Revisiting Overconfidence In Investment Decision-Making: Further Evidence From The U.S. Market

nvestor overconfidence leads to excessive trading due to positive returns, causing inefficiencies in stock markets. Using a novel methodology, we build on the previous literature by investigating the existence of overconfidence by studying the causal relationship between return and trading volume covering the COVID-19 period. We implement a nonlinear approach to Granger causality based on multilayer feedforward neural networks on daily returns and trading volumes from 2016 to 2021, covering 1424 daily observations of the S&P 500 index. The results provide evidence of overconfidence among investors. Such behavior may be linked to the increase in the number of investors. However, there is a decline in the rate of returns during the study period, implying uncertainty caused by the COVID-19 pandemic

Overconfidence bias, over/under-reaction of financial analysts on the Tunisian stock market, and their impact on the earnings forecasts

This paper aims to investigate the effect of financial analysts' recommendations on the overconfidence and over or under-reaction to previous years' earnings, as well as their impact on investment decisions in the Tunisian stock market. Literature mostly turned out that a positive bias in analysts' forecasts overreacted to prior earnings changes. Our study is based on the assumption that overconfidence among analysts can be understood through the accuracy of their forecasts, but also it is detected by the way that analyst provides a clear recommendation or not. The analysis employs a panel regression models using annual and bi-annual data over the period 2010-2015. Empirical results show that analysts on the Tunisian stock market are too confident in their forecasts on average, and there is clearly an overall over-reaction to past earnings changes. However, self-confidence is greater for those forecasts that are equipped with a recommendation, when the over-reaction is greater for the not equipped forecasts. Keywords: Overconfidence; Overreaction; Analysts' recommendations; Earnings forecasts. JEL Classifications: G02,G11,G17,G2

Effect of Twitter investor engagement on cryptocurrencies during the COVID-19 pandemic

This study aims to examine whether the prices and returns of two cryptocurrencies, Dogecoin and Ethereum, are affected by Twitter engagement following the COVID-19 pandemic. We use the autoregressive integrated moving average with explanatory variables model to integrate the effects of investor attention and engagement on Dogecoin and Ethereum returns using data from December 31, 2020, to May 12, 2021. The results provide evidence supporting the hypothesis of a strong effect of Twitter investor engagement on Dogecoin returns; however, no potential impact is identified for Ethereum. These findings add to the growing evidence regarding the effect of social media on the cryptocurrency market and have useful implications for investors and corporate investment managers concerning investment decisions and trading strategies

CEO Entrenchment and Performance: New Evidence Using Nonlinear Principal Component Analysis.

This study revisits the link between CEO Entrenchment and performance from a sample of 1.040 annual observations concerning 138 CEOs of French-listed firms for the 2000-2013 period. The effect of entrenchment, which seems to represent an illustration of the effectiveness of control mechanisms that CEOs are supposed to undergo within firms, reveals ambiguous findings. The financial woes, suffered by some firms such as France Telecom, Vivendi Universal and Eurotunnel testify to the magnitude of this inefficiency and usefulness to discuss corporate governance principles. The VIENOT reports 1 and 2 and the Bouton report have come forward presenting recommendations aimed at implement a system of corporate governance where moral ethics of different actors, confidence, transparency and respect for the interests of stakeholders are consistent. The purpose of this paper is thus to understand the impact of entrenchment on French firm performance. A key aspect of our study is the use of Nonlinear Principal Component Analysis (NLPCA), which is preferred to standard principal component analysis as a more effective method to distill the complex dimensions of CEO Entrenchment into reliable summary scores. Using fixed/random effect models which control of different source of heterogeneity, we find that CEO Entrenchment has a modest association with operating measures of performance (i.e. ratio of earnings to total assets, ROA) and with market-based measures of performance (i.e. Tobin’s Q). The empirical findings also indicate that the magnitude of the economic significance of the entrenchment proxies in the performance models depends on the method utilized to measure CEO Entrenchment

Investor characteristics and the effect of disposition bias on the Tunisian stock market

Drawing evidence from financial theory, which suggests the tendency of investors to sell winning stocks quickly and to hold on to losing ones for a long time, this is the first study to investigate the relevance of the effect of disposition bias on individual investors in the Tunisian equities market. Our analysis is carried out on a sample of 925 Tunisian traders over the period 2009–2014 to find out how gender, age, investor characteristics, portfolio management types, bull or bear market conditions, and external factors are related to the intensity of the disposition effect by separately tracking their trading transaction histories. The findings show mainly robust evidence of disposition bias across different groups of investors. In particular, the study reveals that male and younger Tunisian investors suffer from a strong disposition bias compared with their counterparts, female and mature investors. Furthermore, our results show that other behavioral biases, including market trading volume, the value of a share traded, trading frequency, trading in round numbers, and the investor's overall level of portfolio diversification depend on the disposition effect. Concerning the bull and bear market issue, we divided our data period into bull and bear markets to observe the effect of disposition bias every month of the year, and we found that this effect is even more pronounced in bull markets. Keywords: Behavioral finance, Disposition effect, Investor characteristics, Market trends, Tunisian investors, Tunisia's stock market, JEL Classification: G11, G1

Earnings announcement effect on the Tunisian stock market

This paper treats the post-earnings announcement drift. Precisely, it revisits the benefits announcement effect using various measurements of surprise unexpected earnings. In addition, this work tries to explain the persistence of post-earnings announcement drift on the financial markets using adapted methodology. The empirical study on the Tunisian stock market shows the persistence of the post-earnings announcement drift over the year 2013. It indicates that the observed post-earnings announcement drift seems to be due to the behavior of investors under psychological biases. This finding shows that the information provided by the prevision and revision of earnings forecasts is not immediately included in the price, but there is an anchoring bias in relation to the past earnings, as well as on the investor time of response to the new information provided by the market

The accuracy of financial analysts’ earnings forecasts and the Tunisian market reliance with time

Unlike previous studies which have examined the role of financial analysts in developed economies, the aim of this paper is to investigate whether following the Tunisian stock market opening, both the analyst forecast accuracy and the market’s reliance on analyst forecasts, increase with time. This study is based on the hypothesis that accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience, and also that the reliance on analyst forecasts should increase with time as the market opens and investors become more sophisticated. The methodology employs bi-annual panel data for Tunisian stock market from 2010 to 2015. Our results are consistent with the expectations. First, results generally confirm that both the accuracy and the higher quality of analyst earnings forecasts are increasing with time. Second, we find evidence that earnings expectations are not mainly based on analyst forecast in the first sub-period (2010–2012). However, these findings are reversed in the second sub-period (2013–2015) and for the whole period (2010–2015) as analyst forecast better explain returns and exhibit greater relative information content

Bitcoin volatility and the introduction of bitcoin futures: A portfolio construction approach

We evaluate the introduction of Bitcoin futures on Bitcoin return and volatility using realized volatility and GARCH model pre-and post-futures. We also assess the portfolio construction implications by building two portfolios containing the top 25 S&P stocks, one without futures and one with. GARCH and realized volatility show mixed results. We provide that futures make Bitcoin riskier and more vulnerable to fluctuations over time. However, Bitcoin futures improve the portfolio's volatility and returns profile. Our findings offer implications regarding portfolio strategies implemented by risk-averse and risk-seeking investors and managers as we show how Bitcoin futures can hedge investments

Loss aversion, overconfidence of investors and their impact on market performance evidence from the US stock markets

Purpose: The current study aims to investigate the impacts of two behavioral biases, namely, loss aversion and overconfidence on the performance of US companies. First, the impact of loss aversion on the economic performance of companies was assessed. Second, the impact of overconfidence on market performance was discussed. Design/methodology/approach: This study used around 6,777 quarterly observations on the population of US-insured industrial and services companies over the 2006-2016 period. Ordinary least squares (OLS) regression in two panel data models were used to test the hypotheses formulated for the study. Findings: It was documented that the loss-aversion bias negatively affects the economic performance of companies and this is achieved for both sectors. In contrast, the findings suggest that overconfidence positively affects market performance of industrial firms but negatively affects market performance in service firms. Further robust evidence was found that overconfidence bias seems to be dominant, and hence, investors may tend to be more overconfident rather than more loss-averse. Originality/value: This research can be extended by focusing on the following question: What is the impact of the contradictory (positive and negative) effects of an investor's loss aversion and overconfidence on the US company performance in case of realization of a stock market crisis or stock market crash