QQE with EMA Cross Strategy - GauravThis QQE and EMA Crossover based strategy is made to test on Index. Test and use wisely.
Indicatori e strategie
Crypto Swing Levels with StrategyAuthor: Ravi Kumar
Description :
AIM: This indicator helps you identify the swing level for crypto.
Background : This strategy is based on the last 5 min candle closed for the day as per Indian time standard. i.e: 23:55
Strategy 1: The code identifies the high and low of the 23:55 5-minute candle and draws 0.83% from the high and 0.83% from below to identify the first-level range.
Repeat the above steps to get further above and below ranges.
Strategy 2:
Using Strategy 1 , one can find the beautiful swing levels but when to buy and when to sell I am merging default indicators settings
1. MACD indicator
2. RSI
Buy Condition:
A long (buy) signal is generated when:
delta (MACD histogram) crosses above the threshold.
The closing price is above the longMA (indicating an uptrend).
rsi Value is below overbought Level, avoiding overbought conditions.
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Sell Condition:
A short (sell) signal is triggered when:
delta crosses below the -threshold.
The closing price is below longMA (indicating a downtrend).
rsi Value is above oversold Level, avoiding oversold conditions.
How to use Indicator :
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Step-1: Chart timeframe should be in 5 min
Step -2:Once Indicator will came you will see a message to select date and time range. Select yesterday date to forecast the levels for upcoming days.
Example : if you want to see levels for 4th nov then in setting select the date as 3rd Nov.
Step-3 : Now your levels are ready.
Note: It will help you to identify crucial levels of cryptos.
CCI Threshold StrategyThe CCI Threshold Strategy is a trading approach that utilizes the Commodity Channel Index (CCI) as a momentum indicator to identify potential buy and sell signals in financial markets. The CCI is particularly effective in detecting overbought and oversold conditions, providing traders with insights into possible price reversals. This strategy is designed for use in various financial instruments, including stocks, commodities, and forex, and aims to capitalize on price movements driven by market sentiment.
Commodity Channel Index (CCI)
The CCI was developed by Donald Lambert in the 1980s and is primarily used to measure the deviation of a security's price from its average price over a specified period.
The formula for CCI is as follows:
CCI=(TypicalPrice−SMA)×0.015MeanDeviation
CCI=MeanDeviation(TypicalPrice−SMA)×0.015
where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average of the Typical Price
Mean Deviation = Average of the absolute deviations from the SMA
The CCI oscillates around a zero line, with values above +100 indicating overbought conditions and values below -100 indicating oversold conditions (Lambert, 1980).
Strategy Logic
The CCI Threshold Strategy operates on the following principles:
Input Parameters:
Lookback Period: The number of periods used to calculate the CCI. A common choice is 9, as it balances responsiveness and noise.
Buy Threshold: Typically set at -90, indicating a potential oversold condition where a price reversal is likely.
Stop Loss and Take Profit: The strategy allows for risk management through customizable stop loss and take profit points.
Entry Conditions:
A long position is initiated when the CCI falls below the buy threshold of -90, indicating potential oversold levels. This condition suggests that the asset may be undervalued and due for a price increase.
Exit Conditions:
The long position is closed when the closing price exceeds the highest price of the previous day, indicating a bullish reversal. Additionally, if the stop loss or take profit thresholds are hit, the position will be exited accordingly.
Risk Management:
The strategy incorporates optional stop loss and take profit mechanisms, which can be toggled on or off based on trader preference. This allows for flexibility in risk management, aligning with individual risk tolerances and trading styles.
Benefits of the CCI Threshold Strategy
Flexibility: The CCI Threshold Strategy can be applied across different asset classes, making it versatile for various market conditions.
Objective Signals: The use of quantitative thresholds for entry and exit reduces emotional bias in trading decisions (Tversky & Kahneman, 1974).
Enhanced Risk Management: By allowing traders to set stop loss and take profit levels, the strategy aids in preserving capital and managing risk effectively.
Limitations
Market Noise: The CCI can produce false signals, especially in highly volatile markets, leading to potential losses (Bollinger, 2001).
Lagging Indicator: As a lagging indicator, the CCI may not always capture rapid market movements, resulting in missed opportunities (Pring, 2002).
Conclusion
The CCI Threshold Strategy offers a systematic approach to trading based on well-established momentum principles. By focusing on overbought and oversold conditions, traders can make informed decisions while managing risk effectively. As with any trading strategy, it is crucial to backtest the approach and adapt it to individual trading styles and market conditions.
References
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Lambert, D. (1980). Commodity Channel Index. Technical Analysis of Stocks & Commodities, 2, 3-5.
Pring, M. J. (2002). Technical Analysis Explained. New York: McGraw-Hill.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
VWAP Stdev Bands Strategy (Long Only)The VWAP Stdev Bands Strategy (Long Only) is designed to identify potential long entry points in trending markets by utilizing the Volume Weighted Average Price (VWAP) and standard deviation bands. This strategy focuses on capturing upward price movements, leveraging statistical measures to determine optimal buy conditions.
Key Features:
VWAP Calculation: The strategy calculates the VWAP, which represents the average price a security has traded at throughout the day, weighted by volume. This is an essential indicator for determining the overall market trend.
Standard Deviation Bands: Two bands are created above and below the VWAP, calculated using specified standard deviations. These bands act as dynamic support and resistance levels, providing insight into price volatility and potential reversal points.
Trading Logic:
Long Entry Condition: A long position is triggered when the price crosses below the lower standard deviation band and then closes above it, signaling a potential price reversal to the upside.
Profit Target: The strategy allows users to set a predefined profit target, closing the long position once the specified target is reached.
Time Gap Between Orders: A customizable time gap can be specified to prevent multiple orders from being placed in quick succession, allowing for a more controlled trading approach.
Visualization: The VWAP and standard deviation bands are plotted on the chart with distinct colors, enabling traders to visually assess market conditions. The strategy also provides optional plotting of the previous day's VWAP for added context.
Use Cases:
Ideal for traders looking to engage in long-only positions within trending markets.
Suitable for intraday trading strategies or longer-term approaches based on market volatility.
Customization Options:
Users can adjust the standard deviation values, profit target, and time gap to tailor the strategy to their specific trading style and market conditions.
Note: As with any trading strategy, it is important to conduct thorough backtesting and analysis before live trading. Market conditions can change, and past performance does not guarantee future results.
Dynamic RSI Mean Reversion StrategyDynamic RSI Mean Reversion Strategy
Overview:
This strategy uses an RSI with ATR-Adjusted OB/OS levels in order to enhance the quality of it's mean reversion trades. It also incorporates a form of trend filtering in an effort to minimize downside and maximize upside. The backtest has fewer trades, as it uses substantial filtering to enhance trade quality. As you can see, I didn't cherry pick the results, so the results aren't the most beautiful thing you'll see in your life. I did this to ensure nobody gets misled. If you need a higher frequency of trades, consider removing the trend filter or increasing the length of the EMAs used for trend detection.
Features:
Dynamic OB/OS Levels: Uses ATR to adjust overbought and oversold thresholds dynamically, making the RSI more responsive in varying volatility conditions. This approach enhances signal strength by expanding the RSI range in high volatility and tightening it in low volatility.
Mean Reversion Focus: Designed for mean reversion but incorporates a trend-following filter to reduce countertrend trades. When the RSI is high, it often indicates an uptrend, so a trend filter prevents shorting in these cases and the same goes for downtrends and longing.
Trend Filtering: A moving average cross trend filter checks for the trend direction, with the RSI signal line color-coded to reflect trend shifts. Entries occur when the RSI crosses above or below the dynamic thresholds and is not a countertrend trade.
Stop Losses: Stop losses are set based on ATR distance from the entry price, providing volatility-adjusted protection.
Note:
If you're using this strategy on assets with a higher price, remember to increase the initial capital in the strategy settings. Otherwise, the strategy won't generate any (or many) trades and you'll end up with some inaccurate results.
Recommended Use:
Test it on different assets and timeframes. I’ve found the best results with standard RSI inputs, a relatively slow ATR, and a slower MA cross for trend filtering. Thus, the defaults are set that way. If the trend metrics are too slow, you’ll filter out too many good trades while allowing crummy ones; if too fast, most trades may be filtered out. As always, this has a lot of configurability so experiment to find the balance that works for your trading style.
Strategy of Losing Money (MIZE)Best way to loose money! If you want to loose money quick, then use it on one hour chart bitcoin, your money would dissapear in a couple of days!
MA Crossover with RSI FilterExplanation of Key Components
Input Parameters:
shortMaLength and longMaLength: Configure the lengths for the short and long moving averages.
rsiLength: RSI period length, typically set to 14.
rsiOverbought and rsiOversold: Levels used to filter entry signals and avoid trades when the market may be too overbought or oversold.
Moving Averages:
shortMa and longMa calculate the short and long moving averages.
Entry Conditions:
Long Condition: Enters a long position when the short MA crosses above the long MA, indicating an uptrend, and RSI is below the overbought level.
Short Condition: Enters a short position when the short MA crosses below the long MA, indicating a downtrend, and RSI is above the oversold level.
Exit Conditions:
Take Profit and Stop Loss: Optional criteria for exiting trades based on percentage gains or losses. For instance, you can take profit at 2% gain and stop at 1% loss.
Plotting:
Plots the short and long moving averages on the chart and displays the RSI with overbought/oversold levels.
How to Use
Copy the code and paste it into TradingView’s Pine Script editor.
Click “Add to Chart” to see the signals plotted on your chart.
Open the “Strategy Tester” tab to view the backtest results, including net profit, win rate, and other key metrics.
Tips for Optimization
Adjust Moving Average Periods: Test different values for shortMaLength and longMaLength to find the most profitable combination for the specific asset or timeframe.
Change Take Profit and Stop Loss Percentages: Fine-tuning these levels can significantly affect your overall profit and risk.
Add Additional Filters: Volume filters or additional indicators can be added to refine the entries.
This strategy is versatile and performs well in trending markets. You can further customize it for other indicators if needed!
MACD & Stochastic Oscillator StrategyThis script uses the MACD crossover along with a Stochastic Oscillator filter to generate buy/sell signals. The MACD is effective for identifying momentum, while the Stochastic helps confirm overbought or oversold conditions.
Buy at 1900, Sell on NDOGTesting the price from Asia Killzone to NDOG. The script will buy/sell on Asia KZ and take profit (TP) on NDOG. Test the data to see the percentage will go back to NDOG
MA 21 and MA 144 with Buy/Sell StrategyMA 21 and MA 144 with Buy/Sell Strategy. Its a combination of 2 moving average which generate the signals when they cross each other.
Trade Moments MA's + DPO + MACD StrategyExplanation of Key Components
Zero-Lag Moving Average (ZLMA): Uses an EMA-based approach to reduce lag.
EMA & SMA: Classic moving averages for trend confirmation.
DPO: Detrends the price, helping to see cyclical movement in the data.
Impulse MACD: Difference between the MACD line and signal line for momentum tracking.
Trade Logic:
Buy Signal: ZLMA crossing above SMA with a positive Impulse MACD.
Sell Signal: ZLMA crossing below EMA with a negative Impulse MACD.
This strategy provides visual buy/sell signals on the chart with customizable moving average lengths, which you can adjust as needed to optimize your trading approach.
2 dây EMA (Đường trung bình động theo cấp số mũ) với các thông số bạn đã yêu cầu. Chiến lược này sẽ thực hiện mua khi EMA 22 cắt lên EMA 250 và bán khi EMA 22 cắt xuống EMA 250, với điểm dừng lỗ (SL) được xác định dựa trên giá trung bình của 4 phiên gần nhất. Tỷ lệ R
là 1:2 và có khả năng dời SL lên tới tỷ lệ R
1:10.
only 200-40ema.....Gotta just check the resultsGoing long when the price crosses 200ema and close when the price goes below 40 ema.Just to test the outcomes.
Smart Money Concept Strategy with Labels Refined 25% BacktestingKey Enhancements Made
Refined Entry Conditions:
The script now requires both a Change of Character and a Break of Structure to confirm long or short entries. This adds an extra layer of validation.
Order Block Detection:
A function orderBlock has been added to identify potential order blocks based on recent highs and lows. This helps traders identify areas where institutional orders may have been placed.
Liquidity Checks:
The script checks if the current price is within the identified order block range before executing trades. This ensures that trades are only taken when price action aligns with institutional behavior.
Dynamic Labels:
Labels for CHoCH and BOS are dynamically generated on the chart to help visualize significant market structure changes.
Conclusion
This enhanced script integrates advanced functionalities that align with Smart Money Concepts by focusing on market structure through Break of Structure and Change of Character while utilizing Order Blocks for more precise entries. You can further refine this strategy by incorporating additional indicators or modifying parameters based on your trading style. Always conduct thorough backtesting before applying any new strategies in live trading scenarios.
VWAP Support and Rejection StrategyScript calculates vwaps that are stable during the given period (day, week, month, year). Vwap recalculates when there is a new week for example. Signals are calculated based on price movement and vwaps crossover/crossunder.
MA Crossover with RSI FilterThis script combines a short-term moving average crossover with an RSI filter to reduce false signals. A buy is triggered when the short-term MA crosses above the long-term MA, provided RSI is above a threshold (indicating an uptrend), and a sell is triggered when the crossover reverses.
Daily ORB Strategy with 5-Min Breakout15 Min daily ORB breakout strategy entry/exit and take profit or stoploss using Vwap
