It has been a challenge so I am publishing this to the community to help test this.
What I have observed: the strategy will not repaint in real time. That is, if you have the chart open and keep it open, the signals are the same as the ones that are sent out by the strategy. In certain cases, when I reload the chart- the signals might be off from what was sent. In some ways, that is repainting, but it is repainting based on losing the real time data and recalculating from a different set of bars- since I am running it on a one minute chart then the start becomes different when you refresh.
To address repainting while keeping the strategy calculating as quickly as possibly I have altered the logic in the following ways:
I have made an assumption which might not work for everyone- at the first tick of the next bar, you can almost safefly assume in crypto that if you are looking at the previous bar for information, the open of the current bar was the close of the previous bar. This for the most part holds true in crypto with good liquidity. If you are trading a pair that jumps around due to low volume- this might not be the strategy to use. I might publish a different version with a different logic.
I have altered the security repaint to use isbarconfirmed, so at the very end of the bar (as soon as the bar is confirmed), we recalculate to the higher time frames. So as soon as the data is available, it is at that point that we can then safely calculate higher time frames. This is unique and experimental, but seems to do well at creating good signals for entry.
I have employed my own intervals by utilizing the resolution as an integer (used by the previous authors)- but in this case, I use the interval to take a snapshot of the higher time frame. With open close cross, the different moving averages can cause the repainting as they change to show the exact point of the cross. The interval feature I created minimizes this by utilizing the previous bar info until the interval is closed and then we recalculate the variants. You can use the interval offset feature to denote which minute is the one that starts and ends the interval. So for instance, Trading View uses minue 1 and minute 31 for 30 minute intervals. If you offset your 30 minute interval would start on minute 16 and do its calculations based on the last 30 minutes,
As with most of my scripts, I have started using filters and a "show data" feature that will give you the ability to see the values of indicators that you cannot plot in the overlay. This allows you to figure out how to filter losing trades or market conditions.
I have also added a trailing stop and created a fixed stop loss as seems to perform better than the original occ strategy. The original one seemed to repaint enough that it would close too quickly and not give the posiition enough time to become profitable. In certain cases where there was a large move, it would perform well, but for the most part the trades would not close profitably even though the backtest said that it did - probably due to the delay in execution and pinescript not having a confirmation on what the actual position price was.
This is still in beta mode, so please forward test first and use at your own risk.
If you spot repaint issues, please send me a message and try to explain the situation.
Period Dollar Cost Average BacktesterHere is a simple script to calculate the profits and other dollar cost average strategy statistics. This strategy was created to avoid asset price volatility, so the pump and dump scheme does not affect the portfolio. By dividing the investment amount into periods, the investor doesn’t need to analyze the market, fundamental analysis, or anything. The goal is to increase the asset holdings and avoid fast and robust price movements.
This indicator has some configurations.
Amount to buy: the amount to buy at each time
Broker fee %: the fee percentage that the broker has for spot trade
Frequency: the frequency of the investments. Example: 1 Day means that every day, it will buy an amount of the asset
Starting Date: when the indicator will start the investment simulation
Ending Date: when the indicator will end the investment simulation
InfoCell With/Height: it relates to the panel for view purposes. Change the values to fit better on your screen.
This indicator has three lines:
Total Invested (green): total amount invested at the end of the period
Total Net Profit (pink): total profit by converting the amount of the asset bought at the latest closing price
Holding Profits (yellow): the amount that would be in the portfolio if the investor had invested all the capital in a signal trade at the beginning of the period.
The statistics panel has some information to help you understand buying the asset in one or more trades. So, besides those three lines that were mentioned above, here are the other statistics:
Entry Price: The price of the asset when the first investment was made
Gross Profit: Total amount of profit, not excluding the losses
Gross Losses: Total amount of losses, not excluding the profits
Profit Factor: The Gross Profit divided by the Gross Loss. A value above 1 means it’s profitable.
Profit/Trades: Net profit per trade. This includes the broker fees.
Recovery Factor: The Net profit divided by the relative drawdown. The higher the recovery factor, the faster the recovery of a loss
Total Asset Bought: The amount of the asset that was bought at the end of the investment plan
Absolute Drawdown: The total amount of losses that made the account balance go below its initial value
Relative Drawdown: The max drawdown that occurred, no matter the account balance amount
Total Trades: number of times the investment was made in the selected period
Total Fee: total Fee that was spent on the total investment
Total Winning Trades: the total amount of winning trades. A trade is considered a winner if the net profit is up compared with the latest investment.
Total Losing Trades: the total amount of losing trades. A trade is considered a loser if the net profit is down compared to the latest investment.
Max consecutive wins: the max amount of consecutive winning trades
Max consecutive losses: the max amount of consecutive losing trades
The chart above uses the default configuration of the indicator. Placed on the BTCUSD market, taking the time range of January 1st, 2018 to January 1st, 2022, 4 years. Buying a BTC amount with 10 USDT every day in that period would generate a more than 500% profit. Compared to the profit amount by just holding the count, which was close to 350% profit, the dollar cost average by period would be much more profitable.
T7 JNSARJNSAR stands for Just Nifty -0.14% Stop & Reverse. This is a Trend Following Daily Bar Trading System for NIFTY -0.14% . Original idea belongs to ILLANGO @ I coded the pine version of this system based on a request from @stocksonfire. Use it at your own risk after validation at your end. Neither me or my company is responsible for any losses you may incur using this system. Hope you like this system and enjoy trading it !!!
Updated V3 code for the T7 JNSAR system earlier published here V2 and here V1
Following updates made to the code
1. Added a 22 Period Simple moving average filter over and above the standard JNSAR value for generating trading signals. This simple filter reduces the whipsaw trades drastically along with similar improvements in the max draw down and overall profitability of the system. The SMA filter is turned ON by default but can be turned OFF by user through the settings window.
2. Backtest option is now turned ON by default.
Also am republishing the trading rules here again with some modification
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty -0.14% Index. This system was developed and backtested only for NIFTY -0.14% Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2017 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Trade with only that amount of money you can afford to loose. Initial capital that you need to have to trade one lot of NIFTY -0.14% should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Place an After Market Order @ Market Price with your broker after market close so that you get to execute the trade next trading day @ Market open to capture near similar price as the daily open price seen on the chart. This execution mode will give you the best chance to minimize the slippage and mimic the backtester results as closely as practically possible.
7. Follow all the 6 rules above religiously, as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
Happy Trading !!! As always am looking out for your valuable feedback.
Dskyz (DAFE) Quantum Sentiment Flux - Beginners Dskyz (DAFE) Quantum Sentiment Flux - Beginners:
Welcome to the Dskyz (DAFE) Quantum Sentiment Flux - Beginners , a strategy and concept that’s your ultimate wingman for trading futures like MNQ, NQ, MES, and ES. This gem combines lightning-fast momentum signals, market sentiment smarts, and bulletproof risk management into a system so intuitive, even newbies can trade like pros. With clean DAFE visuals, preset modes for every vibe, and a revamped dashboard that’s basically a market GPS, this strategy makes futures trading feel like a high-octane sci-fi mission.
Built on the Dskyz (DAFE) legacy of Aurora Divergence, the Quantum Sentiment Flux is designed to empower beginners while giving seasoned traders a lean, sentiment-driven edge. It uses fast/slow EMA crossovers for entries, filters trades with VIX, SPX trends, and sector breadth, and keeps your account safe with adaptive stops and cooldowns. Tuned for more action with faster signals and a slick bottom-left dashboard, this updated version is ready to light up your charts and outsmart institutional traps. Let’s dive into why this strat’s a must-have and break down its brilliance.
Why Traders Need This Strategy
Futures markets are a wild ride—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional games that can wreck unprepared traders. Beginners often get lost in complex systems or burned by impulsive trades. The Quantum Sentiment Flux is the antidote, offering:
Dead-Simple Setup: Preset modes (Aggressive, Balanced, Conservative) auto-tune signals, risk, and sizing, so you can trade without a quant degree.
Sentiment Superpower: VIX filter, SPX trend, and sector breadth visuals keep you aligned with market health, dodging chop and riding trends.
Ironclad Safety: Tighter ATR-based stops, 2:1 take-profits, and preset cooldowns protect your capital, even in chaotic sessions.
Next-Level Visuals: Green/red entry triangles, vibrant EMAs, a sector breadth background, and a beefed-up dashboard make signals and context pop.
DAFE Swagger: The clean aesthetics, sleek dashboard—ties it to Dskyz’s elite brand, making your charts a work of art.
Traders need this because it’s a plug-and-play system that blends beginner-friendly simplicity with pro-level market awareness. Whether you’re just starting or scalping 5min MNQ, this strat’s your key to trading with confidence and style.
Strategy Components
1. Core Signal Logic (High-Speed Momentum)
The strategy’s engine is a momentum-based system using fast and slow Exponential Moving Averages (EMAs), now tuned for faster, more frequent trades.
How It Works:
Fast/Slow EMAs: Fast EMA (Aggressive: 5, Balanced: 7, Conservative: 9 bars) and slow EMA (12/14/18 bars) track short-term vs. longer-term momentum.
Crossover Signals:
Buy: Fast EMA crosses above slow EMA, and trend_dir = 1 (fast EMA > slow EMA + ATR * strength threshold).
Sell: Fast EMA crosses below slow EMA, and trend_dir = -1 (fast EMA < slow EMA - ATR * strength threshold).
Strength Filter: ma_strength = fast EMA - slow EMA must exceed an ATR-scaled threshold (Aggressive: 0.15, Balanced: 0.18, Conservative: 0.25) for robust signals.
Trend Direction: trend_dir confirms momentum, filtering out weak crossovers in choppy markets.
Evolution:
Faster EMAs (down from 7–10/21–50) catch short-term trends, perfect for active futures markets.
Lower strength thresholds (0.15–0.25 vs. 0.3–0.5) make signals more sensitive, boosting trade frequency without sacrificing quality.
Preset tuning ensures beginners get optimized settings, while pros can tweak via mode selection.
2. Market Sentiment Filters
The strategy leans hard into market sentiment with a VIX filter, SPX trend analysis, and sector breadth visuals, keeping trades aligned with the big picture.
VIX Filter:
Logic: Blocks long entries if VIX > threshold (default: 20, can_long = vix_close < vix_limit). Shorts are always allowed (can_short = true).
Impact: Prevents longs during high-fear markets (e.g., VIX spikes in crashes), while allowing shorts to capitalize on downturns.
SPX Trend Filter:
Logic: Compares S&P 500 (SPX) close to its SMA (Aggressive: 5, Balanced: 8, Conservative: 12 bars). spx_trend = 1 (UP) if close > SMA, -1 (DOWN) if < SMA, 0 (FLAT) if neutral.
Impact: Provides dashboard context, encouraging trades that align with market direction (e.g., longs in UP trend).
Sector Breadth (Visual):
Logic: Tracks 10 sector ETFs (XLK, XLF, XLE, etc.) vs. their SMAs (same lengths as SPX). Each sector scores +1 (bullish), -1 (bearish), or 0 (neutral), summed as breadth (-10 to +10).
Display: Green background if breadth > 4, red if breadth < -4, else neutral. Dashboard shows sector trends (↑/↓/-).
Impact: Faster SMA lengths make breadth more responsive, reflecting sector rotations (e.g., tech surging, energy lagging).
Why It’s Brilliant:
- VIX filter adds pro-level volatility awareness, saving beginners from panic-driven losses.
- SPX and sector breadth give a 360° view of market health, boosting signal confidence (e.g., green BG + buy signal = high-probability trade).
- Shorter SMAs make sentiment visuals react faster, perfect for 5min charts.
3. Risk Management
The risk controls are a fortress, now tighter and more dynamic to support frequent trading while keeping accounts safe.
Preset-Based Risk:
Aggressive: Fast EMAs (5/12), tight stops (1.1x ATR), 1-bar cooldown. High trade frequency, higher risk.
Balanced: EMAs (7/14), 1.2x ATR stops, 1-bar cooldown. Versatile for most traders.
Conservative: EMAs (9/18), 1.3x ATR stops, 2-bar cooldown. Safer, fewer trades.
Impact: Auto-scales risk to match style, making it foolproof for beginners.
Adaptive Stops and Take-Profits:
Logic: Stops = entry ± ATR * atr_mult (1.1–1.3x, down from 1.2–2.0x). Take-profits = entry ± ATR * take_mult (2x stop distance, 2:1 reward/risk). Longs: stop below entry, TP above; shorts: vice versa.
Impact: Tighter stops increase trade turnover while maintaining solid risk/reward, adapting to volatility.
Trade Cooldown:
Logic: Preset-driven (Aggressive/Balanced: 1 bar, Conservative: 2 bars vs. old user-input 2). Ensures bar_index - last_trade_bar >= cooldown.
Impact: Faster cooldowns (especially Aggressive/Balanced) allow more trades, balanced by VIX and strength filters.
Contract Sizing:
Logic: User sets contracts (default: 1, max: 10), no preset cap (unlike old 7/5/3 suggestion).
Impact: Flexible but risks over-leverage; beginners should stick to low contracts.
Built To Be Reliable and Consistent:
- Tighter stops and faster cooldowns make it a high-octane system without blowing up accounts.
- Preset-driven risk removes guesswork, letting newbies trade confidently.
- 2:1 TPs ensure profitable trades outweigh losses, even in volatile sessions like April 27, 2025 ES slippage.
4. Trade Entry and Exit Logic
The entry/exit rules are simple yet razor-sharp, now with VIX filtering and faster signals:
Entry Conditions:
Long Entry: buy_signal (fast EMA crosses above slow EMA, trend_dir = 1), no position (strategy.position_size = 0), cooldown passed (can_trade), and VIX < 20 (can_long). Enters with user-defined contracts.
Short Entry: sell_signal (fast EMA crosses below slow EMA, trend_dir = -1), no position, cooldown passed, can_short (always true).
Logic: Tracks last_entry_bar for visuals, last_trade_bar for cooldowns.
Exit Conditions:
Stop-Loss/Take-Profit: ATR-based stops (1.1–1.3x) and TPs (2x stop distance). Longs exit if price hits stop (below) or TP (above); shorts vice versa.
No Other Exits: Keeps it straightforward, relying on stops/TPs.
5. DAFE Visuals
The visuals are pure DAFE magic, blending clean function with informative metrics utilized by professionals, now enhanced by faster signals and a responsive breadth background:
EMA Plots:
Display: Fast EMA (blue, 2px), slow EMA (orange, 2px), using faster lengths (5–9/12–18).
Purpose: Highlights momentum shifts, with crossovers signaling entries.
Sector Breadth Background:
Display: Green (90% transparent) if breadth > 4, red (90%) if breadth < -4, else neutral.
Purpose: Faster breadth_sma_len (5–12 vs. 10–50) reflects sector shifts in real-time, reinforcing signal strength.
- Visuals are intuitive, turning complex signals into clear buy/sell cues.
- Faster breadth background reacts to market rotations (e.g., tech vs. energy), giving a pro-level edge.
6. Sector Breadth Dashboard
The new bottom-left dashboard is a game-changer, a 3x16 table (black/gray theme) that’s your market command center:
Metrics:
VIX: Current VIX (red if > 20, gray if not).
SPX: Trend as “UP” (green), “DOWN” (red), or “FLAT” (gray).
Trade Longs: “OK” (green) if VIX < 20, “BLOCK” (red) if not.
Sector Breadth: 10 sectors (Tech, Financial, etc.) with trend arrows (↑ green, ↓ red, - gray).
Placeholder Row: Empty for future metrics (e.g., ATR, breadth score).
Purpose: Consolidates regime, volatility, market trend, and sector data, making decisions a breeze.
- VIX and SPX metrics add context, helping beginners avoid bad trades (e.g., no longs if “BLOCK”).
Sector arrows show market health at a glance, like a cheat code for sentiment.
Key Features
Beginner-Ready: Preset modes and clear visuals make futures trading a breeze.
Sentiment-Driven: VIX filter, SPX trend, and sector breadth keep you in sync with the market.
High-Frequency: Faster EMAs, tighter stops, and short cooldowns boost trade volume.
Safe and Smart: Adaptive stops/TPs and cooldowns protect capital while maximizing wins.
Visual Mastery: DAFE’s clean flair, EMAs, dashboard—makes trading fun and clear.
Backtestable: Lean code and fixed qty ensure accurate historical testing.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Pick Preset: Aggressive (scalping), Balanced (versatile), or Conservative (safe). Balanced is default.
Set Contracts: Default 1, max 10. Stick low for safety.
Check Dashboard: Bottom-left shows preset, VIX, SPX, and sectors. “OK” + green breadth = strong buy.
Backtest: Run in strategy tester to compare modes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see VIX filter and stops in action.
Why It’s Brilliant
The Dskyz (DAFE) Quantum Sentiment Flux - Beginners is a masterpiece of simplicity and power. It takes pro-level tools—momentum, VIX, sector breadth—and wraps them in a system anyone can run. Faster signals and tighter stops make it a trading machine, while the VIX filter and dashboard keep you ahead of market chaos. The DAFE visuals and bottom-left command center turn your chart into a futuristic cockpit, guiding you through every trade. For beginners, it’s a safe entry to futures; for pros, it’s a scalping beast with sentiment smarts. This strat doesn’t just trade—it transforms how you see the market.
Final Notes
This is more than a strategy—it’s your launchpad to mastering futures with Dskyz (DAFE) flair. The Quantum Sentiment Flux blends accessibility, speed, and market savvy to help you outsmart the game. Load it, watch those triangles glow, and let’s make the markets your canvas!
Official Statement from Pine Script Team
(see TradingView help docs and forums):
"This warning may appear when you call functions such as ta.sma inside a request.security in a loop. There is no runtime impact. If you need to loop through a dynamic list of tickers, this cannot be avoided in the present version... Values will still be correct. Ignore this warning in such contexts."
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
[3Commas] HA & MAHA & MA
🔷What it does: This tool is designed to test a trend-following strategy using Heikin Ashi candles and moving averages. It enters trades after pullbacks, aiming to let profits run once the risk-to-reward ratio reaches 1:1 while securing the position.
🔷Who is it for: It is ideal for traders looking to compare final results using fixed versus dynamic take profits by adjusting parameters and trade direction—a concept applicable to most trading strategies.
🔷How does it work: We use moving averages to define the market trend, then wait for opposite Heikin Ashi candles to form against it. Once these candles reverse in favor of the trend, we enter the trade, using the last swing created by the pullback as the stop loss. By applying the breakeven ratio, we protect the trade and let it run, using the slower moving average as a trailing stop.
A buy signal is generated when:
The previous candle is bearish (ha_bear ), indicating a pullback.
The fast moving average (ma1) is above the slow moving average (ma2), confirming an uptrend.
The current candle is bullish (ha_bull), showing trend continuation.
The Heikin Ashi close is above the fast moving average (ma1), reinforcing the bullish bias.
The real price close is above the open (close > open), ensuring bullish momentum in actual price data.
The signal is confirmed on the closed candle (barstate.isconfirmed) to avoid premature signals.
dir is undefined (na(dir)), preventing repeated signals in the same direction.
A sell signal is generated when:
The previous candle is bullish (ha_bull ), indicating a temporary upward move before a potential reversal.
The fast moving average (ma1) is below the slow moving average (ma2), confirming a downtrend.
The current candle is bearish (ha_bear), showing trend continuation to the downside.
The Heikin Ashi close is below the fast moving average (ma1), reinforcing bearish pressure.
The real price close is below the open (close < open), confirming bearish momentum in actual price data.
The signal is confirmed after the candle closes (barstate.isconfirmed), avoiding premature entries.
dir is undefined (na(dir)), preventing consecutive signals in the same direction.
In simple terms, this setup looks for trend continuation after a pullback, confirming entries with both Heikin Ashi and real price action, supported by moving average alignment to avoid false signals.
If the price reaches a 1:1 risk-to-reward ratio, the stop will be moved to the entry point. However, if the slow moving average surpasses this level, it will become the new exit point, acting as a trailing stop
🔷Why It’s Unique
Easily visualizes the benefits of using risk-to-reward ratios when trading instead of fixed percentages.
Provides a simple and straightforward approach to trading, embracing the "keep it simple" concept.
Offers clear visualization of DCA Bot entry and exit points based on user preferences.
Includes an option to review the message format before sending signals to bots, with compatibility for multi-pair and futures contract pairs.
🔷 Considerations Before Using the Indicator
⚠️Very important: The indicator must be used on charts with real price data, such as Japanese candlesticks, line charts, etc. Do not use it on Heikin Ashi charts, as this may lead to unrealistic results.
🔸Since this is a trend-following strategy, use it on timeframes above 4 hours, where market noise is reduced and trends are clearer. Also, carefully review the statistics before using it, focusing on pairs that tend to have long periods of well-defined trends.
🔸Disadvantages:
False Signals in Ranges: Consolidating markets can generate unreliable signals.
Lagging Indicator: Being based on moving averages, it may react late to sudden price movements.
🔸Advantages:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Uses Heikin Ashi candles to identify trend continuation after pullbacks.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸The strategy provides a systematic way to analyze markets but does not guarantee successful outcomes. Use it as an additional tool rather than relying solely on an automated system.
Trading results depend on various factors, including market conditions, trader discipline, and risk management. Past performance does not ensure future success, so always approach the market cautiously.
🔸Risk Management: Define stop-loss levels, position sizes, and profit targets before entering any trade. Be prepared for potential losses and ensure your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
MA1 Length: 9.
MA2 Length: 18.
MA Calculations: EMA.
Take Profit Ratio: Disable. Ratio 1:4.
Breakeven Ratio: Enable, Ratio 1:1.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +324.88 USDT (+3.25%).
Max Drawdown: -81.18 USDT (-0.78%).
Total Closed Trades: 672.
Percent Profitable: 35.57%.
Profit Factor: 1.347.
Average Trade: +0.48 USDT (+0.48%).
Average # Bars in Trades: 13.
🔷 HOW TO USE
🔸 Adjust Settings:
The default values—MA1 (9) and MA2 (18) with EMA calculation—generally work well. However, you can increase these values, such as 20 and 40, to better identify stronger trends.
🔸 Choose a Symbol that Typically Trends:
Select an asset that tends to form clear trends. Keep in mind that the Strategy Tester results may show poor performance for certain assets, making them less suitable for sending signals to bots.
🔸 Experiment with Ratios:
Test different take profit and breakeven ratios to compare various scenarios—especially to observe how the strategy performs when only the trade is protected.
🔸This is an example of how protecting the trade works: once the price moves in favor of the position with a 1:1 risk-to-reward ratio, the stop loss is moved to the entry price. If the Slow MA surpasses this level, it will act as a trailing stop, aiming to follow the trend and maximize potential gains.
🔸In contrast, in this example, for the same trade, if we set a take profit at a 1:3 risk-to-reward ratio—which is generally considered a good risk-reward relationship—we can see how a significant portion of the upward move is left on the table.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
MA 1: Fast MA Length
MA 2: Slow MA Length
MA Calc: MA's Calculations (SMA,EMA, RMA,WMA)
TP Ratio: This is the take profit ratio relative to the stop loss, where the trade will be closed in profit.
BE Ratio: This is the breakeven ratio relative to the stop loss, where the stop loss will be updated to breakeven or if the MA2 is greater than this level.
Strategy: Order Type direction in which trades are executed.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Smart MA Crossover BacktesterSmart MA Crossover Backtester - Strategy Overview
Strategy Name: Smart MA Crossover Backtester
Published on: TradingView
Applicable Markets: Works well on crypto (tested profitably on ETH)
Strategy Concept
The Smart MA Crossover Backtester is an improved Moving Average (MA) crossover strategy that incorporates a trend filter and an ATR-based stop loss & take profit mechanism for better risk management. It aims to capture trends efficiently while reducing false signals by only trading in the direction of the long-term trend.
Core Components & Logic
Moving Averages (MA) for Entry Signals
Fast Moving Average (9-period SMA)
Slow Moving Average (21-period SMA)
A trade signal is generated when the fast MA crosses the slow MA.
Trend Filter (200-period SMA)
Only enters long positions if price is above the 200-period SMA (bullish trend).
Only enters short positions if price is below the 200-period SMA (bearish trend).
This helps in avoiding counter-trend trades, reducing whipsaws.
ATR-Based Stop Loss & Take Profit
Uses the Average True Range (ATR) with a multiplier of 2 to calculate stop loss.
Risk-Reward Ratio = 1:2 (Take profit is set at 2x ATR).
This ensures dynamic stop loss and take profit levels based on market volatility.
Trading Rules
✅ Long Entry (Buy Signal):
Fast MA (9) crosses above Slow MA (21)
Price is above the 200 MA (bullish trend filter active)
Stop Loss: Below entry price by 2× ATR
Take Profit: Above entry price by 4× ATR
✅ Short Entry (Sell Signal):
Fast MA (9) crosses below Slow MA (21)
Price is below the 200 MA (bearish trend filter active)
Stop Loss: Above entry price by 2× ATR
Take Profit: Below entry price by 4× ATR
Why This Strategy Works Well for Crypto (ETH)?
🔹 Crypto markets are highly volatile – ATR-based stop loss adapts dynamically to market conditions.
🔹 Long-term trend filter (200 MA) ensures trading in the dominant direction, reducing false signals.
🔹 Risk-reward ratio of 1:2 allows for profitable trades even with a lower win rate.
This strategy has been tested on Ethereum (ETH) and has shown profitable performance, making it a strong choice for crypto traders looking for trend-following setups with solid risk management. 🚀
HTC peppermint_07 CCI w signal + s&r RSI
This CCI version enhances the traditional Commodity Channel Index (CCI) by integrating a dynamically calculated Relative Strength Index (RSI) that acts as support and resistance as shown in the screenshot, it can add as a confirmation to the divergence found in the CCI.
Key Features:
Enhanced CCI: The primary plot (black line but customizable) represents the standard CCI, providing insight into price momentum and potential overbought/oversold conditions.
Dynamic RSI Support/Resistance: The upper and lower bands (medium cyan line) are derived from a smoothed RSI, dynamically adjusting to the current market volatility. These bands serve as potential support and resistance levels for the CCI as additional confirmation for the divergence.
Overbought/Oversold Zones: The traditional overbought (+100) and oversold (-100) levels for CCI are marked with horizontal dotted lines.
Benefits:
Improved Entry/Exit Signals: Combining CCI with dynamic RSI support/resistance may offer more precise trading signals compared to using CCI alone.
Dynamic Adaptation: The RSI-based bands adapt to changing market conditions, potentially providing more relevant support and resistance levels.
Divergence Confirmation: dynamic s&r RSI adds confluence to potential trend reversals identified by the CCI.
Potential Usage:
Traders might use this indicator to:
Identify potential overbought/oversold conditions using the CCI and its relationship to the dynamic RSI bands.
Look for breakouts beyond the dynamic support/resistance levels as potential entry points.
Confirm potential trend reversals using RSI divergence (cyan and red label above divergence) signals.
Further Development Considerations:
Customizable Parameters: Allowing users to adjust the CCI length, RSI periods, and smoothing factors would enhance flexibility.
Alert Conditions: Adding alerts for breakouts, overbought/oversold conditions, and divergence signals would improve usability.
Backtesting: Thoroughly backtesting the indicator's performance across different assets and timeframes is essential before using it for live trading.
DISCLAIMER: !!
indicator is a custom technical analysis tool designed for educational and informational purposes only. It should not be construed as financial advice or a recommendation to buy or sell any security. Trading involves substantial risk of loss and may not be suitable for all investors.
Key Points to Consider:
No Guarantee of Profitability: The indicator's past performance is not indicative of future results. No trading strategy can guarantee profits or eliminate the risk of losses. You could lose some or all of your investment.
Use at Your Own Risk: Use of this indicator is solely at your own discretion and risk. You are responsible for your trading decisions. The developers and distributors of this indicator are not liable for any losses incurred as a result of using it.
Not Financial Advice: This indicator does not provide financial advice. Consult with a qualified financial advisor before making any investment decisions.
Backtesting Limitations: Backtested results, if presented, should be viewed with caution. Past performance may not reflect future results due to various factors, including changing market conditions and the limitations of backtesting methodologies.
Indicator Limitations: Technical indicators, including this one, are not perfect. They can generate false signals, and their effectiveness can vary depending on market conditions and the specific parameters used.
Parameter Optimization: Optimizing indicator parameters for past performance can lead to overfitting, which may not translate to future profitability.
No Warranty: The indicator is provided "as is" without any warranty of any kind, either express or implied, including but not limited to warranties of merchantability, fitness for a particular purpose, or non-infringement.
Changes and Updates: The developers may make changes or updates to the indicator without notice.
By using the "HTC peppermint_07 CCI w signal + s&r RSI" indicator, you acknowledge and agree to the terms of this disclaimer. If you do not agree with these terms, do not use the indicator.
Martingale with MACD+KDJ opening conditionsStrategy Overview:
This strategy is based on a Martingale trading approach, incorporating MACD and KDJ indicators. It features pyramiding, trailing stops, and dynamic profit-taking mechanisms, suitable for both long and short trades. The strategy increases position size progressively using a Multiplier, a key feature of Martingale systems.
Key Concepts:
Martingale Strategy: A trading system where positions are doubled or increased after a loss to recover previous losses with a single successful trade. In this script, the position size is incremented using a Multiplier for each addition.
Pyramiding: Allows adding to existing trades when market conditions are favorable, enhancing profitability during trends.
Settings:
Basic Inputs:
Initial Order: Defines the starting size of the position.
Default: 150.0
MACD Settings: Customize the fast, slow, and signal smoothing lengths.
Default: Fast Length: 9, Slow Length: 26, Signal Smoothing: 9
KDJ Settings: Customize the length and smoothing parameters for KDJ.
Default: Length: 14, Smooth K: 3, Smooth D: 3
Max Additions: Sets the number of additional positions (pyramiding).
Default: 5 (Min: 1, Max: 10)
Position Sizing: Percent to add to positions on favorable conditions.
Default: 1.0%
Martingale Multiplier:
Add Multiplier: This value controls the scaling of additional positions according to the Martingale principle. After each loss, a new position is added, and its size is increased by the Multiplier factor. For example, with a multiplier of 2, each new addition will be twice as large as the previous one, accelerating recovery if the price moves favorably.
Default: 1.0 (no multiplication)
Can be adjusted up to 10x to aggressively increase position size after losses.
Trade Execution:
Long Trades:
Entry Condition: A long position is opened when the MACD line crosses over the signal line, and the KDJ’s %K crosses above %D.
Additions (Martingale): After the initial long position, new positions are added if the price drops by the defined percentage, and each new addition is increased using the Multiplier. This continues up to the set Max Additions.
Short Trades:
Entry Condition: A short position is opened when the MACD line crosses under the signal line, and the KDJ’s %K crosses below %D.
Additions (Martingale): After the initial short position, new positions are added if the price rises by the defined percentage, and each new addition is increased using the Multiplier.
Exit Conditions:
Take Profit: Exits are triggered when the price reaches the take-profit threshold.
Stop Loss: If the price moves unfavorably, the position will be closed at the set stop-loss level.
Trailing Stop: Adjusts dynamically as the price moves in favor of the trade to lock in profits.
On-Chart Visuals:
Long Signals: Blue triangles below the bars indicate long entries, and green triangles mark additional long positions.
Short Signals: Red triangles above the bars indicate short entries, and orange triangles mark additional short positions.
Information Table:
The strategy displays a table with key metrics:
Open Price: The entry price of the trade.
Average Price: The average price of the current position.
Additions: The number of additional positions taken.
Next Add Price: The price level for the next position.
Take Profit: The price at which profits will be taken.
Stop Loss: The stop-loss level to minimize risk.
Usage Instructions:
Adjust the parameters to your trading style using the input settings.
The Multiplier amplifies your position size after each addition, so use it cautiously, especially in volatile markets.
Monitor the signals and table on the chart for entry/exit decisions and trade management.
SL ManagerSTOP LOSS MANAGER
Overview:
The "SL Manager" indicator is designed to assist traders in managing their stop loss (SL) and take profit (TP) levels for both long and short positions. This tool helps you visualize intermediate levels, enhancing your trading decisions by providing crucial information on the chart.
Usage:
This indicator is particularly useful for traders who want to manage their trades more effectively by visualizing potential adjustment points for their stop loss and take profit levels. It helps in making informed decisions to maximize profits and minimize risks by providing clear levels to take partial profits and adjust stop losses.
Features:
Position Input: Select between "long" and "short" positions.
Entry Price: Specify the entry price of your trade.
Take Profit: Define the price level at which you want to take profit.
Stop Loss: Set the stop loss price level to manage your risk.
Intermediate Levels:
For both long and short positions, the indicator calculates and plots the following intermediate levels:
50% Take Profit (TP 50%): Midway between the entry price and the take profit level, where you can take partial profits and move your SL up to the 25% mark.
75% Take Profit (TP 75%): Three-quarters of the way from the entry price to the take profit level, where you can take partial profits and move your SL to breakeven.
Stop Loss Move to 25% (SL Move to 25%): A level where the stop loss can be adjusted to lock in profits.
Visualization:
The indicator plots the calculated levels directly on the chart, provided the data for the current day is available. Different color codes and line styles distinguish between the various levels:
TP 50% and TP 75% are plotted in green.
SL Move to 25% is plotted in red .
Entry/Breakeven is plotted in blue.
Machine Learning: SuperTrend Strategy TP/SL [YinYangAlgorithms]The SuperTrend is a very useful Indicator to display when trends have shifted based on the Average True Range (ATR). Its underlying ideology is to calculate the ATR using a fixed length and then multiply it by a factor to calculate the SuperTrend +/-. When the close crosses the SuperTrend it changes direction.
This Strategy features the Traditional SuperTrend Calculations with Machine Learning (ML) and Take Profit / Stop Loss applied to it. Using ML on the SuperTrend allows for the ability to sort data from previous SuperTrend calculations. We can filter the data so only previous SuperTrends that follow the same direction and are within the distance bounds of our k-Nearest Neighbour (KNN) will be added and then averaged. This average can either be achieved using a Mean or with an Exponential calculation which puts added weight on the initial source. Take Profits and Stop Losses are then added to the ML SuperTrend so it may capitalize on Momentum changes meanwhile remaining in the Trend during consolidation.
By applying Machine Learning logic and adding a Take Profit and Stop Loss to the Traditional SuperTrend, we may enhance its underlying calculations with potential to withhold the trend better. The main purpose of this Strategy is to minimize losses and false trend changes while maximizing gains. This may be achieved by quick reversals of trends where strategic small losses are taken before a large trend occurs with hopes of potentially occurring large gain. Due to this logic, the Win/Loss ratio of this Strategy may be quite poor as it may take many small marginal losses where there is consolidation. However, it may also take large gains and capitalize on strong momentum movements.
Tutorial:
In this example above, we can get an idea of what the default settings may achieve when there is momentum. It focuses on attempting to hit the Trailing Take Profit which moves in accord with the SuperTrend just with a multiplier added. When momentum occurs it helps push the SuperTrend within it, which on its own may act as a smaller Trailing Take Profit of its own accord.
We’ve highlighted some key points from the last example to better emphasize how it works. As you can see, the White Circle is where profit was taken from the ML SuperTrend simply from it attempting to switch to a Bullish (Buy) Trend. However, that was rejected almost immediately and we went back to our Bearish (Sell) Trend that ended up resulting in our Take Profit being hit (Yellow Circle). This Strategy aims to not only capitalize on the small profits from SuperTrend to SuperTrend but to also capitalize when the Momentum is so strong that the price moves X% away from the SuperTrend and is able to hit the Take Profit location. This Take Profit addition to this Strategy is crucial as momentum may change state shortly after such drastic price movements; and if we were to simply wait for it to come back to the SuperTrend, we may lose out on lots of potential profit.
If you refer to the Yellow Circle in this example, you’ll notice what was talked about in the Summary/Overview above. During periods of consolidation when there is little momentum and price movement and we don’t have any Stop Loss activated, you may see ‘Signal Flashing’. Signal Flashing is when there are Buy and Sell signals that keep switching back and forth. During this time you may be taking small losses. This is a normal part of this Strategy. When a signal has finally been confirmed by Momentum, is when this Strategy shines and may produce the profit you desire.
You may be wondering, what causes these jagged like patterns in the SuperTrend? It's due to the ML logic, and it may be a little confusing, but essentially what is happening is the Fast Moving SuperTrend and the Slow Moving SuperTrend are creating KNN Min and Max distances that are extreme due to (usually) parabolic movement. This causes fewer values to be added to and averaged within the ML and causes less smooth and more exponential drastic movements. This is completely normal, and one of the perks of using k-Nearest Neighbor for ML calculations. If you don’t know, the Min and Max Distance allowed is derived from the most recent(0 index of data array) to KNN Length. So only SuperTrend values that exhibit distances within these Min/Max will be allowed into the average.
Since the KNN ML logic can cause these exponential movements in the SuperTrend, they likewise affect its Take Profit. The Take Profit may benefit from this movement like displayed in the example above which helped it claim profit before then exhibiting upwards movement.
By default our Stop Loss Multiplier is kept quite low at 0.0000025. Keeping it low may help to reduce some Signal Flashing while not taking extra losses more so than not using it at all. However, if we increase it even more to say 0.005 like is shown in the example above. It can really help the trend keep momentum. Please note, although previous results don’t imply future results, at 0.0000025 Stop Loss we are currently exhibiting 69.27% profit while at 0.005 Stop Loss we are exhibiting 33.54% profit. This just goes to show that although there may be less Signal Flashing, it may not result in more profit.
We will conclude our Tutorial here. Hopefully this has given you some insight as to how Machine Learning, combined with Trailing Take Profit and Stop Loss may have positive effects on the SuperTrend when turned into a Strategy.
Settings:
SuperTrend:
ATR Length: ATR Length used to create the Original Supertrend.
Factor: Multiplier used to create the Original Supertrend.
Stop Loss Multiplier: 0 = Don't use Stop Loss. Stop loss can be useful for helping to prevent false signals but also may result in more loss when hit and less profit when switching trends.
Take Profit Multiplier: Take Profits can be useful within the Supertrend Strategy to stop the price reverting all the way to the Stop Loss once it's been profitable.
Machine Learning:
Only Factor Same Trend Direction: Very useful for ensuring that data used in KNN is not manipulated by different SuperTrend Directional data. Please note, it doesn't affect KNN Exponential.
Rationalized Source Type: Should we Rationalize only a specific source, All or None?
Machine Learning Type: Are we using a Simple ML Average, KNN Mean Average, KNN Exponential Average or None?
Machine Learning Smoothing Type: How should we smooth our Fast and Slow ML Datas to be used in our KNN Distance calculation? SMA, EMA or VWMA?
KNN Distance Type: We need to check if distance is within the KNN Min/Max distance, which distance checks are we using.
Machine Learning Length: How far back is our Machine Learning going to keep data for.
k-Nearest Neighbour (KNN) Length: How many k-Nearest Neighbours will we account for?
Fast ML Data Length: What is our Fast ML Length?? This is used with our Slow Length to create our KNN Distance.
Slow ML Data Length: What is our Slow ML Length?? This is used with our Fast Length to create our KNN Distance.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
MA RSI @KINGThis Pine Script is designed to create a trading indicator with moving averages (MA) and relative strength index (RSI), along with arrow signals and background color changes based on those signals. Here's a description of its functions:
1. Moving Averages and RSI Calculation:
- Two moving averages (`fastMA` and `slowMA`) are calculated based on user-input lengths.
- The Relative Strength Index (`rsi`) is calculated based on a user-defined length.
2. Crossover Conditions:
- `crossoverUp` is true when the fastMA crosses above the slowMA and RSI is above an overbought level.
- `crossoverDown` is true when the fastMA crosses below the slowMA and RSI is below an oversold level.
3. Arrow Signals:
- Triangle-shaped arrows (`arrowUp` and `arrowDown`) are plotted below and above bars, indicating buy (green) and sell (red) signals, respectively.
4. Background Color Changes:
- The background color (`bgColor`) changes based on buy and sell signals.
- If there's a buy signal (`crossoverUp`), the background color is set to a light blue with 40% transparency.
- If there's a sell signal (`crossoverDown`), the background color is set to a light red with 40% transparency.
- On the next opposite signal, the background color is scaled up (transparency set to 80%) to indicate a stronger signal.
In summary, this script provides visual cues through arrows and background color changes to assist traders in identifying potential buy and sell signals based on moving average crossovers and RSI conditions. The background color variations aim to highlight the strength of the signal, with scaling based on consecutive signals in the same direction.
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1. Buy Signal:
- Condition: The arrow points up (green) with a background color indicating a buy signal.
- Confirmation: Ensure that there is a strong upward crossover (fastMA above slowMA) and RSI is above the overbought level.
2. Sell Signal:
- Condition: The arrow points down (red) with a background color indicating a sell signal.
- Confirmation: Ensure that there is a strong downward crossover (fastMA below slowMA) and RSI is below the oversold level.
3. Exit Signal:
- Condition: No arrow is present, and the background color is reset.
- Confirmation: Confirm that there is no active buy or sell signal.
Example Trading Rules:
Opening a Long Position (Buy):
- Enter a long (buy) position when:
- The green arrow appears with a light blue background.
- Confirm that the fastMA is above the slowMA.
- Confirm that RSI is above the overbought level.
Opening a Short Position (Sell):
- Enter a short (sell) position when:
- The red arrow appears with a light red background.
- Confirm that the fastMA is below the slowMA.
- Confirm that RSI is below the oversold level.
Exiting a Position:
- Close the position when:
- There is no arrow present (neither green nor red).
- The background color is reset, indicating no active signal.
Risk Management:
Position Sizing: Determine the size of your positions based on your risk tolerance and the size of your trading account.
Stop-Loss and Take-Profit: Set stop-loss orders to limit potential losses and take-profit orders to secure profits.
Risk-Reward Ratio: Consider maintaining a favorable risk-reward ratio in your trades.
Notes:
Backtesting: Before applying this strategy in a live market, it's crucial to backtest it using historical data to assess its performance.
Market Conditions: Adapt the strategy to different market conditions, and be aware that no strategy is guaranteed to be profitable.
Continuous Monitoring: Regularly monitor the performance of the strategy and make adjustments as needed.
Educational Purpose: This strategy is for educational purposes only. Always consult with financial professionals and use your judgment when making trading decisions.
Remember that trading involves risk, and past performance is not indicative of future results. It's recommended to paper trade or use a demo account to test the strategy before risking real capital.
Best wishes on your trading journey! May your strategies be profitable, your risks well-managed, and your decisions guided by wisdom and success. Happy trading!
Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2
This script was originally shared by Wunderbit as a free open source script for the community to work with. This is my second published iteration of this idea.
WHAT THIS SCRIPT DOES:
It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading.
This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry.
This is a new and improved version geared for lower timeframes (15-5 minutes), but can be run on larger ones as well. I am testing it live as my high frequency trader.
HOW IT DOES IT:
It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability.
Take profits are now trailing profits, and the stop loss is now fixed. Why? I found that the trailing stop loss with ATR in the previous version yields very good results for back tests but becomes very difficult to deploy live due to transaction fees. As you can see the average trade is a higher profit percentage than the previous version.
HOW IS MY VERSION ORIGINAL:
Now instead of using ATR stop loss, we have a fixed stop loss - counter intuitively to what some may believe this performs better in live trading scenarios since it gives the strategy room to move. I noticed that the ATR trailing stop was stopping out too fast and was eating away balance due to transaction fees.
The take profit on the other hand is now a trailing profit with a customizable deviation. This ensures that you can have a minimum profit you want to take in order to exit.
I have depracated the old ATR trailing stop as it became too confusing to have those as different options. I kept the old version for others that want to experiment with it. The source code still requires some cleanup, but its fully functional.
I added in a way to show RSI values and ATR values with a checkbox so that you can use the new an improved ATR Filter (and grab the right RSI values for the RSI filter). This will help to filter out times of very low volatility where we are unlikely to find a profitable trade. Use the "Show Data" checkbox to see what the values are on the indicator pane, then use those values to gauge what you want to filter out.
Both versions
Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.)
Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address.
Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off)
Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots.
HOW TO USE IT:
It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found.
Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor.
Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well.
Select a time frame in configuration for your indicator calculations.
Select the strategy config for time frame (resolution). I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers.
Optimize your indicator without filters : customize your settings for MACD and MFI that are profitable with your chart and selected time frame calculation. Try different Take Profits (try about 2-5%) and stop loss (try about 5-8%). See if your back test is profitable and continue to optimize.
Use the Trend, RSI, ATR Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio.
You can use the open and close messages for a platform integration, but I choose to set mine up on the destination platform and let the platform close it. With certain platforms you cannot be sure what your entry point actually was compared to Trading View due to slippage and timing, so I let the platform decide when it is actually profitable.
Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
Short Selling EMA Cross (By Coinrule)BINANCE:AVAXUSDT
This short selling script works best in periods of downtrends and general bearish market conditions, with the ultimate goal to sell as the the price decreases further and buy back before a rebound.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to to hodl this cash, or use it to reinvest when the market reaches attractive buying levels.
Entry
The exponential moving average ( EMA ) 20 and EMA 50 have been used for the variables determining the entry to the short. EMAs can operate better than simple moving averages due to the additional weighting placed on the most recent data points, whereas simple moving averages weight all the data the same. This means that price is tracked more closely and the most recent volatile moves can be captured and exploited more efficiently using EMAs.
Our backtesting data revealed that the most profitable timeframe was the 30-minute timeframe, this also enabled a good frequency of trades and high profitability.
A fast (shorter term) exponential moving average , in this strategy the EMA 20, crossing under a slow (longer term) moving average, in this example the EMA 50, signals the price of an asset has started to trend to the downside, as the most recent data signals price is declining compared to earlier data. The entry acts on this principle and executes when the EMA 20 crosses under the EMA 50.
Enter Short: EMA 20 crosses under EMA 50.
Exit
This script utilises a take profit and stop loss for the exit. The take profit is set at -8% and the stop loss is set at +16% from the entry price. This would normally be a poor trade due to the risk:reward equalling 0.5. However, when looking at the backtesting data, the high profitability of the strategy (93.33%) leads to increased confidence and showcases the high probability of success according to historical data.
The take profit (-8%) and the stop loss (+16%) of the strategy are widely placed to ensure the move is captured without being stopped out due to relief rallies. The stop loss also plays a role of mitigating losses and minimising risk of being stuck in a short position once there has been a fundamental trend reversal and the market has become bullish .
Exit Short: -8% price decrease from entry price.
OR
Exit Short: +16% price increase from entry price.
Tip: Research what coins have consistent and large token unlocks / highly inflationary tokenomics, and target these during bear markets to short as they will most likely have substantial selling pressure that outweighs demand - leading to declining prices.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
The backtesting data was recorded from December 1st 2021, just as the market was beginning its downtrend. We therefore recommend analysing the market conditions prior to utilising this strategy as it operates best on weak coins during downtrends and bearish conditions.
Grover Llorens Activator Strategy AnalysisThe Grover Llorens Activator is a trailing stop indicator deeply inspired by the parabolic SAR indicator, and aim to provide early exit points and reversal detection. The indicator was posted not so long ago, you can find it here :
Today a strategy using the indicator is proposed, and its profitability is analyzed on 3 different markets with the main time frame being 1 hour, remember that lower time frames involve lower absolute price changes, therefore we are way more affected by the spread, and we can require a larger position sizing depending on our investment target, trading higher time-frames is always a good practice and this is why 1 hour is selected. Based on the result we might make various conclusions regarding the indicator accuracy and might have ideas on future improvements of the indicator.
I'am not great when it comes to strategy design, i still hope to share correct and useful information in this post, let me know your thoughts on the post format and if i should make more of these.
Setup And Rules
The analysis is solely based on the indicator signals, money management isn't taken into account, this allow us to have an idea on the indicator robustness and resilience, particularly on extremely volatile markets and ones exhibiting a chaotic structure, altho it is normally good practice to close any position before a market closure in order to avoid any potential major gaps.
The settings used are 480 for length and 14 for mult, this create relatively mid term signals that are suited for a trend indicator such as the Grover Llorens Activator, unfortunately we can't infer the indicator optimal settings, thats how it is with any technical indicator anyway.
Here are the rules of our strategy :
long : closing price cross over the indicator
short : closing price cross under the indicator
We use constant position sizing, once a signal is triggered all the previous positions are closed.
Description Of The Statistics Used
Various statistics are presented in this post, here is a brief description of the main ones :
Percent Profitability (higher = better): Percentage of winning trades, that is : winning trades/total number of trades × 100
Maximum Drawdown (lower = better) : The highest difference between a peak and a valley in the balance, that is : peak - valley , in percentage : (peak - valley)/peak × 100
Profit Factor (higher = better) : Gross profit divided by gross loss, values under 1 represent gross losses superior to the gross profits
Remember that more volatility = more risk, since higher absolute price changes can logically cause larger losses.
EURUSD
The first market analyzed is the Forex market with the EURUSD major pair with a position sizing of 1000 units (1 micro lot). Since October EURUSD is not showing any particular strong trend but posses a discrete rising motion, fortunately cycles can be observed.
The equity was rising until two trades appeared causing a decline in the equity. Before October a bearish market could be observed.
We can see that the equity is rising, the trend still posses various retracements that affect our indicator, however we can see that the indicator totally nail the end of the trend, thats the power of converging toward the price.
In short :
$ 86.63 net profit
340 closed trades
37.65 % profitable (thats a lot of loosing trades)
1.19 profit factor
$ 76.67 max drawdown
Applying a spread would create negative results (in general the average spread is used), not a great start...
BTCUSD
The cryptocurrency market is relatively more volatile than others, which also mean potentially higher returns, we test the indicator using certainly the most traded cryptocurrency, BTCUSD. We will use a position sizing of 1 unit.
In the case of BTCUSD the strategy balance is relatively stationary around the initial capital, with of course high dispersion.
from september to december the market is bearish with various ranging periods, no apparent cycles can be observed, except maybe in the ranging period of october, this ranging period is followed by a non linear trend (relatively parabolic) that the indicator failed to capture in its integrity (this is a recurrent problem and it is starting to piss me off xD).
In short :
$ 2010.64 net profit (aka how i bet the crypto market)
395 closed trades
38.23 % profitable
1.036 profit factor
$ 5738.01 max drawdown (aka how i lost to the crypto market)
AMD
AMD stand for Advanced Micro Devices and is a company focused on the development of computer technology, i love the microprocessor market and i really like AMD who start this year in a pretty great way with a net bullish trend.
The performance of the indicator on AMD is decent (at last !) with the equity producing many new higher highs. The indicator performance still drop in the middle end of 2019 with a large equity drawdown of 17$ caused by the gap of august 8. Unfortunately AMD, like lot of well behaving stocks can only tells us that the indicator has good performances on heavily trending markets with no excess of noise or chaotic structures.
In short :
$ 17.86 net profit (Enough for a consistent lunch)
295 closed trades
36.27 % profitable
1.414 profit factor
$ 10.37 max drawdown.
Conclusion
A strategy using the recently proposed Grover Llorens activator has been presented. We can easily conclude that the indicator can't possibly generate long term returns under chaotic and volatile markets, and could even produce unnecessary trades in trending markets without much parasitic fluctuations such as noise and retracements (think about a simple linear trend) since the indicator converge toward the price and would therefore automatically cross over/under the trend, thus guaranteeing a false signal.
However we have seen its ability to provide accurate early reversal detection shine from time to time, thus over performing lagging indicators in this aspect, however the duration of price fluctuations isn't fixed at a certain period, the rate of convergence should be way faster during volatile fluctuations, of moderate speed during more cyclic fluctuations, and really slow with apparent long term trends, this could be achieved by making the indicator adaptive, but it won't really make it necessarily perform better.
That said i still believe that converging trend indicators are really interesting and aim to capture the non lasting behavior of price fluctuations, they shouldn't receive so much hate (think about the poor p-sar).
Thanks for reading !
Red and Green Ignored Bar by Oliver VelezOn this occasion I present a script that detects Ignored Red Candles and Ignored Green Candles, basically it is a Price Action event that indicates a possible continuation of the current trend and gives the opportunity to climb it with a Very tight risk, before delving into detail I would like to leave this note:
Note: the detection of this event does not guarantee that the signal will be good, the trader must have the ability to determine its quality based on aspects such as trend, maturity, support / resistance levels, expansion / contraction of the market, risk / benefit, etc, if you do not have knowledge about this you should not use this indicator since using it without a robust trading plan and experience could cause you to partially or totally lose your money, if this is your case you should train before If you try to extract money from the market, this script was created to be another tool in your trading plan in order to configure the rules at your discretion, execute them consistently and have AUTOMATIC ALERTS when the event occurs, which is where I find more value because you can have many instruments waiting for the event to be generated, in the time frame you want and without having to observe the mer When the alert is generated, the Trader should evaluate the quality of the alert and define whether or not to execute it (higher timeframes, they can give you more time to execute the operation correctly).
Let's continue….
This event was created by Oliver Velez recognized trader / mentor of price action, the event has a very interesting particularity since it allows to take a position with a very limited risk in trend movements, this achieves favorable operations of good ratio and small losses when taking An adjusted risk, if the trade works, a good ratio is quickly achieved and we agree with a key point in the “Keep small losses and big profits” trading, this makes it easier to have a positive mathematical hope when your level of Success is not very high, so leave you in the field of profitability.
THE EVENT:
The event has a bullish configuration (Ignored Red Candle) and a bearish configuration (Ignored Green Candle), below I detail the “Hard” rules (later I explain why “Hard”):
1- Last 3 bars have to be GREEN-RED-GREEN (possible bullish configuration) or RED-GREEN-RED (possible bearish configuration), the first bar is called Control Bar, the second is called Ignored Bar and the third Signal Bar as shown in the following image:
2- Be in a trend determined by simple moving averages (Slow of 20 periods and Fast of 8 periods), as a general rule you can take the direction of MA20 but the Trader has to determine if there is a trend movement or not.
3- Control bar of good range, little tail and with a body greater than 55%.
4- Ignored bar preferably narrow range, little tail and that is located in the upper 1/3 of the control bar.
5- Signal bar cannot override the minimum of the ignored bar.
6- Activation / Confirmation of event by means of signal bar in overcoming the body of the ignored bar.
Some examples of ignored bars (with “Hard” and “Flexible” rules):
Features and configuration of the indicator:
To access the indicator settings, press the wheel next to the indicator name VVI_VRI "Configuration options".
- Operation mode (Filtering Type):
• Filtering Complete: all filters activated according to the configuration below.
• Without Filtering: all filters deactivated, all VRI / VVI are displayed without any selection criteria.
• Trend Filter only: shows only VRI / VVI that are in accordance with what is set in “Trend Settings”
- Configuration Moving Averages:
• See Slow Media: slow moving average display with direction detection and color change.
• See Fast Media: display of fast moving average with direction detection and color change.
• Type: possibility to choose the type of media: DEMA, EMA, HullMA, SMA, SSMA, SSMA, TEMA, TMA, VWMA, WMA, ZEMA)
• Period: number of previous bars.
• Source: possibility to choose the type of source, open, close, high, low, hl2 hlc3, ohlc4.
• Reaction: this configuration affects the color change before a change of direction, 1 being an immediate reaction and higher values, a more delayed reaction obtaining les false "changes of direction", a value of 3 filters the direction quite well.
- Trend Configuration
• Uptrend Condition P / VRI: possibility to select any of these conditions:
o Bullish MA direction
o Quick bullish MA direction
o Slow and fast bullish MA direction
o Price higher than slow MA
o Price higher than fast MA
o Price higher than slow and fast MA
o Price higher than slow MA and bullish direction
o Price higher than fast MA and bullish direction
o Price higher than slow, fast MA and bullish direction
o No condition
• Condition P / VVI bear trend: possibility of selecting any of these conditions:
o Slow bearish MA direction
o Fast bearish MA direction
o Slow and fast bearish MA direction
o Price less than slow MA
o Price less than fast MA
o Price less than slow and fast MA
o Price lower than slow MA and bearish direction
o Price less than fast MA and bearish direction
o Price less than slow, fast MA and bearish direction
o No condition
- Control bar configuration
• Minimum body percentage%: possibility to select what body percentage the bar must have.
• Paint control bar: when selected, paint the control bar.
• See control bar label: when selected, a label with the legend BC is plotted.
- Configuration bar ignored
• Above X% of the control bar: possibility to select above what percentage of the control bar the ignored bar must be located.
• Paint ignored bar: when selected, paint the ignored bar.
- Signal bar configuration
• You cannot override the minimum of the ignored bar: when selected, the condition is added that the signal bar cannot override the minimum of the ignored bar.
• Paint signal bar: when selected, paint the signal bar.
• See arrow: when selected it shows the direction arrow of the possible movement.
• See bear and arrow: when selected it shows bear and arrow label
• See bull and arrow: when selected it shows bull and arrow label
The following image shows the ignored bar and painted signal:
- Take profit / loss
The profit / loss taking varies depending on the trader and its risk / monetary plan, the proposal is a recommendation based on the nature of the event that is to have a small risk unit (stop below the minimum of the ignored bar), look for objectives in ratios greater than 2: 1 and eliminate the risk in 1: 1 by taking the stop to BE, all parameters are configurable and are the following:
• See recommended stop loss and take profit: trace the levels of Stop, BE, TP1 and TP2, as well as their prices to know them quickly based on the assumed risk
• To: select which event you want to draw the SL and TP (VRI, VVI)
• Extend stop loss line x bars: allows extending the stop line by x number of bars
• Extend take profit line x bars: allows extending the stop line by x number of bars
• Ratio to move to break even: allows you to select the minimum ratio to move stop to break even (default 1: 1)
• Take profit 1 ratio: allows you to select the ratio for take profit 1 (default 2: 1)
• Take profit 2 ratio: allows you to select the ratio for take profit 2 (default 4: 1)
- Alerts
• It is possible to configure the following alerts:
-VRI DETECTED
-VVI DETECTED
-VRI / VVI DETECTED
Final Notes:
- The term hard rules refers to the fact that an event is sought with the rules detailed above to obtain a high quality event but this brings 2 situations to consider, less
number of events and events that are generated in a strong impulse may be leaked, a very large control bar followed by an ignored narrow body away from moving averages, despite having a good chance of continuing, taking a stop very tight in a strong impulse you can touch it by the simple fact of the own volatility at that time.
- The setting of the parameters “Minimum body percentage% (control bar)”, “Above x% of the control bar (bar ignored)” and “Cannot override the minimum of the ignored bar” can bring large Benefits in terms of number of events and that can also be of high quality, feel free to find the best configuration for your instrument to operate.
- It is recommended to look for trending events, near moving averages and at an early stage of it.
- The display of several nearby VRIs or VVIs in an advanced trend may indicate a depletion of it.
- The alerts can be worked in 2 ways: at the closing of the candle (confirms event but the risk unit may be larger or smaller) or immediately the body of the ignored bar is exceeded, in case you are operating from the mobile and miss many events because of the short time I recommend that you operate in a superior time frame to have more time.
- The indicator is configured with “flexible” rules to have more events, but without any important criteria, each trader has to look for the best configuration that suits his instrument.
- It is recommended to partially close the operation based on the ratio and always keep a part of the position to apply manual trailing stop and try to maximize profits.
The code is open feel free to use and modify it, a mention in credits is appreciated.
If you liked this SCRIPT THUMB UP!
Greetings to all, I wish you much green!
Complete Trend Trading System [Fhenry0331]This system was designed for the beginner trader to make money swing trading. Your losses will be small and your gains will be mostly large. You will show consistent profit. Period.
The system works on any security you like to trade. I used GBPUSD as an example because of the up swing and down swing it had recently. I tried to put as much information of how the system works in the chart. Hope it helps and is not to cluttered.
I will reiterate how the system works here: Everything is based off of closed price.
Legend
Uptrend: Buy
Green bar: initial start of an uptrend or uptrend continuing. Place order above that bar. If the initial bar does not stray too far from the MVWAP , I will place orders above subsequent bars if no filled occurred.
If initial start of the trend is missed, I will wait for the pullback. A pullback is a close below the MVWAP, and a close above the EMA (Low), RSI is above 50. Orders are placed above the pullback bars with plotted char "B" and also plotted green triangle up. Again orders are placed above those bars. the bars do not notate automatic buys. Don't chase anything. You will miss the initial bar on something because of news or earnings and it rocket up. Just wait, it will pullback. If it doesn't, to hell with it, on to the next.
Take profits: In the indicator you will see "T." That notates to take some profits. It is a suggestion. I was always told to take profits into spikes, as well as you can never lose money if you take profits. Up to you if you want to scale out and take the suggested profits or not.
Exit Completely: In an uptrend, close your entire position on bars colored yellow or red. (Again, closed bars)
In uptrend bars colored orange and black, do nothing, they are just pullback bars. Look for the buy pullback signal, then follow pullback buy rules for an uptrend.
Downtrend: Short
Red bar: initial start of a downtrend or downtrend continuing. Place order below the bar. If the initial bar does not stray too far fro the MVWAP, place orders below subsequent bars.
If initial start on the downtrend is missed, wait for the pullback. A pullback is a close above the MVWAP, and close below the EMA(Low). RSI is below 50. Orders are placed below the pullback bars with the plotted char "S" and also plotted red triangle. Again those bars are not automatic shorts, orders are placed below them. Don't chase anything. Wait for price to come into your plan. The idea FOMO is the stupidest thing ever, how can you miss out on something when it is always there. The market is always there and something will come into your zone. Chill.
"T": same as in uptrend, suggestion to take some profits.
Exit Completely: In a downtrend, close your entire position on bars colored orange or green.
In downtrend you will see bars colored yellow and black, do nothing, they are pullback bars. Look for the pullback short signal and follow pullback short rules.
If you have any questions get at me. Take a look at it on what you trade. Flip it through different securities.
Best of luck in all you do.
P.S. You should not take a trade right before earnings. You should also exit a trade right before earnings.
T7 JNSARUpdated code for the T7 JNSAR system earlier published here -
Following updates made to the code
1. Buy / Sell arrows now appear when the corresponding conditions are met.
2. Support for Heikin-Ashi Candles added
3. Different Backtesting Position Sizing Algorithms added for evaluation
Also am republishing the trading rules here again with some modification
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty Index. This system was developed and backtested only for NIFTY Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2016 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Trade with only that amount of money you can afford to loose. Initial capital that you need to have to trade one lot of NIFTY should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Place an After Market Order @ Market Price with your broker after market close so that you get to execute the trade next trading day @ Market open to capture near similar price as the daily open price seen on the chart. This execution mode will give you the best chance to minimise the slippage and mimic the backtester results as closely as practically possible.
7. Follow all the 6 rules above religiously, as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
Happy Trading !!! As always am looking out for your valuable feedback.
T7 JNSARJNSAR stands for Just Nifty Stop & Reverse. This is a trend following daily bar trading system for NIFTY. Original idea belongs to ILLANGO @ I coded the pine version of this system based on a request from @stocksonfire. Use it at your own risk after validation at your end. Neither me or my company is responsible for any losses you may incur using this system. Hope you like this system and enjoy trading it !!!
While trading this system you must follow these simple rules.
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty Index. This system was developed and backtested only for NIFTY Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2016 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Initial capital that you need to have to trade one lot of NIFTY should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Follow all the 5 rules above religiously as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
Range Oscillator Strategy + Stoch Confirm🔹 Short summary
This is a free, educational long-only strategy built on top of the public “Range Oscillator” by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. It’s a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades.
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0. Legal / risk disclaimer
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• This script is FREE and public. I do not charge any fee for it.
• It is for EDUCATIONAL PURPOSES ONLY.
• It is NOT financial advice and does NOT guarantee profits.
• Backtest results can be very different from live results.
• Markets change over time; past performance is NOT indicative of future performance.
• You are fully responsible for your own trades and risk.
Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital.
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1. About default settings and risk (very important)
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The script is configured with the following defaults in the `strategy()` declaration:
• `initial_capital = 10000`
→ This is only an EXAMPLE account size.
• `default_qty_type = strategy.percent_of_equity`
• `default_qty_value = 100`
→ This means 100% of equity per trade in the default properties.
→ This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade.
TradingView’s House Rules recommend risking only a small part of equity per trade (often 1–2%, max 5–10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to:
1. Open **Strategy Settings → Properties**.
2. Set:
• Order size: **Percent of equity**
• Order size (percent): e.g. **1–2%** per trade
3. Make sure **commission** and **slippage** match your own broker conditions.
• By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets.
If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading.
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2. What this strategy tries to do (conceptual overview)
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This is a LONG-ONLY strategy designed to explore the combination of:
1. **Range Oscillator (Zeiierman-based)**
- Measures how far price has moved away from an adaptive mean.
- Uses an ATR-based range to normalize deviation.
- High positive oscillator values indicate strong price expansion away from the mean in a bullish direction.
2. **Stochastic as a timing filter**
- A classic Stochastic (%K and %D) is used.
- The logic requires %K to be below a user-defined level and then crossing above %D.
- This is intended to catch moments when momentum turns up again, rather than chasing every extreme.
3. **EMA Exit Filter (trend slope)**
- An EMA with configurable length (default 70) is calculated.
- The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition.
- This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted.
4. **Optional risk-management layer**
- Percentage-based Stop Loss and Take Profit (SL/TP).
- Risk/Reward (R-multiple) exit based on the distance from entry to SL.
- Implemented as OCO orders that work *on top* of the logical exits.
The goal is not to create a “holy grail” system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes.
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3. Components and how they work together
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(1) Range Oscillator (based on “Range Oscillator (Zeiierman)”)
• The script computes a weighted mean price and then measures how far price deviates from that mean.
• Deviation is normalized by an ATR-based range and expressed as an oscillator.
• When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction.
• When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled).
(2) Stochastic confirmation
• Classic Stochastic (%K and %D) is calculated.
• An entry requires:
- %K to be below a user-defined “Cross Level”, and
- then %K to cross above %D.
• This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point.
(3) EMA Exit Filter
• The EMA length is configurable via `emaLength` (default 70).
• The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA.
• If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition.
• This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit.
(4) Risk management (optional)
• Stop Loss (SL) and Take Profit (TP):
- Defined as percentages relative to average entry price.
- Both are disabled by default, but you can enable them in the Inputs.
• Risk/Reward Exit:
- Uses the distance from entry to SL to project a profit target at a configurable R-multiple.
- Also optional and disabled by default.
These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first.
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4. Entry & Exit logic (high level)
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A) Time filter
• You can choose a **Start Year** in the Inputs.
• Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`).
• This prevents accidental use of tiny cherry-picked windows and makes tests more honest.
B) Entry condition (long-only)
A long entry is allowed when ALL the following are true:
1. `timeCondition` is true (inside the backtest window).
2. If `useOscEntry` is true:
- Range Oscillator value must be above `entryLevel`.
3. If `useStochEntry` is true:
- Stochastic condition (`stochCondition`) must be true:
- %K < `crossLevel`, then %K crosses above %D.
If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`.
C) Exit condition (logical exits)
A position can be closed when:
1. `timeCondition` is true AND a long position is open, AND
2. At least one of the following is true:
- If `useOscExit` is true: Oscillator is below `exitLevel`.
- If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`).
In that case, `strategy.close("Long")` is called.
D) Risk-management exits
While a position is open:
• If SL or TP is enabled:
- `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages.
• If Risk/Reward exit is enabled:
- `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance.
These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels.
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5. Recommended backtest configuration (to avoid misleading results)
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To align with TradingView House Rules and avoid misleading backtests:
1. **Initial capital**
- 10 000 (or any value you personally want to work with).
2. **Order size**
- Type: **Percent of equity**
- Size: **1–2%** per trade is a reasonable starting point.
- Avoid risking more than 5–10% per trade if you want results that could be sustainable in practice.
3. **Commission & slippage**
- Commission: around 0.1% if that matches your broker.
- Slippage: a few ticks (e.g. 3) to account for real fills.
4. **Timeframe & markets**
- Volatile symbols (e.g. crypto like BTCUSDT, or major indices).
- Timeframes: 1H / 4H / **1D (Daily)** are typical starting points.
- I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes.
5. **No “caution warning”**
- Make sure your chosen symbol + timeframe + settings do not trigger TradingView’s caution messages.
- If you see warnings (e.g. “too few trades”), adjust timeframe/symbol or the backtest period.
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5a. About low trade count and rare signals
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This strategy is intentionally designed to trade RARELY:
• It is **long-only**.
• It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter).
• On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest.
TradingView’s House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case:
• The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window.
• The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals.
• Because of the low trade count, results should NOT be interpreted as statistically strong or “proven” – they are only one sample of how this logic would have behaved on past data.
Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample.
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6. How to use this strategy (step-by-step)
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1. Add the script to your chart.
2. Open the **Inputs** tab:
- Set the backtest start year.
- Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter.
- Optionally enable SL, TP, and Risk/Reward exits.
3. Open the **Properties** tab:
- Set a realistic account size if you want.
- Set order size to a realistic % of equity (e.g. 1–2%).
- Confirm that commission and slippage are realistic for your broker.
4. Run the backtest:
- Look at Net Profit, Max Drawdown, number of trades, and equity curve.
- Remember that a low trade count means the statistics are not very strong.
5. Experiment:
- Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params.
- See how the metrics and trade frequency change.
6. Forward-test:
- Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time.
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7. Originality and usefulness (why this is more than a mashup)
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This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component:
• Range Oscillator:
- Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric.
• Stochastic:
- Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn.
• EMA Exit Filter:
- Trend-slope-based safety net to exit when the medium-term direction changes against the position.
• Risk module:
- Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic.
It aims to give traders a ready-made **framework to study and modify**, not a black box or “signals” product.
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8. Limitations and good practices
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• No single strategy works on all markets or in all regimes.
• This script is long-only; it does not short the market.
• Performance can degrade when market structure changes.
• Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit.
Good practices:
- Test on multiple symbols and timeframes.
- Focus on stability and drawdown, not only on how high the profit line goes.
- View this as a learning tool and a basis for your own research.
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9. Licensing and credits
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• Core oscillator idea & base code:
- “Range Oscillator (Zeiierman)”
- © Zeiierman, licensed under CC BY-NC-SA 4.0.
• Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer:
- Modifications by jokiniemi.
Please respect both the original license and TradingView House Rules if you fork or republish any part of this script.
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10. No payments / no vendor pitch
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• This script is completely FREE to use on TradingView.
• There is no paid subscription, no external payment link, and no private signals group attached to it.
• If you have questions, please use TradingView’s comment system or private messages instead of expecting financial advice.
Use this script as a tool to learn, experiment, and build your own understanding of markets.
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11. Example backtest settings used in screenshots
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To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration:
• Symbol: BTCUSDT (or similar major BTC pair)
• Timeframe: 1D (Daily)
• Backtest period: from 2018 to the most recent data
• Initial capital: 10 000
• Order size type: Percent of equity
• Order size: 2% per trade
• Commission: 0.1%
• Slippage: 3 ticks
• Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default
• Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled
If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.
