As a model validation risk professional, my research experience provides effective challenge of enterprise bank balance sheet DFAST stress testing models. My role is to help banks understand the model risks associated with key financial variables such as deposit balances, loan growth rates, loan loss and recovery rates. Because of the systemic risks associated with banks, financial institutions must provide a credible estimate of the worst case scenario of their credit related losses so that they can hold sufficient capital reserves to be resilient and withstand stressful episodes. These reserves will heavily depend on the projected values of their loans, deposits, and other modeled balance sheet variable forecasts. This makes models especially important for banks.
As a consultant, I conducted research that extends the central findings of my thesis on return predictability. The aim of my applied research is to develop an investment product that taps into systematic, predictable sources of returns in global financial markets that are uncorrelated with global equity returns. In addition, I strive to make the product simple and intuitive to understand. Further, if the promise of the idea delivers in practice, I will help investors gain access to global financial returns that are robust to various investment environments.
My research closely examines the underlying forces driving return predictability in financial markets. I aim to reconcile the empirical evidence of predictable returns in major financial markets in relation to theoretical explanations of time-varying excess returns. The approach that I use leverages financial econometric analysis, meta-analysis of the existing academic literature and the various interpretations of the underlying data and quantitative analyses, and an integration of seemingly conflicting opinions into a coherent view. I offer interesting and practical interpretations of the real-world data in relation to macroeconomics that is relevant to policymakers, academics, and financial market participants. Moreover, the quantitative methods I use crossover seamlessly into risk management and data scientist research methods.
I have taught various finance and economics courses as an instructor. In my efforts to enhance the learning experience for a wide array of students, I aim to make the course intuitive, problem-solving oriented and pertinent to real-world events. Teaching has also enabled me to develop effective communication techniques useful for explaining concepts and ideas to a general audience.