In this study, a modeling method to analyze multidimensional time series based on complex networks is proposed. The rate of return sequence of the closing price and the trading volume fluctuation sequence of the Shanghai Composite Index, the Shenzhen Component Index, the S & P 500 index, and the Dow Jones Industrial Average are analyzed. The two-dimensional time series is transformed into a com...

This paper examines the forecasting ability of the dividend-price ratio for international stock market returns. Hitherto, existing research has only considered this issue in-sample and in a linear framework. Hence, this paper provides the first systematic study of non-linear forecasting within the present value model context. Using an asymmetric variant of the popular ESTR model we demonstrate ...

This paper investigates the relationship between aggregate stock market trading volume and the serial correlation of daily stock returns. For both stock indexes and individual large stocks, the first-order daily return autocorrelation tends to decline with volume. The paper explains this phenomenon using a model in which risk-averse "market makers" accommodate buying or selling pressure from "l...

Prior to the Telecommunications Act of 1996, many U.S. states restructured their regulatory framework by replacing rate-of-return regulation with competition in both the local exchange service and local long-distance markets and adopting price regulation (price caps and price freezes). Using a panel data set of incumbent Ž rm prices for three services, I investigate whether price regulation and...

This paper aimed to evaluate Water Use Efficiency (WUE) indices for crops and horticulture productions. In doing so, after gathering data from 164 farmers, we investigated water withdrawal cost indices and monetary return per cubic meter of water through two econometric and managerial approaches . Besides, water shadow pricesand dry matters of per cub meter of water were calculated. The results...

this paper analyses efficiency of short horizon event study methodology in general and efficiency of various test statistics based on price and trading volume in the period (iranian calendar) 1380:1389-q1 (2240 days) applying simulation method. we evaluate efficiency of 8 test statistics including parametric, non-parametric and induced variance statistics. we find various test statistics have e...

Stock price forecasting has been mostly realized using quantitative information. However, recent studies have demonstrated that sentiment information hidden in corporate annual reports can be successfully used to predict short-run stock price returns. Soft computing methods, like neural networks and support vector regression, have shown promising results in the forecasting of stock price due to...