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In the current study, the significance of extreme positive returns has been investigated in the pricing of stocks in the Indian equity market. This study aims to understand if investors in India have a preference for lottery-like stocks. The existing literature provides support for MAX effect in several countries, where risk seeking in the form of gambling is an acceptable form of social behavior, suggesting a preference for lottery-like stocks. This motivates the authors to investigate whether such preference for lottery-like stocks is prevalent in a country such as India with a different cultural setting, where gambling is not socially and legally encouraged.

The MAX effect is tested in the Indian market for the period from January 2003 to March 2017. The average number of firms per month in this study is 2,949. Univariate and bivariate portfolio-level analyses, as well as Fama MacBeth regressions, are conducted to observe the difference between average raw and risk-adjusted returns between the stocks lying in the highest and lowest MAX deciles. Several tests have been performed for checking the robustness of the findings.

Unlike the extant literature, the authors have not found any evidence of a negative relationship between extreme positive returns and expected returns. The univariate and bivariate analyses suggest that high MAX deciles over-perform low MAX deciles. Fama Macbeth regressions also do not support the negative relationship documented for other markets. This suggests that investors are not euphoric about lottery-like stocks in India. One may devise profitable trading strategies by going long on high MAX deciles and short on low MAX deciles.

This study finds a behavioral aspect of Indian investors, which seems to be in contrast to that of other countries. While there is a strong preference for lottery-like stocks in other markets, investors in India do not end up overpaying for such stocks in the market. This tendency might be an outcome of a different social and regulatory setting in India. In view of the fact that India is increasingly becoming an important investment destination, it becomes important to devise investment strategies based on the peculiarities of this market rather than simply extrapolating the findings of other markets.

The purpose of this paper is to investigate a unique sample of lottery-like stocks and contextualize their short-run price behavior with respect to behavioral principles.

The authors conduct a short-run event-study of the abnormal returns for stock market investments in Australian small-cap oil and gas (O & G) explorers centered on the drilling commencement (spudding) of 157 wildcat oil or gas wells drilled between January 2000 and June 2010.

Small-cap stock market investments associated with newly spudded wildcat O & G wells are negative NPV gambles rather than fair (zero NPV) investments. Once a wildcat well is spudded, the 30-day expected abnormal return is 6-8 percent: wealth-maximizing stockholders are advised to sell upon news of spudding, but gamblers may wish to hold on for the chance of a 10.6 percent 30-day average abnormal return (if the well is not plugged and abandoned). In the lead-up to each gamble the authors observe a significant pre-spudding stock price run-up on average, perhaps indicative of positively affected investors aroused by an easily imagined successful wildcat gusher as per evidence on the influence of image and affect on investors’ decisions (MacGregor et al., 2000; Loewenstein et al., 2001; Rottenstreich and Hsee, 2001; Peterson, 2002).

The wildcat drilling events considered in this paper are lottery-like by nature, and spudding represents the distinct moment when the gamble is unambiguously on, following shortly on from which investors either strike it lucky or strike out. The specifically small-cap wildcatters are typically heavily vested in one well at a time, therefore the sample stocks are uniquely lottery like. This differs from other studies which infer the lottery-like nature of their sample stocks from characteristics such as price and idiosyncratic volatility.

This paper investigates how the gambling measure captures market bubble events, and how it predicts stock return and option return.

This paper proposes a gambling activity measure by jointly considering open interest and moneyness of out-of-the-money (OTM) individual equity call options.

The new measure, CallMoney, captures excessive optimism during the dot-com bubble, the oil price bubble and the pre-GFC stock market bubble. CallMoney robustly and negatively predicts both OTM and at-the-money call option returns cross-sectionally. The option return predictability of CallMoney is stronger when stock price is further from its 52-weeks high, capital gains overhang is lower, and when information uncertainty of the underlying stock is higher. CallMoney also robustly and negatively predicts cross-sectional stock returns.

The gambling measure has the advantages of being economically intuitive, model-free, easy to measure. The measure performs more robustly than existing lottery measures with respect to option and stock return predictability and more reliably captures the overpricing of options and stocks. The work helps understanding the gambling related anomalies in equity option returns and stock returns.

This study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.

This study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.

The study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.

This research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.

This study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.

This study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

The study investigates the impact of higher moments on cross-sectional returns in the Indian equity market.

Using the daily data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019, the study evaluates the relationship between higher moments (skewness and kurtosis) and stock returns at individual stock and portfolio levels. The variations in the returns of the equal-weighted and the value-weighted portfolios are analysed, where the portfolios are constructed by sorting the stocks on skewness and kurtosis. The returns are adjusted for five common factors – market excess-returns, size, value, momentum and illiquidity, to controls other cross-sectional effects. Besides, the study employs Fama-MacBeth cross-sectional regression and time-series tests of higher moments as robustness measures.

The study presents higher moments anomaly in the Indian equity market. Contrary to what is expected based on a risk-averse rational agent model, a robust positive relationship is observed between the skewness and stock returns. The relationship between the kurtosis and stock returns is negative, albeit statistically weak. These results are robust for the Fama-MacBeth cross-sectional regression and time-series tests.

It is among the earlier attempts to investigate the pricing impact of higher moments at different levels of asset prices in an emerging market. Besides the standard portfolio methodology for explaining cross-sectional variations, the study also employs the time-series tests for higher moment factors, hence provides more robust results. Results have wider implications for asset pricing in emerging markets and highlight many issues for further research.

This paper investigates the role of economic disagreement in the cross-sectional pricing of individual stocks. Economic disagreement is quantified with ex ante measures of cross-sectional dispersion in economic forecasts from the Survey of Professional Forecasters (SPF), determining the degree of disagreement among professional forecasters over changes in economic fundamentals.

The authors introduce a broad index of economic disagreement based on the innovations in the cross-sectional dispersion of economic forecasts for output, inflation and unemployment so that the index is a shock measure that captures different aspects of disagreement over economic fundamentals and also reflects unexpected news or surprise about the state of the aggregate economy. After building the broad index of economic disagreement, the authors test out-of-sample performance of the index in predicting the cross-sectional variation in future stock returns.

Univariate portfolio analyses indicate that decile portfolios that are long in stocks with the lowest disagreement beta and short in stocks with the highest disagreement beta yield a risk-adjusted annual return of 7.2%. The results remain robust after controlling for well-known pricing effects. The results are consistent with a preference-based explanation that ambiguity-averse investors demand extra compensation to hold stocks with high disagreement risk and the investors are willing to pay high prices for stocks with large hedging benefits. The results also support the mispricing hypothesis that the high disagreement beta provides an indirect way to measure dispersed opinion and overpricing.

Most literature measures disagreement about individual stocks with the standard deviation of earnings forecasts made by financial analysts and examines the cross-sectional relation between this measure and individual stock returns. Unlike prior studies, the authors focus on disagreement about the economy instead of disagreement about earnings growth. The authors' argument is that disagreement about the economy is a major factor that would explain disagreement about stock fundamentals. The authors find that disagreement in economic forecasts does indeed have a significant impact on the cross-sectional pricing of individual stocks.

The purpose of this paper is to explore some commonly held beliefs about individuals investing in over-the-counter (OTC) stocks (those traded on Over-the-counter Bulletin Board (OTCBB) and Pink Sheets), a fairly pervasive activity. The authors frame the analysis within the context of direct gambling, aspirational preferences in behavioral portfolios, and private information.

Contrary to popular perceptions, the modeling of the deliberate act of buying OTC stocks at a discount brokerage house finds that unlike the typical lottery buyers/gamblers, OTC investors are older, wealthier, more experienced at investing, and display greater portfolio diversification than their non-OTC investing counterparts.

Behavioral portfolio investors (Shefrin and Statman, 2000) invest their money in layers, each of which corresponds to an aspiration or goal. Consistent with sensation seeking and aspirations in behavioral portfolios, OTC investors also display higher trading activity. Penny stocks seem to have different characteristics and trading behavior than other OTC stocks priced over one dollar. Irrespective of the price of OTC stocks, the authors find little evidence of information content in OTC trades.

The paper provides insight into individual investor decision making by empirically exploring the demographic and portfolio characteristics of individuals trading in OTC stocks.

The portfolio of low-risk stocks outperforms the portfolio of high-risk stocks and market portfolios on a risk-adjusted basis. This phenomenon is called the low-risk effect. There are several economic and behavioral explanations for the existence and persistence of such an effect. However, it is still unclear whether specific sector orientation drives the low-risk effect. The study seeks to answer the following important questions in Indian equity markets: (a) Whether sector bets or stock bets mainly drive the low-risk effect? (b) Is it a mere proxy for the well-known value effect? (c) Does the low-risk effect prevail in long-only portfolios?

The study is based on all the listed stocks on the National Stock Exchange (NSE) of India from December 1994 to September 2018. It classifies them into 11 Global Industry Classification Standard (GICS) sectors to construct stock-level and sector-level BAB (Betting Against Beta) and long-only low-risk portfolios. It follows the study of Asness et al. (2014) to construct various BAB portfolios. It applies Fama–French (FF) three-factor and Fama–French–Carhart (FFC) four-factor asset pricing models in addition to Capital Asset Pricing Model (CAPM) to examine the strength of BAB, sector-level BAB, stock-level BAB and long-only low-beta portfolios.

Both sector- and stock-level bets contribute to the return of the low-risk investing strategy, but the stock-level effect is dominant. Only betting on safe sectors or industries will not earn economically significant alpha. The low-risk effect is unique and not a value effect in disguise. Both long-short and long-only portfolios within sectors and industry groups deliver positive excess returns. Consumer staples, financial, materials and healthcare sectors mainly contribute to the returns of the low-risk effect in India. This study offers empirical evidence against the Samuelson (1998) micro-efficient market given the strong performance of the stock-level low-risk effect.

The superior performance of the low-risk investment strategies at both stock and sector levels offers investors an opportunity to strategically invest in stocks from the right sectors and earn high risk-adjusted returns with lower drawdowns over an entire market cycle. Besides, it paves the way for stock exchanges and index manufacturers to launch sector-specific low-volatility indices for relevant sectors. Passive funds can launch index funds and exchange-traded funds by tracking these indices. Active fund managers can espouse sector-specific low-risk investment strategies based on the results of this and similar other studies.

The study is the first of its kind. It offers insights into the portfolio characteristics and performance of the long-short and the long-only variant of low-risk portfolios within sectors and industry groups. It decomposes the low-risk effect into sector-level and stock-level effects.