Mutanabby_AI | ONEUSDT_MR1
ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit
This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce.
Backtested Period: June 2019 – December 2025 (~6 years)
Performance Summary
| Metric | Value |
|--------|-------|
| Net Profit | +417.68% |
| Win Rate | 74.68% |
| Profit Factor | 4.019 |
| Total Trades | 237 |
| Sharpe Ratio | 0.364 |
| Sortino Ratio | 1.917 |
| Max Drawdown | 51.08% |
| Avg Win | +3.14% |
| Avg Loss | -2.30% |
| Buy & Hold Return | -80.44% |
Strategy Logic :
Entry Conditions (Long Only):
The strategy seeks confluence of three conditions that identify exhausted selling:
1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall)
2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing)
3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred)
When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted.
Exit Conditions:
- Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength)
- Trailing Stop: 11x ATR trailing stop that locks in profits as price rises
Risk Management
- Position Sizing:Fixed position based on account equity divided by entry price
- Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains
- Pyramiding:Up to 4 orders allowed (can scale into winning positions)
- **Commission:** 0.1% per trade (realistic exchange fees included)
Important Disclaimers
⚠️ This is NOT financial advice.
- Past performance does not guarantee future results
- Backtest results may contain look-ahead bias or curve-fitting
- Real trading involves slippage, liquidity issues, and execution delays
- This strategy is optimized for ONEUSDT specifically — results may differ on other pairs
- Always test before risking real capital
Recommended Usage
- Timeframe:*1H (as designed)
- Pair: ONEUSDT (Binance)
- Account Size: Ensure sufficient capital to survive max drawdown
Source Code
Feedback Welcome
I'm sharing this strategy freely for educational purposes. Please:
- Drop a comment with your backtesting results any you analysis
- Share any modifications that improve performance
- Let me know if you spot any issues in the logic
Happy trading
As a quant trader, do you think this strategy will survive in live trading?
Yes or No? And why?
I want to hear from you guys
Kryptowährung
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
ETH - 12HR Double Kernel Regression Strategy ETH Double Kernel Regression Strategy
This ETH -focused, 12-hour Double Kernel Regression strategy is designed to cut through market noise and guide you toward data-backed, higher-probability trades. By utilizing two kernel regression models—Fast and Slow—this approach gauges momentum shifts and confirms trends. The strategy intelligently switches between these kernels based on identifying FOMO patterns, allowing it to adapt to changing market conditions. This ensures you enter trades when the trend is genuinely gaining strength, rather than blindly "buying the dip."
Key Concepts
Fine-Tuned Since Inception:
The strategy’s logic and filters—including price thresholds, trend moving averages (MAs), and kernel confirmations—are meticulously fine-tuned to perform consistently across all market conditions. This proactive planning enables confident entries during bullish recoveries, eliminating the need to second-guess every signal.
“Buy the Rise, Sell the Dip” Logic:
Unlike the traditional mantra, this strategy waits for slow kernel confirmation before entering uptrends. When market conditions shift, it identifies optimal entry points and holds steady if the trade isn’t losing money. This reduces guesswork and helps prevent buying into false rallies.
Sell the Hype:
The crypto market is often cluttered with noise—meme coins, last-minute hype, and social media influencers. The Double Kernel Regression approach distinguishes genuine trends from hype-driven movements. When the price exceeds simple moving averages (SMAs), the fast kernel generates a sell signal. This carefully crafted strategy helps you navigate the chaotic landscape, especially during hype-driven rallies, and ensures you sell at the top.
Try It Out
Import this strategy into your TradingView platform and observe how it reacts in real-time as market conditions change. Evaluate the signals, adjust parameters if necessary, and experience firsthand how combining sound trading philosophy with a data-driven backbone can transform your trading journey.
ETH Signal 15m
This strategy uses the Supertrend indicator combined with RSI to generate buy and sell signals, with stop loss (SL) and take profit (TP) conditions based on ATR (Average True Range). Below is a detailed explanation of each part:
1. General Information BINANCE:ETHUSDT.P
Strategy Name: "ETH Signal 15m"
Designed for use on the 15-minute time frame for the ETH pair.
Default capital allocation is 15% of total equity for each trade.
2. Backtest Period
start_time and end_time: Define the start and end time of the backtest period.
start_time = 2024-08-01: Start date of the backtest.
end_time = 2054-01-01: End date of the backtest.
The strategy will only run when the current time falls within this specified range.
3. Supertrend Indicator
Supertrend is a trend-following indicator that provides buy or sell signals based on the direction of price changes.
factor = 2.76: The multiplier used in the Supertrend calculation (increasing this value makes the Supertrend less sensitive to price movements).
atrPeriod = 12: Number of periods used to calculate ATR.
Output:
direction: Determines the buy/sell direction based on Supertrend.
If direction decreases, it signals a buy (Long).
If direction increases, it signals a sell (Short).
4. RSI Indicator
RSI (Relative Strength Index) is a momentum indicator, often used to identify overbought or oversold conditions.
rsiLength = 12: Number of periods used to calculate RSI.
rsiOverbought = 70: RSI level considered overbought.
rsiOversold = 30: RSI level considered oversold.
5. Entry Conditions
Long Entry:
Supertrend gives a buy signal (ta.change(direction) < 0).
RSI must be below the overbought level (rsi < rsiOverbought).
Short Entry:
Supertrend gives a sell signal (ta.change(direction) > 0).
RSI must be above the oversold level (rsi > rsiOversold).
The strategy will only execute trades if the current time is within the backtest period (in_date_range).
6. Stop Loss (SL) and Take Profit (TP) Conditions
ATR (Average True Range) is used to calculate the distance for Stop Loss and Take Profit based on price volatility.
atr = ta.atr(atrPeriod): ATR is calculated using 12 periods.
Stop Loss and Take Profit are calculated as follows:
Long Trade:
Stop Loss: Set at close - 4 * atr (current price minus 4 times the ATR).
Take Profit: Set at close + 2 * atr (current price plus 2 times the ATR).
Short Trade:
Stop Loss: Set at close + 4 * atr (current price plus 4 times the ATR).
Take Profit: Set at close - 2.237 * atr (current price minus 2.237 times the ATR).
Summary:
This strategy enters a Long trade when the Supertrend indicates an upward trend and RSI is not in the overbought region. Conversely, a Short trade is entered when Supertrend signals a downtrend, and RSI is not oversold.
The trade is exited when the price reaches the Stop Loss or Take Profit levels, which are determined based on price volatility (ATR).
Disclaimer:
The content provided in this strategy is for informational and educational purposes only. It is not intended as financial, investment, or trading advice. Trading in cryptocurrency, stocks, or any financial markets involves significant risk, and you may lose more than your initial investment. Past performance is not indicative of future results, and no guarantee of profit can be made. You should consult with a professional financial advisor before making any investment decisions. The creator of this strategy is not responsible for any financial losses or damages incurred as a result of following this strategy. All trades are executed at your own risk.
Intelle_city - World Cycle - Ath & Atl - Logarithmic - Strategy.Overview
Indicators: Strategy !
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Strategy - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for a buy-sell strategy; there is also a signal indicator from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Strategy - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для стратегии покупок продаж, есть также и сигнальный от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Strategy – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator ist für eine Kauf-Verkaufs-Strategie konzipiert; es gibt auch einen Signalindikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Boftei's StrategyI wrote this strategy about a year ago, but decided to publish it just now. I have not been able to implement this strategy in the market. If you can, then I will be happy for you.
This strategy is based on my "Botvenko Script". (It finds the difference between the logarithms of closing prices from different days.) (Check this script in my profile)
Then the strategy makes trades when the "Botvenko Script" indicator crosses the levels set earlier and manually selected for each currency pair/shares: long/short opening/closing levels, long/short re-entry levels. (They are drawn with horizontal dotted lines.) The names of these lines are: buy/sell level, long/short retry - too low/high, long close up/down, dead - close the short. Manual selection of each of the parameters provides a qualitative entry of the strategy into the deal. However, without restraining mechanisms, the strategy enters into rather controversial deals. In order to avoid going long/short during bear/bull markets, which is unacceptable, I added a fan of EMA lines.
The fan consists of several EMA lines, which are set according to Fibonacci numbers (21, 55, 89, 144). If the lines in the fan are arranged in ascending order (ema_21>ema_55 and ema_55>ema_89 and ema_89>ema_144), then this indicates a bull market, during which I banned shorting. And vice versa: during the bear market (ema_21
Shorting when Bollinger Band Above Price with RSI (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
The relative strength index ( RSI ) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
The short order is placed on assets that present strong momentum when it's more likely that it is about to reverse. The rule strategy places and closes the order when the following conditions are met:
ENTRY
The closing price is greater than the upper standard deviation of the Bollinger Bands
The RSI is less than 70.
EXIT
The trade is closed when the RSI is less than 70
The lower standard deviation of the Bollinger Band is less than the closing price.
This strategy was backtested from the beginning of 2022 to capture how this strategy would perform in a bear market.
The strategy assumes each order to trade 70% of the available capital to make the results more realistic. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume.
Token Metrics IndicatorThe Token Metrics Combined Indicator v2 is a comprehensive technical analysis tool designed to output Long/Short signals for crypto assets on TradingView. It combines multiple indicators, including Token Metrics Clouds, Token Metrics Trend Lines , Token Metrics Channels, and signals, to give a comprehensive outlook on the market trend and potential entry/exit points.
Users can backtest the signals to understand the strategy's historical performance, learn how to use it, identify its pros and cons, and determine the market conditions it best suits. It is important to note that the backtesting performance does not indicate future results.
The methods for calculating fixed stop-losses vary depending on the trading pattern. A fixed stop-loss is used for long-term trading, while a trading stop-loss is used for high-frequency trading. This provides flexible investment risk management, allowing you to assign different stop-loss percentages to different trading strategies.
The Length input allows users to control the indicator’s sensitivity, with a default value of 20 bars for long-term trading and 9 bars for high-frequency trading. The Adjustment Factor input has a default value of 0.1 and can be adjusted to adapt to changing levels of volatility . The Stop-loss input allows users to control their risk tolerance, with a default value of 8% for long-term trading and 2% for high-frequency trading.
Token Metrics Clouds incorporates a bullish / bearish trend indicator, which uses two adaptive moving averages that adapt to volatility , reducing false trend signals during range-bound environments and providing a more accurate representation of market trends.
The Token Metrics Trendline is a long-term indicator that uses an adaptive moving average to identify long-term trends. This can also be used for long-term resistance and support levels, providing a comprehensive overview of the current market situation for both long-term and high-frequency traders.
The Token Metrics Signals indicator provides long, short, and close signals, indicating when to enter and exit long or short positions based on the TM trend-following strategy.
The Token Metrics Channels indicator is a top/bottom indicator that adjusts to current levels of volatility . This uses adaptive Donchian channels to determine the previous short-term swing high and low, providing insight into where short-term resistance or support might be forming and where breakouts can occur. The look-back periods change according to the strategy time frame, offering a flexible and dynamic approach to market analysis.
Long-term trading is a trend-following strategy best suited for daily and weekly timeframes. This strategy works well in trending markets but may produce false signals in choppy or range-bound markets.
High-frequency trading is a mean-reverting strategy best suited for 15-minute, 30-minute, and 1-hour timeframes. This strategy performs well in choppy or range-bound markets but may not be effective in strong trending markets.
Ichimoku Cloud and ADX with Trailing Stop Loss (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
DMI is simple to interpret. When +DI > - DI, it means the price is trending up. On the other hand, when -DI > +DI, the trend is weak or moving on the downside. The ADX does not give an indication of the direction but about the strength of the trend.
Typically values of ADX above 25 mean that the trend is steeply moving up or down, based on the -DI and +DI positioning. This script aims to capture swings in the DMI, and thus, in the trend of the asset, using a contrarian approach.
Trading on high values of ADX, the strategy tries to spot extremely oversold and overbought conditions. Values of ADX above 45 may suggest that the trend has overextended and is maybe about to reverse.
This strategy combines the Ichimoku Cloud with the ADX indicator to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
MACD line crosses over the signal line
-DI is greater than +DI
ADX is greater than 45
Close Position:
3% increase trailing
3% decrease trailing
The script is backtested from December 2022 and provides good returns.
A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
RSI and MA with Trailing Stop Loss and Take Profit (by Coinrule)The relative strength index is a momentum indicator used in technical analysis. It measures the speed and magnitude of a coin's recent price changes to evaluate overvalued or undervalued conditions in the price of that coin. The RSI is displayed as an oscillator (a line graph essentially) on a scale of zero to 100. When the RSI reaches oversold levels, it can provide a signal to go long. When the RSI reaches overbought levels, it can mark a good exit point or alternatively, an entry for a short position. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A moving average (MA) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. Essentially it is used to help smooth out price data by creating a constantly updated average price.
The Strategy enters and closes trades when the following conditions are met:
Entry Conditions:
RSI is greater than 50
MA9 is greater than MA50
RSI increases by 5
Exit Conditions:
Price increases by 1% trailing
Price decreases by 2% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
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.
Macro Score - DFMA-BasedA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMA - Democratic Fibonacci Moving Average - is a separate indicator that we have released that takes 10 different Fibonacci MAs (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMA line. This helps by creating a consensus on the trend based on moving averages alone. Crossovers of the DFMA with the various Fib MA lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMA line/Fib MA (233) as well as the crosses of the Fib MA (3)/DFMA. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These foursignals hold a lighter weight than the MA cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a blue momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score (-5/5).
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Default Properties, for AVAX 20M:
DPO - 40, uncentered
CMO - 25, open
K/D - 3/3
RSI Stoch Length - 3
Stoch Length - 4
Stoch Source - open
JVB Length - 25
JVB Smoothing - 2
DFMA source - close
Macro Length - 13
TP % - 1.5%
TTP % - 0.005%
SL % - 2%
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
Fast EMA above Slow EMA with MACD (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average . An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the coin when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bullish
EMA8 is greater than EMA26
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include AXSUSDT on the 5-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly.
Additionally, the trailing stop loss and take profit conditions can also be changed to match your needs.
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.
Macro Score -- User-Customized Scores and SignalsA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger. This particular strategy allows the user to choose between 18 different signals to be used in scoring as well as allowing the user to determine the individual weights of each score as well as the overall threshold to determine long or short signals. Weights for each score range between 1 and 5, with 5 being the greatest weight. The overall threshold for long or short is dependent on the total possible weights added together (i.e. if your weights total -10 or +10, a threshold within this range must be used).
The macro score itself is printed in an underlay as a white line that goes between the maximum positive and negative values for all weights added together for this strategy. In addition to the macro score line, a green momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score. The length of the Macro Score's momentum line can be found in the settings.
The current signals to choose from include:
- ADX Threshold - if the Average Directional Index is above a set threshold, signal positive or negative
- CMF Threshold - if the Chaikin Money Flow oscillator is above 0, signal positive; otherwise, signal negative
- CMO > TSI Signal - signal positive if there is a cross of the Chande Momentum Oscillator and the True Strength Index signal line
- CMO Threshold - if the Chande Momentum Oscillator is above 0, signal positive; otherwise, signal negative
- DPO Threshold - if the Detrended Price Oscillator is above 0, signal positive; otherwise, signal negative
- EOM Threshold - if the Ease of Money Oscillator is above 0, signal positive; otherwise, signal negative
- Jurik Threshold - if the Jurik price line (from the Jurik Volatility Bands) is above 0, signal positive; otherwise, signal negative
- MACD Threshold - if the MACD signal line is above 0, signal positive; otherwise, signal negative
- McGinley Cross - a crossover of a fast McGinley Dynamic length line and a slow McGinley Dynamic line signals positive; otherwise, signal negative
- PSAR - if the direction of the PSAR is heading long, signal positive; otherwise, signal negative
- ROC Threshold - if the Rate of Change oscillator is above 0, signal positive; otherwise, signal negative
- RSI Threshold - if the Relative Strength Index is above 50, signal positive; otherwise, signal negative
- Stoch RSI Threshold - if the Stoch RSI is above 50, signal positive; otherwise, signal negative
- Supertrend - if the Supertrend determines long, signal positive; otherwise, signal negative
- TSI Cross - a crossover of the True Strength Index value line and the TSI signal line signals positive; otherwise, signal negative
- TSI Signal Threshold - if the TSI signal line is above 0, signal positive; otherwise, signal negative
- Williams Alligator Cross - if the Williams Alligator lips cross the teeth and jaw, signal positive; otherwise, signal negative
- Williams %R - if the Williams %R is above -50, signal positive; otherwise, signal negative
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Sample setup for SOLUSDT 30M:
- Score 1 - Value 4, PSAR (0.05 start, 0.02 increment, 0.2 max value; sourced open)
- Score 2 - Value 4, Jurik Threshold (JVB Length 25, JVB Smoothing 6, JVB Price Threshold 0)
- Score 3 - Value 5, DPO Threshold (DPO Length 40, uncentered)
- Score 4 - Value 5, CMO Threshold (CMO Length 40, sourced open)
- Score 5 - Value 2, MACD Threshold (Fast Length 12, Slow Length 30, sourced open)
- Macro Length 21
- Long Threshold - -3
- Short Threshold - +3
- Take Profit % - 0.9/0.9
- Trail % - 0.005
- Stop Loss % - 1.4
Sample setup for AVAXUSDT 20M:
- Score 1 - Value 3, TSI Cross (Long Length 25, Short Length 16, Signal Length 17)
- Score 2 - Value 2, TSI Signal Threshold (same settings as the TSI Cross)
- Score 3 - Value 2, Jurik Threshold (JVB Length 20, JVB Smoothing 8, JVB Price Threshold 0)
- Score 4 - Value 2, DPO Threshold (DPO Length 40, uncentered)
- Score 5 - Value 1, Stoch Threshold (K/D 3, RSI (Stoch) Length 10, Stochastic Length 4, sourced open)
- Macro Length 13
- Long Threshold - +5
- Short Threshold - -5
- Take Profit % - 1.2/1.2
- Trail % - 0.005
- Stop Loss % - 1.5
Big Whale Purchases and SalesBig Whale Purchases and Sales - plots big whale transactions on your chart!
People that hold more than 1% of a crypto currencies circulating supply are considered whales and have a huge influence on price, not just because they can move the market with their huge transactions, but also because other traders often track their wallets and follow their example. Taking a look at whale holdings, one can see why whale worship is so common in crypto: While Bitcoin has a relatively low whale concentration, many of the Top 100 Cryptocurrencies have whales control 60% or more of their circulating supply.
Integrating IntoTheBlock data, this script plots the transactions of these whales and, in strategy mode, copy trades them.
Features:
Strategy Mode: Switches the script between an indicator and a strategy.
Standard Deviations: The number of Standard Deviations that a transaction needs to surpass to be considered worth plotting. Setting this to 0 will show all whale transactions, higher settings will only show the biggest transactions.
Blockchain: The Chain on which Whale activity is tracked.
Simple RSI and SMA Long and Short (by Coinrule)The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A simple moving average ( SMA ) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range.
The Strategy enters and closes the trade when the following conditions are met:
LONG
SMA100 is greater than SMA150
RSI is greater than 50
SHORT
SMA100 is less than SMA150
RSI is less than 50
When a long position is opened, it remains open until the conditions for a short are met at which point the long position is closed and the short position is opened. Then, when the conditions for the long position are met, the short will be closed and a long will be opened.
This strategy is back tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
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.
Ichimoku Cloud and ADX with Trailing Stop Loss (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
DMI is simple to interpret. When +DI > - DI, it means the price is trending up. On the other hand, when -DI > +DI , the trend is weak or moving on the downside. The ADX does not give an indication about the direction but about the strength of the trend.
Typically values of ADX above 25 mean that the trend is steeply moving up or down, based on the -DI and +D positioning. This script aims to capture swings in the DMI, and thus, in the trend of the asset, using a contrarian approach.
Trading on high values of ADX, the strategy tries to spot extremely oversold and overbought conditions. Values of ADX above 45 may suggest that the trend has overextended and is may be about to reverse.
This strategy combines the Ichimoku Cloud with the ADX indicator to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
MACD line crosses over the signal line
-DI is greater than +DI
ADX is greater than 45
Close Position:
3% increase trailing
3% decrease trailing
The script is backtested from 1 January 2018 and provides good returns.
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.
This script also works well on MATIC (1d timeframe), ETH (1d timeframe), and SOL (1d timeframe).
Trend Follower Intraday [ Adjustable TF ]Trend Follower Intraday for 3 minute Time-Frame (Adjustable) , that has the time condition for Indian Markets as well.
Unlike the Free Scripts - Risk Management , Position Sizing , Partial Exit etc. are also included .
Send us a Message to know more about the strategy.
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The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) EMA1 crosses above EMA2 , is a Long condition .
2) EMA1 crosses below EMA2 , is a Short condition .
3) Green Section indicates Long position.
4) Red Section indicates Short position.
5) Allowed hours specifies the trade entry timing.
6) ATR STOP is the stop-loss value on chart , can be adjusted in INPUTS.
7) Target 1 is the 1st target value on chart , can be adjusted in INPUTS.
8) RISK is Maximum Risk per trade for the intraday trade can be changed .
9) Total Capital used can be adjusted under INPUTS.
10) ATR TRAIL is used for trailing after entry, as mentioned in the inputs below.
11) Check trades under the list of trades .
12) Trade only in liquid stocks .
13) Risk only 1-5% of total capital.
14) Inputs can be changed for better back-test results, but also manually check the trades before setting alerts
15) SQUARE OFF TIME - As you change the time frame , also change the square-off time to the candle's closing time.
Eg: For 3min Time-frame , Hour = 2Hrs | Minute = 57min
16) Strategy stops for the day if you have a loss .
17) COMMISSION value is set to 20Rs and SLIPPAGE value is set to 2 . Go to properties to change it .
*The input values and the results are mentioned under "BACKTEST RESULTS" below*
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// ————————> RISK MANAGEMENT <——————— //
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Risk management is done based on max loss per trade and can be adjusted in the INPUTS.
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// ————————> POSITION SIZE <——————— //
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Quantity of each trade is different based on the loss
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// ————————> PROPERTIES <——————— //
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COMMISSION , SLIPPAGE ,RECALCULATE is already mentioned in the code.
COMMISSION can be charges , based on the broker charges.
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// ————————> TIME CONDITION <————————— //
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The time can be changed in the INPUT.
The Indian Markets open at 9:15am and closes at 3:30pm.
The 'Allowed hours' under Inputs specifies the time at which Entries should happen .
"Close All" function closes all the trades before 3pm , at the open of the next candle.
To change the time to close all trades , check INPUT.
All open trades get closed by 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
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// ————————> BACKTEST RESULTS ( 123 CLOSED TRADES ) <————————— //
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INPUTS can be changed for better Back-Test results.
The strategy applied to NSE:JSWENERGY (3 min Time-Frame and with a capital of 3,00,000 ) gives us 81% profitability , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.957 ,net Profit of 43,000Rs .
Sharpe Ratio = 0.745
Sortino Ratio = 2.091
No strategy in the world promises 100% profits in all market conditions , so always define your risk before trading.
Also check Back-Test results manually ,before setting Alerts
The Graph has a Linear Curve with Consistent Profits.
The INPUTS are as follows,
1) EMA1 ————————————————> 38
2) EMA2 ————————————————> 118
3) ALLOWED HRS ———————————> 9:35 TO 14:30
4) ATR STOP ——————————————> 3.2
5) RISK ——————————————————> 3000
6) ATR TRAIL ———————————————> 2.6
7) TARGET 1 ————————————————> 2.4
8) MAX POSITION VALUE ——————————> 3,00,000
8) MAX DRAWDOWN —————————————> 9,000
8) SQUARE-OFF ————————————————> 14:57
NSE:JSWENERGY
Apply it to your charts Now !
NSE:JSWENERGY
Send us a message for FREE TRIALS | Instant Access
Thank You ☺
Catching the Bottom (by Coinrule)This script utilises the RSI and EMA indicators to enter and close the trade.
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
An exponential moving average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average (SMA), which applies an equal weight to all observations in the period.
The strategy enters and exits the trade based on the following conditions.
ENTRY
RSI has a decrease of 3.
RSI <40.
EMA100 has crossed above the EMA50.
EXIT
RSI is greater than 65.
EMA9 has crossed above EMA50.
This strategy is back tested from 1 April 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include ETH on the 5m timeframe, BNB on 5m timeframe, XRP on the 45m timeframe, MATIC on the 30m timeframe and MATIC on the 2H timeframe.
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.
EMA and MACD with Trailing Stop Loss (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bearish
EMA7 is greater than EMA14
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include XRPUSDT on the 1-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly
In order to further improve the strategy, the EMA can be changed from 7 and 14 to, say, EMA20 and EMA50. Furthermore, the trailing stop loss can also be changed to ideally suit the user to match their needs.
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.
BTC Profitable Wallets StrategyBTC Profitable Wallets Strategy - plots the percentage of profitable BTC wallets and places long orders when the profitable wallet share crosses above 50%, historically a very accurate point to catch the next Bull Run early.
The only setting is a smoothing option using the Moving Average method and length of your choice.
On Chain Data is queried from IntoTheBlock.
This is a 'HODL' strategy, with no exit given. If you'd like to see the historical performance check the Open Profit or place a sell order at the current date.
BTC Hashrate ribbonsBTC Hash Rate ribbons / Hash Rate cross
This strategy goes long when BTCs Hash Rate 30 day moving average crosses above the 60 day moving average, signifying that miner capitulation is over and recovery has started.
When the opposite signal is given, which signifies the beginning of miner capitulation, the strategy goes short (or flat, depending on configuration). This is generally considered the most popular Hash Rate related strategy.
The strategy is based on this medium article: medium.com
Thanks to the recent integration of IntoTheBlock data into Tradingview, we can now effortlessly show Hash Rate data on our chart,
keep in mind however, that IntoTheBlock doesn't provide Hash Rate data on timeframes below daily, so this strategy is based used on the daily, weekly or even monthly time frames.
Hash Rate definition:
The Bitcoin hash rate is the number of times per second that computers on the Bitcoin network are hashing data to verify transactions and perform the encryption that secures the network. The hash rate is an indicator of how healthy the Bitcoin network is at any given time, and is driven primarily by difficulty mining and the number of miners. Generally, a high hash rate is considered a good thing.
More precisely, the Bitcoin hash rate is the number of times per second that computers on the Bitcoin network are hashing data to verify transactions and perform the encryption that secures the network.
