Trading Strategies Overview

Introduction to weekly trading concepts and strategy patterns for TradePsykl.

Documentation Structure

• Strategy Template - Standardized format for documenting strategies
• Stock Selection - Selection criteria and sector rotation analysis
• Tools & Screeners - Screener setup and analysis platforms
• Data Sources - APIs for price data, earnings, and fundamentals
• This document - Weekly trading concepts and strategy types

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What Is Weekly Trading?

Weekly trading makes decisions based on weekly price charts rather than daily or intraday timeframes. This approach:

• Trades less frequently, focusing on broader market movements
• Filters out short-term noise and volatility
• Suits part-time traders with limited screen time
• Typically holds positions for days to weeks

Weekly Trading vs. Day Trading

Feature	Weekly Trading	Day Trading
Holding Period	Days to weeks	Minutes to hours
Frequency	Few trades per week	Multiple trades daily
Volatility Focus	Filters short-term noise	Exploits intraday volatility
Screen Time	Minimal (weekend analysis)	Full trading day
Transaction Costs	Lower (fewer trades)	Higher (frequent trading)

Weekly Trading vs. Swing Trading

Feature	Weekly Trading	Swing Trading
Timeframe	Weekly charts	Daily charts
Holding Period	1-4 weeks	2-10 days
Analysis Style	Longer-term trends	Short-medium price swings
Volatility Exposure	Less sensitive to daily moves	More exposed to daily volatility
Adaptability	Slower position adjustments	Quicker reaction to changes

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Strategy Categories

Trend-Following Strategies

Moving Average Crossover

• Buy: Short-term MA crosses above long-term MA (e.g., 10-week over 50-week)
• Sell: Reverse crossover occurs
• Best for: Bull markets with sustained trends

Breakout Strategy

• Buy: Price breaks above recent high (e.g., 4-week high)
• Exit: Trailing stop-loss or breakdown
• Best for: Bull markets with strong momentum

Momentum Strategy

• Rank stocks by 4-week or 12-week momentum
• Buy top performers, rebalance weekly/monthly
• Best for: Trending markets with broad strength

Mean Reversion Strategies

RSI Reversion

• Buy: RSI < 30 (oversold)
• Sell: RSI > 70 (overbought)
• Best for: Range-bound or bear markets

Bollinger Band Bounce

• Buy: Price touches lower band + RSI oversold
• Exit: Mean or upper band
• Best for: Range-bound markets

Quantitative Strategies

Dual Momentum

• Combine relative momentum (vs. other assets) + absolute momentum (vs. history)
• Rotate into strongest assets weekly
• Best for: Bull markets

Value + Momentum Hybrid

• Screen undervalued stocks with strong weekly momentum
• Hold 4-12 weeks
• Best for: All market conditions

Event-Driven Strategies

Earnings Drift

• Buy stocks with strong post-earnings moves
• Hold 1-4 weeks
• Requires: Real-time earnings data

Sector Rotation

• Rank sectors by weekly performance
• Invest in top 2-3 via ETFs
• Adaptable: Shift to defensive sectors in bear markets

Volatility Compression

• Buy when weekly volatility drops below threshold
• Anticipate breakout, ride trend
• Best for: Uncertain/choppy markets

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Market Regime Considerations

Bull Market Strategies - Work best when markets trend upward

• Moving Average Crossover
• Breakout Strategy
• Momentum Strategy
• Dual Momentum

Bear/Sideways Market Strategies - Work best in range-bound conditions

• RSI Reversion
• Bollinger Band Bounce
• Volatility Compression

All-Weather Strategies - Adapt to changing conditions

• Sector Rotation (shift defensive in bear markets)
• Value + Momentum Hybrid (balance fundamentals + technicals)

Using Market Regime Filters

Improve performance by detecting market conditions:

• Calculate SPY position relative to 40-week or 200-day MA
• Bull regime: Price > 1% above MA → activate trend-following
• Bear regime: Price > 1% below MA → switch to mean-reversion
• Neutral: Price within ±1% → use defensive strategies

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Strategy Type Comparison

Rule-Based vs. Event-Driven

Rule-Based Strategies

• Follow predefined, deterministic rules
• Based on technical indicators, price patterns, math conditions
• Examples: RSI crossover, MA crossover, 4-week breakout

Pros:

• Easy to backtest and automate
• Transparent and explainable
• Ideal for systematic trading

Cons:

• Can be rigid in changing markets
• May miss macro context or news events

Event-Driven Strategies

• React to external events (earnings, economic reports, news)
• Examples: Earnings surprise, FDA announcements, rate decisions

Pros:

• Capture high-impact moves
• Adaptable to real-world catalysts
• Used in hedge funds and quant setups

Cons:

• Harder to automate and backtest
• Requires real-time data and NLP
• Can be noisy or unpredictable

Hybrid Approach: Use rules to filter candidates, events to trigger trades

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Example Strategy: Weekly Pivot

See Strategy Template for how to document complete strategies.

Quick Overview:

• Type: Rule-based, trend-following
• Logic: Trade weekly pivot points calculated from previous week's high/low/close
• Entry: Price crosses pivot levels with confirmation
• Risk: Stop-loss and take-profit rules
• ML Features: Price relative to pivot, volatility, volume