The impact of big winners on passive and active equity investment strategies

We investigate the impact of big winner stocks on the performance of active and passive investment strategies using a combination of numerical and analytical techniques. Our analysis is based on historical stock price data from 2006 to 2021 for a large variety of global indexes. We show that the log-normal distribution provides a reasonable fit for total returns for the majority of world stock indexes but highlight the limitations of this model. Using an analytical expression for a finite sum of log-normal random variables, we show that the typical return of a concentrated portfolio is less than that of an equally weighted index. This finding indicates that active managers face a significant risk of underperforming due to the potential for missing out on the substantial returns generated by big winner stocks. Our results suggest that passive investing strategies, that do not involve the selection of individual stocks, are likely to be more effective in achieving long-term financial goals.Comment: 15 pages, 3 figures, 4 table

Portfolio Optimization Rules beyond the Mean-Variance Approach

In this paper, we revisit the relationship between investors' utility functions and portfolio allocation rules. We derive portfolio allocation rules for asymmetric Laplace distributed $ALD(\mu,\sigma,\kappa)$ returns and compare them with the mean-variance approach, which is based on Gaussian returns. We reveal that in the limit of small $\frac{\mu}{\sigma}$, the Markowitz contribution is accompanied by a skewness term. We also obtain the allocation rules when the expected return is a random normal variable in an average and worst-case scenarios, which allows us to take into account uncertainty of the predicted returns. An optimal worst-case scenario solution smoothly approximates between equal weights and minimum variance portfolio, presenting an attractive convex alternative to the risk parity portfolio. We address the issue of handling singular covariance matrices by imposing conditional independence structure on the precision matrix directly. Finally, utilizing a microscopic portfolio model with random drift and analytical expression for the expected utility function with log-normal distributed cross-sectional returns, we demonstrate the influence of model parameters on portfolio construction. This comprehensive approach enhances allocation weight stability, mitigates instabilities associated with the mean-variance approach, and can prove valuable for both short-term traders and long-term investors

Optimal portfolio allocation with uncertain covariance matrix

In this paper, we explore the portfolio allocation problem involving an uncertain covariance matrix. We calculate the expected value of the Constant Absolute Risk Aversion (CARA) utility function, marginalized over a distribution of covariance matrices. We show that marginalization introduces a logarithmic dependence on risk, as opposed to the linear dependence assumed in the mean-variance approach. Additionally, it leads to a decrease in the allocation level for higher uncertainties. Our proposed method extends the mean-variance approach by considering the uncertainty associated with future covariance matrices and expected returns, which is important for practical applications

Comment on "Casimir energies with finite-width mirrors"

We comment on a recent publication [1] by Fosco, Lombardo and Mazzitelli on Casimir energies for material slabs (`finite width mirrors') and report a discrepancy between results obtained there for a single mirror and some previous calculations. We provide a simple consistency check which proves that the method used in [1] is not reliable when applied to approximations of piecewise constant profile of the mirror. We also present an alternative method for calculation of the Casimir energy in such systems based on our recent work. Our results coincide both with perturbation theory and with some older \cite{Bordag'95} and more recent \cite{Vassilevitch'08} calculations, but differ from those of [1].Comment: Published version, 4 page