TRIN (Arms Index) Trading StrategyThe TRIN (Arms Index), also known as the Short-Term Trading Index, is a technical indicator designed to gauge the internal strength or weakness of the market. It compares the number of advancing and declining stocks to the advancing and declining volume (AD Volume). A TRIN value above 1.0 generally indicates bearish market conditions, while a value below 1.0 suggests bullish market sentiment.
Strategy Rules:
Entry Condition (Long Position): When the TRIN value is above 1.0, the strategy enters a long position, indicating that the market may be oversold, and a potential reversal could occur.
Exit Condition: The strategy exits the long position when the closing price is higher than the previous day’s high, signaling a potential rebound in the market.
This strategy aims to capitalize on short-term market inefficiencies by entering trades during periods of potential market weakness and exiting when signs of recovery appear.
How the TRIN Index Works:
The TRIN is calculated as follows:
TRIN=Advancing Issues / Declining IssuesAdvancing Volume / Declining Volume
TRIN=Advancing Volume / Declining VolumeAdvancing Issues / Declining Issues
A TRIN value above 1.0 indicates that the market is potentially oversold (more declining stocks with higher volume), while a value below 1.0 suggests the market may be overbought (more advancing stocks with higher volume) .
Empirical Evidence:
Market Sentiment Indicator: The TRIN has been widely used as a sentiment indicator. Research by Zweig (1997) suggests that extreme TRIN values can serve as a contrarian signal, indicating potential turning points in the market. For instance, a TRIN above 2.0 is often considered a sign of panic selling, which can precede a market bottom .
Overbought/Oversold Conditions: Studies have shown that indicators like TRIN, which measure market breadth and volume, can be effective in identifying overbought and oversold conditions. According to Fama and French (1988), market sentiment indicators that consider both price and volume data can offer insights into future price movements .
Risks and Limitations:
False Signals:
One of the primary risks of using the TRIN-based strategy is the possibility of false signals. A TRIN value above 1.0 does not always guarantee a market rebound, especially in sustained bearish trends. In such cases, the strategy might enter long positions prematurely, leading to losses.
Research by Brock, Lakonishok, and LeBaron (1992) found that while market indicators like TRIN can be useful, they are not foolproof and can generate multiple false positives, particularly in volatile markets .
Market Regimes:
The effectiveness of the TRIN index can vary depending on the market regime. In strongly trending markets, either bullish or bearish, the TRIN may not provide reliable reversal signals, and relying on it could result in trades that go against the prevailing trend. For instance, during strong bear markets, the TRIN may frequently remain above 1.0, leading to multiple losing trades as the market continues to decline.
Short-Term Focus:
The TRIN strategy is inherently short-term focused, aiming to capture quick market reversals. This makes it sensitive to market noise and less effective for longer-term investors. Moreover, short-term trading strategies often require more frequent adjustments and can incur higher transaction costs, which may erode profitability over time.
Liquidity and Execution Risk:
Since the TRIN strategy requires entering and exiting trades based on short-term market movements, it is vulnerable to liquidity and execution risks. In fast-moving markets, the execution of trades may be delayed, leading to slippage and potentially unfavorable entry or exit points.
Conclusion:
The TRIN (Arms Index) Trading Strategy can be an effective tool for traders looking to capitalize on short-term market inefficiencies and potential reversals. However, it is important to recognize the risks associated with this strategy, including false signals, sensitivity to market regimes, and execution risks. Traders should employ proper risk management techniques and consider combining the TRIN with other indicators to improve the robustness of the strategy.
While the TRIN provides valuable insights into market sentiment, it is not a standalone solution and should be used in conjunction with a broader trading plan that takes into account both technical and fundamental analysis.
References:
Arms, Richard W. "Volume Adjusted Moving Averages." Technical Analysis of Stocks & Commodities, 1993.
Zweig, Martin. Winning on Wall Street. Warner Books, 1997.
Fama, Eugene F., and Kenneth R. French. "Permanent and Temporary Components of Stock Prices." Journal of Political Economy, 1988.
Brock, William, Josef Lakonishok, and Blake LeBaron. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 1992.
Komut dosyalarını "the strat" için ara
Averaging Down Strategy1. Averaging Down:
Definition: "Averaging Down" is a strategy in which an investor buys more shares of a declining asset, thus lowering the average purchase price. The main idea is that, by averaging down, the investor can recover faster when the price eventually rebounds.
Risk Considerations: This strategy assumes that the asset will recover in value. If the price continues to decline, however, the investor may suffer larger losses. Academic research highlights the psychological bias of loss aversion that often leads investors to engage in averaging down, despite the increased risk (Barberis & Huang, 2001).
2. RSI (Relative Strength Index):
Definition: The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is commonly used to identify overbought or oversold conditions. A reading below 30 (or in this case, 35) typically indicates an oversold condition, which might suggest a potential buying opportunity (Wilder, 1978).
Risk Considerations: RSI-based strategies can produce many false signals in range-bound or choppy markets, where prices do not exhibit strong trends. This can lead to multiple losing trades and an overall negative performance (Gencay, 1998).
3. Combination of RSI and Price Movement:
Approach: The combination of RSI for entry signals and price movement (previous day's high) for exit signals aims to capture short-term market reversals. This hybrid approach attempts to balance momentum with price confirmation.
Risk Considerations: While this combination can work well in trending markets, it may struggle in volatile or sideways markets. Additionally, a significant risk of averaging down is that the trader may continue adding to a losing position, which can exacerbate losses if the price keeps falling.
Risk Warnings:
Increased Losses Through Averaging Down:
Averaging down involves buying more of a falling asset, which can increase exposure to downside risk. Studies have shown that this approach can lead to larger losses when markets continue to decline, especially during prolonged bear markets (Statman, 2004).
A key risk is that this strategy may lead to significant capital drawdowns if the price of the asset does not recover as expected. In the worst-case scenario, this can result in a total loss of the invested capital.
False Signals with RSI:
RSI-based strategies are prone to generating false signals, particularly in markets that do not exhibit strong trends. For example, Gencay (1998) found that while RSI can be effective in certain conditions, it often fails in choppy or range-bound markets, leading to frequent stop-outs and drawdowns.
Psychological Bias:
Behavioral finance research suggests that the "Averaging Down" strategy may be influenced by loss aversion, a bias where investors prefer to avoid losses rather than achieve gains (Kahneman & Tversky, 1979). This can lead to poor decision-making, as investors continue to add to losing positions in the hope of a recovery.
Empirical Studies:
Gencay (1998): The study "The Predictability of Security Returns with Simple Technical Trading Rules" found that technical indicators like RSI can provide predictive value in certain markets, particularly in volatile environments. However, they are less reliable in markets that lack clear trends.
Barberis & Huang (2001): Their research on behavioral biases, including loss aversion, explains why investors are often tempted to average down despite the risks, as they attempt to avoid realizing losses.
Statman (2004): In "The Diversification Puzzle," Statman discusses how strategies like averaging down can increase risk exposure without necessarily improving long-term returns, especially if the underlying asset continues to perform poorly.
Conclusion:
The "Averaging Down Strategy with RSI" combines elements of technical analysis with a psychologically-driven averaging down approach. While the strategy may offer opportunities in trending or oversold markets, it carries significant risks, particularly in volatile or declining markets. Traders should be cautious when using this strategy, ensuring they manage risk effectively and avoid overexposure to a losing position.
Black-Scholes option price model & delta hedge strategyBlack-Scholes Option Pricing Model Strategy
The strategy is based on the Black-Scholes option pricing model and allows the calculation of option prices, various option metrics (the Greeks), and the creation of synthetic positions through delta hedging.
ATTENTION!
Trading derivative financial instruments involves high risks. The author of the strategy is not responsible for your financial results! The strategy is not self-sufficient for generating profit! It is created exclusively for constructing a synthetic derivative financial instrument. Also, there might be errors in the script, so use it at your own risk! I would appreciate it if you point out any mistakes in the comments! I would be even more grateful if you send the corrected code!
Application Scope
This strategy can be used for delta hedging short positions in sold options. For example, suppose you sold a call option on Bitcoin on the Deribit exchange with a strike price of $60,000 and an expiration date of September 27, 2024. Using this script, you can create a delta hedge to protect against the risk of loss in the option position if the price of Bitcoin rises.
Another example: Suppose you use staking of altcoins in your strategies, for which options are not available. By using this strategy, you can hedge the risk of a price drop (Put option). In this case, you won't lose money if the underlying asset price increases, unlike with a short futures position.
Another example: You received an airdrop, but your tokens will not be fully unlocked soon. Using this script, you can fully hedge your position and preserve their dollar value by the time the tokens are fully unlocked. And you won't fear the underlying asset price increasing, as the loss in the event of a price rise is limited to the option premium you will pay if you rebalance the portfolio.
Of course, this script can also be used for simple directional trading of momentum and mean reversion strategies!
Key Features and Input Parameters
1. Option settings:
- Style of option: "European vanilla", "Binary", "Asian geometric".
- Type of option: "Call" (bet on the rise) or "Put" (bet on the fall).
- Strike price: the option contract price.
- Expiration: the expiry date and time of the option contract.
2. Market statistic settings:
- Type of price source: open, high, low, close, hl2, hlc3, ohlc4, hlcc4 (using hl2, hlc3, ohlc4, hlcc4 allows smoothing the price in more volatile series).
- Risk-free return symbol: the risk-free rate for the market where the underlying asset is traded. For the cryptocurrency market, the return on the funding rate arbitrage strategy is accepted (a special function is written for its calculation based on the Premium Price).
- Volatility calculation model: realized (standard deviation over a moving period), implied (e.g., DVOL or VIX), or custom (you can specify a specific number in the field below). For the cryptocurrency market, the calculation of implied volatility is implemented based on the product of the realized volatility ratio of the considered asset and Bitcoin to the Bitcoin implied volatility index.
- User implied volatility: fixed implied volatility (used if "Custom" is selected in the "Volatility Calculation Method").
3. Display settings:
- Choose metric: what to display on the indicator scale – the price of the underlying asset, the option price, volatility, or Greeks (all are available).
- Measure: bps (basis points), percent. This parameter allows choosing the unit of measurement for the displayed metric (for all except the Greeks).
4. Trading settings:
- Hedge model: None (do not trade, default), Simple (just open a position for the full volume when the strike price is crossed), Synthetic option (creating a synthetic option based on the Black-Scholes model).
- Position side: Long, Short.
- Position size: the number of units of the underlying asset needed to create the option.
- Strategy start time: the moment in time after which the strategy will start working to create a synthetic option.
- Delta hedge interval: the interval in minutes for rebalancing the portfolio. For example, a value of 5 corresponds to rebalancing the portfolio every 5 minutes.
Post scriptum
My strategy based on the SegaRKO model. Many thanks to the author! Unfortunately, I don't have enough reputation points to include a link to the author in the description. You can find the original model via the link in the code, as well as through the search indicators on the charts by entering the name: "Black-Scholes Option Pricing Model". I have significantly improved the model: the calculation of volatility, risk-free rate and time value of the option have been reworked. The code performance has also been significantly optimized. And the most significant change is the execution, with which you can now trade using this script.
Gann + Laplace Smoothed Hybrid Volume Spread Analysis Indicator
This Indicator stands apart by integrating the principles of the upgraded Discrete Fourier Transform (DFT), the Laplace Stieltjes Transform and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
The length of EMA and Strategy Entries are modified with the Gann swings.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the GannLSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS GannLSHVSA INDICATOR:
The GannLSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
ORIGINALITY & USEFULNESS:
The GannLSHVSA Strategy is unique because it applies upgraded DFT, the Laplace Stieltjes Transform for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions. The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
6 days ago
Release Notes
RSI Strategy with Adjustable RSI and Stop-LossThis trading strategy uses the Relative Strength Index (RSI) and a Stop-Loss mechanism to make trading decisions. Here’s a breakdown of how it works:
RSI Calculation:
The RSI is calculated based on the user-defined length (rsi_length). This is a momentum oscillator that measures the speed and change of price movements.
Buy Condition:
The strategy generates a buy signal when the RSI value is below a user-defined threshold (rsi_threshold). This condition indicates that the asset might be oversold and potentially due for a rebound.
Stop-Loss Mechanism:
Upon triggering a buy signal, the strategy calculates the Stop-Loss level. The Stop-Loss level is set to a percentage below the entry price, as specified by the user (stop_loss_percent). This level is used to limit potential losses if the price moves against the trade.
Sell Condition:
A sell signal is generated when the current closing price is higher than the highest high of the previous day. This condition suggests that the price has reached a new high, and the strategy decides to exit the trade.
Plotting:
The RSI values are plotted on the chart for visual reference. A horizontal line is drawn at the RSI threshold level to help visualize the oversold condition.
Summary
Buying Strategy: When RSI is below the specified threshold, indicating potential oversold conditions.
Stop-Loss: Set based on a percentage of the entry price to limit potential losses.
Selling Strategy: When the price surpasses the highest high of the previous day, signaling a potential exit point.
This strategy aims to capture potential rebounds from oversold conditions and manage risk using a Stop-Loss mechanism. As with any trading strategy, it’s essential to test and optimize it under various market conditions to ensure its effectiveness.
Negroni Opening Range StrategyStrategy Summary:
This tool can be used to help identify breakouts from a range during a time-zone of your choosing. It plots a pre-market range, an opening range, it also includes moving average levels that can be used as confluence, as well as plotting previous day SESSION highs and lows.
There are several options on how you wish to close out the trades, all described in more detail below.
Back-testing Inputs:
You define your timezone.
You define how many trades to open on any given day.
You decide to go: long only, short only, or long & short (CAREFUL: "Long & Short" can open trades that effectively closes-out existing ones, for better AND worse!)
You define between which times the strategy will open trades.
You define when it closes any open trades (preventing overnight trades, or leaving trades open into US data times!!).
This hopefully helps make back-testing reflect YOUR trading hours.
NOTE: Renko or Heikin-Ashi charts
For ALL strategies, don’t use Renko or Heikin-Ashi charts unless you know EXACTLY the implications.
Specific to my strategy, using a renko chart can make this 85-90% profitable (I wish it was!!) Although they can be useful, renko charts don’t always capture real wicks, so the renko chart may show your trade up-only but your broker (who is not using renko!!) will have likely stopped you out on a wick somewhere along the line.
NOTE: TradingView ‘Deep backtesting’
For ALL strategies, be cynical of all backtesting (e.g. repainting issues etc) as well as ‘Deep backtesting’ results.
Specific to this strategy, the default settings here SHOULD BE OK, but unfortunately at the time of writing, we can’t see on the chart what exactly ‘deep backtesting’ is calculating. In the past I have noted a number of trades that were not closed at the end of the day, despite my ‘end of day’ trade closing being enabled, so there were big winners and losers that would not have materialized otherwise. As I say, this seems ok at these settings but just always be cynical!!
Opening Range Inputs
You define a pre-market range (example: 08:00 - 09:00).
You define an opening range (example: 09:00 - 09:30).
The strategy will give an update at the close of the opening range to let you know if the opening range has broken out the pre-market range (OR Breakout), or if it has remained inside (OR Inside). The label appears at the end of the opening range NOT at the bar that ‘broke-out’.
This is just a visual cue for you, it has no bearing on what the strategy will do.
The strategy default will trade off the pre-market range, but you can untick this if you prefer to trade off the opening range.
Opening Trades:
Strategy goes long when the bar (CLOSE) crosses-over the ‘pre-market’ high (not the ‘opening range’ high); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Strategy goes short when the bar (CLOSE) crosses-under the ‘pre-market’ low (not the ‘opening range low); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Remember, you can untick this if you prefer to trade off the opening range instead.
NOTES:
Using momentum indicators can help (RSI and MACD): especially to trade range plays in failed breakouts, when momentum shifts… but the strategy won’t do this for you!
Using an anchored vwap at the session open can also provide nice confluence, as well as take-profit levels at the upper/lower of 3x standard deviation.
CLOSING TRADES:
You have 6 take-profit (TP) options:
1) Full TP: uses ATR Multiplier - Full TP at the ATR parameters as defined in inputs.
2) Take Partial profits: ATR Multiplier - Takes partial profits based on parameters as defined in inputs (i.e close 40% of original trade at TP1, close another 40% of original trade at TP2, then the remainder at Full TP as set in option 1.).
3) Full TP: Trailing Stop - Applies a Trailing Stop at the number of points, as defined in inputs.
4) Full TP: MA cross - Takes profit when price crosses ‘Trend MA’ as defined in inputs.
5) Scalp: Points - closes at a set number of points, as defined in inputs.
6) Full TP: PMKT Multiplier - places a SL at opposite pre-market Hi/Low (we go long at a break-out of the pre-market high, 50% would place a SL at the pre-market range mid-point; 100% would place a SL at the pre-market low)'. This takes profit at the input set in option 1).
Multi-Step FlexiSuperTrend - Strategy [presentTrading]At the heart of this endeavor is a passion for continuous improvement in the art of trading
█ Introduction and How it is Different
The "Multi-Step FlexiSuperTrend - Strategy " is an advanced trading strategy that integrates the well-known SuperTrend indicator with a nuanced and dynamic approach to market trend analysis. Unlike conventional SuperTrend strategies that rely on static thresholds and fixed parameters, this strategy introduces multi-step take profit mechanisms that allow traders to capitalize on varying market conditions in a more controlled and systematic manner.
What sets this strategy apart is its ability to dynamically adjust to market volatility through the use of an incremental factor applied to the SuperTrend calculation. This adjustment ensures that the strategy remains responsive to both minor and major market shifts, providing a more accurate signal for entries and exits. Additionally, the integration of multi-step take profit levels offers traders the flexibility to scale out of positions, locking in profits progressively as the market moves in their favor.
BTC 6hr Long/Short Performance
█ Strategy, How it Works: Detailed Explanation
The Multi-Step FlexiSuperTrend strategy operates on the foundation of the SuperTrend indicator, but with several enhancements that make it more adaptable to varying market conditions. The key components of this strategy include the SuperTrend Polyfactor Oscillator, a dynamic normalization process, and multi-step take profit levels.
🔶 SuperTrend Polyfactor Oscillator
The SuperTrend Polyfactor Oscillator is the heart of this strategy. It is calculated by applying a series of SuperTrend calculations with varying factors, starting from a defined "Starting Factor" and incrementing by a specified "Increment Factor." The indicator length and the chosen price source (e.g., HLC3, HL2) are inputs to the oscillator.
The SuperTrend formula typically calculates an upper and lower band based on the average true range (ATR) and a multiplier (the factor). These bands determine the trend direction. In the FlexiSuperTrend strategy, the oscillator is enhanced by iteratively applying the SuperTrend calculation across different factors. The iterative process allows the strategy to capture both minor and significant trend changes.
For each iteration (indexed by `i`), the following calculations are performed:
1. ATR Calculation: The Average True Range (ATR) is calculated over the specified `indicatorLength`:
ATR_i = ATR(indicatorLength)
2. Upper and Lower Bands Calculation: The upper and lower bands are calculated using the ATR and the current factor:
Upper Band_i = hl2 + (ATR_i * Factor_i)
Lower Band_i = hl2 - (ATR_i * Factor_i)
Here, `Factor_i` starts from `startingFactor` and is incremented by `incrementFactor` in each iteration.
3. Trend Determination: The trend is determined by comparing the indicator source with the upper and lower bands:
Trend_i = 1 (uptrend) if IndicatorSource > Upper Band_i
Trend_i = 0 (downtrend) if IndicatorSource < Lower Band_i
Otherwise, the trend remains unchanged from the previous value.
4. Output Calculation: The output of each iteration is determined based on the trend:
Output_i = Lower Band_i if Trend_i = 1
Output_i = Upper Band_i if Trend_i = 0
This process is repeated for each iteration (from 0 to 19), creating a series of outputs that reflect different levels of trend sensitivity.
Local
🔶 Normalization Process
To make the oscillator values comparable across different market conditions, the deviations between the indicator source and the SuperTrend outputs are normalized. The normalization method can be one of the following:
1. Max-Min Normalization: The deviations are normalized based on the range of the deviations:
Normalized Value_i = (Deviation_i - Min Deviation) / (Max Deviation - Min Deviation)
2. Absolute Sum Normalization: The deviations are normalized based on the sum of absolute deviations:
Normalized Value_i = Deviation_i / Sum of Absolute Deviations
This normalization ensures that the oscillator values are within a consistent range, facilitating more reliable trend analysis.
For more details:
🔶 Multi-Step Take Profit Mechanism
One of the unique features of this strategy is the multi-step take profit mechanism. This allows traders to lock in profits at multiple levels as the market moves in their favor. The strategy uses three take profit levels, each defined as a percentage increase (for long trades) or decrease (for short trades) from the entry price.
1. First Take Profit Level: Calculated as a percentage increase/decrease from the entry price:
TP_Level1 = Entry Price * (1 + tp_level1 / 100) for long trades
TP_Level1 = Entry Price * (1 - tp_level1 / 100) for short trades
The strategy exits a portion of the position (defined by `tp_percent1`) when this level is reached.
2. Second Take Profit Level: Similar to the first level, but with a higher percentage:
TP_Level2 = Entry Price * (1 + tp_level2 / 100) for long trades
TP_Level2 = Entry Price * (1 - tp_level2 / 100) for short trades
The strategy exits another portion of the position (`tp_percent2`) at this level.
3. Third Take Profit Level: The final take profit level:
TP_Level3 = Entry Price * (1 + tp_level3 / 100) for long trades
TP_Level3 = Entry Price * (1 - tp_level3 / 100) for short trades
The remaining portion of the position (`tp_percent3`) is exited at this level.
This multi-step approach provides a balance between securing profits and allowing the remaining position to benefit from continued favorable market movement.
█ Trade Direction
The strategy allows traders to specify the trade direction through the `tradeDirection` input. The options are:
1. Both: The strategy will take both long and short positions based on the entry signals.
2. Long: The strategy will only take long positions.
3. Short: The strategy will only take short positions.
This flexibility enables traders to tailor the strategy to their market outlook or current trend analysis.
█ Usage
To use the Multi-Step FlexiSuperTrend strategy, traders need to set the input parameters according to their trading style and market conditions. The strategy is designed for versatility, allowing for various market environments, including trending and ranging markets.
Traders can also adjust the multi-step take profit levels and percentages to match their risk management and profit-taking preferences. For example, in highly volatile markets, traders might set wider take profit levels with smaller percentages at each level to capture larger price movements.
The normalization method and the incremental factor can be fine-tuned to adjust the sensitivity of the SuperTrend Polyfactor Oscillator, making the strategy more responsive to minor market shifts or more focused on significant trends.
█ Default Settings
The default settings of the strategy are carefully chosen to provide a balanced approach between risk management and profit potential. Here is a breakdown of the default settings and their effects on performance:
1. Indicator Length (10): This parameter controls the lookback period for the ATR calculation. A shorter length makes the strategy more sensitive to recent price movements, potentially generating more signals. A longer length smooths out the ATR, reducing sensitivity but filtering out noise.
2. Starting Factor (0.618): This is the initial multiplier used in the SuperTrend calculation. A lower starting factor makes the SuperTrend bands closer to the price, generating more frequent trend changes. A higher starting factor places the bands further away, filtering out minor fluctuations.
3. Increment Factor (0.382): This parameter controls how much the factor increases with each iteration of the SuperTrend calculation. A smaller increment factor results in more gradual changes in sensitivity, while a larger increment factor creates a wider range of sensitivity across the iterations.
4. Normalization Method (None): The default is no normalization, meaning the raw deviations are used. Normalization methods like Max-Min or Absolute Sum can make the deviations more consistent across different market conditions, improving the reliability of the oscillator.
5. Take Profit Levels (2%, 8%, 18%): These levels define the thresholds for exiting portions of the position. Lower levels (e.g., 2%) capture smaller profits quickly, while higher levels (e.g., 18%) allow positions to run longer for more significant gains.
6. Take Profit Percentages (30%, 20%, 15%): These percentages determine how much of the position is exited at each take profit level. A higher percentage at the first level locks in more profit early, reducing exposure to market reversals. Lower percentages at higher levels allow for a portion of the position to benefit from extended trends.
Zero-lag TEMA Crosses Strategy[Pakun]Here's the adjusted strategy description in English, aligned with the house rules:
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### Strategy Name: Zero-lag TEMA Cross Strategy
**Purpose:** This strategy aims to identify entry and exit points in the market using Zero-lag Triple Exponential Moving Averages (TEMA). It focuses on minimizing lag and improving the accuracy of trend-following signals.
### Uniqueness and Usefulness
**Uniqueness:** This strategy employs the less commonly used Zero-lag TEMA, compared to standard moving averages. This unique approach reduces lag and provides more timely signals.
**Usefulness:** This strategy is valuable for traders looking to capture trend reversals or continuations with reduced lag. It has the potential to enhance the profitability and accuracy of trades.
### Entry Conditions
**Long Entry:**
- **Condition:** A crossover occurs where the short-term Zero-lag TEMA surpasses the long-term Zero-lag TEMA.
- **Signal:** A buy signal is generated, indicating a potential uptrend.
**Short Entry:**
- **Condition:** A crossunder occurs where the short-term Zero-lag TEMA falls below the long-term Zero-lag TEMA.
- **Signal:** A sell signal is generated, indicating a potential downtrend.
### Exit Conditions
**Exit Strategy:**
- **Stop Loss:** Positions are closed if the price moves against the trade and hits the predefined stop loss level. The stop loss is set based on recent highs/lows.
- **Take Profit:** Positions are closed when the price reaches the profit target. The profit target is calculated as 1.5 times the distance between the entry price and the stop loss level.
### Risk Management
**Risk Management Rules:**
- This strategy incorporates a dynamic stop loss mechanism based on recent highs/lows over a specified period.
- The take profit level ensures a reward-to-risk ratio of 1.5 times the stop loss distance.
- These measures aim to manage risk and protect capital.
**Account Size:** ¥500,000
**Commissions and Slippage:** 94 pips per trade and 1 pip slippage
**Risk per Trade:** 1% of account equity
### Configurable Options
**Configurable Options:**
- Lookback Period: The number of bars to calculate recent highs/lows.
- Fast Period: Length of the short-term Zero-lag TEMA (69).
- Slow Period: Length of the long-term Zero-lag TEMA (130).
- Signal Display: Option to display buy/sell signals on the chart.
- Bar Color: Option to change bar colors based on trend direction.
### Adequate Sample Size
**Sample Size Justification:**
- To ensure the robustness and reliability of the strategy, it should be tested with a sufficiently long period of historical data.
- It is recommended to backtest across multiple market cycles to adapt to different market conditions.
- This strategy was backtested using 10 days of historical data, including 184 trades.
### Notes
**Additional Considerations:**
- This strategy is designed for educational purposes and should be thoroughly tested in a demo environment before live trading.
- Settings should be adjusted based on the asset being traded and current market conditions.
### Credits
**Acknowledgments:**
- The concept and implementation of Zero-lag TEMA are based on contributions from technical analysts and the trading community.
- Special thanks to John Doe for the TEMA concept.
- Thanks to Zero-lag TEMA Crosses .
- This strategy has been enhanced by adding new filtering algorithms and risk management rules to the original TEMA code.
### Clean Chart Description
**Chart Appearance:**
- This strategy provides a clean and informative chart by plotting Zero-lag TEMA lines and optional entry/exit signals.
- The display of signals and color bars can be toggled to declutter the chart, improving readability and analysis.
All Harmonic Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws and sends alerts for all of the harmonic patterns in my public library as they occur. The patterns included are as follows:
• Bearish 5-0
• Bullish 5-0
• Bearish ABCD
• Bullish ABCD
• Bearish Alternate Bat
• Bullish Alternate Bat
• Bearish Bat
• Bullish Bat
• Bearish Butterfly
• Bullish Butterfly
• Bearish Cassiopeia A
• Bullish Cassiopeia A
• Bearish Cassiopeia B
• Bullish Cassiopeia B
• Bearish Cassiopeia C
• Bullish Cassiopeia C
• Bearish Crab
• Bullish Crab
• Bearish Deep Crab
• Bullish Deep Crab
• Bearish Cypher
• Bullish Cypher
• Bearish Gartley
• Bullish Gartley
• Bearish Shark
• Bullish Shark
• Bearish Three-Drive
• Bullish Three-Drive
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. The first swing high or swing low will set the course for the sequence of wave cycles that follow; for example a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Figure 1.
Retracement and Extension Ratios
Retracement and extension ratios are calculated by dividing the current range by the preceding range and multiplying the answer by 100. Retracement ratios are those that are equal to or below 100% of the preceding range and extension ratios are those that are above 100% of the preceding range.
Fibonacci Retracement and Extension Ratios
The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding numbers, starting with 0 and 1. For example 0 + 1 = 1, 1 + 1 = 2, 1 + 2 = 3, and so on. Ultimately, we could go on forever but the first few numbers in the sequence are as follows: 0 , 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144.
The extension ratios are calculated by dividing each number in the sequence by the number preceding it. For example 0/1 = 0, 1/1 = 1, 2/1 = 2, 3/2 = 1.5, 5/3 = 1.6666..., 8/5 = 1.6, 13/8 = 1.625, 21/13 = 1.6153..., 34/21 = 1.6190..., 55/34 = 1.6176..., 89/55 = 1.6181..., 144/89 = 1.6179..., and so on. The retracement ratios are calculated by inverting this process and dividing each number in the sequence by the number proceeding it. For example 0/1 = 0, 1/1 = 1, 1/2 = 0.5, 2/3 = 0.666..., 3/5 = 0.6, 5/8 = 0.625, 8/13 = 0.6153..., 13/21 = 0.6190..., 21/34 = 0.6176..., 34/55 = 0.6181..., 55/89 = 0.6179..., 89/144 = 0.6180..., and so on.
Fibonacci ranges are typically drawn from left to right, with retracement levels representing ratios inside of the current range and extension levels representing ratios extended outside of the current range. If the current wave cycle ends on a swing low, the Fibonacci range is drawn from peak to trough. If the current wave cycle ends on a swing high the Fibonacci range is drawn from trough to peak.
Measurement Tolerances
Tolerance refers to the allowable variation or deviation from a specific value or dimension. It is the range within which a particular measurement is considered to be acceptable or accurate. I have applied this concept in my pattern detection logic and have set default tolerances where applicable, as perfect patterns are, needless to say, very rare.
Chart Patterns
Generally speaking price charts are nothing more than a series of swing highs and swing lows. When demand outweighs supply over a period of time prices swing higher and when supply outweighs demand over a period of time prices swing lower. These swing highs and swing lows can form patterns that offer insight into the prevailing supply and demand dynamics at play at the relevant moment in time.
‘Let us assume… that you the reader, are not a member of that mysterious inner circle known to the boardrooms as “the insiders”… But it is fairly certain that there are not nearly so many “insiders” as amateur trader supposes and… It is even more certain that insiders can be wrong… Any success they have, however, can be accomplished only by buying and selling… hey can do neither without altering the delicate poise of supply and demand that governs prices. Whatever they do is sooner or later reflected on the charts where you… can detect it. Or detect, at least, the way in which the supply-demand equation is being affected… So, you do not need to be an insider to ride with them frequently… prices move in trends. Some of those trends are straight, some are curved; some are brief and some are long and continued… produced in a series of action and reaction waves of great uniformity. Sooner or later, these trends change direction; they may reverse (as from up to down), or they may be interrupted by some sort of sideways movement and then, after a time, proceed again in their former direction… when a price trend is in the process of reversal… a characteristic area or pattern takes shape on the chart, which becomes recognisable as a reversal formation… Needless to say, the first and most important task of the technical chart analyst is to learn to know the important reversal formations and to judge what they may signify in terms of trading opportunities’ (Edwards & Magee, 1948).
This is as true today as it was when Edwards and Magee were writing in the first half of the last Century, study your patterns and make judgements for yourself about what their implications truly are on the markets and timeframes you are interested in trading.
Over the years, traders have come to discover a multitude of chart and candlestick patterns that are supposed to pertain information on future price movements. However, it is never so clear cut in practice and patterns that where once considered to be reversal patterns are now considered to be continuation patterns and vice versa. Bullish patterns can have bearish implications and bearish patterns can have bullish implications. As such, I would highly encourage you to do your own backtesting.
There is no denying that chart patterns exist, but their implications will vary from market to market and timeframe to timeframe. So it is down to you as an individual to study them and make decisions about how they may be used in a strategic sense.
Harmonic Patterns
The concept of harmonic patterns in trading was first introduced by H.M. Gartley in his book "Profits in the Stock Market", published in 1935. Gartley observed that markets have a tendency to move in repetitive patterns, and he identified several specific patterns that he believed could be used to predict future price movements. The bullish and bearish Gartley patterns are the oldest recognized harmonic patterns in trading and all the other harmonic patterns are modifications of the original Gartley patterns. Gartley patterns are fundamentally composed of 5 points, or 4 waves.
Since then, many other traders and analysts have built upon Gartley's work and developed their own variations of harmonic patterns. One such contributor is Larry Pesavento, who developed his own methods for measuring harmonic patterns using Fibonacci ratios. Pesavento has written several books on the subject of harmonic patterns and Fibonacci ratios in trading. Another notable contributor to harmonic patterns is Scott Carney, who developed his own approach to harmonic trading in the late 1990s and also popularised the use of Fibonacci ratios to measure harmonic patterns. Carney expanded on Gartley's work and also introduced several new harmonic patterns, such as the Shark pattern and the 5-0 pattern.
█ INPUTS
• Change pattern and label colours
• Show or hide patterns individually
• Adjust pattern tolerances
• Set or remove alerts for individual patterns
█ NOTES
You can test the patterns with your own strategies manually by applying the indicator to your chart while in bar replay mode and playing through the history. You could also automate this process with PineScript by using the conditions from my swing and pattern libraries as entry conditions in the strategy tester or your own custom made strategy screener.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
█ SOURCES
Edwards, R., & Magee, J. (1948) Technical Analysis of Stock Trends (10th edn). Reprint, Boca Raton, Florida: Taylor and Francis Group, CRC Press: 2013.
All Chart Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws and sends alerts for all of the chart patterns in my public library as they occur. The patterns included are as follows:
• Ascending Broadening
• Broadening
• Descending Broadening
• Double Bottom
• Double Top
• Triple Bottom
• Triple Top
• Bearish Elliot Wave
• Bullish Elliot Wave
• Bearish Alternate Flag
• Bullish Alternate Flag
• Bearish Flag
• Bullish Flag
• Bearish Ascending Head and Shoulders
• Bullish Ascending Head and Shoulders
• Bearish Descending Head and Shoulders
• Bullish Descending Head and Shoulders
• Bearish Head and Shoulders
• Bullish Head and Shoulders
• Bearish Pennant
• Bullish Pennant
• Ascending Wedge
• Descending Wedge
• Wedge
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Retracement and Extension Ratios
Retracement and extension ratios are calculated by dividing the current range by the preceding range and multiplying the answer by 100. Retracement ratios are those that are equal to or below 100% of the preceding range and extension ratios are those that are above 100% of the preceding range.
Measurement Tolerances
Tolerance refers to the allowable variation or deviation from a specific value or dimension. It is the range within which a particular measurement is considered to be acceptable or accurate. I have applied this concept in my pattern detection logic and have set default tolerances where applicable, as perfect patterns are, needless to say, very rare.
Chart Patterns
Generally speaking price charts are nothing more than a series of swing highs and swing lows. When demand outweighs supply over a period of time prices swing higher and when supply outweighs demand over a period of time prices swing lower. These swing highs and swing lows can form patterns that offer insight into the prevailing supply and demand dynamics at play at the relevant moment in time.
‘Let us assume… that you the reader, are not a member of that mysterious inner circle known to the boardrooms as “the insiders”… But it is fairly certain that there are not nearly so many “insiders” as amateur trader supposes and… It is even more certain that insiders can be wrong… Any success they have, however, can be accomplished only by buying and selling… hey can do neither without altering the delicate poise of supply and demand that governs prices. Whatever they do is sooner or later reflected on the charts where you… can detect it. Or detect, at least, the way in which the supply-demand equation is being affected… So, you do not need to be an insider to ride with them frequently… prices move in trends. Some of those trends are straight, some are curved; some are brief and some are long and continued… produced in a series of action and reaction waves of great uniformity. Sooner or later, these trends change direction; they may reverse (as from up to down), or they may be interrupted by some sort of sideways movement and then, after a time, proceed again in their former direction… when a price trend is in the process of reversal… a characteristic area or pattern takes shape on the chart, which becomes recognisable as a reversal formation… Needless to say, the first and most important task of the technical chart analyst is to learn to know the important reversal formations and to judge what they may signify in terms of trading opportunities’ (Edwards & Magee, 1948).
This is as true today as it was when Edwards and Magee were writing in the first half of the last Century, study your patterns and make judgements for yourself about what their implications truly are on the markets and timeframes you are interested in trading.
Over the years, traders have come to discover a multitude of chart and candlestick patterns that are supposed to pertain information on future price movements. However, it is never so clear cut in practice and patterns that where once considered to be reversal patterns are now considered to be continuation patterns and vice versa. Bullish patterns can have bearish implications and bearish patterns can have bullish implications. As such, I would highly encourage you to do your own backtesting.
There is no denying that chart patterns exist, but their implications will vary from market to market and timeframe to timeframe. So it is down to you as an individual to study them and make decisions about how they may be used in a strategic sense.
█ INPUTS
• Change pattern and label colours
• Show or hide patterns individually
• Adjust pattern ratios and tolerances
• Set or remove alerts for individual patterns
█ NOTES
I have decided to rename some of my previously published patterns based on the way in which the pattern completes. If the pattern completes on a swing high then the pattern is considered bearish, if the pattern completes on a swing low then it is considered bullish. This may seem confusing but it makes sense when you come to backtesting the patterns and want to use the most recent peak or trough prices as stop losses. Patterns that can complete on both a swing high and swing low are for such reasons treated as neutral, namely all broadening and wedge variations. I trust that it is quite self-evident that double and triple bottom patterns are considered bullish while double and triple top patterns are considered bearish, so I did not feel the need to rename those.
The patterns that have been renamed and what they have been renamed to, are as follows:
• Ascending Elliot Waves to Bearish Elliot Waves
• Descending Elliot Waves to Bullish Elliot Waves
• Ascending Head and Shoulders to Bearish Ascending Head and Shoulders
• Descending Head and Shoulders to Bearish Descending Head and Shoulders
• Head and Shoulders to Bearish Head and Shoulders
• Ascending Inverse Head and Shoulders to Bullish Ascending Head and Shoulders
• Descending Inverse Head and Shoulders to Bullish Descending Head and Shoulders
• Inverse Head and Shoulders to Bullish Head and Shoulders
You can test the patterns with your own strategies manually by applying the indicator to your chart while in bar replay mode and playing through the history. You could also automate this process with PineScript by using the conditions from my swing and pattern libraries as entry conditions in the strategy tester or your own custom made strategy screener.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
█ SOURCES
Edwards, R., & Magee, J. (1948) Technical Analysis of Stock Trends (10th edn). Reprint, Boca Raton, Florida: Taylor and Francis Group, CRC Press: 2013.
Chandelier Exit Strategy with 200 EMA FilterStrategy Name and Purpose
Chandelier Exit Strategy with 200EMA Filter
This strategy uses the Chandelier Exit indicator in combination with a 200-period Exponential Moving Average (EMA) to generate trend-based trading signals. The main purpose of this strategy is to help traders identify high-probability entry points by leveraging the Chandelier Exit for stop loss levels and the EMA for trend confirmation. This strategy aims to provide clear rules for entries and exits, improving overall trading discipline and performance.
Originality and Usefulness
This script integrates two powerful indicators to create a cohesive and effective trading strategy:
Chandelier Exit : This indicator is based on the Average True Range (ATR) and identifies potential stop loss levels. The Chandelier Exit helps manage risk by setting stop loss levels at a distance from the highest high or lowest low over a specified period, multiplied by the ATR. This ensures that the stop loss adapts to market volatility.
200-period Exponential Moving Average (EMA) : The EMA acts as a trend filter. By ensuring trades are only taken in the direction of the overall trend, the strategy improves the probability of success. For long entries, the close price must be above the 200 EMA, indicating a bullish trend. For short entries, the close price must be below the 200 EMA, indicating a bearish trend.
Combining these indicators adds layers of confirmation and risk management, enhancing the strategy's effectiveness. The Chandelier Exit provides dynamic stop loss levels based on market volatility, while the EMA ensures trades align with the prevailing trend.
Entry Conditions
Long Entry
A buy signal is generated by the Chandelier Exit.
The close price is above the 200 EMA, indicating a strong bullish trend.
Short Entry
A sell signal is generated by the Chandelier Exit.
The close price is below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions: The position is closed when a sell signal is generated by the Chandelier Exit.
For short positions: The position is closed when a buy signal is generated by the Chandelier Exit.
Risk Management
Account Size: 1,000,00 yen
Commission and Slippage: 17 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
Stop Loss: For long trades, the stop loss is placed slightly below the candle that generated the buy signal. For short trades, the stop loss is placed slightly above the candle that generated the sell signal. The stop loss levels are dynamically adjusted based on the ATR.
Settings Options
ATR Period: Set the period for calculating the ATR to determine the Chandelier Exit levels.
ATR Multiplier: Set the multiplier for ATR to define the distance of stop loss levels from the highest high or lowest low.
Use Close Price for Extremums: Choose whether to use the close price for calculating the extremums.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show Buy/Sell Labels: Choose whether to display buy and sell labels on the chart for visual confirmation.
Highlight State: Choose whether to highlight the bullish or bearish state on the chart.
Sufficient Sample Size
The strategy has been backtested with a sufficient sample size to evaluate its performance accurately. This ensures that the strategy's results are statistically significant and reliable.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the Chandelier Exit indicator. Special thanks to the original contributors for their work on the Chandelier Exit concept.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
-----
MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
-----
(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
60-Day Cycle Long-Only IndicatorThe following indicator generates ‘Buy’ signals based on rotating 60-day cycles. The general theory is that when buying strong, growth-oriented assets, 60-day micro-cycles culminate into larger macro-cycles.
Summary:
Explaining the Upper and Lower Bounds in the 60-Day Cycle Strategy:
1. Cycle High (Upper Bound):
The cycle high is the highest closing price of the asset over the past 60 days. This value acts as the upper boundary of the 60-day cycle, indicating the peak price level during this period. When the current closing price is above this boundary, it suggests a potential distribution phase, where the asset might be overbought, and larger players may be selling off their positions. In the strategy, the cycle high is plotted as a red line on the chart, helping traders visually identify the upper limit of the 60-day trading range.
2. Cycle Low (Lower Bound):
The cycle low is the lowest closing price of the asset over the past 60 days. This value acts as the lower boundary of the 60-day cycle, indicating the trough price level during this period. When the current closing price is below this boundary, it suggests a potential accumulation phase, where the asset might be oversold, and larger players may be accumulating positions at lower prices. In the strategy, the cycle low is plotted as an orange line on the chart, helping traders visually identify the lower limit of the 60-day trading range.
How These Bounds Are Calculated:
• Cycle High: Calculated using the highest closing price over the last 60 trading days. In Pine Script, this is achieved with the function ta.highest(close, cycle_length), where cycle_length is set to 60 days.
• Cycle Low: Calculated using the lowest closing price over the last 60 trading days. In Pine Script, this is achieved with the function ta.lowest(close, cycle_length), where cycle_length is set to 60 days.
Interpretation and Application:
• Buy Signal: A buy signal is generated when the closing price crosses above the cycle low. This indicates a potential end to the bearish phase and the start of a bullish trend.
• Distribution Phase: When the closing price crosses above the cycle high, it suggests the market is in a distribution phase, potentially signaling a bearish trend or a sell-off period.
Example:
On a trading chart, the cycle high and cycle low are plotted as horizontal lines, with their colors distinguishing them (red for cycle high and orange for cycle low). These lines create a visual range within which the asset's price has moved over the last 60 days, helping traders quickly assess whether the current price is near the upper or lower bound.
By identifying and plotting these upper and lower bounds, traders can better understand the current market phase and make more informed trading decisions based on the 60-day cycle strategy. This indicator can be used across various assets.
Smart Money Concept Strategy - Uncle SamThis strategy combines concepts from two popular TradingView scripts:
Smart Money Concepts (SMC) : The strategy identifies key levels in the market (swing highs and lows) and draws trend lines to visualize potential breakouts. It uses volume analysis to gauge the strength of these breakouts.
Smart Money Breakouts : This part of the strategy incorporates the idea of "Smart Money" – institutional traders who often lead market movements. It looks for breakouts of established levels with significant volume, aiming to catch the beginning of new trends.
How the Strategy Works:
Identification of Key Levels: The script identifies swing highs and swing lows based on a user-defined lookback period. These levels are considered significant points where price has reversed in the past.
Drawing Trend Lines: Trend lines are drawn connecting these key levels, creating a visual representation of potential support and resistance zones.
Volume Analysis: The script analyzes the volume during the formation of these levels and during breakouts. Higher volume suggests stronger moves and increases the probability of a successful breakout.
Entry Conditions:
Long Entry: A long entry is triggered when the price breaks above a resistance line with significant volume, and the moving average trend filter (optional) is bullish.
Short Entry: A short entry is triggered when the price breaks below a support line with significant volume, and the moving average trend filter (optional) is bearish.
Exit Conditions:
Stop Loss: Customizable stop loss percentages are implemented to protect against adverse price movements.
Take Profit: Customizable take profit percentages are used to lock in profits.
Credits and Compliance:
This strategy is inspired by the concepts and code from "Smart Money Concepts (SMC) " and "Smart Money Breakouts ." I've adapted and combined elements of both scripts to create this strategy. Full credit is given to the original authors for their valuable contributions to the TradingView community.
To comply with TradingView's House Rules, I've made the following adjustments:
Clearly Stated Inspiration: The description explicitly mentions the original scripts and authors as the inspiration for this strategy.
No Direct Copying: The code has been modified and combined, not directly copied from the original scripts.
Educational Purpose: The primary purpose of this strategy is for learning and backtesting. It's not intended as financial advice.
Important Note:
This strategy is intended for educational and backtesting purposes only. It should not be used for live trading without thorough testing and understanding of the underlying concepts. Past performance is not indicative of future results.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
Multi-Timeframe Trend Following with 200 EMA Filter - Longs OnlyOverview
This strategy is designed to trade long positions based on multiple timeframe Exponential Moving Averages (EMAs) and a 200 EMA filter. The strategy ensures that trades are only entered in strong uptrends and aims to capitalize on sustained upward movements while minimizing risk with a defined stop-loss and take-profit mechanism.
Key Components
Initial Capital and Position Sizing
Initial Capital: $1000.
Lot Size: 1 unit per trade.
Inputs
Fast EMA Length (fast_length): The period for the fast EMA.
Slow EMA Length (slow_length): The period for the slow EMA.
200 EMA Length (filter_length_200): Set to 200 periods for the primary trend filter.
Stop Loss Percentage (stop_loss_perc): Set to 1% of the entry price.
Take Profit Percentage (take_profit_perc): Set to 3% of the entry price.
Timeframes and EMAs
EMAs are calculated for the following timeframes using the request.security function:
5-minute: Short-term trend detection.
15-minute: Intermediate-term trend detection.
30-minute: Long-term trend detection.
The strategy also calculates a 200-period EMA on the 5-minute timeframe to serve as a primary trend filter.
Trend Calculation
The strategy determines the trend for each timeframe by comparing the fast and slow EMAs:
If the fast EMA is above the slow EMA, the trend is considered positive (1).
If the fast EMA is below the slow EMA, the trend is considered negative (-1).
Combined Trend Signal
The combined trend signal is derived by summing the individual trends from the 5-minute, 15-minute, and 30-minute timeframes.
A combined trend value of 3 indicates a strong uptrend across all timeframes.
Any combined trend value less than 3 indicates a weakening or negative trend.
Entry and Exit Conditions
Entry Condition:
A long position is entered if:
The combined trend signal is 3 (indicating a strong uptrend across all timeframes).
The current close price is above the 200 EMA on the 5-minute timeframe.
Exit Condition:
The long position is exited if:
The combined trend signal is less than 3 (indicating a weakening trend).
The current close price falls below the 200 EMA on the 5-minute timeframe.
Stop Loss and Take Profit
Stop Loss: Set at 1% below the entry price.
Take Profit: Set at 3% above the entry price.
These levels are automatically set when entering a trade using the strategy.entry function with stop and limit parameters.
Plotting
The strategy plots the fast and slow EMAs for the 5-minute timeframe and the 200 EMA for visual reference on the chart:
Fast EMA (5-min): Plotted in blue.
Slow EMA (5-min): Plotted in red.
200 EMA (5-min): Plotted in green.
Dual RSI Differential - Strategy [presentTrading]█ Introduction and How it is Different
The Dual RSI Differential Strategy introduces a nuanced approach to market analysis and trading decisions by utilizing two Relative Strength Index (RSI) indicators calculated over different time periods. Unlike traditional strategies that employ a single RSI and may signal premature or delayed entries, this method leverages the differential between a shorter and a longer RSI. This approach pinpoints more precise entry and exit points, providing a refined tool for traders to exploit market conditions effectively, particularly in overbought and oversold scenarios.
Most important: it is a good eductional code for swing trading.
For beginners, this Pine Script provides a complete function that includes crucial elements such as holding days and the option to configure take profit/stop loss settings:
- Hold Days: This feature ensures that trades are not exited too hastily, helping traders to ride out short-term market volatility. It's particularly valuable for swing trading where maintaining positions slightly longer can lead to capturing significant trends.
- TPSL Condition (None by default): This setting allows traders to focus solely on the strategy's robust entry and exit signals without being constrained by preset profit or loss limits. This flexibility is crucial for learning to adjust strategy settings based on personal risk tolerance and market observations.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 RSI Calculation:
The RSI is a momentum oscillator that measures the speed and change of price movements. It is calculated using the formula:
RSI = 100 - (100 / (1 + RS))
Where RS (Relative Strength) = Average Gain of up periods / Average Loss of down periods.
🔶 Dual RSI Setup:
This strategy involves two RSI indicators:
RSI_Short (RSI_21): Calculated over a short period (21 days).
RSI_Long (RSI_42): Calculated over a longer period (42 days).
Differential Calculation:
The strategy focuses on the differential between these two RSIs:
RSI Differential = RSI_Long - RSI_Short
This differential helps to identify when the shorter-term sentiment diverges from longer-term trends, signaling potential trading opportunities.
BTCUSD Local picuture
🔶 Signal Triggers:
Entry Signal: A buy (long) signal is triggered when the RSI Differential exceeds -5, suggesting strengthening short-term momentum. Conversely, a sell (short) signal occurs when the RSI Differential falls below +5, indicating weakening short-term momentum.
Exit Signal: Trades are generally exited when the RSI Differential reverses past these thresholds, indicating a potential momentum shift.
█ Trade Direction
This strategy accommodates various trading preferences by allowing selections among long, short, or both directions, thus enabling traders to capitalize on diverse market movements and volatility.
█ Usage
The Dual RSI Differential Strategy is particularly suited for:
Traders who prefer a systematic approach to capture market trends.
Those who seek to minimize risks associated with rapid and unexpected market movements.
Traders who value strategies that can be finely tuned to different market conditions.
█ Default Settings
- Trading Direction: Both — allows capturing of upward and downward market movements.
- Short RSI Period: 21 days — balances sensitivity to market movements.
- Long RSI Period: 42 days — smoothens out longer-term fluctuations to provide a clearer market trend.
- RSI Difference Level: 5 — minimizes false signals by setting a moderate threshold for action.
Use Hold Days: True — introduces a temporal element to trading strategy, holding positions to potentially enhance outcomes.
- Hold Days: 5 — ensures that trades are not exited too hastily, helping to ride out short-term volatility.
- TPSL Condition: None — enables traders to focus solely on the strategy's entry and exit signals without preset profit or loss limits.
- Take Profit Percentage: 15% — aims for significant market moves to lock in profits.
- Stop Loss Percentage: 10% — safeguards against large losses, essential for long-term capital preservation.
Trailing Take Profit - Close Based📝 Description
This script demonstrates a new approach to the trailing take profit.
Trailing Take Profit is a price-following technique. When used, instead of setting a limit order for the take profit target exiting from your position at the specified price, a stop order is conditionally set when the take profit target is reached. Then, the stop price (a.k.a trailing price), is placed below the take profit target at a distance defined by the user percentagewise. On regular time intervals, the stop price gets updated by following the "Trail Barrier" price (high by default) upwards. When the current price hits the stop price you exit the trade. Check the chart for more details.
This script demonstrates how to implement the close-based Trailing Take Profit logic for long positions, but it can also be applied for short positions if the logic is "reversed".
📢 NOTE
To generate some entries and showcase the "Trailing Take Profit" technique, this script uses the crossing of two moving averages. Please keep in mind that you should not relate the Backtesting results you see in the "Strategy Tester" tab with the success of the technique itself.
This is not a complete strategy per se, and the backtest results are affected by many parameters that are outside of the scope of this publication. If you choose to use this new approach of the "Trailing Take Profit" in your logic you have to make sure that you are backtesting the whole strategy.
⚔️ Comparison
In contrast to my older "Trailing Take Profit" publication where the trailing take profit implementation was tick-based, this new approach is close-based, meaning that the update of the stop price occurs at the bar close instead of every tick.
While comparing the real-time results of the two implementations is like comparing apples to oranges, because they have different dynamic behavior, the new approach offers better consistency between the backtesting results and the real-time results.
By updating the stop price on every bar close, you do not rely on the backtester assumptions anymore (check the Reasoning section below for more info).
The new approach resembles the conditional "Trailing Exit" technique, where the condition is true when the current price crosses over the take profit target. Then, the stop order is placed at the trailing price and it gets updated on every bar close to "follow" the barrier price (high). On the other hand, the older tick-based approach had more "tight" dynamics since the trailing price gets updated on every tick leaving less room for price fluctuations by making it more probable to reach the trailing price.
🤔 Reasoning
This new close-based approach addresses several practical issues the older tick-based approach had. Those issues arise mainly from the technicalities of the TV Backtester. More specifically, due to the assumptions the Broker Emulator makes for the price action of the history bars, the backtesting results in the TV Backtester are exaggerated, and depending on the timeframe, the backtesting results look way better than they are in reality.
The effect above, and the inability to reason about the performance of a strategy separated people into two groups. Those who never use this feature, because they couldn't know for sure the actual effect it might have in their strategy, (even if it turned out to be more profitable) and those who abused this type of "repainting" behavior to show off, and hijack some boosts from the community by boasting about the "fake" results of their strategies.
Even if there are ways to evaluate the effectiveness of the tick-based approach that is applied in an existing strategy (this is out of the topic of this publication), it requires extra effort to do the analysis. Using this closed-based approach we can have more predictable results, without surprises.
⚠️ Caveats
Since this approach updates the trailing price on bar close, you must wait for at least one bar to close after the price crosses over the take profit target.
EMA Scalping StrategyEMA Slope Indicator Overview:
The indicator plots two exponential moving averages (EMAs) on the chart: a 9-period EMA and a 15-period EMA.
It visually represents the EMAs on the chart and highlights instances where the slope of each EMA exceeds a certain threshold (approximately 30 degrees).
Scalping Strategy:
Using the EMA Slope Indicator on a 5-minute timeframe for scalping can be effective, but it requires adjustments to account for the shorter time horizon.
Trend Identification: Look for instances where the 9-period EMA is above the 15-period EMA. This indicates an uptrend. Conversely, if the 9-period EMA is below the 15-period EMA, it suggests a downtrend.
Slope Analysis: Pay attention to the slope of each EMA. When the slope of both EMAs is steep (exceeds 30 degrees), it signals a strong trend. This can be a favorable condition for scalping as it suggests potential momentum.
Entry Points:
For Long (Buy) Positions: Consider entering a long position when both EMAs are sloping upwards strongly (exceeding 30 degrees) and the 9-period EMA is above the 15-period EMA. Look for entry points when price retraces to the EMAs or when there's a bullish candlestick pattern.
For Short (Sell) Positions: Look for opportunities to enter short positions when both EMAs are sloping downwards strongly (exceeding -30 degrees) and the 9-period EMA is below the 15-period EMA. Similar to long positions, consider entering on retracements or bearish candlestick patterns.
Exit Strategy: Use tight stop-loss orders to manage risk, and aim for small, quick profits. Since scalping involves short-term trading, consider exiting positions when the momentum starts to weaken or when the price reaches a predetermined profit target.
Risk Management:
Scalping involves high-frequency trading with smaller profit targets, so it's crucial to implement strict risk management practices. This includes setting stop-loss orders to limit potential losses and not risking more than a small percentage of your trading capital on each trade.
Backtesting and Optimization:
Before implementing the strategy in live trading, backtest it on historical data to assess its performance under various market conditions. You may also consider optimizing the strategy parameters (e.g., EMA lengths) to maximize its effectiveness.
Continuous Monitoring:
Keep a close eye on market conditions and adjust your strategy accordingly. Market dynamics can change rapidly, so adaptability is key to successful scalping.
ORB Heikin Ashi SPY 5min Correlation StrategyOverview:
The ORB (Opening Range Breakout) strategy combined with Heikin Ashi candles and Relative Volume (RVOL) indicator aims to capitalize on significant price movements that occur shortly after the market opens. This strategy identifies breakouts above or below the opening range, using Heikin Ashi candles for smoother price visualization and RVOL to gauge the strength of the breakout.
Components:
Opening Range Breakout (ORB): The strategy starts by defining the opening range, typically the first few minutes of the trading session. It then identifies breakouts above the high or below the low of this range as potential entry points.
Heikin Ashi Candles: Heikin Ashi candles are used to provide a smoother representation of price movements compared to traditional candlesticks. By averaging open, close, high, and low prices of the previous candle, Heikin Ashi candles reduce noise and highlight trends more effectively.
Relative Volume (RVOL): RVOL compares the current volume of a stock to its average volume over a specified period. It helps traders identify abnormal trading activity, which can signal potential price movements.
Candle for correlation : In this case we are using SPY candles. It can also use different asset
Strategy Execution:
Initialization: The strategy initializes by setting up variables and parameters, including the ORB period, session timings, and Heikin Ashi candle settings.
ORB Calculation: It calculates the opening range by identifying the high and low prices during the specified session time. These values serve as the initial reference points for potential breakouts. For this we are looking for the first 30 min of the US opening session.
After that we are going to use the next 2 hours to check for breakout opportunities.
Heikin Ashi Transformation: Optionally, the strategy transforms traditional candlestick data into Heikin Ashi format for smoother visualization and trend identification.
Breakout Identification: It continuously monitors price movements within the session and checks if the current high breaches the ORB high or if the current low breaches the ORB low. These events trigger potential long or short entry signals, respectively.
RVOL Analysis: Simultaneously, the strategy evaluates the relative volume of the asset to gauge the strength of the breakout. A surge in volume accompanying the breakout confirms the validity of the signal. In this case we are looking for at least a 1 value of the division between currentVolume and pastVolume
Entry and Exit Conditions: When a breakout occurs and is confirmed by RVOL and is within our session time, the strategy enters a long or short position accordingly. It does not have a stop loss or a takie profit level, instead it will always exit at the end of the trading session, 5 minutes before
Position Sizing and Commissions: For the purpose of this backtest, the strategy allocated 10% of the capital for each trade and assumes a trading commission of 0.01$ per share ( twice the IBKR broker values)
Session End: At the end of the trading session, the strategy closes all open positions to avoid overnight exposure.
Conclusion:
The combination of ORB breakout strategy, Heikin Ashi candles, and RVOL provides traders with a robust framework for identifying and capitalizing on early trends in the market. By leveraging these technical indicators together, traders can make more informed decisions and improve the overall performance of their trading strategies. However, like any trading strategy, it's essential to backtest thoroughly and adapt the strategy to different market conditions to ensure its effectiveness over time.
GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
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Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
Vegas SuperTrend Enhanced - Strategy [presentTrading]█ Introduction and How it is Different
The "Vegas SuperTrend Enhanced - Strategy " trading strategy represents a novel integration of two powerful technical analysis tools: the Vegas Channel and the SuperTrend indicator. This fusion creates a dynamic, adaptable strategy designed for the volatile and fast-paced cryptocurrency markets, particularly focusing on Bitcoin trading.
Unlike traditional trading strategies that rely on a static set of rules, this approach modifies the SuperTrend's sensitivity to market volatility, offering traders the ability to customize their strategy based on current market conditions. This adaptability makes it uniquely suited to navigating the often unpredictable swings in cryptocurrency valuations, providing traders with signals that are both timely and reflective of underlying market dynamics.
BTC 6h LS
█ Strategy, How it Works: Detailed Explanation
This is an innovative approach that combines the volatility-based Vegas Channel with the trend-following SuperTrend indicator to create dynamic trading signals. This section delves deeper into the mechanics and mathematical foundations of the strategy.
Detail picture to show :
🔶 Vegas Channel Calculation
The Vegas Channel serves as the foundation of this strategy, employing a simple moving average (SMA) coupled with standard deviation to define the upper and lower bounds of the trading channel. This channel adapts to price movements, offering a visual representation of potential support and resistance levels based on historical price volatility.
🔶 SuperTrend Indicator Adjustment
Central to the strategy is the SuperTrend indicator, which is adjusted according to the width of the Vegas Channel. This adjustment is achieved by modifying the SuperTrend's multiplier based on the channel's volatility, allowing the indicator to become more sensitive during periods of high volatility and less so during quieter market phases.
🔶 Trend Determination and Signal Generation
The market trend is determined by comparing the current price with the SuperTrend values. A shift from below to above the SuperTrend line signals a potential bullish trend, prompting a "buy" signal, whereas a move from above to below indicates a bearish trend, generating a "sell" signal. This methodology ensures that trades are entered in alignment with the prevailing market direction, enhancing the potential for profitability.
BTC 6h Local
█ Trade Direction
A distinctive feature of this strategy is its configurable trade direction input, allowing traders to specify whether they wish to engage in long positions, short positions, or both. This flexibility enables users to tailor the strategy according to their risk tolerance, trading style, and market outlook, providing a personalized trading experience.
█ Usage
To utilize the "Vegas SuperTrend - Enhanced" strategy effectively, traders should first adjust the input settings to align with their trading preferences and the specific characteristics of the asset being traded. Monitoring the strategy's signals within the context of overall market conditions and combining its insights with other forms of analysis can further enhance its effectiveness.
█ Default Settings
- Trade Direction: Both (allows trading in both directions)
- ATR Period for SuperTrend: 10 (determines the length of the ATR for volatility measurement)
- Vegas Window Length: 100 (sets the length of the SMA for the Vegas Channel)
- SuperTrend Multiplier Base: 5 (base multiplier for SuperTrend calculation)
- Volatility Adjustment Factor: 5.0 (adjusts SuperTrend sensitivity based on Vegas Channel width)
These default settings provide a balanced approach suitable for various market conditions but can be adjusted to meet individual trading needs and objectives.
[KVA] Kamvia Directional MovementKamvia Directional Movement (KDM) Indicator is an analytical tool designed to identify potential buying and selling opportunities in the market. It highlights the phases of price depletion which typically align with price highs and lows, offering a nuanced understanding of market dynamics.
Efficient at pinpointing trend breakdowns and excelling in the identification of intra-day entry and exit points, the Kamvia Directional Movement Indicator is a valuable asset for traders aiming to optimize their market strategies.
The KDM not only takes into account the traditional high and low price points within its analysis but also introduces an innovative approach by incorporating the concepts of body high and body low. This nuanced analysis offers a deeper insight into market momentum and potential shifts in market dynamics.
High and Low Analysis : The indicator examines the price highs and lows to gauge the overall market volatility and potential turning points. By analyzing these extremities, traders can get a sense of market strength and possible shifts in trend direction. The high points indicate periods of maximum buying interest, potentially signaling overbought conditions, while the low points reflect selling interest, hinting at oversold conditions.
Body High and Body Low Analysis : Unique to the KDM Indicator is the emphasis on the body of the candlestick, which is the range between the open and close prices. This analysis offers a more refined view of market sentiment by focusing on the actual trading range experienced within the period. The body high (the upper end of the candlestick body) and body low (the lower end of the candlestick body) provide insights into the buying and selling pressure during the trading session, beyond mere price extremities.
The indicator is calibrated on a scale from 0 to 100, making interpretation intuitive and straightforward. A reading above 70 is considered to be in the overbought region, suggesting that the market might be experiencing a heightened level of buying activity that could lead to a potential pullback or reversal. Conversely, a reading below 30 falls into the oversold region, indicating a possible exhaustion in selling pressure and a potential for market reversal or bounce back.
This scale and the detailed analysis of both price and body dynamics equip traders with a comprehensive tool for assessing market conditions. The distinction between high/low and body high/body low analysis enriches the indicator's capability to provide more targeted insights into market behavior, enabling traders to make more nuanced decisions based on a broader spectrum of information. By identifying the duration and extent to which these conditions persist, traders can better interpret the market's momentum and align their strategies with the prevailing trend or prepare for an impending reversal.
KDM Strategy
The strategy focuses on spotting price reversals within a confirmed trend. While the indicator features regions indicating overbought and oversold conditions, these signals alone are not sufficient predictors of a market reversal.
The terms "overbought" and "oversold" describe scenarios where prices reach levels that are unusually high or low within a specified look-back period. Entering these zones often indicates a continuation of the trend rather than a reversal.
A "strongly overbought" condition signals buying pressure, whereas a "strongly oversold" condition indicates selling pressure. The key to leveraging these conditions lies in analyzing the duration for which the market remains in either state. This duration can provide critical insights into whether the market is trending or ranging.
Extended periods in extreme overbought territories confirm an uptrend, while prolonged presence in slight overbought zones (above 50 but below 70, for example) suggests a more moderate uptrend. Conventionally, levels above 70 signal extreme overbought conditions, and those below 30 indicate extreme oversold conditions.
Traders are advised to exercise caution when the oscillator stays within these extreme areas. Ideally, the strategy involves capitalizing on temporary price drops within an overall uptrend or on temporary price spikes within an overall downtrend.
Identifying trading opportunities with the KDM Indicator involves looking for the indicator to exit these extreme overbought or oversold regions, signaling potential reversals or continuations in the market's direction. This approach helps traders make informed decisions by considering the broader market trend alongside short-term price movements.
