Measuring gambling activity in options market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bei Chen ◽  
Quan Gan

PurposeThis paper investigates how the gambling measure captures market bubble events, and how it predicts stock return and option return.Design/methodology/approachThis paper proposes a gambling activity measure by jointly considering open interest and moneyness of out-of-the-money (OTM) individual equity call options.FindingsThe 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.Originality/valueThe 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.

2013 ◽  
Vol 48 (5) ◽  
pp. 1519-1544 ◽  
Author(s):  
George J. Jiang ◽  
Tong Yao

AbstractWe identify large discontinuous changes, known as jumps, in daily stock prices and explore the role of jumps in cross-sectional stock return predictability. Our results show that small and illiquid stocks have higher jump returns to the extent that cross-sectional differences in jumps fully account for the size and illiquidity effects. Based on value-weighted portfolios, jumps also account for the value premium. On the other hand, jumps are not the cause of momentum or net share issue effects. The findings of our study shed new light on stock return dynamics and present challenges to conventional explanations of stock return predictability.


2017 ◽  
Vol 7 (1) ◽  
pp. 33-66 ◽  
Author(s):  
Worawuth Kongsilp ◽  
Cesario Mateus

Purpose The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis. Design/methodology/approach Using a broad sample of stock options traded on the American Stock Exchange and the Chicago Board Options Exchange from January 2001 to December 2010, the effect of different idiosyncratic volatility forecasting measures are examined on future stock returns in four different periods (Bear and Bull markets). Findings First, the authors find clear and robust empirical evidence that the implied idiosyncratic volatility is the best stock return predictor for every sub-period both in Bear and Bull markets. Second, the cross-section firm-specific characteristics are important when it comes to stock returns forecasts, as the latter have mixed positive and negative effects on Bear and Bull markets. Third, the authors provide evidence that short selling constraints impact negatively on stock returns for only a Bull market and that liquidity is meaningless for both Bear and Bull markets after the recent financial crisis. Practical implications These results would be helpful to disclose more information on the best idiosyncratic volatility measure to be implemented in global financial crises. Originality/value This study empirically analyses the effect of different idiosyncratic volatility measures for a period that involves both the dotcom bubble and the recent financial crisis in four different periods (Bear and Bull markets) and contributes the existing literature on volatility measures, volatility risk and stock return predictability in global financial crises.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asgar Ali ◽  
Manish Bansal

PurposeThe current study aims at examining the impact of upward and downward earnings management on the cross-sections of stock return. The study also examines the moderating role of cross-sectional effects on the association between earnings management and stock returns.Design/methodology/approachThe study employed univariate and bivariate-sorted portfolio-level analysis to investigate the issue. Fama–Macbeth cross-sectional regression is used to analyze the moderating role of different cross-sectional effects. The study used a sample of 3085 Bombay Stock Exchange (BSE) listed stocks spanning over 20 years from January 2000 to December 2019.FindingsThe findings suggest that investors have different perceptions toward different forms of earnings management. In other words, results exhibit that investors perceive downward earnings management as an element of risk; hence, they discount the returns at a higher rate. On the contrary, results show that upward earnings management is positively perceived by the investors; hence, they hold the stocks even at a lower rate of return. This relation is found to be consistent even after controlling the impact of marker effect, size effect, value effect and momentum effect.Originality/valueThis study is among pioneering studies that consider the direction of earnings management while examining its impact on the stock return. This study is also among the earlier attempts to examine the moderating role of four different cross-sectional effects by taking a uniform sample of stocks over the same period.


2015 ◽  
Vol 41 (12) ◽  
pp. 1280-1297
Author(s):  
Keming Li ◽  
Mohammad Riaz Uddin ◽  
J. David Diltz

Purpose – Prior research has documented the role of information uncertainty in the cross-sectional variation in stock returns. Miller (1977) hypothesizes that if information uncertainty is caused by differences of opinion, prices will reflect only the positive beliefs due to short-sale constraints. These anomalous stock price behaviors may result from mispricing. In contrast, Merton (1974) asserts that default risk is a function of the uncertainty in the asset value process. Information uncertainty may be subsumed by credit or default risk. The paper aims to discuss these issues. Design/methodology/approach – The authors employ various sorting techniques and Fama-MacBeth Regressions to test the hypotheses. Findings – The authors provide empirical evidence consistent with Merton’s (1974) default risk hypothesis and inconsistent with Miller’s (1977) mispricing hypothesis. Research limitations/implications – Risk aversion and not misplacing is the primary factor driving information-related anomalies in equities markets. Practical implications – It would be quite difficult to find arbitrage opportunities in equities markets because there appears to be little, if any, mis-pricing due to information uncertainties. Originality/value – This study provides important information about the primary underlying information-related source of certain empirical anomalies in the cross-section of stock returns.


2020 ◽  
Vol 12 (4) ◽  
pp. 435-454
Author(s):  
Madhumita Chakraborty ◽  
Sowmya Subramaniam

PurposeThe study examines the cross-sectional and asymmetric relationship of investor sentiment with the stock returns and volatility in India.Design/methodology/approachThe investor sentiment is captured using a market-based measure Market Mood Index (MMI) and a survey-based measure Consumer Sentiment Index (CSI). The asymmetric effect of the relationship is examined using quantile causality approach and cross-sectional effect is examined by considering indices such as the BSE Sensex, and the various size indices such as BSE Large cap, BSE Mid cap and BSE Small cap.FindingsThe result of the study found that investor sentiment (MMI) cause stock returns at extreme quantiles. Lower sentiment induces fear-induced selling, thereby lowers the returns and high sentiment is followed by lower future returns as market reverts to fundamentals. On the other hand, bullish shifts in sentiment lower the volatility. There exists a positive feedback effect of stock return and volatility in the formation of investor sentiment.Originality/valueThe study captures both asymmetric and cross-sectional relationship of investor sentiment and stock market in an emerging economy, India. The study uses a novel data set (i.e.) MMI which captures the sentiment based on market indicators and are widely disseminated to the public.


2017 ◽  
Vol 30 (4) ◽  
pp. 379-394 ◽  
Author(s):  
Raheel Safdar ◽  
Chen Yan

Purpose This study aims to investigate information risk in relation to stock returns of a firm and whether information risk is priced in China. Design/methodology/approach The authors used accruals quality (AQ) as their measure of information risk and performed Fama-Macbeth regressions to investigate association of AQ with future realized stock returns. Moreover, two-stage cross-sectional regression analysis was performed, both at firm level and at portfolio level, to test if the AQ factor is priced in China in addition to existing factors in the Fama French three-factor model. Findings The authors found poor AQ being associated with higher future realized stock returns. Moreover, they found evidence of market pricing of AQ in addition to existing factors in the Fama French three-factor model. Further, subsample analysis revealed that investors value AQ more in non-state owned enterprises than in state owned enterprises. Research limitations/implications The study sample comprises A-shares only and the generalization of the findings is limited by the peculiar institutional and economic setup in China. Originality/value This study contributes to market-based accounting literature by providing further insight into how and if investors value information risk, and it seeks to fill gap in empirical literature by providing evidence from the Chinese capital market.


2008 ◽  
Vol 16 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Robyn McLaughlin ◽  
Assem Safieddine

PurposeThis paper seeks to examine the potential for regulation to reduce information asymmetries between firm insiders and outside investors.Design/methodology/approachExtensive prior research has established that there are substantial effects of information asymmetry in seasoned equity offers (SEOs). The paper tests for a mitigating effect of regulation on such information asymmetries by examining differences in long‐run operating performance, changes in that performance, and announcement‐period stock returns between unregulated industrial firms and regulated utilities that issue seasoned equity. The authors also segment the samples by firm size, since smaller firms are likely to have greater asymmetries.FindingsConsistent with regulated utility firms having lower levels of information asymmetry, they have superior changes in abnormal operating performance than industrial firms pre‐ to post‐issue and their announcement period returns are significantly less negative. These findings are most pronounced for the smallest firms, firms likely to have the greatest information asymmetries and where regulation could have its greatest effect.Research limitations/implicationsThe paper does not examine costs of regulation. Thus, future research could seek to measure the cost/benefit trade‐off of regulation in reducing information asymmetry. Also, future research could examine cross‐sectional differences between different industries and regulated utilities.Practical implicationsRegulation reduces information asymmetry. Thus, regulation or mandated disclosure may be appropriate in industries/markets where information asymmetry is severe.Originality/valueThis paper is the first to compare the operating performance of regulated and unregulated SEO firms.


2014 ◽  
Vol 40 (3) ◽  
pp. 300-324 ◽  
Author(s):  
Véronique Bessière ◽  
Taoufik Elkemali

Purpose – This article aims to examine the link between uncertainty and analysts' reaction to earnings announcements for a sample of European firms during the period 1997-2007. In the same way as Daniel et al., the authors posit that overconfidence leads to an overreaction to private information followed by an underreaction when the information becomes public. Design/methodology/approach – In this study, the authors test analysts' overconfidence through the overreaction preceding a public announcement followed by an underreaction after the announcement. If overconfidence occurs, over- and underreactions should be, respectively, observed before and after the public announcement. If uncertainty boosts overconfidence, the authors predict that these two combined misreactions should be stronger when uncertainty is higher. Uncertainty is defined according to technology intensity, and separate two types of firms: high-tech or low-tech. The authors use a sample of European firms during the period 1997-2007. Findings – The results support the overconfidence hypothesis. The authors jointly observe the two phenomena of under- and overreaction. Overreaction occurs when the information has not yet been made public and disappears just after public release. The results also show that both effects are more important for the high-tech subsample. For robustness, the authors sort the sample using analyst forecast dispersion as a proxy for uncertainty and obtain similar results. The authors also document that the high-tech stocks crash in 2000-2001 moderated the overconfidence of analysts, which then strongly declined during the post-crash period. Originality/value – This study offers interesting insights in two ways. First, in the area of financial markets, it provides a test of a major over- and underreaction model and implements it to analysts' reactions through their revisions (versus investors' reactions through stock returns). Second, in a broader way, it deals with the link between uncertainty and biases. The results are consistent with the experimental evidence and extend it to a cross-sectional analysis that reinforces it as pointed out by Kumar.


2016 ◽  
Vol 24 (3) ◽  
pp. 343-362
Author(s):  
Latif Cem Osken ◽  
Ceylan Onay ◽  
Gözde Unal

Purpose This paper aims to analyze the dynamics of the security lending process and lending markets to identify the market-wide variables reflecting the characteristics of the stock borrowed and to measure the credit risk arising from lending contracts. Design/methodology/approach Using the data provided by Istanbul Settlement and Custody Bank on the equity lending contracts of Securities Lending and Borrowing Market between 2010 and 2012 and the data provided by Borsa Istanbul on Equity Market transactions for the same timeframe, this paper analyzes whether stock price volatility, stock returns, return per unit amount of risk and relative liquidity of lending market and equity market affect the defaults of lending contracts by using both linear regression and ordinary least squares regression for robustness and proxying the concepts of relative liquidity, volatility and return constructs by more than variable to correlate findings. Findings The results illustrate a statistically significant relationship between volatility and the default state of the lending contracts but fail to establish a connection between default states and stock returns or relative liquidity of markets. Research limitations/implications With the increasing pressure for clearing security lending contracts in central counterparties, it is imperative for both central counterparties and regulators to be able to precisely measure the risk exposure due to security lending transactions. The results gained from a limited set of lending transactions merit further studies to identify non-borrower and non-systemic credit risk determinants. Originality/value This is the first study to analyze the non-borrower and non-systemic credit risk determinants in security lending markets.


Author(s):  
Söhnke M. Bartram ◽  
Harald Lohre ◽  
Peter F. Pope ◽  
Ananthalakshmi Ranganathan

AbstractThe literature on cross-sectional stock return predictability has documented over 450 factors. We take the perspective of an institutional investor and navigate this zoo of factors by focusing on the evidence relevant to the practicalities of factor-based investment strategies. Establishing a sound theoretical rationale is key to identifying “true” factors, and we emphasize the need to recognize data-mining concerns that may cast doubt on the relevance of many factors. From a practical investment perspective, much of the factor evidence documented by academics may be more apparent than real. The performance of many factors is dependent on the inclusion of small- and micro-cap stocks in academic studies, although such stocks would likely be excluded from the real investment universe due to illiquidity and transaction costs. Nevertheless, a parsimonious set of factors emerges in equities and other asset classes, including currencies, fixed income, and commodities. These factors can serve as meaningful ingredients to factor-based portfolio construction.


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