Given a finite set of m scenarios, computing a portfolio with the minimium Value-at-Risk (VaR) is computationally difficult: the portfolio VaR function is non-convex, non-smooth, and has many local minima. Instead of formulating an n-asset optimal VaR portfolio problem as minimizing a loss quantile function to determine the asset holding vector R, we consider it as a minimization problem in an ...

Abstract. Asset/Liability management, optimal fund design and optimal portfolio selection have been key issues of interest to the (re)insurance and investment banking communities, respectively, for some years especially in the design of advanced risk transfer solutions for clients in the Fortune 500 group of companies. The new concept of limited risk arbitrage investment management in a diffusi...

Introduction: The portfolio can be seen as a tool for assessmentof a variety of learning activities that differ in content, usage, andassessment. The portfolio not only meets the learner’s educationalneeds but also the political and public reassurance demand thatthe health professional has achieved the required competency ofthe curriculum that allows him or her to practice safely with orwithout...

In this research, performance of portfolios formed by use of grid strategy based on new variables (aggressive, indifference and defensive stocks) presented by Rahnamaye Roodposhti (1388), and traditional ones (growth, growth-value and value stocks), calculated with Sharpe and Treynor performance measures and tested by an Active portfolio management approach to identify the portfolios by perform...

1Jonathan B. Berk Haas School of Business University of California, Berkeley and National Bureau of Economic Research Email: [email protected] P roponents of “efficient markets” argue that it is impossible to consistently beat the market. In support of their view they point to the evidence that, as a group, active managers do not beat the market and conclude that even these investment prof...

Portfolio optimization problem has been studied extensively. In this paper, we look at this problem from a different perspective. Several researchers argue that the USA equity market is efficient. Some of the studies show that the stock market is not efficient around the earning season. Based on these findings, we formulate the problem as a classification problem by using state of the art machi...

We propose a composite realized kernel to estimate the ex-post covariation of asset prices. Composite realized kernels are a data efficient method where the covariance estimate is composed of univariate realized kernels to estimate variances and bivariate realized kernels to estimate correlations. We analyze the merits of our composite realized kernels in an ultra high dimensional environment, ...

This work presents a new prediction-based portfolio optimization model that can capture short-term investment opportunities. We used neural network predictors to predict stocks’ returns and derived a risk measure, based on the prediction errors, that have the same statistical foundation of the mean-variance model. The efficient diversification effects holds thanks to the selection of predictors...

Standard market risk optimization tools, based on assumptions of normality, are ineffective for credit risk. In this paper, we develop three scenario optimization models for portfolio credit risk. We first create the trade risk profile and find the best hedge position for a single asset or obligor. The second model adjusts all positions simultaneously to minimize the regret of the portfolio sub...

This paper extends Merton’s continuous time (instantaneous) mean-variance analysis and the mutual fund separation theory. Given the existence of a Markovian state price density process, the optimal portfolios from concave utility maximization are instantaneously mean-variance efficient independent of the concave utility function’s form. The Capital Asset Pricing Model holds with the market port...