HansenSmaOffsetV1 Strategy: In-Depth Analysis

Strategy ID: #195 (195th of 465 strategies) Strategy Type: Range Breakout Timeframe: 15 Minutes (15m)

I. Strategy Overview

HansenSmaOffsetV1 is a range breakout strategy based on SMA offset bands. The strategy constructs a price channel by calculating upper and lower offsets of a Simple Moving Average, buying when price touches the lower band and selling when it touches the upper band, capturing rebound and pullback opportunities in range-bound markets.

Core Features

Feature	Description
Entry Conditions	1 buy signal, based on lower band breakout and green candle confirmation
Exit Conditions	1 sell signal, based on upper band breakout and red candle confirmation
Protections	Hard stop-loss -10%, tiered ROI take-profit
Timeframe	15 Minutes
Dependencies	TA-Lib, qtpylib, numpy

II. Strategy Configuration Analysis

2.1 Core Risk Parameters

# ROI Exit Table
minimal_roi = {
    "0": 0.10,   # Immediate exit: 10% profit
    "30": 0.05,  # After 30 minutes: 5% profit
    "60": 0.02,  # After 60 minutes: 2% profit
}

# Stop-Loss Settings
stoploss = -0.10  # Hard stop-loss -10%

Design Philosophy:

Aggressive Take-Profit: Immediate exit set at 10%, pursuing quick profits
Time Decay: Longer holding time means lower take-profit threshold, reducing holding risk
Symmetrical Stop-Loss: -10% stop-loss and 10% immediate take-profit form a symmetrical risk-reward ratio

2.2 Order Type Configuration

The strategy uses default order type configuration with no special settings.

III. Entry Conditions Details

3.1 Entry Signal Logic

The strategy has only one entry signal, with simple logic:

# Entry signal: lower band breakout + green candle confirmation
dataframe.loc[
    (
        (dataframe['high'] < dataframe['smad1']) &    # High below lower band
        (dataframe['hopen'] < dataframe['hclose'])     # Heikin-Ashi green candle
    ),
    'buy'] = 1

3.2 Condition Analysis

Condition	Technical Meaning	Market Logic
`high < smad1`	Candle high below SMA lower band	Price breaks below support, touching range bottom
`hopen < hclose`	Heikin-Ashi green candle	Short-term momentum turning strong, rebound signal confirmed

3.3 Entry Condition Classification

Condition Type	Core Logic	Signal #
Range Reversal	Lower band breakout + green candle confirmed	Condition #1

IV. Exit Logic Details

4.1 Exit Signal Logic

The strategy has only one exit signal:

# Exit signal: upper band breakout + red candle confirmation
dataframe.loc[
    (
        (dataframe['low'] > dataframe['smau1']) &      # Low above upper band
        (dataframe['hopen'] > dataframe['hclose'])     # Heikin-Ashi red candle
    ),
    'sell'] = 1

4.2 Condition Analysis

Condition	Technical Meaning	Market Logic
`low > smau1`	Candle low above SMA upper band	Price breaks above resistance, touching range top
`hopen > hclose`	Heikin-Ashi red candle	Short-term momentum turning weak, pullback signal confirmed

4.3 Exit Condition Classification

Condition Type	Core Logic	Signal #
Range Reversal	Upper band breakout + red candle confirmed	Condition #1

V. Technical Indicator System

5.1 Core Indicators

The strategy uses two types of technical indicators: SMA offset bands and Heikin-Ashi smoothed price.

Indicator Category	Specific Indicator	Calculation	Purpose
Trend Indicator	SMA Offset Upper Band	SMA(20) × 1.05	Resistance identification
Trend Indicator	SMA Offset Lower Band	SMA(20) × 0.95	Support identification
Smoothed Indicator	Heikin-Ashi Close	(O+H+L+C) / 4	Price smoothing
Smoothed Indicator	Heikin-Ashi Open	(prev 2 O+C) / 2	Trend confirmation
Auxiliary Indicator	HA Close MA	SMA(hclose, 6)	Short-term trend
Auxiliary Indicator	HA Open MA	SMA(hopen, 6)	Short-term trend

5.2 SMA Offset Band Explained

SMA offset bands are the core indicators of this strategy. Construction method:

# Upper band: SMA(20) + 5%
dataframe['smau1'] = ta.SMA(dataframe['close'], timeperiod=20) * 1.05

# Lower band: SMA(20) - 5%
dataframe['smad1'] = ta.SMA(dataframe['close'], timeperiod=20) * 0.95

Design Features:

Fixed offset of ±5%, constructing a channel approximately 10% wide
Channel adjusts dynamically to market volatility
Upper band as resistance, lower band as support

5.3 Heikin-Ashi Smoothed Price

The strategy uses a simplified Heikin-Ashi price for trend confirmation:

# HA Close: average of four prices
dataframe['hclose'] = (dataframe['open'] + dataframe['high'] + 
                       dataframe['low'] + dataframe['close']) / 4

# HA Open: average of previous 2 candles' open and close
dataframe['hopen'] = ((dataframe['open'].shift(2) + 
                       dataframe['close'].shift(2)) / 2)

# HA High: max of three prices
dataframe['hhigh'] = dataframe[['open', 'close', 'high']].max(axis=1)

# HA Low: min of three prices
dataframe['hlow'] = dataframe[['open', 'close', 'low']].min(axis=1)

Design Features:

Smooths price noise, filters false signals
Green candle (hopen < hclose) indicates uptrend
Red candle (hopen > hclose) indicates downtrend

VI. Risk Management Highlights

6.1 Tiered Take-Profit Mechanism

The strategy uses a time-decaying ROI take-profit mechanism:

Holding Time	Take-Profit Threshold	Risk Appetite
Immediate exit	10%	Aggressive
After 30 minutes	5%	Moderate
After 60 minutes	2%	Conservative

Design Philosophy:

Longer holding time means greater risk exposure
Lowering take-profit threshold locks in existing profits
Avoids uncertainty of prolonged holding

6.2 Hard Stop-Loss Protection

stoploss = -0.10  # 10% fixed stop-loss

Features:

Forms 1:1 risk-reward ratio with immediate take-profit
Maximum single-trade loss controlled at 10%
No trailing stop; simple and direct execution

6.3 Signal Filtering Mechanism

The strategy filters false signals through dual conditions:

Filter Layer	Function	Effect
Band Breakout	Price must exceed channel boundary	Excludes in-channel oscillation
Candle Pattern	HA green/red candle confirmation	Excludes false breakouts

VII. Strategy Pros & Cons

Strengths

Simple Logic: Entry and exit rules are clear, easy to understand and maintain
Few Parameters: Only depends on SMA period and offset ratio; low overfitting risk
Range Adaptation: Performs well in ranging markets, captures rebounds and pullbacks
Computationally Efficient: Simple indicator calculations, low resource consumption

Weaknesses

Weak in Trend Markets: Will frequently trade counter-trend in unilateral trends
False Signal Risk: No trend direction filter; may frequently get stopped out in ranging markets
Fixed Offset: 5% offset doesn't adapt to all market volatility environments
No Volume Confirmation: Lacks volume verification; signal reliability limited

VIII. Applicable Scenarios

Market Environment	Recommendation	Notes
Range-bound	Suitable	Core matching scenario; strategy's original design intent
Sideways Consolidation	Suitable	Upper and lower bands trigger frequently; capture ranging gains
Unilateral Trend	Use with Caution	Frequent counter-trend trades; need to adjust offset or pause
High Volatility	Use with Caution	Fixed 5% offset may be too narrow; need to widen channel

IX. Applicable Market Environment Analysis

HansenSmaOffsetV1 is a typical range trading strategy. Based on its code architecture and logic, it is best suited for ranging sideways markets, and performs poorly during unilateral trend markets.

9.1 Strategy Core Logic

Mean Reversion Philosophy: Price tends to revert after deviating from moving average
Channel Trading Mode: Classic range strategy of buy at lower band, sell at upper band
Trend Confirmation Filter: HA candle patterns provide short-term momentum verification

9.2 Performance in Different Market Environments

Market Type	Rating	Analysis
Slow Bull Trend	⭐⭐☆☆☆	After buying at lower band, price continues rising but exits too early at upper band
Ranging Sideways	⭐⭐⭐⭐⭐	Core matching scenario; bands trigger frequently; stable returns
Downtrend	⭐⭐☆☆☆	After buying at lower band, price continues falling; frequent stop-loss triggers
High Volatility	⭐⭐⭐☆☆	Fixed channel width may generate many false signals

9.3 Key Configuration Recommendations

Config Item	Suggested Value	Notes
SMA Period	20	Default; balances sensitivity and stability
Offset Ratio	5%	Default; can adjust for high-volatility markets
Stop-Loss Ratio	-10%	Symmetrical with immediate take-profit
Number of Pairs	15	Author's suggested holding number
Stake Mode	unlimited	Author's suggested capital management mode

X. Important Notes: Strategy Usage Considerations

10.1 Market Identification

Before using this strategy, determine whether the market is in a ranging state:

Ranging Signal: Price repeatedly crosses within the SMA channel
Trend Signal: Price continuously runs on one side of the channel
Recommendation: In trend markets, consider pausing the strategy or widening the offset

10.2 Parameter Optimization Space

Parameter	Default	Optimization Direction
SMA Period	20	Can adjust 15-30 based on market characteristics
Offset Ratio	5%	Can widen to 7-10% in high-volatility markets
Stop-Loss Ratio	-10%	Adjust based on risk appetite

10.3 Signal Confirmation Suggestions

The strategy lacks volume confirmation; recommended to combine with:

Volume surge to confirm breakout validity
RSI or MACD to assist in judging overbought/oversold
Multi-timeframe confirmation of trend direction

10.4 Backtesting vs. Live Trading Differences

Range strategies may perform excellently in backtesting, but in live trading:

Slippage may erode profits
High trade frequency means significant fee impact
When ranging transitions to trend, may suffer consecutive losses

XI. Summary

HansenSmaOffsetV1 is a simply designed, clearly logical range breakout strategy. Its core value lies in:

Simple and Effective: SMA offset bands construct channel; HA candles confirm signals; rules transparent and easy to execute
Range Adaptation: Specifically designed for ranging markets; captures mean reversion opportunities
Easy to Understand: Few parameters; beginner-friendly; easy to understand and optimize

For quantitative traders, this strategy is a good starting point for learning range trading logic. However, use cautiously or combine with trend filters in trend markets. It is recommended to adjust the offset based on target market volatility characteristics and add volume or trend direction filters to improve signal quality.

I. Strategy Overview​

Core Features​

II. Strategy Configuration Analysis​

2.1 Core Risk Parameters​

2.2 Order Type Configuration​

III. Entry Conditions Details​

3.1 Entry Signal Logic​

3.2 Condition Analysis​

3.3 Entry Condition Classification​

IV. Exit Logic Details​

4.1 Exit Signal Logic​

4.2 Condition Analysis​

4.3 Exit Condition Classification​

V. Technical Indicator System​

5.1 Core Indicators​

5.2 SMA Offset Band Explained​

5.3 Heikin-Ashi Smoothed Price​

VI. Risk Management Highlights​

6.1 Tiered Take-Profit Mechanism​

6.2 Hard Stop-Loss Protection​

6.3 Signal Filtering Mechanism​

VII. Strategy Pros & Cons​

Strengths​

Weaknesses​

VIII. Applicable Scenarios​

IX. Applicable Market Environment Analysis​

9.1 Strategy Core Logic​

9.2 Performance in Different Market Environments​

9.3 Key Configuration Recommendations​

X. Important Notes: Strategy Usage Considerations​

10.1 Market Identification​

10.2 Parameter Optimization Space​

10.3 Signal Confirmation Suggestions​

10.4 Backtesting vs. Live Trading Differences​

XI. Summary​