Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
7 documents
This document describes data structures for tracking option contracts, underlying instruments, and option chains in a portfolio. It updates positions from trades and holdings, derives mid prices from top of book quotes, and connects options with pricing…
The document describes an options volatility trading module built around live pricing, portfolio risk tracking, and execution. It outlines three pricing models for different exercise styles and underlyings, with routines to calculate theoretical prices and…
The document describes a graphical workflow for downloading historical bars, configuring a CTA strategy backtest, reviewing performance statistics, and inspecting trades on a candlestick chart. Data can come from a domestic market data service, an…
The document describes two portfolio analytics displays. The volatility chart plots call and put mid-implied volatilities against strike, alongside a pricing implied-volatility curve, and allows individual option chains to be shown or hidden. Curve data is…
The strategy compares a synthetic futures price, calculated from a call price minus a put price plus the strike, with the traded futures price. It measures the difference and opens a three-leg position when the spread crosses a configurable entry level: one…
The document explains a graphical workflow for maintaining historical market data. Users can download data from connected market data services or trading interfaces, import CSV files, inspect stored records, export selected ranges, and delete contract data.…
This option algorithm combines reference-price calculation with a two-sided quoting and opportunistic execution rule. It sets a minimum price spread and a volatility-based spread proportional to the option’s cash vega, then uses the larger value to place bid…