v2.3.0

Highlights (since v2.2.x)

• Trade Simulator — chronological simulation with capital tracking, position limits, and equity curves
• Portfolio Simulation — weighted multi-strategy backtesting via simulate_portfolio()
• Early Exits — stop-loss, take-profit, and max-hold-days rules
• 80+ Entry Signals — RSI, MACD, Bollinger Bands, EMA, ATR, IV Rank, and more
• Custom Signals — drive entries from any DataFrame with a boolean flag column
• Risk Metrics — Sharpe, Sortino, VaR, CVaR, Calmar, Omega, tail ratio
• Slippage Modeling — mid, spread, liquidity-based, or per-leg slippage
• Commissions — per-contract, base fee, and min fee structures
• Data CLI — optopsy-data for downloading and caching market data
• Plugin System — extend with custom strategies, signals, and data providers

v2.3.0b5

What's New

underlying_price is now optional

• csv_data() no longer requires an underlying_price column — only underlying_symbol, option_type, expiration, quote_date, strike, bid, ask, and delta are needed
• TA-based signals (RSI, Bollinger, MACD, etc.) now require a close column in stock data rather than falling back to underlying_price
• apply_signal() auto-merges Yahoo Finance stock prices when the options data lacks a price column, so IV rank and other price-based signals work out of the box

Standalone data CLI (optopsy-data)

• New optopsy-data CLI for downloading and caching historical options data
• optopsy-data symbols command to list available symbols [EODHD only]
• optopsy-data download SPY -s flag to download stock prices alongside options
• optopsy-data cache subcommand for cache management (size, clear)

Revamped sample files

• Replaced 12 repetitive examples with 5 progressive samples covering the full API: basic strategies, signal composition, simulation with risk management, portfolio backtesting, and strategy comparison

Documentation

• New MkDocs documentation site with auto-deploy on push
• Updated docs to reflect the optional underlying_price architecture

v2.3.0b4

What's New

New Strategies

• 10 retail-friendly strategies — cash-secured put, collar, covered call, protective put, and more are now first-class strategies (#207)

Core Engine

• Per-leg delta targeting — select strikes by delta with target, min, max per leg (#179)
• P&L-based early exits — stop-loss and take-profit rules for automatic position management (#190)
• Max hold days — max_hold_days parameter for time-based early exits (#201)
• Commission modeling — per-contract, base fee, and min fee structures (#188)
• Per-leg slippage — configure slippage independently for each leg (#203)
• Portfolio simulation — weighted multi-strategy, multi-symbol portfolio backtesting via simulate_portfolio() (#202)
• Actual stock data for covered strategies — covered calls and protective puts now use real stock prices via yfinance (#183)
• Stock exit date alignment — stock exit dates now align with actual option exit quote dates (#199)
• 80+ entry signals — expanded to support all pandas-ta-classic indicators (#189)
• Migrated to pandas-ta-classic — replaced unmaintained pandas-ta fork (#184)

AI Chat UI

• Delta targeting, early exits, and commissions in agent tools — the chat agent can now use all new core features (#206)
• Collapsed tool steps — tool call details are grouped into a single dropdown for cleaner chat history (#208)
• Session summarizer — summarize_session tool for recapping analysis sessions (#204)
• Pluggable auth — extend authentication via optopsy.auth entry points (#178)
• UI theming — brand colors, favicon, and dark mode support (#177)

Bug Fixes

• Fix single-leg pct_change sign calculation (#185)
• Apply slippage model to stock-backed covered strategies (#200)

Docs & README

• Updated documentation for all new features
• Reorganized README with Installation section moved below Features

v2.3.0b3

New Features

• Entry-point-based plugin system — third-party packages can register custom strategies, data providers, and tools via entry_points (#175)
• Global result store with content-hashed caching and a query_results tool for the chat agent (#163)
• custom_signal() — new public API for arbitrary DataFrame-based entry/exit signals (#166)
• Multi-series charting support in the create_chart tool (#161)
• Chainlit UI improvements — conversation starters, settings panel, action buttons, rich elements (#160)
• Plotly chart persistence across session resume (#156)
• Risk metrics module — Sharpe, Sortino, VaR, CVaR, and more (#113)
• IV rank signals and volatility surface tools (#129)
• Compare results tool for side-by-side strategy comparison (#115)
• Data quality check tool with strategy-aware mode (#140)

Bug Fixes

• Fix Interval column serialization error in ResultStore Parquet writes
• Fix orphaned tool_result blocks causing API errors on session resume (#148)
• Fix spurious yfinance re-fetches from interior gap detection (#147)
• Fix NaN propagation in liquidity slippage model when volume is null
• Prevent agent from duplicating results or proactively creating charts
• CSV download is now on-demand via action button
• Fix Interval column rendering and DataFrame resume errors

v2.3.0b2

New Features

• Lightweight backtest simulation layer (#105) — simulate strategy performance over historical data
• Plotly chart tool (#106) — create_chart agent tool for interactive visualizations
• Pydantic tool argument validation (#107) — structured validation for all agent tool inputs

v2.3.0b1

What's New

Beta release introducing the AI-powered chat UI for interactive options backtesting.

New Features

• AI Chat Interface (optopsy-chat) — Chainlit + LiteLLM powered conversational backtesting
• EODHD Data Provider — Live options chain and stock price data with smart caching
• Pluggable Provider System — Extensible architecture for adding new data sources

Improvements

• Replaced Black with Ruff for formatting and linting
• Added mypy, pytest-cov, and vulture to CI
• Updated README badges

Install

pip install optopsy==2.3.0b1        # core only
pip install optopsy[ui]==2.3.0b1    # with chat UI

v2.2.0

New Features

• Calendar and diagonal spread strategies
• Tiered slippage modeling (mid, spread, liquidity modes)
• Greeks support with delta filtering and grouping

Version 2.1.0

New Features

10 New Options Strategies

• Butterfly Strategies (3-leg)

  • Long/Short Call Butterfly
  • Long/Short Put Butterfly

• Iron Condor & Iron Butterfly (4-leg)

  • Iron Condor / Reverse Iron Condor
  • Iron Butterfly / Reverse Iron Butterfly

• Covered Strategies (synthetic)

  • Covered Call
  • Protective Put

Version 2.0.3

This release contains the following updates:

• Improve typing and documentation throughout the codebase

Version 2.0.2

This release updates the dependency requirements to support modern Python and pandas versions:

• Updated pandas requirement to >=2.0.0
• Updated numpy requirement to >=1.26.0
• Updated pytest requirement to >=7.0.0
• Added version attribute to package for programmatic version access
• Exported version in all for public API access

This is a maintenance release that modernizes dependencies while maintaining backward compatibility with the existing API.