strato Strategy Analysis

Strategy Number: #26 (26th of 465 strategies)
Strategy Type: Stochastic RSI Momentum
Timeframe: 1 minute (1m)

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I. Strategy Overview

strato is a momentum strategy based on Stochastic RSI. The strategy uses Stochastic RSI (StochRSI) to capture short-term overbought/oversold opportunities, combined with K and D line crossovers to generate buy/sell signals. Key features are extremely short timeframe (1 minute) and quick turnover.

Core Features

Feature	Description
Entry Conditions	1 condition: StochRSI K < 18 + K >= D
Exit Conditions	1 condition: StochRSI K > 80 + D >= K
Protection	Hard stoploss
Timeframe	1 minute
Dependencies	TA-Lib, technical
Special Features	Ultra short-term trading

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II. Strategy Configuration Analysis

2.1 Base Risk Parameters

# ROI exit table
minimal_roi = {
    "0": 0.012    # Immediate exit: 1.2% profit
}

# Stoploss setting
stoploss = -0.1  # -10% hard stoploss

Design Logic:

• Low ROI: 1.2% ROI, pursuing quick turnover
• Standard Stoploss: -10% hard stoploss

2.2 Order Type Configuration

order_types = {
    "entry": "market",
    "exit": "market",
    "stoploss": "market",
    "stoploss_on_exchange": False,
}

order_time_in_force = {
    "entry": "GTC",
    "exit": "GTC",
}

Description: Uses market orders to ensure quick execution.

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III. Entry Conditions Explained

3.1 Entry Logic

# Entry conditions
dataframe.loc[
    (
        (dataframe["k"] < 18) &           # StochRSI K < 18 (oversold)
        (dataframe["k"] >= dataframe["d"])  # K >= D (golden cross confirmation)
    ),
    "enter_long",
] = 1

Logic Analysis:

• StochRSI Oversold: K < 18, confirming short-term oversold
• K Line Confirmation: K >= D, confirming momentum strengthening

3.2 Indicator Calculation

# RSI
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)

# Stochastic RSI
p = 14  # RSI period
d = 3   # D line period
k = 3   # K line period

srsi = (dataframe["rsi"] - dataframe["rsi"].rolling(p).min()) / (
    dataframe["rsi"].rolling(p).max() - dataframe["rsi"].rolling(p).min()
)
dataframe["k"] = srsi.rolling(k).mean() * 100
dataframe["d"] = dataframe["k"].rolling(d).mean()

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IV. Exit Logic Explained

4.1 Exit Conditions

# Exit conditions
dataframe.loc[
    (
        (dataframe["k"] > 80) &           # StochRSI K > 80 (overbought)
        (dataframe["d"] >= dataframe["k"])  # D >= K (death cross confirmation)
    ),
    "exit_long",
] = 1

Logic Analysis:

• StochRSI Overbought: K > 80, confirming short-term overbought
• D Line Confirmation: D >= K, confirming momentum weakening

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V. Technical Indicator System

5.1 Core Indicators

Indicator Category	Specific Indicator	Parameters	Purpose
Momentum	RSI	14 periods	Base momentum
Momentum	Stochastic RSI	14/3/3	Overbought/Oversold

5.2 Stochastic RSI Calculation

# SRSI = (RSI - RSI_min) / (RSI_max - RSI_min)
srsi = (rsi - rsi.rolling(14).min()) / (rsi.rolling(14).max() - rsi.rolling(14).min())

# K line = 3-period moving average of SRSI × 100
k = srsi.rolling(3).mean() * 100

# D line = 3-period moving average of K line
d = k.rolling(3).mean()

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VI. Risk Management Features

6.1 Hard Stoploss

stoploss = -0.1  # -10%

Description: Standard stoploss, controlling single trade loss within 10%.

6.2 Low ROI Quick Exit

minimal_roi = {"0": 0.012}  # 1.2%

Purpose:

• Exit at 1.2% profit
• With 1-minute timeframe for quick turnover

6.3 Market Orders

order_types = {
    "entry": "market",
    "exit": "market",
    "stoploss": "market",
}

Purpose: Ensures quick execution, suitable for 1-minute ultra short-term trading.

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VII. Strategy Pros & Cons

✅ Advantages

1. Simple Logic: StochRSI golden/death cross, easy to understand
2. Low Computation: Few indicators, low hardware requirements
3. Low ROI: 1.2% ROI, quick turnover
4. Market Orders: Ensures quick execution
5. High Learning Value: Suitable for learning StochRSI strategies

⚠️ Limitations

1. 1-Minute Timeframe: Signals extremely fast, needs low latency execution
2. No Trend Filter: No long-term trend judgment
3. No BTC Correlation: Does not detect Bitcoin market trend
4. Fee Sensitive: 1-minute trading is frequent, fees significantly impact profits
5. Many False Signals: 1-minute level has many false signals

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VIII. Applicable Scenarios

Market Environment	Recommended Configuration	Description
Ranging Market	Default configuration	StochRSI most suitable for ranging markets
Uptrend	Default configuration	Low ROI enables quick turnover
Downtrend	Pause	No trend filter, easy to lose
High Volatility	Adjust stoploss	May need to adjust stoploss threshold
Low Volatility	Adjust ROI	Lower ROI threshold for small moves

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IX. Summary

strato is a simple StochRSI momentum strategy, its core value lies in:

1. Simple Logic: StochRSI golden/death cross, easy to understand
2. Low Computation: Few indicators, low hardware requirements
3. Low ROI: 1.2% ROI, quick turnover
4. Market Orders: Ensures quick execution
5. High Learning Value: Suitable for learning StochRSI strategies

For quantitative traders, this is an excellent ultra short-term learning template. Recommendations:

• Use as an introductory case for learning StochRSI strategies
• Understand 1-minute trading risks
• Can add trend filters, BTC correlation, etc. on this basis
• Note fee impact, testthoroughly before live trading

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