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seasonal

Generate calendar-based trading signals from OHLCV data using month and weekday patterns.

Updated Apr 19, 2026
Search Tags:#time-series#ohlcv#seasonal#trading-signals#weekday-effect#calendar-effects#month-effect
One-click install
npx skills add https://github.com/ajithkumar31082004-bit/Vibe-Trading --skill seasonal-ajithkumar31082004-bit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seasonal
Source: https://github.com/ajithkumar31082004-bit/Vibe-Trading/tree/main/Vibe-Trading-main/agent/src/skills/seasonal
Command: npx skills add https://github.com/ajithkumar31082004-bit/Vibe-Trading --skill seasonal-ajithkumar31082004-bit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Time-based calendar patterns help identify systematic trading opportunities, providing a repeatable approach to generate signals from month-of-year and day-of-week regularities in OHLCV data.

Core Features & Use Cases

  • Calendar-based signals derived from month and optional weekday effects
  • Optional weekday overlay for additional confirmation
  • Combined mode requiring both month and weekday signals for action
  • Configurable bullish/bearish months and weekdays to tailor strategies
  • Works with any OHLCV dataset to produce 1/0/-1 signals for backtesting

Quick Start

Run the Seasonal calendar signal engine on your OHLCV data to generate calendar-based trading signals.

Frequently Asked Questions about seasonal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate trading signals from calendar effects in OHLCV data?▼

To generate trading signals from calendar effects, you process OHLCV data by applying configurable bullish and bearish months, producing 1, -1, or 0 outputs for backtesting workflows.

What are calendar effects in time-series trading and how do they work?▼

Calendar effects in time-series trading are systematic month-of-year and day-of-week patterns. They produce actionable 1, 0, or -1 signals by identifying repeatable seasonal regularities in historical OHLCV data.

Can I use day-of-week patterns alongside month-of-year effects for trade confirmation?▼

Yes, you can use an optional weekday overlay alongside month-of-year patterns. A combined mode requires both the month and weekday signals to align before generating an actionable 1 or -1 trading signal.

Do I need a specific backtesting framework to use calendar-based trading signals?▼

No specific backtesting framework is required. The signal engine produces clean 1, -1, and 0 outputs from OHLCV data, ensuring clean integration with any standard backtesting workflow you choose.

What are the limitations of using seasonal patterns for backtesting strategies?▼

Seasonal pattern strategies rely strictly on historical month and weekday regularities, meaning they do not account for real-time market volatility or fundamental shifts, limiting their effectiveness in unprecedented market conditions.

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