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Hull Moving Average Strategy

Hull Moving Average Strategy

Beginner Daily 9/10 Popularity

A trend-following strategy using Exponential Moving Averages to identify entry and exit points. Well-suited for NSE — EMAs work reliably on both equity and F&O instruments.

Complexity
Beginner
Easy to implement
NSE Suitability
High
9.2 / 10 score
Timeframe
Daily
Short to medium term
Best For
Beginner Traders
5–20 days moves
Indicators Used
1
EMA
Win Rate (Backtest)
66.7%
Above 50% threshold
Avg Return / Trade
+0.51%
Per trade, after costs
Max Drawdown
-1.8%
Within typical range
Trades / Year
6
Small sample — interpret with caution
About the Hull Moving Average Strategy Strategy
The Hull Moving Average Strategy captures trend direction and momentum shifts by using exponential moving averages weighted toward recent price action. This approach identifies when an asset transitions between uptrends and downtrends, making it suitable for trending market conditions on NSE.

The strategy is particularly relevant for Indian equities and futures because NSE exhibits distinct intraday volatility patterns and reliable liquidity during market hours. Stocks often move in sustained trends during morning and afternoon sessions, creating consistent opportunities for trend-following entries. The strategy works across liquid large-cap and mid-cap stocks where false signals are minimized.

The setup looks for price crossovers above or below the Hull Moving Average. Buy signals trigger when price closes above the average after a period below it, while sell signals form on reversals below. On the daily timeframe, this filters out noise inherent in shorter periods while remaining responsive enough to catch meaningful directional moves before significant portions of the trend have already passed.

Traders typically combine these signals with position sizing rules and stop-loss discipline to manage risk across multiple trades. The strategy works best during trending phases rather than choppy, range-bound markets.
Who This Strategy Is For
This Beginner strategy suits Beginner Traders comfortable with a Daily timeframe and holding periods around 5–20 days. It's built for the Equity, Futures segment on NSE, so it fits traders who can check positions without needing intraday execution speed. Because it uses a small, well-known set of indicators, it's a reasonable starting point if you're new to systematic NSE trading.
Equity Curve (Backtest) HIGH QUALITY
Tested on: TITAN  ·  2024-05-13 to 2026-06-30
Total Return
+3%
CAGR
1.6%
Sharpe Ratio
1.12
Sortino Ratio
1.68
Calmar Ratio
0.89
Win Rate
66.7%
NSE Market Fit
9 OUT OF 10
Very High Fit
This strategy is well-suited for current NSE market conditions.
Win rate quality Excellent
Risk-adjusted return Excellent
Drawdown control Excellent
Trade frequency (sample size) Needs Caution
Sharpe ratio Excellent
Monthly Returns Heatmap
202420252026
Jan — — —
Feb — — —
Mar — — +0.5%
Apr — — —
May — — —
Jun — — —
Jul — -0.8% —
Aug — — —
Sep +1% +1.2% —
Oct — +1.2% —
Nov — — —
Dec -0.1% — —
Positive return Negative return
Performance vs Nifty 50
Nifty 50 comparison isn't available for this backtest period yet.
Trade Distribution
6 Total
Profitable 4 (66.7%)
Losing 2 (33.3%)
↑ Avg Win +965
↓ Avg Loss -412
★ Best Trade +1,237
▼ Worst Trade -771
Returns Distribution
Recent Backtest Results
Period Symbol Capital Total Return CAGR Max Drawdown Win Rate Trades Sharpe Ratio View
2 Years (2024–2026) TITAN ₹100,000 +3% 1.6% -1.8% 66.7% 6 1.12 View
💡 Tip: Backtest on more data to increase confidence. Our users get best results with 3+ years of backtesting. Run Extended Backtest
How It Works (Quick Overview)
1
Step 1
Identify the market context — determine if conditions are trending or ranging, and confirm the higher timeframe direction
2
Step 2
Wait for the specific entry signal defined by the strategy rules — do not enter without full confirmation
3
Step 3
Execute with pre-defined stop loss and target — manage the trade according to the exit rules without discretionary override
View Detailed Rules & Setup →

Best Market Conditions

This strategy performs best in:

HMA direction changes from red to green
Price crosses above HMA with conviction
HMA slope is steep — strong trend
Multiple timeframe HMA alignment
Volume expanding in trend direction
How This Strategy Works
1
Identify the market context — determine if conditions are trending or ranging, and confirm the higher timeframe direction
2
Wait for the specific entry signal defined by the strategy rules — do not enter without full confirmation
3
Execute with pre-defined stop loss and target — manage the trade according to the exit rules without discretionary override
Entry & Exit Rules
✓ Entry Conditions
HMA direction changes from red to green
Price crosses above HMA with conviction
HMA slope is steep — strong trend
Multiple timeframe HMA alignment
Volume expanding in trend direction
✕ Avoid When
HMA oscillating — flat slope — no clear trend
Whipsaw market — HMA flips too frequently
Low-volume stocks — HMA signal unreliable
Near major event — HMA color change may be temporary
Very short period HMA — too sensitive
Risk Management Rules
Risk Per Trade
1.0%
of total capital
Min Capital
₹25,000
Hold Period
5–20 days
Segment
Equity, Futures
Common Mistakes to Avoid
⚠️ The most common mistake with trend-following setups like this is entering too late after the move has already extended, or holding through a trend reversal because the exit signal lags price. Stick to the defined exit rules rather than holding for a 'better' price.
Full Backtest Report

Backtested on TITAN · 2024-05-13 to 2026-06-30 · Capital ₹100,000

Equity Curve

Live tracking coming soon

We're building forward-tested, paper-trade tracking for this strategy so you can see how it performs on live NSE data — not just historical backtests. Check back soon.

Sample Trade Walkthrough
GRASIM 2024-02-05 · Long
WIN
Entry ₹
₹2,148.00
Stop Loss ₹
₹2,060.00
Target ₹
₹2,324.00
Exit ₹
₹2,322.00
Grasim Industries HMA(20) flipped from red to green on Feb 5 after 14 days of declining. Price simultaneously crossed above HMA with a gap-up open on good sector news. HMA slope turned steeply upward. Entered at ₹2,148. Stop at ₹2,060 (recent swing low). Target 2:1 RR at ₹2,324. Hit in 17 sessions with consistent trend continuation.
Strategy Parameters

The exact rules and default values this strategy uses — adjust them when you run a full backtest.

ParameterDefaultMinMaxTypeDescription
hma_period 20 5 100 integer Hull Moving Average period
signal_period 9 3 30 integer Shorter HMA for signal line
atr_mult 2.0 0.5 4.0 decimal Stop = ATR × multiplier
rr 2.0 1.0 5.0 decimal Target RR
Frequently Asked Questions
The Hull Moving Average (HMA), developed by Alan Hull, uses a weighted moving average calculation with the square root of the period to significantly reduce lag while maintaining smoothness, addressing the traditional trade-off in moving averages between responsiveness and noise reduction that simpler MAs cannot achieve simultaneously.
A 20-period HMA on daily charts provides excellent balance of responsiveness and reliability for swing trading. For faster intraday signals on 15-minute charts, a 9-14 period HMA captures shorter-term trend changes more quickly, though with somewhat more noise compared to the smoother daily chart application.
Most charting platforms color the HMA line green when sloping upward and red when sloping downward (or use similar visual differentiation), providing an immediate visual trend signal. A color change from red to green, especially combined with price crossing above the HMA, signals a potential trend shift to bullish.
HMA typically generates entry signals earlier than equivalent-period EMAs due to its reduced lag construction, potentially capturing more of a trend's early move. However, this increased responsiveness can also mean slightly more false signals during choppy conditions compared to a slower, more conservative EMA approach.
Related Strategies

Looking for alternatives? Adaptive Moving Average is a similar Beginner strategy in the same Trend category, with High NSE suitability.

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Moving Average Ribbon
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9 EMA Trend Ride
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SEBI Compliance Disclaimer

MomentumIQ is an educational platform for strategy research and backtesting. We do not provide investment advice, recommendations, or tips. All backtest results are hypothetical, based on historical data, and for educational purposes only. Past performance is not indicative of future results. Backtested results may not account for brokerage, slippage, taxes, or other real-world costs. Please consult a SEBI-registered investment advisor before making any investment decisions.