I develop a multi-account alpha-tracking error framework that simultaneously optimizes across an investor’s multiple accounts with different tax treatments, existing holdings, lots, and opportunity sets while considering taxes trade costs in single optimization. The objective function includes optional term for nonpecuniary preferences, such as various environmental, social, governance (ESG) ch...

We consider the problem of portfolio selection, with transaction costs and constraints on exposure to risk. Linear transaction costs, bounds on the variance of the return, and bounds on different shortfall probabilities are efficiently handled by convex optimization methods. For such problems, the globally optimal portfolio can be computed very rapidly. Portfolio optimization problems with tran...

Classical statistical models can solve the problem of portfolio optimization and can determine the efficient frontier of investment when there are few investable assets and constraints. But these models cannot easily solve optimization problems when we consider real-world constraints. Therefore, data mining techniques such as evolutionary algorithms are important in portfolio optimization. The ...

in traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. so decision maker cannot estimate them exactly. financial optimization is one of the most attractive areas in decision under uncertainty. in the portfolio selection problem the decision maker considers simultaneously conflicting objectives such as ra...

With the advent of Web 2.0, various types of data are being produced every day. This has led to the revolution of big data. Huge amount of structured and unstructured data are produced in financial markets. Processing these data could help an investor to make an informed investment decision. In this paper, a framework has been developed to incorporate both structured and unstructured data for p...

In accordance with Basel Capital Accords, the Capital Requirements (CR) for market risk exposure of banks is a nonlinear function of Value-at-Risk (VaR). Importantly, the CR is calculated based on a bank’s actual portfolio, i.e. the portfolio represented by its current holdings. To tackle mean-VaR portfolio optimization within the actual portfolio framework (APF), we propose a novel mean-VaR op...

Portfolio optimization involves the optimal assignment of limited capital to different available financial assets to achieve a reasonable trade-off between profit and risk. We consider an alternative Markowitz’s mean-variance model in which the variance is replaced with an industry standard risk measure, Value-atRisk (VaR), in order to better assess market risk exposure associated with financia...