F theory posits that capital markets convey through stock prices their expectation of the firm’s future performance. We use concepts from principal-agent theory and prospect theory to provide a theoretical explanation for the role stock price variation plays in managerial decision making. We then empirically investigate what specific decisions managers undertake in response to stock price varia...

Portfolio optimization is the process of making investment decisions on holding a set of financial assets to meet various criteria. A variety of investment assets around the world make this multi-faceted decision problem very complicated. Econometric and statistical models as well as machine learning and data mining techniques have been used by many researchers and analysts to propose heuristic...

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...

I study how growth affects liquidity of global stock exchanges and how liquidity determines cross-sectional returns on those stock exchange index portfolios. I measure portfolio liquidity by turnover ratio computed as value of shares traded over the market capitalization. I obtain data from FIBV, an association of global stock exchanges. In a multiple regression model for turnover ratio, I find...

This paper further studies the recently proposed Adaptive Supervised Learning Decision (ASLD) network for trading and portfolio management [5] in two sets of stock market data. One is the Hang Seng index in Hong Kong markets. The other is a portfolio of indexes from six major markets in the world. Being different from the study on foreign exchange rates [5], we find that in generating the tradi...

In this paper, we deal with second-order stochastic dominance (SSD) portfolio efficiency with respect to all portfolios that can be created from a considered set of assets. Assuming scenario approach for distribution of returns several SSD portfolio efficiency tests were proposed. We introduce a δ-SSD portfolio efficiency approach and we analyze the stability of SSD portfolio efficiency and δ-S...

This paper treats the risk-averse optimal portfolio problem with consumption in continuous time for a stochastic-jump-volatility, jump-diffusion (SJVJD) model of the underlying risky asset and the volatility. The new developments are the use of the SJVJD model with logtruncated-double-exponential jump-amplitude distribution in returns and exponential jumpamplitude distribution in volatility for...

A large number of portfolio selection models have appeared in the literature since the pioneering work of Markowitz. However, even when computational and empirical results are described, they are often hard to replicate and compare due to the unavailability of the datasets used in the experiments. We provide here several datasets for portfolio selection generated using real-world price values f...

Using the restrictions implied by the heteroskedasticity of stock returns, we identify four factors in the U.S. industry returns. The first correlates highly with the market portfolio; the second is a portfolio of stocks that produce investment goods minus stocks that produce consumption goods; the third differentiates between cyclical and noncyclical stocks. The fourth, a portfolio of industri...