Financial Anomalies Research Articles

The Millennials Acts in Finance

This paper demonstrates that the Millennials exhibit a unique personality treats that has implications on their portfolio choice, and hence on the stock market. Specifically, Millennials display greater propensity to participate in the stock market, exhibit more confident, as they trade more frequently, and more diverse (invest more in many stocks and foreign assets). At the macro level, we find that the stock market behaves differently surrounding holidays, and the statistical significance of key financial anomalies disrupted. Collectively, we infer that the financial market not only exposed to business cycles, but also to generation cycles.

Momentum Effect, Value Effect, Risk Premium and Predictability of Stock Returns - A Study on Indian Market

Efficient market hypothesis (EMH), one of the central pillars of modern financial theories, often fails to explain the ?financial anomalies?. One fatal challenge of EMH probably comes from the theoretical assumption of ?rational man?. According to EMH, the fully rational investor may change his demand for financial assets on the basis of available information. According to EMH, at any given point of time, the stock price should reflect all the available information, and predictability of stock returns should be impossible. However, the literature shows ample evidence of abnormal returns related to firm and market specific attributes. In financial literature, these variations are often termed as ?financial anomalies?. Within the framework of behavioural finance, there are research results that contain evidence on predictability of future stock market returns based on financial anomalies (Stanivuk et al., 2012). Value effect and momentum effect are the two prominent financial anomalies (Ho, 2012). This paper explores the predictability of Indian stock market returns using multiple discriminant analysis. Our result shows that the risk premium, momentum and value effect may have significant power for predicting the Indian stock market returns. The validity test of the model also corroborates the impact of financial anomalies over predictability of stock returns.

Holidays Financial Anomalies

We introduce new financial calendar anomalies on post holidays as well as best and worst day of the year. We find that the excess return in the stock market abnormal returns post major holidays: Thanksgiving (Black Friday), Christmas and New Year. Furthermore, we analyze the best and worst day of the year to invest and find that December 30th and October 19th are the best and worst days in a calendar year to invest, respectively. Our results are robust as we account for time fixed effect. Collectively, our results suggests that stock market has abnormal return on post holidays.

Modeling growth rates and anomalies of financing, investment and dividend decisions

As far as uncertainty is prevalent, financial anomalies increase the complexity of financial decisions. The possible consequence of an anomaly is either an over or underreaction. This paper suggests that the use of mathematical programming can lessen the degree of complexity when planning for financing, investment and dividend decisions. The authors develop a comprehensive form of the External Financing Needed model in order to show the generic and combined relationship among the three financial decisions. The comprehensive model shows nonlinear relationships between the three financial decisions. The paper uses a simulated numerical example to illustrate how financial objective functions (e.g. targets) can be set out under certain constraints. The latter serve as a remedy for financial anomalies. The results show that financing, investment and dividend decisions can be made optimally to serve having consistent financial statements.

Investor sentiment, heterogeneous agents and asset pricing model

This paper presents a sentiment asset pricing model with heterogeneous agents. In the model, the sentiment equilibrium prices have a number proportion-weighted average structure among heterogeneous investors, and idiosyncratic sentiments can have a significant impact on the equilibrium price at the aggregate level because the demand function is nonlinear in the sentiment. Moreover, we also find that even if the individual sentiment affects the demand in a linear way, the sentiment may still has a significant effect on the equilibrium price in the aggregate due to the fluctuation of the number distribution of investors. The model could offer a partial explanation to the financial anomaly of overreaction.

News and social media emotions in the commodity market

PurposeEmotion plays a significant role in both institutional and individual investors’ decision-making process. Emotions affect the perception of risk and the assessment of monetary value. However, there is a lack of empirical evidence available that addresses how investors’ emotions affect commodity market returns. The purpose of this paper is to investigate whether media-based emotions can be used to predict future commodity returns.Design/methodology/approachThe authors examine the short-term predictive power of media-based emotion indices on the following five days’ commodity returns. The research adopts a proprietary data set of commodity-specific market emotions, which is computed based on a comprehensive textual analysis of sources from newswires, internet news sources and social media. Time series econometrics models (threshold generalized autoregressive conditional heteroskedasticity and vector autoregressive) are employed to analyze 14 years (January 1998-December 2011) of daily observations of the CRB commodity market index, crude oil and gold returns, and the market-level sentiments and emotions (optimism, fear and joy).FindingsThe empirical results suggest that the commodity-specific emotions (optimism, fear and joy) have significant influence on individual commodity returns, but not on commodity market index returns. Additionally, the research findings support the short-term predictability of the commodity-specific emotions on the following five days’ individual commodity returns. Compared to the previous studies of news sentiment on commodity returns (Borovkova, 2011; Borovkova and Mahakena, 2015; Smales, 2014), this research provides further evidence of the effects of news and social media-based emotions (optimism, fear and joy) in the commodity market. Additionally, this work proposes that market emotion incorporates both a sentimental effect and appraisal effect on commodity returns. Empirical results are shown to support both the sentimental effect and appraisal effect when market sentiment is controlled in crude oil and gold spot markets.Originality/valueThis paper adopts the valence-arousal approach and cognitive appraisal approach to explain financial anomalies caused by investors’ emotions. Additionally, this is the first paper to explore the predictive power of investors’ emotions (optimism, fear and joy) on commodity returns.

Autosimilarty, Long Memory and Chaos: Evidence from the Tunisian Market

Fractal Finance came to the rescue of the classical models unable to explain financial anomalies and of linear models inadequate to characterize complex processes. The characterization of financial series is still topical. The calculation of the Hurst exponent, the fractal dimension, the Lyapunov exponent, the window of Theiler and the realization of the determinism test, have allowed us to understand the dynamics of the Tunisian indexes returns. Clearly, findings show that the returns are, on the one hand, nonlinear, follow alpha-stable laws, have a long memory and on the other hand, are not chaotic. Thus, the hypothesis of a Brownian fractal motion is privileged.

IPO Price, Heterogeneous Priors and Gradual Information Flows

This paper attempts to develop a theoretical framework that builds on heterogeneous beliefs to explain the financial anomalies related to IPO stocks. In particular, we develop a dynamic analysis framework to study the valuation of IPO price and the short-term probability of falling below IPO price based on perspectives of investors' heterogeneous priors and gradual information flow. Our study shows that the valuation of IPO price increases as the degree of heterogeneity due to investors' heterogeneous priors increases. Moreover, the short-term probability of falling below IPO price increases as the degree of investors' cognitive biases caused by gradual information flow increases.

Does Disagreement Explain Financial Anomalies?

We find that disagreement helps explain well-known ten cross-sectional financial anomalies. Specifically, we first show that the underperformance of short legs of the anomalies is most pronounced among high disagreement stocks. This results in stronger financial anomalies among high disagreement stocks, and stronger disagreement effect among stocks in the short legs. Also, the disagreement-mimicking portfolio (return spread between low and high disagreement stocks) subsumes the profits from the long-short anomaly strategies. Finally, disagreement-induced overpricing significantly contributes to the effect of investor sentiment on financial anomalies (Stambaugh, Yu, and Yuan, 2012). Overall evidence highlights the contribution of disagreement to financial anomalies.

Real Anomalies: Are Financial Markets a Sideshow?

We examine the importance of asset pricing anomalies on the real economy. In order to assess distortions quantitatively, we estimate the joint dynamic distribution of firm characteristics that have been linked to anomalies, and other firm variables, such as investment, capital, and value added. Based on a model that matches these joint dynamics, we then evaluate the counterfactual dynamic distribution of these quantities absent financial market imperfections and find that they can cause significant deviations. Financial market anomalies can thus cause material real inefficiencies. This implies that financial intermediaries that reduce and/or eliminate such market imperfections can provide large value added to the economy. We show that mispricing is particularly destructive for high Tobin’s q firms. Further, the persistence and the amount of mispriced capital are a major determinant of the real economic consequences. Our flexible framework can be extended to evaluate the potential real effects associated with the ever-growing set of financial market imperfections.

Aversion of information ambiguity and momentum effect in China’s stock market

Purpose – The empirical studies have indicated that the information uncertainty is one of the reasons leading to the momentum effect in the stock market. Based on this conclusion, the concept of “information uncertainty” is deepened into the concept hierarchy of “information ambiguity,” the purpose of this paper is to explain the momentum effect in the China’s stock market from information ambiguity. Design/methodology/approach – Based on the information ambiguity, the paper puts forward two hypotheses, portfolio analysis and cross-sectional regression analysis method were used to empirically test these hypothesis based on the weekly data. Findings – The empirical results support the two hypotheses. Originality/value – Finally, the paper discusses the importance from ambiguity to understand financial anomalies, such as momentum effect.

Financial Distress and Accrual Anomaly: Evidence from the Vietnamese Stock Market

We examine three widely debated topics in accounting and finance: financial distress, accounting choices and accrual anomaly. We find that the differential persistence of accruals and cash flows is significantly larger for firms with lower financial distress risk. Accordingly, accrual anomaly is economically and statistically positive for firms with low financial distress risk, but insignificant for those with high financial distress risk. We also find that firms with high financial distress risk practice more conservative accounting than those with low financial distress risk. These findings suggest that creditors’ monitoring prevents managers of distressed firms from aggressive accounting choices.

Sentiment approach to underestimation and overestimation pricing model

Based on the underestimation model in bear markets and the overestimation model in bull markets, we propose two types of sentiment asset pricing models to study the effects of investor sentiment on stock prices and limit of arbitrage. The two sentiment asset pricing models demonstrate that investor sentiment has a systematic and significant impact on stock prices; furthermore, investor sentiment plays a significant role on the limit of arbitrage. We find that our framework can be helpful in understanding a range of financial anomalies: overreaction, underreaction, the fire sales and the limit of arbitrage.

Beyond Momentum: Investigating Statistical Learning for Winners--Minus--Losers Anomalies

Financial market anomalies are reviewed and categorized, and the “winners minus losers” anomalies - short-term reversal, Momentum and long-term reversion - are discussed. Literature on extensions to the Momentum anomaly, by incorporating market and fundamental information, is examined. Statistical learning strategies are reviewed, with the goal of applying them to consolidating and improving Momentum.

Back to the Future. A Behavioural Perspective on Technical Analysis into PIGS Countries

(ProQuest: ... denotes formulae omitted.)1. IntroductionDuring the economic recession that started in 2008, some members of the European Union, namely: Portugal, Italy, Greece and Spain, were grouped together and given the acronym PIGS. The reason why these countries were grouped together is due to the great weakness and instability of their economies which became a very big and open problem in 2009. Several members of PIGS were in serious financial trouble due to their external or sovereign debt. Their debt became very risky due to their weak economy.Accurately predicting the future is a difficult thing in any academic discipline, particularly in a discipline that involves limitless human interactions. For a discipline like behavioural finance, which focuses on the study of worldly human behavior, there is too much timeless abstraction and too little scrutiny of real-world events. The typical economics theory (Efficient Market - EMH) starts with the study of how rational agents interact in frictionless markets, producing an outcome that is best for everyone. In the early 1990s, several financial economists conducted studies in the field of behavioural finance. Behavioural finance isfinance from a broader social science perspective including psychology and sociology (Shiller 2003).Technical analysis is the study of prices of stocks, with charts as the primary tool, to make better investments. In other words, technical analysis is a methodology for forecasting the direction of stock prices through the study of past market data, primarily price and volume (Kirkpatrick & Dahlquist 2006). The basic idea of technical analysis is to forecast the equity prices based on past prices.In behavioral theories, investors suffer from cognitive biases and cannot process available information rationally (Thaler 1993). Consistent with the experimental results that motivate behavioral finance, the background assumption in most behavioral theories is that investors act irrationally. In contrast, Efficient Market Theory states that security prices represent everything that is known about the security at a given moment. This theory concludes the notion that it is impossible to forecast prices, since prices already reflect everything that is currently known about the security. In behavioural finance, it is observed that there are rational and irrational expectations about returns. The same applies to technical analysis.In behavioral economics and quantitative analysis, the same tools of technical analysis are mostly used (Mizrach & Weerts 2009; Azzopardi 2010). Shiller (1981) attributed financial anomalies to irrationality, using the evidence that stock prices move too much relative to news about future dividends. Lakonishok et al. (1994) presented evidence to show that excess returns earned by portfolios based on publicly available accounting and price data are consistent with excessive extrapolation of past performance into the future. Hong & Stein (1999) also studied overreaction and underreaction, modelling the interactions of traders who follow price trends. Brav & Heaton (2002) showed that rational uncertainty and behavioral biases can deliver similar price patterns. In behavioural models, noise traders buy when prices rise and sell when prices fall, the same as technical analysis.Several studies tried to incorporate the Behavioural phenomenon into Technical Analysis. Behavioural models suggest that technical trading profits may be available even in the long run if technical trading strategies are based on noise or other models and not on information such as news or fundamental factors (Shleifer & Summers, 1990). According to some articles from the psychological literature (Mussweiler 2003; Mussweiler & Strack 1999b; Tversky & Kahneman 1974), investment decisions are likely to be influenced by past prices as depicted in charts. They suggested that investors' expectations about future stock prices are assimilated to a salient high or low on the chart. …

Multi-period sentiment asset pricing model with information

This paper presents a multi-period trading sentiment asset pricing model under asymmetric information. In the model, the rational investor trades on information so that the information is gradually incorporated into prices, whereas the sentiment investor trades on sentiment as if it were information. Moreover, the speed of information incorporated into price becomes faster and faster, while the speed of sentiment factored into price gets slower and slower over time. We find that the existence of sentiment investor makes financial market possible, but decreases market efficiency. The model also offers a partial explanation to the financial anomalies of short-run momentum and long-term reversal.

A Cold Shower for the Hot Hand Fallacy

The hot hand fallacy has long been considered a massive and widespread cognitive illusion with important implications in economics and finance. We develop a novel empirical strategy to correct for limitations in the canonical study and replications, conduct an improved field experiment to test for the hot hand in its original domain (basketball shooting), and gather all extant controlled shooting data. In contrast with the previous results, we find strong evidence of hot hand shooting in every dataset, and that expert observers can predict which shooters have a tendency to become hot.

Transformations of Efficient Market Hypothesis under the Influence of Behavioral Finance

The paper provides a theoretical study on efficient market hypothesis (EMH) changes under the influence of behavioral finance. Authors of the paper briefly provide the basic assumptions of efficient markets theory and remind how the top of its dominance was reached in the 1970s. At the same time the goal of the paper is to develop the unbiased and complex overview of the today’s market efficiency and show its transformations under the impact of market participants’ irrationality. In the paper authors introduce the interaction between market efficiency, market arbitrage, irrationality of market participants and highlight the importance to revise the reliability of efficient market theory assumptions in order to achieve high performance of investment portfolios. Through the behavioral finance point of view authors not only aggregate the critics EMH faces during the recent years, but also evaluate today’s opportunities for arbitrage and provide arbitrage critics. According to documented by experimental economists departures from market efficiency and taking into consideration their nature, i.e. investors’ irrationality as a result of influence of a set of specific behavioral (both cognitive and emotional) biases, an alternative to EMH approach called “The Adaptive Markets Hypothesis” espoused by Andrew Lo in 2004 is introduced. The supporters of the EMH have responded to these challenges by arguing that, while behavioral biases and corresponding inefficiencies do exist from time to time, there is a limit to their prevalence and impact because of opposing forces dedicated to exploiting such opportunities. Finally, basic financial market anomalies are presented in the paper as an example of market inefficiency. On the one hand, their persistence in the face of public scrutiny seems to be a clear violation of the EMH. On the other - most of these anomalies can be exploited by relatively simple trading strategies, and, while the resulting profits may not be riskless, they seem usually profitable relative to their risks. Summing up of the investigation presented in the paper, authors conclude that many classical EMH supporters set the cases theoretically without empirical or real measurement analysis. Therefore the discussion on EMH is still on-going, but real market analysis should be done instead of evolving EMH theoretical evaluation models, which remain theoretical and do not always work properly in the conditions of real financial market. DOI: 10.5901/mjss.2014.v5n13p327

Agent-based Modeling and Investors’ Behavior Explanation of Asset Price Dynamics on Artificial Financial Markets

Standard asset pricing models based on rational expectations and homogeneity have problems explaining the complex and volatile nature of financial markets. The heterogeneity in expectations can lead to market instability and complicate dynamics of prices, which are driven by endogenous market forces. In this sense, we use Agent-based computational approach and more specifically artificial Stock Market modeling to explore the market dynamics from a behavioral perspective. Our aim is to point out that the investors’ irrationality explains various numbers of financial anomalies, especially the phenomena that traditional financials models have never been able to explain. We built a virtual financial market that contains three types of investors: fundamentalists, non-fundamentalist and loss adverse investors. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Dynamic sentiment asset pricing model

Conventional wisdom suggests that the equilibrium stock price is not affected by investor sentiment, and the equilibrium price at an early time is higher than the one at a later time. In contrast to this wisdom, we present a dynamic asset pricing model with investor sentiment and we find that investor sentiment has a significant impact on the equilibrium stock price. The equilibrium stock price, which is affected by pessimistic sentiment at time 0, may be lower than the one at time 1. Moreover, consistent with the reality stock market, our model shows that time varying sentiments can lead to various price changes. Finally, the model could offer a partial explanation for the financial anomaly of high volatility.