Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm i...

This paper discusses nonparametric series estimation of integrable cointegration models using Hermite functions. We establish the uniform consistency and asymptotic normality of the series estimator. The Monte Carlo simulation results show that the performance of the estimator is numerically satisfactory. We then apply the estimator to estimate the stock return predictive function. The out–of–s...

Identifying homogeneous groups of stocks, where these stocks have similar movement of returns is called stock return comovement analysis. Stock return comovement analysis is important to financial analysts, decision makers, and academic researchers, in many financial implications. This paper examines firms’ social media, in particular, microblogging metrics’ role on analyzing stock return comov...

Recent studies in financial economics suggest that technical analysis may have merit to predictability of stock. When attempting to create an efficient portfolio of stocks, there are numerous factors to consider. The problem is that the evaluation involves many qualitative factors, which causes most approximations to go off track. This paper presents a genetic programming approach to portfolio ...

There has been considerable public discussion of the investment performance of the University of California Retirement Plan (UCRP). Much of that discussion has been based on simple comparisons of the realized investment returns of UCRP to those of other pension plans, such as CalPERS. Such comparisons provide no economically meaningful or statistically significant information about the quality ...

This study tests the hypothesis that market value added (MVA) is more highly associated with stock return (SR) than traditional performance measures. The purpose of this study is to provide empirical evidence on the relative and incremental information content of MVA and traditional performance measures, namely, net income (NI), net operational profit after tax (NOPAT), and earning per shares (...

Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified...

This paper examines predictability in stock return in developed and emergingmarkets by testing long memory in stock returns using wavelet approach. Wavelet-based maximum likelihood estimator of the fractional integration estimator is superior to the conventional Hurst exponent and Geweke and Porter-Hudak estimator in terms of asymptotic properties and mean squared error. We use 4-year moving wi...

for assessment of portfolio performance, it's crucial to adjust the return by the risk which is taken. so it seems undeniable that for measuring the risk-adjusted return of portfolio, we need an appropriate and developed model for risk and asset pricing. fama & french 3 factor model could explain several return anomalies. recent studies show that capital productivity effects on stock retur...