Entropy Variations of Multi-Scale Returns of Optimal and Noise Traders Engaged in “Bucket Shop Trading”

In this paper a comparative, coarse grained, entropy data analysis of multi-scale log-returns distribution, produced by an ideal “optimal trader” and one thousand “noise traders” performing “bucket shop” trading, by following four different financial daily indices, is presented. A sole optimal trader is assigned to each one of these four analyzed markets, DJIA, IPC, Nikkei and DAX. Distribution of differential entropies of the corresponding multi-scale log-returns of the optimal and noise traders are calculated. Kullback-Leiber distances between the different optimal traders returns distributions are also calculated and results discussed. We show that the entropy of returns distribution of optimal traders for each analyzed market indeed reaches minimum values with respect to entropy distribution of noise traders and we measure this distance in σ units for each analyzed market. We also include a discussion on stationarity of the introduced multi-scale log-returns observable. Finally, a practical application of the obtained results related with ranking markets by their entropy measure as calculated here is presented.

Investor sentiment and liquidity in emerging stock markets

PurposeBehavioral finance and market microstructure studies suggest that the investor sentiment and liquidity are related. This paper aims to examine the aggregate sentiment–liquidity relationship in emerging markets (EMs) for both the sample period and crisis period. Then, it verifies this relationship, using the asymmetric sentiment.Design/methodology/approachThis study uses a sample consisting of stocks listed on the SSE Shanghai composite index (348 stocks), the JKSE (118 stocks), the IPC (14 stocks), the RTS (12 stocks), the WSE (106 stocks) and FTSE/JSE Africa (76 stocks). This is for the period ranging from February, 2002 until March, 2021 (230 monthly observations). We use the panel data and apply generalized method-of-moments (GMM) of dynamic panel estimators.FindingsThe empirical analysis shows the following results: first, it demonstrates a significant relationship between the aggregate investor sentiment and the stock market liquidity for the sample period and crisis one. Second, referring to the asymmetric sentiment, we have empirically given proof that the market is significantly more liquid in times of the optimistic sentiment than it is in times of the pessimistic sentiment. Third, using panel causality tests, we document a unidirectional causality between the investor sentiment and liquidity in a direct manner through the noise traders and the irrational market makers and also a bidirectional causality in an indirect channel.Practical implicationsThe results reported in this paper have implications for regulators and investors in EMs. Firstly, the study informs the regulators that the increases and decreases in the stock market liquidity are related to the investor sentiment, not financial shocks. We empirically evince that the traded value is higher in the crisis. Secondly, we inform insider traders and rational market makers that the persistence of increases in the trading activity in both quiet and turbulent times is associated with investor participants such as noise traders and irrational market makers.Originality/valueThe originality of this work lies in employing the asymmetric sentiment (optimistic/pessimistic) in order to denote the sentiment–liquidity relationship in EMs for the sample period and the 2007–2008 subprime crisis.

Insider Trading with Memory under Random Deadline

In this paper, we study a model of continuous-time insider trading in which noise traders have some memories and the trading stops at a random deadline. By a filtering theory on fractional Brownian motion and the stochastic maximum principle, we obtain a necessary condition of the insider’s optimal strategy, an equation satisfied. It shows that when the volatility of noise traders is constant and the noise traders’ memories become weaker and weaker, the optimal trading intensity and the corresponding residual information tend to those, respectively, when noise traders have no any memory. And, numerical simulation illustrates that if both the trading intensity of the insider and the volatility of noise trades are independent of trading time, the insider’s expected profit is always lower than that when the asset value is disclosed at a finite fixed time; this is because the trading time ahead is a random deadline which yields the loss of the insider’s information.

Islamic index market sentiment: evidence from the ASEAN market

Purpose The purpose of this paper is to examine investor sentiment by measuring the impact of market sentiment shocks on the volatility of the Islamic stock index of five ASEAN countries, with noise traders as a proxy for market sentiment. Design/methodology/approach The GJR-GARCH model is used to capture the empirically observed fact that negative shocks in the past period have a stronger impact on variance than positive shocks in the present. Findings All five ASEAN Islamic stock indices show clustering volatility. However, only three countries, namely, Malaysia, Thailand and Singapore, demonstrate leverage effects. In addition, the effect of market sentiment on Islamic stock index returns is observed in the Indonesian and Malaysian markets, which are the two largest Islamic markets with a dominant Muslim population in the ASEAN. This finding implies that the trading behaviours of Muslim investors in the Shariah market are the same as their behaviours in the conventional market, that is, nonadherence to the Sunnah. Practical implications Whilst establishing investment strategies, creating portfolios and providing client-advisory services, investors and fund managers should factor in the presence of market sentiment and its impact on stock performance and volatility. In addition, a capital market system preventing rumour-based transactions is compelling. Social implications In some markets, the Islamic financial products awareness should be increased through education to attract increased domestic investors with the potential to boost growth in the Islamic stock market. Originality/value Investigation market sentiment impacts on the Islamic stock index using noise traders as a proxy.

Comparing trading behaviour and profit composition in prediction markets

Prediction markets have established itself as forecasting technique, especially within the IT industry. While the majority of existing studies focuses either on the output of such markets or its design settings, the traders who actually produce the forecasts got only little attention yet. Within this work, we develop a classification scheme for traders of a prediction market that is grounded on both, financial and prediction market literature. Over a period of three years, 127 prediction markets have been observed and its 4.329 traders are separated into seven subgroups (beginners, noise traders, average traders, experts, donkey traders, market makers and superior traders), based on their knowledge, experience and selectivity. We find empirical evidence for the existence of these subgroups and thus for the heterogeneity among the traders. For each of these subgroups, we analyze the trading behaviour and the profit composition.

Investor sentiment and the risk-return tradeoff

The purpose of this paper is to investigate the risk-return tradeoff allowing for the presence of noise traders, i.e., a subset of investors who either base their trading strategies on sentiment or hold unjustified optimistic/pessimistic views regarding market prospects. We measure noise traders’ sentiment relying on two sets of indices, namely the Baker and Wurgler sentiment index and the Michigan Consumer Confidence Index, in the US stock market. Under the assumption of the presence of noise traders’ sentiment, the risk-return tradeoff is tested through two sets of models: Merton’s Intertemporal CAPM and the GARCH-in-mean model. First, we find that the relationship between risk and return allowing for the presence of noise trader risk as measured by the Baker and Wurgler sentiment index is positive and statistically significant when tested through Merton’s Intertemporal CAPM. Second, the risk-return tradeoff tested through GARCH-in-mean models augmented by noise traders’ risk as measured through survey-based measures of sentiment establishes no clear evidence for a significant mean–variance relationship. Overall, we confirm Merton’s (1973) hypothesis that the more risk an investor bears, the greater his expected returns. This paper contributes to the asset pricing literature by trying to shed some light on the risk-return tradeoff from the standpoint of behavioral finance.

Individual Investors, Average Skewness, and Market Returns

Understanding individual investors’ short-term behavior toward skewness is essential for the management and investment of corporate social responsibility because the skewness-seeking behavior of individual investors, which causes a bubble in the market, makes the market as a whole more vulnerable, and it is difficult for the market to be sustainable. In the Korean stock market, we investigated whether average skewness can predict future market returns at the market level and whether the mispricing is associated with demand for the skewness of individual noise traders. Measuring the demand for skewness by the proportion of trading money of individual investors, we found that average skewness negatively predicts future market excess return when the demand for skewness is strong. The result is robust to controlling for market variance as well as other predictors. Our finding indicates that the overall market is overpriced when individual investors excessively trade to seek huge returns in spite of a small probability.

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.