Quantitative Options Backtester: Hybrid Multi-Asset Strategy (2020–Present)

Python, Financial Research, Finance, Business Analysis, Risk Management, Financial Analysis, Data Analysis, Portfolio Management, Backtesting, Algorithmic Trading · Quantitative Options Backtester: Hybrid Multi-Asset Strategy (2020–Present) Project Overview Looking for an experienced quantitative developer to backtest a multi-asset hybrid options portfolio from January 2, 2020, to present, using historical split-adjusted equity and options data. Portfolio & Allocation Parameters Initial Capital: $100,000 cash + 25% margin leverage ($125,000 total deployed capital). Start date: Jan 2, 2020. Active Income Sleeve (38.7%): Split equally into two large-cap growth assets. Sell monthly out-of-the-money (OTM) covered calls (30–45 DTE, ~30 delta) on 100% of the holdings. Long-Term Growth Sleeve (61.3%): Distributed across a basket of unconstrained large-cap growth equities with zero option overlays. Risk Management & Execution Rules Option Rolls & Assignment: Automatically manage monthly option rollovers, assignments, and repurchases. Margin Accounting: Factor in historical broker margin interest rates on the borrowed 25% capital. Tail-Risk Hedging: Simulate buying annual OTM index put options on a benchmark index ETF to enforce a strict maximum drawdown limit of ~10%. Deliverables Full backtest code (Python/QuantConnect or equivalent). Complet