There’s a reason Wall Street firms recruit from MIT. For many investors, the financial markets are governed entirely by mathematical equations applied to aspects of a security’s price and trading ...

We formulate a novel Markov regime-switching factor model to describe the cyclical nature of asset returns in modern financial markets. Maintaining a factor model structure allows us to easily derive ...

Standard MPT is often broken because it drives forward-looking models using backward-looking return data. This tool fixes that by replacing historical average returns with a fundamentally derived ...

The goal is to implement, analyze, and compare various stochastic control techniques—from classical methods to modern machine learning approaches—with applications to real-world problems in portfolio ...

This study investigates advanced portfolio optimization techniques that integrate copula functions and GARCH models to enhance risk-adjusted performance in the European stock market. Traditional ...

Abstract: A new stochastic optimization algorithm referred to by the authors as the `Mean-Variance Optimization' (MVO) algorithm is presented in this paper. MVO falls into the category of the ...

(a) in the limit of low uncertainty in estimated asset mean returns, the robust portfolio converges toward the mean-variance portfolio obtained with the same inputs, and (b) in the limit of high ...

We were visiting a hedge fund some years back when we had our first taste of the problem with mean-variance optimization—the tool advisors use to balance risk and reward in client portfolios. We ...