Link Short Strategy - ShortHello everyone.
My strategy is only for LINK/USDT based on a grid bot strategy that can be found on a traditional exchange such as: Bitget, Bybit, Bingx...
I've customized it.
### Pine Script strategy summary:
1. **General description:**
- The strategy uses crosses between an **EMA (exponential moving average)** and a **SMA (simple moving average)** to identify short trading opportunities.
- It is active between specific price ranges defined for each segment (LongRange and ShortRange).
2. **Indicators:**
- **EMA9**: Exponential moving average over 13 periods (configurable).
- SMA6**: Simple moving average over 5 periods (configurable).
3. Position logic:** **Short Entry
- Short Entry** :
- Condition: EMA crossing under SMA (**emaCrossSmaDown**) when price is between `ShortRangeLow` and `ShortRangeHigh`.
- A **short** position is opened with `strategy.entry(“Short”, strategy.short)`.
- Long Exit**:
- Inverse condition (EMA crossing above SMA) when price is between `LongRangeLow` and `LongRangeHigh`.
- Long positions are closed if in profit.
4. **Stop Loss (SL) management:**
- Each segment (1 to 5) has a **Stop Loss (SL)** level defined by adding a fixed margin of 0.5 to the `LongRangeLow` level:
- Example: `slLevel = LongRangeLow + 0.5`.
- The **SL** applies only if the position has been opened between the defined ranges (`ShortRangeLow` and `ShortRangeHigh`).
5. **Display:**
- The EMA9 and SMA6 indicators are plotted on the chart for clear visualization.
- Price ranges (ShortRange and LongRange) are also plotted, with distinct colors for each segment.
6. **Multiple segments:**
- The strategy is repeated for 5 distinct price ranges (segmented into ShortRange and LongRange):
- Segment 1: LongRangeHigh = 11.13, ShortRangeHigh = 12.00.
- Segment 2: LongRangeHigh = 13.70, ShortRangeHigh = 14.85.
- Segment 3 : LongRangeHigh = 17.38, ShortRangeHigh = 19.10.
- Segment 4 : LongRangeHigh = 23.70, ShortRangeHigh = 25.75.
- Segment 5 : LongRangeHigh = 28.50, ShortRangeHigh = 30.40.
7. **Activation dates:**
- The strategy is active only between August 5, 2024 and September 1, 2026.
---
### Highlights :
- Well-integrated **Stop Loss** management to minimize losses.
- Visualization of price ranges facilitates analysis.
- The logic is replicable for several segments, making the strategy adaptable to different market ranges.
### Suggested improvements:
- **Take Profit (TP)**: Add TP levels to automate profit-taking.
- Additional filtering**: Use other indicators to confirm signals (e.g. RSI or MACD).
- Optimization**: Test different lengths for EMAs and SMAs to maximize performance.
Educational
Buy & Hold aka. HODL StrategyThis is a simply HODL or Buy & Hold strategy, which is super useful to see the risk and reward of such a strategy.
The benefit of using this strategy is that you also get to see the Max Drawdown (Risk).
This way you can compare it to the Net Profit (Reward) and decide if it's worth it for you.
This strategy buys on the Start Date and sells either on the End Date or on the last candle if the End Date is in the future.
Remember that the strategy must close the trade (sell) otherwise you don't see any results in the Strategy Tester (this is how it works).
Forex Pair Yield Momentum This Pine Script strategy leverages yield differentials between the 2-year government bond yields of two countries to trade Forex pairs. Yield spreads are widely regarded as a fundamental driver of currency movements, as highlighted by international finance theories like the Interest Rate Parity (IRP), which suggests that currencies with higher yields tend to appreciate due to increased capital flows:
1. Dynamic Yield Spread Calculation:
• The strategy dynamically calculates the yield spread (yield_a - yield_b) for the chosen Forex pair.
• Example: For GBP/USD, the spread equals US 2Y Yield - UK 2Y Yield.
2. Momentum Analysis via Bollinger Bands:
• Yield momentum is computed as the difference between the current spread and its moving
Bollinger Bands are applied to identify extreme deviations:
• Long Entry: When momentum crosses below the lower band.
• Short Entry: When momentum crosses above the upper band.
3. Reversal Logic:
• An optional checkbox reverses the trading logic, allowing long trades at the upper band and short trades at the lower band, accommodating different market conditions.
4. Trade Management:
• Positions are held for a predefined number of bars (hold_periods), and each trade uses a fixed contract size of 100 with a starting capital of $20,000.
Theoretical Basis:
1. Yield Differentials and Currency Movements:
• Empirical studies, such as Clarida et al. (2009), confirm that interest rate differentials significantly impact exchange rate dynamics, especially in carry trade strategies .
• Higher-yields tend to appreciate against lower-yielding currencies due to speculative flows and demand for higher returns.
2. Bollinger Bands for Momentum:
• Bollinger Bands effectively capture deviations in yield momentum, identifying opportunities where price returns to equilibrium (mean reversion) or extends in trend-following scenarios (momentum breakout).
• As Bollinger (2001) emphasized, this tool adapts to market volatility by dynamically adjusting thresholds .
References:
1. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy.
2. Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics.
3. Clarida, R., Davis, J., & Pedersen, N. (2009). Currency Carry Trade Regimes. NBER.
4. Bollinger, J. (2001). Bollinger on Bollinger Bands.
5. Mendelsohn, L. B. (2006). Forex Trading Using Intermarket Analysis.
Engulfing Candlestick StrategyEver wondered whether the Bullish or Bearish Engulfing pattern works or has statistical significance? This script is for you. It works across all markets and timeframes.
The Engulfing Candlestick Pattern is a widely used technical analysis pattern that traders use to predict potential price reversals. It consists of two candles: a small candle followed by a larger one that "engulfs" the previous candle. This pattern is considered bullish when it occurs in a downtrend (bullish engulfing) and bearish when it occurs in an uptrend (bearish engulfing).
Statistical Significance of the Engulfing Pattern:
While many traders rely on candlestick patterns for making decisions, research on the statistical significance of these patterns has produced mixed results. A study by Dimitrios K. Koutoupis and K. M. Koutoupis (2014), titled "Testing the Effectiveness of Candlestick Chart Patterns in Forex Markets," indicates that candlestick patterns, including the engulfing pattern, can provide some predictive power, but their success largely depends on the market conditions and timeframe used. The researchers concluded that while some candlestick patterns can be useful, traders must combine them with other indicators or market knowledge to improve their predictive accuracy.
Another study by Brock, Lakonishok, and LeBaron (1992), "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," explores the profitability of technical indicators, including candlestick patterns, and finds that simple trading rules, such as those based on moving averages or candlestick patterns, can occasionally outperform a random walk in certain market conditions.
However, Jorion (1997), in his work "The Risk of Speculation: The Case of Technical Analysis," warns that the reliability of candlestick patterns, including the engulfing patterns, can vary significantly across different markets and periods. Therefore, it's important to use these patterns as part of a broader trading strategy that includes other risk management techniques and technical indicators.
Application Across Markets:
This script applies to all markets (e.g., stocks, commodities, forex) and timeframes, making it a versatile tool for traders seeking to explore the statistical effectiveness of the bullish and bearish engulfing patterns in their own trading.
Conclusion:
This script allows you to backtest and visualize the effectiveness of the Bullish and Bearish Engulfing patterns across any market and timeframe. While the statistical significance of these patterns may vary, the script provides a clear framework for evaluating their performance in real-time trading conditions. Always remember to combine such patterns with other risk management strategies and indicators to enhance their predictive power.
The Ultimate CheckEasy Strategy, Entry on The Break out on the Moving Averages with a procental stop loss.
JAR - 2ema_strategyusing 2 EMA to open trade and close trade. using D1 chart, EMA 10 & 20, crypto trade. buy only at the moment and will workout both directions.
Up Gap Strategy with DelayThis strategy, titled “Up Gap Strategy with Delay,” is based on identifying up gaps in the price action of an asset. A gap is defined as the percentage difference between the current bar’s open price and the previous bar’s close price. The strategy triggers a long position if the gap exceeds a user-defined threshold and includes a delay period before entering the position. After entering, the position is held for a set number of periods before being closed.
Key Features:
1. Gap Threshold: The strategy defines an up gap when the gap size exceeds a specified threshold (in percentage terms). The gap threshold is an input parameter that allows customization based on the user’s preference.
2. Delay Period: After the gap occurs, the strategy waits for a delay period before initiating a long position. This delay can help mitigate any short-term volatility that might occur immediately after the gap.
3. Holding Period: Once the position is entered, it is held for a user-defined number of periods (holdingPeriods). This is to capture the potential post-gap trend continuation, as gaps often indicate strong directional momentum.
4. Gap Plotting: The strategy visually plots up gaps on the chart by placing a green label beneath the bar where the gap condition is met. Additionally, the background color turns green to highlight up-gap occurrences.
5. Exit Condition: The position is exited after the defined holding period. The strategy ensures that the position is closed after this time, regardless of whether the price is in profit or loss.
Scientific Background:
The gap theory has been widely studied in financial literature and is based on the premise that gaps in price often represent areas of significant support or resistance. According to research by Kaufman (2002), gaps in price action can be indicators of future price direction, particularly when they occur after a period of consolidation or a trend reversal. Moreover, Gaps and their Implications in Technical Analysis (Murphy, 1999) highlights that gaps can reflect imbalances between supply and demand, leading to high momentum and potential price continuation or reversal.
In trading strategies, utilizing gaps with specific conditions, such as delay and holding periods, can enhance the ability to capture significant price moves. The strategy’s delay period helps avoid potential market noise immediately after the gap, while the holding period seeks to capitalize on the price continuation that often follows gap formation.
This methodology aligns with momentum-based strategies, which rely on the persistence of trends in financial markets. Several studies, including Jegadeesh & Titman (1993), have documented the existence of momentum effects in stock prices, where past price movements can be predictive of future returns.
Conclusion:
This strategy incorporates gap detection and momentum principles, supported by empirical research in technical analysis, to attempt to capitalize on price movements following significant gaps. By waiting for a delay period and holding the position for a specified time, it aims to mitigate the risk associated with early volatility while maximizing the potential for sustained price moves.
RSI SMA Cross Strategy MKSBuys when the RSI crosses above its 14-day SMA.
Sells when the RSI crosses below its 14-day SMA.
Uses ₹100,000 as the starting capital, with remaining capital used for new trades.
RSI StrategyCondições de entrada e saída da estratégia:
Entrada em posição longa: A estratégia entra em uma posição comprada (longa) quando o RSI cai abaixo do nível de sobrevenda (20), indicando um possível momento de compra.
Saída de posição longa: A estratégia sai da posição longa em três cenários:
Realização de lucro: Quando o RSI atinge o nível de sobrecompra (70), indicando uma possível reversão de alta para baixa e uma oportunidade de obter lucro.
Stop-loss: Quando o RSI cai abaixo do nível de stop-loss (-15), limitando as perdas em caso de movimento adverso do preço.
Sinal de venda: Quando o RSI atinge novamente o nível de sobrecompra (70), indicando um sinal de venda.
3. Parâmetros da estratégia:
Período do RSI: O período de 14 dias é comumente utilizado para o cálculo do RSI, mas pode ser ajustado de acordo com a preferência do trader e as características do ativo.
Níveis de sobrecompra e sobrevenda: Os níveis de 70 e 20 são valores padrão, mas podem ser ajustados para aumentar ou diminuir a sensibilidade da estratégia.
Nível de stop-loss: O nível de stop-loss de -15 determina o ponto em que a posição é encerrada para limitar as perdas.
EMA 20/8 with RSI 14 StrategyThe **EMA 20/8 with RSI 14 Strategy** is a trading strategy designed to identify entry and exit points in the market using two Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI). It employs a short EMA (8 periods) and a long EMA (20 periods), capitalizing on crossover signals to indicate potential buying or selling opportunities.
The strategy generates a **long entry** when the short EMA crosses above the long EMA while the RSI is below the oversold threshold (30), suggesting a bullish trend reversal. Conversely, a **short entry** is triggered when the short EMA crosses below the long EMA and the RSI exceeds the overbought level (70), indicating a possible bearish trend reversal.
To manage risk, the strategy incorporates stop-loss and take-profit levels set as percentages of the entry price, ensuring structured exit points for both long and short trades. The script visualizes trade conditions using background colors for easy identification of entry signals directly on the chart. Additionally, it operates with a dynamic position sizing method, allowing the strategy to adjust order sizes based on a percentage of available equity, promoting better capital management during backtesting or live trading scenarios.
RSI Trading Strategy with EMA and ATR Profit __ahmad__razavi__
### Code Breakdown
1. **Strategy Declaration**:
```pinescript
//@version=6
strategy("RSI Trading Strategy with EMA and ATR Stop Loss/Take Profit", overlay=true)
```
- `//@version=6`: This specifies that the script uses version 6 of Pine Script.
- `strategy(...)`: This function defines the properties of the trading strategy, including its title and whether it overlays on the price chart (`overlay=true`).
2. **Input Parameters**:
```pinescript
length = input.int(14, minval=1, title="RSI Length")
src = input(close, title="Source")
rsi = ta.rsi(src, length)
```
- `length`: Input for the RSI length, defaulting to 14.
- `src`: Input for the source data (default is the closing price).
- `rsi`: Calculation of the RSI based on the specified source and length.
3. **Smoothing the RSI**:
```pinescript
smoothingLength = input.int(14, minval=1, title="Smoothing Length")
smoothedRsi = ta.ema(rsi, smoothingLength) // Using EMA to smooth RSI
```
- This section defines a smoothing length and calculates a smoothed version of the RSI using an Exponential Moving Average (EMA).
4. **ATR Calculation**:
```pinescript
atrLength = input.int(14, title="ATR Length")
atrMultiplier = input.float(1, title="ATR Multiplier")
atrValue = ta.atr(atrLength) // Calculate ATR
```
- `atrLength`: Input for the ATR calculation period.
- `atrMultiplier`: Input to set how many times the ATR will be used for stop-loss and take-profit levels.
- `atrValue`: Calculation of ATR based on the specified length.
5. **Trading Conditions**:
The following conditions define when to enter long or short positions based on RSI levels:
- **Long Entry Condition**:
```pinescript
if (ta.crossover(smoothedRsi, level2))
strategy.entry("Long", strategy.long)
strategy.exit("Take Profit/Stop Loss", "Long", stop=close - atrMultiplier * atrValue, limit=close + atrMultiplier * atrValue, comment="")
crossCount := crossCount + 1
crossPrice := close
```
- A long position is entered when the smoothed RSI crosses above level 70 (`level2`).
- The exit conditions set a stop-loss and take-profit based on ATR.
- **Short Entry Condition**:
```pinescript
if (ta.crossunder(smoothedRsi, level2))
strategy.entry("Short", strategy.short)
strategy.exit("Take Profit/Stop Loss", "Short", stop=close + atrMultiplier * atrValue, limit=close - atrMultiplier * atrValue, comment="")
crossCount := crossCount + 1
crossPrice := close
```
- A short position is entered when the smoothed RSI crosses below level 70.
- Similar exit conditions apply as in long entries.
- **Additional Long and Short Conditions**:
The script also includes conditions for entering long positions when crossing above level 30 (`level1`) and short positions when crossing below level 30.
6. **Cross Count Table**:
```pinescript
if (not na(crossPrice))
table.cell(crossingTable, 0, crossCount % 5, text=str.tostring(crossCount), bgcolor=color.green)
table.cell(crossingTable, 1, crossCount % 5, text=str.tostring(crossPrice), bgcolor=color.green)
```
- A table is created to display the count of crosses and their prices.
- The table updates every time a crossover occurs.
7. **Plotting RSI and Levels**:
```pinescript
plot(smoothedRsi, title="Smoothed RSI", color=color.blue)
hline(level1, "Level 30", color=color.red)
hline(level2, "Level 70", color=color.green)
```
- The smoothed RSI is plotted in blue.
- Horizontal lines are drawn at levels 30 and 70 to indicate overbought and oversold conditions.
### Summary
This script provides a comprehensive trading strategy that utilizes both RSI and ATR to manage trades effectively. It allows traders to enter positions based on RSI movements while using ATR to set dynamic stop-loss and take-profit levels. Additionally, it keeps track of how many times the RSI has crossed specified levels and displays this information in a table on the chart.
Multi-Timeframe RSI + Volume Trend StrategyThis TradingView strategy combines three core components to identify potential long entries and custom sell signals:
Moving Average (MA) Crossover for Long Entries
Uses a short-term MA crossover (MA A crosses above MA B) while both are above a longer-term MA C.
This indicates a bullish shift in short- and medium-term trends.
A position is only opened if no current long position exists.
Multi-Timeframe RSI Confirmation
Requires the RSI on 1-hour, 4-hour, and Daily charts to be within a specified range (e.g., 20–70).
This filters out entries when RSI is overly high or too low on multiple timeframes, aiming to catch reversals or healthy momentum.
Volume Filter for Buys
Confirms that the current bar’s volume exceeds a specified multiple (e.g., 1.5×) of its recent average volume.
Helps ensure that you only enter on higher-volume bars, potentially signifying stronger market interest.
Custom SELL Condition
High “Sell” Volume: The bar’s volume is above another user-defined threshold (e.g., 1.5× the volume MA).
RSI Cross-Down on Multiple Timeframes: At least two of the three timeframes’ RSIs (1h, 4h, Daily) must cross below 70 on the same bar.
MACD Bearish Crossover: The MACD line crosses below its signal line, suggesting a potential downshift in momentum.
When all these sell criteria align on the same bar, the strategy plots a “SELL” label above that bar. Optionally, you can automate a short entry or exit an existing long position at that point.
Stop Loss & Take Profit (ATR-Based)
Uses the Average True Range (ATR) to define dynamic stop loss and take profit levels.
Each bar recalculates these levels based on a multiplier of the ATR (e.g., 10.5× for stop loss, 30× for take profit).
Key Benefits
Trend Alignment: MA crossovers plus a longer MA filter keep the strategy aligned with a broader uptrend for longs.
Reduced False Signals: RSI confirmation on multiple timeframes and a volume check cut down on low-quality trades.
Adaptive Risk Management: ATR-based stops and targets scale with volatility, preventing stops from being too tight in volatile markets or too loose in quieter conditions.
Usage Tips
Parameter Tuning: Adjust RSI bounds, volume multipliers, and MA lengths to suit your market (crypto, forex, stocks).
Backtesting: Thoroughly test on historical data to gauge performance metrics (profit factor, drawdown, etc.).
Market Conditions: The strategy tends to do best in moderately trending environments. Highly choppy markets may produce more whipsaws.
Alerts: You can add alertcondition() calls to receive notifications when either BUY or SELL signals trigger.
With these features, the Multi-Timeframe RSI + Volume Trend Strategy aims to provide high-probability buy entries backed by bullish crossovers, momentum checks, and sufficient volume, while also identifying bearish conditions for exit or shorting through a robust, multi-factor sell signal.
itsmrk_Breakout Strategy_Testtest educational purpose test educational purpose test educational purpose test educational purpose test educational purpose
IU Higher Timeframe MA Cross StrategyIU Higher Timeframe MA Cross Strategy
The IU Higher Timeframe MA Cross Strategy is a versatile trading tool designed to identify trend by utilizing two customizable moving averages (MAs) across different timeframes and types. This strategy includes detailed entry and exit rules with fully configurable inputs, offering flexibility to suit various trading styles.
Key Features:
- Two moving averages (MA1 and MA2) with customizable types, lengths, sources, and timeframes.
- Both long and short trade setups based on MA crossovers.
- Integrated risk management with adjustable stop-loss and take-profit levels based on a user-defined risk-to-reward (RTR) ratio.
- Clear visualization of MAs, entry points, stop-loss, and take-profit zones.
Inputs:
1. Risk-to-Reward Ratio (RTR):
- Defines the take-profit level in relation to the stop-loss distance. Default is 2.
2. MA1 Settings:
- Source: Select the data source for calculating MA1 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA1 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA1 calculation. Default is 20.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA1 to merge gaps. Default is true.
3. MA2 Settings:
- Source: Select the data source for calculating MA2 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA2 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA2 calculation. Default is 50.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA2 to merge gaps. Default is true.
Entry Rules:
- Long Entry:
- Triggered when MA1 crosses above MA2 (crossover).
- Entry is confirmed only when the bar is closed and no existing position is active.
- Short Entry:
- Triggered when MA1 crosses below MA2 (crossunder).
- Entry is confirmed only when the bar is closed and no existing position is active.
Exit Rules:
- Stop-Loss:
- For long positions: Set at the low of the bar preceding the entry.
- For short positions: Set at the high of the bar preceding the entry.
- Take-Profit:
- For long positions: Calculated as (Entry Price - Stop-Loss) * RTR + Entry Price.
- For short positions: Calculated as Entry Price - (Stop-Loss - Entry Price) * RTR.
Visualization:
- Plots MA1 and MA2 on the chart with distinct colors for easy identification.
- Highlights stop-loss and take-profit levels using shaded zones for clear visual representation.
- Displays the entry level for active positions.
This strategy provides a robust framework for traders to identify and act on trend reversals while maintaining strict risk management. The flexibility of its inputs allows for seamless customization to adapt to various market conditions and trading preferences.
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Gold Trade Setup Strategy
Title: Profitable Gold Setup Strategy with Adaptive Moving Average & Supertrend
Introduction:
This trading strategy for Gold (XAU/USD) combines the Adaptive Moving Average (AMA) and Supertrend, tailored for high-probability setups during specific trading hours. The AMA identifies the trend, while the Supertrend confirms entry and exit points. The strategy is optimized for swing and intraday traders looking to capitalize on Gold’s price movements with precise trade timing.
Strategy Components:
1. Adaptive Moving Average (AMA):
• Reacts dynamically to market conditions, filtering noise in choppy markets.
• Serves as the primary trend indicator.
2. Supertrend:
• Confirms entry signals with clear buy and sell levels.
• Acts as a trailing stop-loss to protect profits.
Trading Rules:
Trading Hours:
• Only take trades between 8:30 AM and 10:30 PM IST.
• Avoid trading outside these hours to reduce noise and low-volume setups.
Buy Setup:
1. Trend Confirmation: The Adaptive Moving Average (AMA) must be green.
2. Signal Confirmation: The Supertrend should turn green after the AMA is green.
3. Trigger: Take the trade when the high of the trigger candle (the candle that turned Supertrend green) is broken.
Sell Setup (Optional if included):
• Reverse the rules for a short trade: AMA and Supertrend should both indicate bearish conditions (red), and take the trade when the low of the trigger candle is broken.
Stop-Loss and Targets:
• Place the stop-loss at the low of the trigger candle for long trades.
• Set a 1:2 risk-reward ratio or use the Supertrend line as a trailing stop-loss.
Timeframes:
• Recommended timeframes: 1H, 4H, or Daily for swing trading.
• For intraday trading, use 15-minute or 30-minute charts.
Why This Strategy Works:
• Combines trend-following (AMA) with momentum-based entries (Supertrend).
• Focused trading hours filter out low-probability setups.
• Provides precise entry, stop-loss, and target levels for disciplined trading.
Conclusion:
This Gold Setup Strategy is designed for traders seeking a structured approach to trading Gold. Follow the rules strictly, backtest the strategy extensively, and share your results. Let’s master the Gold market together!
Tags: #Gold #XAUUSD #SwingTrading #Intraday #Supertrend #AMA #TechnicalAnalysis #GoldStrategy
IU 4 Bar UP StrategyIU 4 Bar UP Strategy
The IU 4 Bar UP Strategy is a trend-following strategy designed to identify and execute long trades during strong bullish momentum, combined with confirmation from the SuperTrend indicator. This strategy is suitable for traders aiming to capitalize on sustained upward market movements.
Features :
1. SuperTrend Confirmation: Incorporates the SuperTrend indicator as a dynamic support/resistance line to filter trades in the direction of the trend.
2. 4 Consecutive Bullish Bars: Detects a series of 4 bullish candles as a signal for strong upward momentum, ensuring robust trade setups.
3. Dynamic Alerts: Sends alerts for trade entries and exits to keep traders informed.
4. Visual Enhancements:
- Plots the SuperTrend indicator on the chart.
- Changes the background color while a trade is active for easy visualization.
Inputs :
- SuperTrend ATR Period: The period used to calculate the Average True Range (ATR) for the SuperTrend indicator.
- SuperTrend ATR Factor: The multiplier for the ATR in the SuperTrend calculation.
Entry Conditions :
A long entry is triggered when:
1. The last 4 consecutive candles are bullish (closing prices are higher than opening prices).
2. The current price is above the SuperTrend line.
3. The strategy is not already in a position.
4. The bar is confirmed (not a partially formed bar).
When all these conditions are met, the strategy enters a long position and provides an alert:
"Long Entry triggered"
Exit Conditions :
The strategy exits the long position when:
1. The closing price drops below the SuperTrend line.
2. An alert is generated: "Close the long Trade"
Visualization :
- The SuperTrend line is plotted, dynamically colored:
- Green when the trend is bullish.
- Red when the trend is bearish.
- The background color turns semi-transparent green while a trade is active, indicating a long position.
Do use proper risk management while using this strategy.
Temporary Help Services Jobs - Trend Allocation StrategyThis strategy is designed to capitalize on the economic trends represented by the Temporary Help Services (TEMPHELPS) index, which is published by the Federal Reserve Economic Data (FRED). Temporary Help Services Jobs are often regarded as a leading indicator of labor market conditions, as changes in temporary employment levels frequently precede broader employment trends.
Methodology:
Data Source: The strategy uses the FRED dataset TEMPHELPS for monthly data on temporary help services.
Trend Definition:
Uptrend: When the current month's value is greater than the previous month's value.
Downtrend: When the current month's value is less than the previous month's value.
Entry Condition: A long position is opened when an uptrend is detected, provided no position is currently held.
Exit Condition: The long position is closed when a downtrend is detected.
Scientific Basis:
The TEMPHELPS index serves as a leading economic indicator, as noted in studies analyzing labor market cyclicality (e.g., Katz & Krueger, 1999). Temporary employment is often considered a proxy for broader economic conditions, particularly in predicting recessions or recoveries. Incorporating this index into trading strategies allows for aligning trades with potential macroeconomic shifts, as suggested by research on employment trends and market performance (Autor, 2001; Valetta & Bengali, 2013).
Usage:
This strategy is best suited for long-term investors or macroeconomic trend followers who wish to leverage labor market signals for equity or futures trading. It operates exclusively on end-of-month data, ensuring minimal transaction costs and noise.
McClellan A-D Volume Integration ModelThe strategy integrates the McClellan A-D Oscillator with an adjustment based on the Advance/Decline (A-D) volume data. The McClellan Oscillator is calculated by taking the difference between the short-term and long-term exponential moving averages (EMAs) of the A-D line. This strategy introduces an enhancement where the A-D volume (the difference between the advancing and declining volume) is factored in to adjust the oscillator value.
Inputs:
• ema_short_length: The length for the short-term EMA of the A-D line.
• ema_long_length: The length for the long-term EMA of the A-D line.
• osc_threshold_long: The threshold below which the oscillator must drop for an entry signal to trigger.
• exit_periods: The number of periods after which the position is closed.
• Data Sources:
• ad_advance and ad_decline are the data sources for advancing and declining issues, respectively.
• vol_advance and vol_decline are the volume data for the advancing and declining issues. If volume data is unavailable, it defaults to na (Not Available), and the fallback logic ensures that the strategy continues to function.
McClellan Oscillator with Volume Adjustment:
• The A-D line is calculated by subtracting the declining issues from the advancing issues. Then, the volume difference is applied to this line, creating a “weighted” A-D line.
• The short and long EMAs are calculated for the weighted A-D line to generate the McClellan Oscillator.
Entry Condition:
• The strategy looks for a reversal signal, where the oscillator falls below the threshold and then rises above it again. The condition is designed to trigger a long position when this reversal happens.
Exit Condition:
• The position is closed after a set number of periods (exit_periods) have passed since the entry.
Plotting:
• The McClellan Oscillator and the threshold are plotted on the chart for visual reference.
• Entry and exit signals are highlighted with background colors to make the signals more visible.
Scientific Background:
The McClellan A-D Oscillator is a popular market breadth indicator developed by Sherman and Marian McClellan. It is used to gauge the underlying strength of a market by analyzing the difference between the number of advancing and declining stocks. The oscillator is typically calculated using exponential moving averages (EMAs) of the A-D line, with the idea being that crossovers of these EMAs indicate potential changes in the market’s direction.
The integration of A-D volume into this model adds another layer of analysis, as volume is often considered a leading indicator of price movement. By factoring in volume, the strategy becomes more sensitive to not just the number of advancing or declining stocks but also how significant those movements are based on trading volume, as discussed in Schwager, J. D. (1999). Technical Analysis of the Financial Markets. This enhanced version aims to capture stronger and more sustainable trends in the market, helping to filter out false signals.
Additionally, volume analysis is often used to confirm price movements, as described in Wyckoff, R. (1931). The Day Trading System. Therefore, incorporating the volume of advancing and declining stocks in the McClellan Oscillator offers a more robust signal for trading decisions.
Z-Strike RecoveryThis strategy utilizes the Z-Score of daily changes in the VIX (Volatility Index) to identify moments of extreme market panic and initiate long entries. Scientific research highlights that extreme volatility levels often signal oversold markets, providing opportunities for mean-reversion strategies.
How the Strategy Works
Calculation of Daily VIX Changes:
The difference between today’s and yesterday’s VIX closing prices is calculated.
Z-Score Calculation:
The Z-Score quantifies how far the current change deviates from the mean (average), expressed in standard deviations:
Z-Score=(Daily VIX Change)−MeanStandard Deviation
Z-Score=Standard Deviation(Daily VIX Change)−Mean
The mean and standard deviation are computed over a rolling period of 16 days (default).
Entry Condition:
A long entry is triggered when the Z-Score exceeds a threshold of 1.3 (adjustable).
A high positive Z-Score indicates a strong overreaction in the market (panic).
Exit Condition:
The position is closed after 10 periods (days), regardless of market behavior.
Visualizations:
The Z-Score is plotted to make extreme values visible.
Horizontal threshold lines mark entry signals.
Bars with entry signals are highlighted with a blue background.
This strategy is particularly suitable for mean-reverting markets, such as the S&P 500.
Scientific Background
Volatility and Market Behavior:
Studies like Whaley (2000) demonstrate that the VIX, known as the "fear gauge," is highly correlated with market panic phases. A spike in the VIX is often interpreted as an oversold signal due to excessive hedging by investors.
Source: Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Z-Score in Financial Strategies:
The Z-Score is a proven method for detecting statistical outliers and is widely used in mean-reversion strategies.
Source: Chan, E. (2009). Quantitative Trading. Wiley Finance.
Mean-Reversion Approach:
The strategy builds on the mean-reversion principle, which assumes that extreme market movements tend to revert to the mean over time.
Source: Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
VIX Spike StrategyThis script implements a trading strategy based on the Volatility Index (VIX) and its standard deviation. It aims to enter a long position when the VIX exceeds a certain number of standard deviations above its moving average, which is a signal of a volatility spike. The position is then exited after a set number of periods.
VIX Symbol (vix_symbol): The input allows the user to specify the symbol for the VIX index (typically "CBOE:VIX").
Standard Deviation Length (stddev_length): The number of periods used to calculate the standard deviation of the VIX. This can be adjusted by the user.
Standard Deviation Multiplier (stddev_multiple): This multiplier is used to determine how many standard deviations above the moving average the VIX must exceed to trigger a long entry.
Exit Periods (exit_periods): The user specifies how many periods after entering the position the strategy will exit the trade.
Strategy Logic:
Data Loading: The script loads the VIX data, both for the current timeframe and as a rescaled version for calculation purposes.
Standard Deviation Calculation: It calculates both the moving average (SMA) and the standard deviation of the VIX over the specified period (stddev_length).
Entry Condition: A long position is entered when the VIX exceeds the moving average by a specified multiple of its standard deviation (calculated as vix_mean + stddev_multiple * vix_stddev).
Exit Condition: After the position is entered, it will be closed after the user-defined number of periods (exit_periods).
Visualization:
The VIX is plotted in blue.
The moving average of the VIX is plotted in orange.
The threshold for the VIX, which is the moving average plus the standard deviation multiplier, is plotted in red.
The background turns green when the entry condition is met, providing a visual cue.
Sources:
The VIX is often used as a measure of market volatility, with high values indicating increased uncertainty in the market.
Standard deviation is a statistical measure of the variability or dispersion of a set of data points. In financial markets, it is used to measure the volatility of asset prices.
References:
Bollerslev, T. (1986). "Generalized Autoregressive Conditional Heteroskedasticity." Journal of Econometrics.
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy.
IU open equal to high/low strategyIU open equal to high/low strategy:
The "IU Open Equal to High/Low Strategy" is designed to identify and trade specific market conditions where the day's first price action shows a strong directional bias. This strategy automatically enters trades based on the relationship between the market's open price and its first high or low of the day.
Entry Conditions:
1. Long Entry: A long position is initiated when the first open price of the session equals the day's first low. This signals a potential upward move.
2. Short Entry: A short position is initiated when the first open price of the session equals the day's first high. This signals a potential downward move.
Exit Conditions:
1. Stop Loss (SL): For both long and short trades, the stop loss is calculated based on the low or high of the candle where the position was entered.
2. Take Profit (TP): The take profit is set using a Risk-to-Reward (RTR) ratio, which is customizable by the user. The TP is calculated relative to the entry price and the distance between the entry and the stop loss.
Additional Features:
- Plots are used to visualize the entry price, stop loss, and take profit levels directly on the chart, providing clear and actionable insights.
- Labels are displayed to indicate the occurrence of the "Open == Low" or "Open == High" conditions for easier identification of potential trade setups.
- A dynamic fill highlights the areas between the entry price and the stop loss or take profit, offering a clear visual representation of the trade's risk and reward zones.
This strategy is designed for traders looking to capitalize on directional momentum at the start of the trading session. It is customizable, allowing users to set their desired Risk-to-Reward ratio and tailor the strategy to fit their trading style.
