Md Mostafa Kamal

Quant Risk Analysis & Modeling

My research investigates the intricate connections between financial markets, risk propagation, and macroeconomic stability. I employ a multidisciplinary approach that integrates quantitative analysis, complex systems modeling, and advanced statistical techniques to dissect the mechanisms driving financial crises and asset price dynamics. My work is situated at the intersection of risk management, asset pricing, and data-driven financial analysis, with the overarching goal of developing more robust frameworks for understanding and mitigating systemic risk.

Core Research Areas:

  • Systemic Risk and Financial Crises: Analyzing the propagation of shocks and contagion effects within interconnected financial systems.
  • Asset Pricing Dynamics: Investigating the determinants of asset valuations and market reactions to new information.
  • Quantitative and Computational Finance: Developing and backtesting novel risk models and analytical tools using advanced computational methods.

Empirical Testing of Value-at-Risk (VaR) Methodologies

Value-at-Risk (VaR) is a cornerstone of market risk management, providing a statistical estimate of potential portfolio losses. However, the reliability of VaR is contingent on the chosen calculation method and its underlying assumptions. My Master’s thesis at Goethe University, titled “Empirical Testing of Value-at-Risk (VaR) Models,” conducted a comprehensive empirical investigation into the performance of twelve distinct VaR approaches.

This research utilized extensive datasets spanning major financial markets—including equities, fixed income, commodities, and foreign exchange—to rigorously backtest each model. The analysis systematically identified the strengths and weaknesses of various methods, such as historical simulation, variance-covariance, and Monte Carlo simulation, under different market conditions. The findings revealed critical limitations in conventional models and highlighted specific scenarios where certain approaches fail to capture tail risk, offering valuable insights for enhancing the robustness of financial risk modeling. The complete thesis, including the datasets and Python-based analytical notebooks, is available upon request.

Central Bank Communication and High-Frequency Market Reactions

Central bank communications are a critical tool for guiding market expectations and influencing asset prices. The tone and sentiment of these announcements can convey subtle but powerful signals to market participants. In a project initiated during my studies at Goethe University, I explored the intersection of computational linguistics and finance by analyzing the sentiment of Federal Open Market Committee (FOMC) meeting minutes.

This research utilized text analytics and sentiment analysis to quantify the tone of central bank communications and examined the subsequent reactions in the U.S. stock market at a high-frequency trading (HFT) level. The study investigates the immediacy and decay of market responses to shifts in monetary policy sentiment, assessing how this information is incorporated into asset prices. A working paper from this project, “FOMC Tone Sentiment and US Stock Market Reactions,” is currently being prepared for submission to a scholarly journal.

Financial Contagion & Risk Spillover: A Complex Network Approach

Financial systems can be conceptualized as complex networks where institutions are interconnected through a web of obligations. Shocks originating in one part of this network can propagate and amplify, leading to systemic crises—a phenomenon known as financial contagion. During my Research Master’s program at Northwestern Polytechnical University, I collaborated on a project that employed complex network theory and graph-based models to investigate risk spillover across global financial markets.

This research examined the topological properties of financial networks and their role in transmitting risk across different asset classes, markets, and geographical regions, with a particular focus on the global financial crisis. By modeling the interconnectedness of financial entities, our work provides a framework for understanding how localized shocks can escalate into widespread systemic events. Several papers from this ongoing research are currently under review or in preparation for submission to peer-reviewed journals.

Work in Progress

  • Kamal, M. M. (2023). FOMC Tone Sentiment and US Stock Market Reactions. (Planning to submit to Finance Research Letters).
  • Kamal, M. M. (2023). Green Financing, Innovations, and Stock Market Performance. (Planning to submit to Energy Economics).
  • Kamal, M. M., Roca, E., Li, B., & Reza, R. (2023). Ripple Effects of Local Housing Prices in Australia. (Planning to submit to Urban Studies).
  • Kamal, M. M., Roca, E., Li, B., Zhao, L., & Reza, R. (2023). Currency Risk Spillover during COVID-19. (Planning to submit to Finance Research Letters).

Publications