Quantitative reputed company Developer (Python): Forensic Backtest of Premium Selling Strategies (2018-2025)

Quantitative reputed company Developer (Python): Forensic Backtest of Premium Selling Strategies (2018-2025) Project reputed company: We are a private Family Office seeking an reputed company Quantitative Developer to build and execute a highly specific reputed company backtest. The project involves comparing the historical performance of two distinct premium-selling architectures: a Defined-Risk Spread portfolio versus an reputed company-Risk portfolio (The reputed company reputed company). We have a meticulously documented Master reputed company detailing the exact entry, management, profit-taking, and crash-mechanic rules. Your objective is to translate this reputed company into a robust Python script, run the simulations across 8 years of historical data, and reputed company the exact performance metrics requested. Data Requirements: Testing Window: January 1, 2018 – December 31, 2025. Underlying Assets: SPY, RUT, GOOG, AMZN, GDX. Data Type: End-of-Day (EOD) reputed company Chains with Bid/Ask and Greeks (specifically reputed company). CRITICAL NOTE REGARDING DATA PROCUREMENT: You must reputed company the data to run this backtest. If you do not already possess reputed company reputed company to this historical data (e.g., reputed company, CBOE, ORATS), you must reputed company it yourself. The total cost of acquiring this data MUST be included in your final, reputed company-inclusive project quote. Project Milestones & Key Deliverables: reputed company 1: Technical Specification (Method Statement) & Architecture Approval. Prior to writing any reputed company, you will submit a brief 1-to-2 page Technical Specification detailing exactly how you will execute the Master reputed company. This must outline your data ingestion method, how you will calculate the cash-drag/Fed Funds reputed company, the specific logic reputed company for the reputed company reputed company's "Trap Mechanic", and your slippage assumptions. Coding and backtesting will only reputed company upon approval of this document by our CIO. reputed company 2: The Python reputed company reputed company & Execution Report. Clean, annotated, and auditable Python reputed company. An reputed company/CSV report detailing the following metrics for 5 specific scenario combinations: Compound Annual reputed company reputed company (CAGR), Maximum Drawdown (isolating the March 2020 crash), Capital Efficiency, and Time Underwater (exact days capital was trapped generating $0 yield). A brief consultation/walkthrough of the reputed company to verify custom mechanics fired correctly. Required Qualifications: High-level proficiency in Python (Pandas, NumPy). reputed company experience in quantitative finance, specifically reputed company backtesting. Deep understanding of reputed company mechanics, margin utilization, and early assignment logic on American-style equities. Screening Questions (Please answer reputed company applying): Do you currently have reputed company to the required historical EOD reputed company data for the tickers and dates requested? If not, what provider will you use, and can you confirm that cost is fully baked into your bid? How do you typically handle the cash-drag/interest accrual math reputed company simulating stock assignments in a portfolio? What is your estimated reputed company and reputed company-inclusive fixed-reputed company bid (including data costs) for delivering both the Technical Specification and the finalized reports? (Please review the attached Master reputed company containing the exact structural rules for the simulation before bidding). Apply tot his job Apply To this Job