Methodology
My workflow is designed around transparency, reproducibility, and analytical rigor. Each step is documented to ensure that results are interpretable and auditable.
Step-by-Step Quantitative Workflow
1) Data Collection
Identify the analytical objective and select appropriate data sources and time horizons. Data may include asset prices, returns, benchmarks, and macro-financial indicators.
2) Data Cleaning and Validation
Apply systematic checks for missing values, inconsistent timestamps, outliers, and corporate-action distortions. Data transformations are documented to preserve traceability.
3) Statistical and Financial Analysis
Compute and analyze key market diagnostics including returns, volatility, correlations, distribution properties, and relevant risk indicators, using consistent statistical definitions.
4) Portfolio Modeling and Allocation
Construct candidate allocations and evaluate diversification properties, constraints, and measurable risk-return trade-offs. Portfolio analytics are presented with explicit assumptions and limitations.
5) Risk Assessment
Quantify risk using volatility, drawdowns, Value-at-Risk (VaR), and scenario-based stress diagnostics. Risk outputs are interpreted in relation to the portfolio objective and data properties.
6) Monitoring and Rebalancing
Implement a monitoring framework for allocation drift, risk changes, and performance relative to benchmarks. Rebalancing logic is rule-based and documented for transparency.