Variability of realized stock returns and trading volume

Using monthly data for 2005–2014 time period, this article documents the relationship between lagged stock returns and trading volume. We show that the dispersion of stock returns in a market portfolio positively affects future trading volume. We also show that extreme negative returns lead to high future trading volume while extreme positive returns have little effect on future trading. Dividing our sample into several sub-samples based on the Standard Industrial Classification (SIC) divisions leads to similar results for most of the SIC divisions.     

Bond rating changes and stock returns: evidence from the Spanish stock market

This study analyzes the effect of corporate bond rating changes by international agencies on stock prices. This topic has not yet been analyzed for the Spanish stock market, despite the growing importance of ratings in Spanish financial markets. On an efficient market, rating changes will only have an effect if they contain some new information. The results from an event study indicate that rating actions cause significant negative abnormal returns in issuing firms around the date of the announcement. This evidence indicates an informational effect related to downgrades, which supports the hypothesis that credit rating agencies provide information that may reduce the asymmetric information problem between firms and investors. In the case of upgrades, our results are compatible with a redistribution of wealth between bondholders and owners or with the reputation hypothesis.      

Nonlinear predictability of stock market returns: Evidence from nonparametric and threshold models

Recent empirical evidence suggests that stock market returns are predictable from a variety of financial and macroeconomic variables. However, with two exceptions this predictability is based upon a linear functional form. This paper extends this research by considering whether a nonlinear relationship exists between stock market returns and these conditioning variables, and whether this nonlinearity can be exploited for forecast improvements. General nonlinearities are examined using a nonparametric regression technique, which suggest possible threshold behaviour. This leads to estimation of a smooth-transition threshold type model, with the results indicating an improved in-sample performance and marginally superior out-of-sample forecast results.     

Noise trading, transaction costs, and the relationship of stock returns and trading volume

This article constructs an economic model of a rational trader who operates in a market with transaction costs and noise trading. The level of trading affects the rational trader's marginal cost of transacting; as a result, trading volume (through its effect on marginal cost) is a source of risk. This engenders an equilibrium relationship between returns and volume. The model also provides a simple way to scrutinize this relationship empirically. Empirical evidence supports the implications of the model.     

Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach

In this paper, we re-examine the relationship between oil price and stock prices in oil exporting and oil importing countries in the following distinct ways. First, we account for possible nonlinearities in the relationship in order to quantify the asymmetric response of stock prices of these two categories to positive and negative oil price changes. Secondly, in order to capture within group differences, we allow for heterogeneity effect in the cross-sections by formulating a nonlinear Panel ARDL model which is the panel data representation of the Shin et al. (2014) model and also analogous to the non-stationary heterogenous panel data model. Thirdly, we evaluate the relative predictability of the linear (symmetric) and nonlinear (asymmetric) Panel ARDL models using the Campbell and Thompson (2008) test. Our results depict that stock prices of both oil exporting and oil importing groups respond asymmetrically to changes in oil price although the response is stronger in the latter than the former. This finding is further corroborated by the out-of-sample forecast results suggesting that the inclusion of positive and negative oil price changes in the predictive model for stock prices will produce better forecast results only for the oil importing countries. Our results are robust to different oil price proxies, lag structure and in-sample periods. Overall, the dichotomy between oil exporting and oil importing countries has implications on oil price-stock nexus.     

A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach

In this article, we re-examine the causality between the stock returns and investor sentiment in China. The number of net added accounts is used as a proxy for investor sentiment. To mimic the different investment horizons of market participants, we use the wavelet method to decompose stock returns and investor sentiment into time series with different frequencies. Additionally, we test for nonlinear causal relationships based on Taylor series approximation. Our results indicate that there is a one-directional linear causality from stock returns to investor sentiment on the original series, while there is a strong bi-directional nonlinear causality between stock returns and investor sentiment at different timescales.