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seasonal

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

6.1k|1.2k|Updated Jun 9, 2022
Search Tags:#finance#data-analysis#backtesting#ohlcv#trading-signals#seasonality#calendar-effects
One-click install
npx skills add https://github.com/charliedream1/ai_quant_trade --skill seasonal-charliedream1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seasonal
Source: https://github.com/charliedream1/ai_quant_trade/tree/main/a_%E5%85%A8%E7%BD%91%E4%BC%98%E7%A7%80%E8%B5%84%E6%BA%90/10_%E5%A4%A7%E6%A8%A1%E5%9E%8B/07_skill%E5%8C%85/vibe_trading_skills/seasonal
Command: npx skills add https://github.com/charliedream1/ai_quant_trade --skill seasonal-charliedream1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Traders can exploit time-based calendar effects by turning recurring patterns into actionable signals on OHLCV data, reducing guesswork and improving timing.

Core Features & Use Cases

  • Month-based signals derived from bullish_months and bearish_months to guide long/short/flat positioning
  • Optional Day-of-Week overlay to add confirmation or refine timing
  • Configurable, per-instrument signals suitable for backtesting or live trading workflows

Quick Start

Input your OHLCV time series with a datetime index into the Seasonal strategy to generate calendar-based 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?▼

Generate calendar-based trading signals from OHLCV data by applying configurable bullish and bearish month parameters to produce a per-instrument signal series of -1, 0, or 1 for backtesting or live workflows.

Can I use day-of-week seasonality to refine my trading backtest signals?▼

Yes, you can apply an optional day-of-week overlay to refine month-based seasonality signals by configuring bullish_weekdays and bearish_weekdays alongside your primary month effects.

What is the best way to turn monthly seasonality patterns into actionable trading positions?▼

Turn monthly seasonality patterns into actionable positions by inputting a daily OHLCV time series with a datetime index to output discrete long, short, or flat signals represented as 1, -1, or 0.

Does this seasonality signal generator work with any financial instrument?▼

Yes, the signal generator applies to any financial instrument that provides daily OHLCV data, outputting configurable calendar-based signals suitable for both backtesting and live trading generation.

How do I configure bullish and bearish months for my trading strategy?▼

Configure bullish_months and bearish_months parameters to define your long and short positioning windows, optionally adding a weekday overlay to add confirmation or refine timing accuracy.

What are the limitations of using calendar effects for backtesting trading strategies?▼

Calendar-based backtesting signals rely purely on time-based patterns in OHLCV data and do not factor in fundamental analysis, limiting effectiveness during non-recurring market events or structural regime changes.

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