Costly Interpretation of Asset Prices

We propose a model in which investors cannot costlessly process information from asset prices. At the trading stage, investors are boundedly rational, and their interpretation of prices injects noise into the price, generating a source of endogenous noise trading. Our setup predicts price momentum and yields excessive return volatility and excessive trading volume. In an overall equilibrium, investors optimally choose sophistication levels by balancing the benefit of beating the market against the cost of acquiring sophistication. There can exist strategic complementarity in sophistication acquisition, leading to multiple equilibria. This paper was accepted by Gustavo Manso, finance.

Analysis of Volatility Volume and Open Interest for Nifty Index Futures Using GARCH Analysis and VAR Model

The generalized autoregressive conditional heteroscedastic model (GARCH) is used to estimate volatility for Nifty Index futures on day trades. The purpose is to find out if a contemporaneous or causal relation exists between volatility volume and open interest for Nifty Index futures traded on the National Stock Exchange of India, and the extent and direction of these relationships. A complete absence of bidirectional causality in any particular instance depicts noise trading and empirical analysis according to this study establishes that volume has a stronger impact on volatility compared to open interest. Furthermore, the impulse originating from volatility of volume and open interest is low.

The Impact of Sentiment on Commodity Return and Volatility

This study empirically investigates the effect of investor sentiment on returns and volatility of eight commodities. The findings suggest that sentiment has a predictive power on these commodities’ return and volatility. Fundamentally, return and volatility are positively associated with sentiment, suggesting that investors in the commodity markets are irrational — entailing the existence of noise trading. The results confirm the prediction of the affect infusion model in which optimistic investors are willing to take more risks, thus, raising returns and volatility. Furthermore, sentiment has a significant asymmetrical impact on volatility, and negative sentiment has a significantly greater impact than positive sentiment.

Noise Trading and Single Stock Futures: Modifying Sentana & Wadhwani’s Model

Derivatives,and their influence on the dynamics of underlying stock markets,is an interesting topic of debate, which predates their introduction. The unresolved influence of derivatives on their underlying stock markets still intrigues many. In this regard, researchers/stake holders are still curious about the (de)stabilizing influence of derivatives on the overall market. In disposition of these observations, two contradicting hypothesis have been studied widely and have remained the focus of attention in several theoretical and empirical studies. These hypotheses are explained in several ways. Among many, one explanation refers to the destabilizing influence of derivatives,due to the enhanced involvement of noise traders, after the introduction of derivatives.This aspect remains the topic of discussion for this study. After the formal introduction of the SSFs (Single Stock Futures) in Pakistan, this topic became a cause of concern for the stakeholders of this market as well. Hence, this study attempts to tap into this aspect of the de(stabilization) debate,by proposing a modified version of the famous Sentana & Wadhwani (1982)model. In order to tap the potential shortcomings of the S&W model, this study contributes to the extant literature in several ways: 1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market,due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speaking, the modified version of the model not only extends the original model in terms of its explanation, but also empirically tests this aspect in the Single Stock Futures (SSFs) market of Pakistan. This model tested whether SSFs promote,or inhibit the noise trading post-SSFs. After putting it to test, the newer model did not report any negative or positive impact of the introduction of SSFs on the underlying stocks. This may conclude that the proclaimed (de)stabilizing role of the SSFs,in the context of Pakistan,is not justified.