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Volatility trading using Long and Short Straddle options strategies on Interactive Broker using Yahoo Finance and TWS API
| Date | Stars |
|---|---|
| 2026-07-24 | 363 |
| 2026-07-25 | 363 |
| 2026-07-28 | 363 |
| 2026-07-30 | 363 |
| 2026-08-06 | 363 |
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# Interactive Brokers: Volatility trading with options [](https://github.com/mcf-long-short/ibkr-options-volatility-trading/actions/workflows/python-package.yaml) ## Introduction `Volatility trading` using `equity options` and `long/short straddle` option strategies combined with a `momentum strategy` to profit from a high/low volatility on a daily level in the US equities. For testing that strategy Interactive Brokers Trader Workstation was used with paper trading account. In order to quickly react on the market moves, simple `market watcher`/`trading bot` was implemented. `MarketWatcher bot` uses data from [Yahoo Finance](https://github.com/JECSand/yahoofinancials) and [Python TWS API](https://tradersacademy.online/trading-courses/python-tws-api). This repository represents group project work for implementing option trading strategies (course in Financial Derivatives for advanced degree [Masters in Computational Finance, Union University](http://mcf.raf.edu.rs/)). ## Trading strategy Our trading strategy is based on `volatility trading`. To exploit and profit from both the high and low volatility, we day traded - getting in and out of the positions in the same trading session. Some positions were held overnight as well. In order to profit on a high or low volatility in the equities we traded `options` using `long straddle` and `short stradle` strategy respectively. For intuition about these strategies we highly recommend watching following videos: - [Long Straddle](https://www.youtube.com/watch?v=4UlIMmXhjsc) - [Short Straddle](https://www.youtube.com/watch?v=Lsk9ppb8ffs) <p align="center"> <img center src="img/option-strategy.png" width="700" > </p> ## Trading Workflow Firstly, we started with doing basic market research and finding `historically the most and least volatile stocks` in the past `1 week`, `2 week` and a `1 month` period in the `Russel 3000 index` (in order to capture both the large-cap and the small-cap companies). From those stocks we chose the top 50 stocks with highest and the top 50 lowest historical weighted volatility: `Weighted volatility = 0.5 * Vol_1_week + 0.3 * Vol_2_week + 0.2 * Vol_1_month`. Using naive expecation for the future volatility based on the historical volatility, combined with the momentum detected from the daily P&L for the target companies, we enter into `long straddle` or `short straddle` positions. Our MarketWatcher bot was alerting us for all potential investment opportunities. From the provided list of `target stocks`, trading bot was sending us `alerts via Email and Slack`, when target stocks have `reached configured daily P&L threashold`: - Long straddle - stocks with absolute daily P&L that are `greater` than `5% P&L threashold` - Short straddle - stocks with absolute daily P&L that are `lower` than `0.5% P&L threashold` Upon getting alerted by the MarketWatcher bot, we `hand picked` into which long and short straddle positions to enter. <p align="center"> <img center src="img/trading-workflow.png" width="700" > </p> ### Future improvements In the next iteration of development we intend to ship more IBKR TWS API functionality so that daily P&L is fetched from there. We would also like to automate the whole process, by first adding support to our trading bot to place orders on TWS and after that to fully implement algotrading strategy. ## How to use MarketWatcher trading bot? After cloning the repo, rename the `env.template` file to `.env` and populate it with your settings: `email notification interval time`, `daily P&L threashold values`, `email settings`, `slack channel webhook links`, ... Create `.yaml file with target stocks` (ticker and long/short straddle strategy indicator for that ticker). MarketWatcher engine listens to real-time ticker data feed and notifies you when there is a `potential opportunity
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