Research

Research Overview

My research lies at the intersection of quantitative finance, derivatives, risk management, and computational finance. I am particularly interested in how option-implied information can be used to study market expectations, tail risk, density forecasting, and financial risk measurement.

As my current papers are still in progress, this page provides a high-level overview of my research interests rather than detailed descriptions of unpublished models, empirical results, or implementation choices.

Research Interests

Option-Implied Information

I study information embedded in option prices and implied distributions, with a focus on how market expectations and risk-neutral measures can be used in empirical finance.

Tail Risk and Market Risk

I am interested in tail behaviour, downside risk, and market risk measurement, especially in settings where extreme outcomes and distributional asymmetry are important.

Density Forecasting

My work considers the evaluation of predictive densities and risk measures, including calibration, scoring, and risk-management-oriented assessment.

Computational Finance

I also work on numerical and computational methods for derivative pricing, implied distribution recovery, and financial modelling.

Current Research Directions

Option-Implied Tail Risk and Market Conditions

This line of research studies how option-implied distributional information can be used to understand downside risk and market conditions. The current version is under development.

Status: Working paper in progress

Density Forecasting and Financial Risk Measurement

This project focuses on option-implied density forecasting and the evaluation of financial risk measures from a risk-management perspective.

Status: Working paper in progress

Sector-Level Option-Implied Information

This research direction explores how option-implied information may vary across sectors and whether sector-level derivatives markets provide additional insights beyond broad market index options.

Status: Early-stage research

Numerical Methods for Implied Distribution Recovery

I am also interested in numerical approaches for recovering and analysing implied distributions from derivative prices, with potential applications in computational finance and risk management.

Status: Methodological research in progress

Research Approach

My research combines theoretical modelling, empirical analysis, numerical methods, and programming-based implementation. I work mainly with derivatives data, option-implied distributions, risk-neutral and physical measures, and evaluation methods for density forecasts and risk measures.

Selected Keywords

Option-Implied Information Risk-Neutral Density Tail Risk Market Risk Density Forecasting Value-at-Risk Expected Shortfall Computational Finance Derivative Pricing Numerical Methods