ianzeng123
Overview
This is a quantitative trading strategy that combines Volume Spread Analysis (VSA), Moving Average Convergence Divergence (MACD), and Fair Value Gap (FVG) technical analysis methods. The strategy utilizes multi-dimensional technical indicators to confirm trading signals and identifies potential price imbalance areas through FVG zones, aiming to capture strong market movement opportunities. By comprehensively considering price momentum, volume anomalies, and price structure gaps, the strategy enhances trading accuracy while providing visual interfaces to improve trading judgment intuitiveness.
Strategy Principles
The core principles of this strategy are based on three independent but interconnected trading concepts:
MACD Indicator Analysis: The strategy uses parameters 12, 26, and 9 to calculate the MACD indicator. When the MACD line (fast line) is above the signal line (slow line) and has a positive value, it is identified as a bullish signal; conversely, when the MACD line is below the signal line and has a negative value, it is identified as a bearish signal. This component primarily confirms market momentum direction.
VSA (Volume Spread Analysis): The strategy detects relationships between price and volume. A bullish VSA signal is generated when the closing price is higher than the opening price, current volume exceeds the 20-day volume average, and the closing price breaks through the highest price of the previous 5 periods. Conversely, a bearish VSA signal is generated when the closing price is lower than the opening price, current volume exceeds the 20-day volume average, and the closing price breaks through the lowest price of the previous 5 periods. This component mainly captures breakout behaviors driven by large transactions.
FVG (Fair Value Gap) Identification: The strategy detects price gaps in the market. An upward FVG is identified when the current candle’s low price is higher than the high price of the candle from two periods ago, and the previous candle is bullish. A downward FVG is identified when the current candle’s high price is lower than the low price of the candle from two periods ago, and the previous candle is bearish. FVGs are viewed as imbalance areas in the market where prices typically return.
The generation of trading signals requires all three conditions to be met simultaneously: - Buy signal: Bullish VSA + Bullish MACD + Price within FVG area + No current long position - Sell signal: Bearish VSA + Bearish MACD + Price within FVG area + No current short position
The strategy also visually displays FVG areas through rectangular boxes and adds labels when trading signals are generated, enhancing the intuitiveness of trading decisions.
Strategy Advantages
Multi-dimensional Confirmation Mechanism: By combining technical indicators (MACD), volume analysis (VSA), and price structure analysis (FVG) from three independent dimensions to confirm trading signals, the strategy significantly reduces the risk of false signals and improves trading precision.
Market Imbalance Capture: The FVG component effectively identifies price imbalance areas in the market, which typically represent “value vacuums” left by institutions rapidly entering or exiting the market, providing high-probability trading opportunities.
Volume Confirmation: Through VSA analysis, the strategy ensures that there is sufficient volume supporting the trading signals, avoiding trading in low liquidity environments and reducing the risks of slippage and false breakouts.
Visual Decision Support: The strategy intuitively displays potential trading areas and entry points through FVG rectangular boxes and trading signal labels, helping traders better understand market structure and trading logic.
Prevention of Overtrading: The strategy’s multiple condition filtering mechanism ensures that trading signals are only generated when strict conditions are met, effectively reducing the problem of overtrading.
Flexible Parameter Control: The code design allows users to adjust key parameters, including MACD parameters, VSA volume thresholds and historical price reference periods, as well as the visual appearance of FVG areas, enabling the strategy to adapt to different market environments and personal trading styles.
Strategy Risks
Signal Lag: MACD is a lagging indicator that may lead to late entries in rapidly changing markets, missing optimal price points. The solution is to consider introducing more sensitive early warning indicators, such as RSI or stochastic indicators, as supplements.
False Signals During High Volatility: During periods of high market volatility, the VSA component may generate incorrect signals due to large but non-directional volume. It is recommended to add a market volatility filter that raises signal confirmation standards when volatility is abnormally high.
Limitations of FVG Identification: The current FVG identification only considers a fixed two-period interval, which may not be suitable for all market conditions. Consider dynamically adjusting the time window for FVG identification or introducing multi-timeframe FVG confirmation.
Lack of Stop Loss: The current strategy does not have an explicit stop-loss mechanism, which could lead to significant losses when trends suddenly reverse. Implementation of stop-loss strategies based on ATR or key support/resistance levels is recommended.
Insufficient Market State Adaptability: The strategy does not distinguish between trending markets and oscillating markets, potentially generating too many trading signals in unsuitable market environments. Consider adding a market state identification component to apply different trading parameters or logic in different market states.
Weak Money Management: The current strategy uses fixed position sizing for trading without considering risk adjustment. Implementation of a volatility-based position sizing mechanism is recommended to optimize capital efficiency and risk control.
Strategy Optimization Directions
Multi-timeframe Analysis Integration: The current strategy only operates within a single timeframe. Trading quality can be improved by integrating trend confirmation from higher timeframes. This can be implemented by using the security function to obtain MACD and VSA signals from higher timeframes, only entering trades when aligned with higher timeframe trends. This will reduce counter-trend trading and significantly improve win rates.
Adaptive Parameter Optimization: Replace the fixed parameters of MACD and VSA with parameters that automatically adjust based on market volatility. For example, extend MACD periods in high-volatility markets to reduce noise, and shorten periods in low-volatility markets to increase sensitivity. This optimization can be implemented by calculating recent ATR and adjusting parameters accordingly.
FVG Expiration Time Setting: Currently, once an FVG forms, it remains valid indefinitely, but in reality, FVGs should have a time limit. It is recommended to add an FVG expiration mechanism, such as making the FVG invalid after a specific number of candles or when the price moves away from the FVG area by a certain percentage. This can reduce erroneous trades based on outdated FVGs.
Integration of Order Flow Analysis: VSA analysis can be enhanced by integrating more detailed order flow data (such as large order ratios, buying/selling pressure, etc.). While this requires additional data sources, it can significantly improve the accuracy of volume analysis.
Risk Management Framework: Add a complete risk management system, including:
- Dynamic stop-loss based on ATR
- Tiered profit-taking strategy (partial position closing at different target prices)
- Position sizing calculation based on account risk percentage
- Daily loss limits and automatic reduction of trading frequency after consecutive losses
Machine Learning Optimization: Consider using simple machine learning models to predict the effectiveness of FVG areas. By training models with historical data, identify which feature combinations make FVGs more likely to be filled, thereby improving the success rate of FVG trading.
Summary
The VSA-MACD-FVG strategy is a multi-dimensional trading system that identifies high-probability trading opportunities by combining technical momentum indicators, volume analysis, and price structure analysis. The main advantages of the strategy lie in its multi-factor confirmation mechanism, which effectively filters out false signals; the main risks come from insufficient market adaptability due to fixed parameters and the absence of a risk management system.
By implementing the suggested optimization directions, especially multi-timeframe analysis, adaptive parameters, and a comprehensive risk management system, the strategy has the potential to become a more robust trading system. Most importantly, the strategy should be customized according to specific trading styles and target markets, and undergo comprehensive backtesting verification before live application.
This strategy is particularly suitable for medium to long-term traders, especially those who focus on market structure and large capital flows. With fine-tuning and supplementation of necessary risk control measures, it can maintain relatively stable performance across various market environments.
/*backtest
start: 2025-01-18 19:45:00
end: 2025-02-26 08:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"TRUMP_USDT"}]
*/
//@version=5
strategy("VSA_MACD_FVG Strategy", overlay=true)
// === MACD Calculation ===
[macdLine, signalLine, hist] = ta.macd(close, 12, 26, 9)
macdBullish = macdLine > signalLine and macdLine > 0
macdBearish = macdLine < signalLine and macdLine < 0
// === VSA Basic Implementation ===
vsaBullish = close > open and volume > ta.sma(volume, 20) and close > ta.highest(high, 5)[1]
vsaBearish = close < open and volume > ta.sma(volume, 20) and close < ta.lowest(low, 5)[1]
// === FVG (Fair Value Gap) Detection ===
fvgUpCondition = low > high[2] and close[1] > open[1]
fvgDownCondition = high < low[2] and close[1] < open[1]
var float fvgTop = 0.0
var float fvgBottom = 0.0
var bool inFVG = false
// Detect and Store FVG
if fvgUpCondition
fvgTop := low
fvgBottom := high[2]
inFVG := true
else if fvgDownCondition
fvgTop := low[2]
fvgBottom := high
inFVG := true
// Check if price is in FVG
priceInFVG = (high >= fvgBottom and low <= fvgTop)
// === Position Tracking ===
isLongOpen = strategy.position_size > 0
isShortOpen = strategy.position_size < 0
// === Trading Conditions ===
buySignal = vsaBullish and macdBullish and priceInFVG and not isLongOpen
sellSignal = vsaBearish and macdBearish and priceInFVG and not isShortOpen
// === Execute Trades ===
if buySignal
strategy.entry("Buy", strategy.long)
if sellSignal
strategy.entry("Sell", strategy.short)
// === Visual Markers ===
if buySignal
label.new(bar_index, low, "BUY",
color=color.green,
textcolor=color.white,
style=label.style_label_up)
if sellSignal
label.new(bar_index, high, "SELL",
color=color.red,
textcolor=color.white,
style=label.style_label_down)
// === Plot MACD for reference ===
plot(macdLine, "MACD", color=color.blue)
plot(signalLine, "Signal", color=color.orange)
plot(hist, "Histogram", style=plot.style_histogram, color=color.gray)