This paper investigates whether the use of robust covariance improves portfolio performance and, in the presence of uncertainty, whether the 1/N strategy is as good as you think. In addition to sample covariance, we use a battery of robust covariance matrix. Our empirical evidence has two...

We study the asymptotic properties of a Tikhonov Regularized (TiR) estimator of a functional parameter based on a minimum distance principle for nonparametric conditional moment restrictions. The estimator is computationally tractable and takes a closed form in the linear case. We derive its...

This paper adopts a copula approach at assessing the dependence structure of the U.S. equity market. Seven types of copulas are considered: Gaussian, Student t, Clayton, rotated Clayton, Gumbel, rotated Gumbel and BB4. By adopting a twenty-two year sample of daily returns on the seventeen Fama...

Investors often adopt mean-variance efficient portfolios for achieving superior risk-adjusted returns. However, such portfolios are sensitive to estimation errors, which affect portfolio performance. To understand the impact of estimation errors, I develop simple and intuitive formulas of the...

I jointly treat two critical issues in the application of mean-variance portfolios, i.e., estimation risk and portfolio instability. I find that theory-based portfolio strategies known to outperform naive diversification (1/N) in the absence of transaction costs, heavily underperform it under...

Tail risk refers to the possibility that a rare event would adversely affect the value of a portfolio in a significant manner. It became much more relevant due to recent periods of strong market turbulence.We describe how to quantify such risk, which tail risk protection strategies were...

Instead of data-mining methods, the author proposes a portfolio committee approach to portfolio selection. Because each optimal portfolio is a combination of three basic elements: strategy, covariance matrix, and risk type; therefore, the author first augments the combination to 250 optimal...

The quantitative practice of portfolio selection aims to select the in-sample optimal portfolio that is robust out of sample. However, at each estimation period, the conventional method is selection by solving a given objective function, without a learning mechanism, or training. This paper...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: Development of A Framework for Liquidity Assessment in Portfolio Construction Process: Presentations to the JP Morgan Global Head of Quant Research & Analytics and US Head of Portfolio Construction Teams:Presentations To: JP Morgan Global Head of Quant...