Developing an investment portfolio for the stock market that will yield positive returns is the primary goal of investors worldwide. A variety of models and algorithms have been developed to decide upon a distribution which maximizes gains in the market, a few examples being the Geometric Brownian Motion model and the universal portfolio. One particular algorithm, known as online gradient desce...

The purpose of stock portfolio selection is how to allocate the capital to a large number of stocks in order to bring a most profitable return for investors. In most of past literatures, experts considered the portfolio of selection problem only based on past crisp or quantitative data. However, many qualitative and quantitative factors will influence the stock portfolio selection in real inves...

Abstract: It is very important to minimize the risk in portfolio selection. For minimizing risk of portfolio at a given expected returns, it is efficient to compose portfolio with stocks which have low cross-correlation among them. In this regard, forecasting the cross-correlations among stock prices has attracted much interest among investors and financial market researchers. Most of studies i...

In these notes, we present some methods and applications of large deviations to finance and insurance. We begin with the classical ruin problem related to the Cramer’s theorem and give en extension to an insurance model with investment in stock market. We then describe how large deviation approximation and importance sampling are used in rare event simulation for option pricing. We finally focu...

This paper considers a problem of multi-period supply portfolio selection and execution with demand information updates. A supply portfolio specifies a buyer’s decision on selecting sourcing mix from among a group of suppliers. We develop a framework for optimal supply portfolio selection and execution. Further, we demonstrate that the optimal portfolio selection follows a base-stock policy and...

In this paper a data mining approach for classification of stocks into clusters is presented. After classification, the stocks could be selected from these groups for building a portfolio. It meets the criterion of minimizing the risk by diversification of a portfolio. The clustering approach categorizes stocks on certain investment criteria. We have used stock returns at different times along ...

Evidence indicates that people fear change and the unknown. We model this behavior as familiarity bias in which individuals focus on adverse scenarios in evaluating defections from the status quo. The model explains portfolio underdiversification, home and local biases. More importantly, equilibrium stock prices reflect an unfamiliarity premium. In an international setting, our model predicts t...

In these notes, we present some methods and applications of large deviations to finance and insurance. We begin with the classical ruin problem related to the Cramer’s theorem and give en extension to an insurance model with investment in stock market. We then describe how large deviation approximation and importance sampling are used in rare event simulation for option pricing. We finally focu...

Stock portfolio selection is a classic problem in finance, and it involves deciding how to allocate an institution’s or an individual’s wealth to a number of stocks, with certain investment objectives (return and risk). In this paper, we adopt the classical Markowitz mean-variance model and consider an additional common realistic constraint, namely, the cardinality constraint. Thus, stock portf...