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Analyze Command

The analyze command runs various analysis methods on stock data to identify trading opportunities, market conditions, and seasonal patterns.

Synopsis

sqa-cli analyze [OPTIONS]

Description

The analyze command provides three powerful analysis methods:

  • FPOP - Future Period of Performance analysis to identify inflection points
  • Regime - Market regime detection (bull, bear, or sideways markets)
  • Seasonal - Seasonal pattern analysis to find best/worst trading months

Options

Option Type Default Description
-t, --ticker SYMBOL String AAPL Stock ticker symbol to analyze
-m, --methods METHODS String (required) Comma-separated list of analysis methods
--fpop-periods DAYS Integer 10 Number of days for FPOP analysis
--regime-window DAYS Integer 60 Moving window size for regime detection
-v, --verbose Boolean false Show detailed output
-h, --help Boolean false Show help message

Analysis Methods

FPOP (Future Period of Performance)

Identifies potential buy and sell opportunities based on future price performance.

How it works: 1. Calculates future returns for each day 2. Identifies inflection points (local minima/maxima) 3. Highlights potential entry/exit points

Use cases: - Finding optimal entry points - Identifying sell signals - Backtesting strategy development

Example output: 

FPOP Analysis (10-day periods):
  Found 15 inflection points
  Buy opportunities: 8
  Sell opportunities: 7
  Average gain potential: 5.2%

Regime Detection

Determines the current market regime to adjust trading strategy.

Market Regimes: - Bull Market: Sustained upward trend - Bear Market: Sustained downward trend - Sideways: Range-bound, no clear trend

How it works: 1. Calculates moving averages over specified window 2. Analyzes price momentum and volatility 3. Classifies current regime

Use cases: - Strategy selection (trend-following vs. mean-reversion) - Risk management - Position sizing

Example output: 

Market Regime Analysis:
  Current Regime: BULL
  Confidence: 87%
  Duration: 45 days
  Trend Strength: Strong

Seasonal Analysis

Analyzes historical patterns to find seasonally strong/weak months.

How it works: 1. Groups returns by month across all years 2. Calculates average monthly performance 3. Identifies best and worst months

Use cases: - Timing entries/exits - Portfolio rebalancing - Calendar-based strategies

Example output: 

Seasonal Pattern Analysis:
  Best Month: November (avg return: +3.2%)
  Worst Month: September (avg return: -1.8%)

  Monthly Returns:
    Jan: +1.2%
    Feb: +0.8%
    Mar: +1.5%
    ...

Examples

Run All Analyses

sqa-cli analyze --ticker AAPL --methods all

Runs FPOP, regime detection, and seasonal analysis on AAPL.

Run Specific Methods

sqa-cli analyze --ticker MSFT --methods fpop,regime

Runs only FPOP and regime detection on MSFT.

Single Method Analysis

sqa-cli analyze --ticker GOOGL --methods seasonal

Runs only seasonal analysis on GOOGL.

Custom FPOP Periods

sqa-cli analyze --ticker TSLA --methods fpop --fpop-periods 15

Uses 15-day periods instead of default 10 days for FPOP analysis.

Custom Regime Window

sqa-cli analyze --ticker AAPL --methods regime --regime-window 90

Uses 90-day moving window for regime detection (default is 60).

Verbose Output

sqa-cli analyze --ticker AAPL --methods all --verbose

Shows detailed processing information and intermediate results.

Common Workflows

Initial Stock Evaluation

When first evaluating a stock:

# Get comprehensive analysis
sqa-cli analyze --ticker AAPL --methods all --verbose

# Review all three perspectives:
# 1. FPOP for entry/exit points
# 2. Regime for current market condition
# 3. Seasonal for timing considerations

Strategy Development

When developing a trading strategy:

# Identify inflection points
sqa-cli analyze --ticker AAPL --methods fpop --fpop-periods 10

# Then use pattern discovery to find rules
sqa-cli pattern --ticker AAPL --min-gain 10

Market Timing

For timing entries:

# Check current regime
sqa-cli analyze --ticker AAPL --methods regime

# Check if current month is favorable
sqa-cli analyze --ticker AAPL --methods seasonal

Tips and Best Practices

FPOP Analysis

  • Short periods (5-10 days): Better for day trading and swing trading
  • Medium periods (10-20 days): Good for position trading
  • Long periods (20+ days): Suitable for long-term investing

Regime Detection

  • Shorter windows (30-60 days): More sensitive to recent changes
  • Longer windows (60-120 days): More stable, fewer false signals
  • Very long windows (120+ days): Captures major market cycles

Seasonal Analysis

  • Requires at least 2-3 years of data for reliability
  • More reliable for large-cap stocks with consistent patterns
  • Consider combining with fundamental analysis
  • Don't rely solely on seasonal patterns

Output Interpretation

FPOP Results

  • Inflection Points: Days where future returns change direction
  • Buy Opportunities: Points where prices are likely to rise
  • Sell Opportunities: Points where prices are likely to fall
  • Gain Potential: Average expected gain from identified opportunities

Regime Results

  • Current Regime: Bull, Bear, or Sideways
  • Confidence: How certain the classification is (0-100%)
  • Duration: How long the regime has persisted
  • Trend Strength: Weak, Moderate, or Strong

Seasonal Results

  • Best/Worst Months: Historically strongest/weakest performance
  • Monthly Averages: Mean return for each month
  • Consistency: How reliable the pattern is

Limitations

  • Past performance doesn't guarantee future results
  • Small sample sizes can lead to unreliable patterns
  • Market conditions change - historical patterns may not repeat
  • Sample data in this project is synthetic - use real data for actual trading
  • backtest - Test strategies based on analysis results
  • pattern - Discover trading patterns around inflection points
  • genetic - Optimize strategy parameters

See Also