collaborators

6 papers

cs.LG2026

A Mathematical Optimization Approach for Expert-Informed Bayesian Best Subset Selection

Nolan Alexander, Henning Mortveit

A central challenge in statistical modeling is identifying the subset of features that belong in the true regression model. The classical best subset selection problem, recently ma…

q-fin.RM2026

On the Structure of Risk Contribution: A Leave-One-Out Decomposition into Inherent and Correlation Risk

Nolan Alexander, Frank Fabozzi

This paper develops a decomposition of standard Risk Contribution (RC) into two economically interpretable components: inherent risk and correlation risk. Using a leave-one-out rep…

q-fin.RM2026

Measuring Strategy-Decay Risk: Minimum Regime Performance and the Durability of Systematic Investing

Nolan Alexander, Frank Fabozzi

Systematic investment strategies are exposed to a subtle but pervasive vulnerability: the progressive erosion of their effectiveness as market regimes change. Traditional risk meas…

q-fin.PM2026

Forecasting Tangency Portfolios and Investing in the Minimum Euclidean Distance Portfolio to Maximize Out-of-Sample Sharpe Ratios

Nolan Alexander, William Scherer

We propose a novel model to achieve superior out-of-sample Sharpe ratios. While most research in asset allocation focuses on estimating the return vector and covariance matrix, the…

q-fin.PM2026

Asset allocation using a Markov process of clustered efficient frontier coefficients states

Nolan Alexander, William Scherer, Jamey Thompson

We propose a novel asset allocation model using a Markov process of states defined by clustered efficient frontier coefficients. While most research in Markov models of the market…

q-fin.PM2026

Using Machine Learning to Forecast Market Direction with Efficient Frontier Coefficients

Nolan Alexander, William Scherer

We propose a novel method to improve estimation of asset returns for portfolio optimization. This approach first performs a monthly directional market forecast using an online deci…