1 citations · 2 across the 5 of their papers we have counts for
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q-fin.PM2026★ 1 cited
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.PM2024★ 1 cited
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…