Stability-Adjusted Portfolios

The authors introduce Stability-Adjusted Portfolios: a methodology for incorporating estimation error in covariances into the portfolio formation process.

The authors compute covariances from all independent subsamples of a chosen size and measure composite errors in these subsamples. These composite errors com­prise small-sample error, independent-sample error, and interval error. They then add these errors to a base-case covariance matrix and, assuming normality, generate stability-adjusted return distributions for all subsamples.  They then combine these distributions into a stability-adjusted return distribution, which is non-normal.

The authors then use full-scale optimization (that works with non-normal distributions) and utility functions to derive optimal portfolios.  These portfolios tend to be less volatile.

KRITZMAN, M., & TURKINGTON, D. (2016). Stability-Adjusted Portfolios. Journal of Portfolio Management, 42(5), 113–122.

A Practitioner's Guide to Market Microstructure Invariance

The authors add to one of their previous papers to show their comprehensive model of market microstructure invariance.  They used their metrics to recast trades as bets, calendar time as business time, and return volatility as dollar volatility.  In doing so, they hypothesized that the amount of risk transferred for each bet is the same for low and high velocity stocks and the dollar cost of executing low and high velocity stocks is the same when measured as the amount of risk transfer.  They support this with detailed equations and charts.

KYLE, A. S., OBIZHAEVA, A. A., & KRITZMAN, M. (2016). A Practitioner's Guide to Market Microstructure Invariance. Journal Of Portfolio Management, 43(1), 43-53.