Explore the vast range of titles available.

We employ a novel brokerage account data set to investigate which individual investors are the most attentive, how investors allocate their attention, and the relation between investor attention and performance. Attention is positively related to investment performance, at both the portfolio return level and the individual trades level. We provide evidence that the superior performance of high-attention investors arises because they purchase attentiongrabbing stocks whose positive performance persists for up to six months. Finally, we show that paying attention is particularly profitable when trading stocks with high uncertainty, but for which a lot of public information is available.

We examine whether climate change news risk is priced in corporate bonds. We estimate bond covariance with a climate change news index and find that bonds with a higher climate change news beta earn lower future returns, consistent with the asset pricing implications of demand for bonds with high potential to hedge against climate risk. Moreover, when investors are concerned about climate risk, they are willing to pay higher prices for bonds issued by firms with better environmental performance. Our findings suggest that corporate policies aimed at improving environmental performance pay off when the market is concerned about climate change risk.

This study aims to integrate two independent analyses, fundamental analysis and technical analysis, for equipping the investors to distinguish value stocks and growth stocks. Price-to-book (P/B) ratio is used as an indicator of fundamental analysis while trading volume and past stock returns are used as technical analysis indicators. One-way ANOVA/Welch with Tukey HSD/Games-Howell Post Hoc tests have been applied for the sample of 2099 stocks listed in Bombay Stock Exchange (BSE) of India for the period from 2010 to 2019. These 2099 stocks have been divided into four grids based on trading volume and past stock returns. The results indicate that four grids have significantly different mean values of P/B ratio. This means both analyses can distinguish value (lowest P/B) stocks and growth (highest P/B) stocks. Thus, this paper helps investors to identify value (lowest P/B) stocks and growth (highest P/B) stocks to invest for expecting the abnormal returns on their investments.

This study assesses whether the accrual-generating process is adequately described by a linear model with respect to a range of underlying determinants examined by prior literature. We document substantial departures from linearity across the distributions of accrual determinants, including measures of size, performance, and growth. To incorporate non-linear relations, we employ a recently developed multivariate matching approach (entropy balancing) to adjust for determinants in place of relying on a linear model. Entropy balancing identifies weights for the control sample to equalize the distribution of determinants across treatment and control samples. In simulations drawing random samples from deciles where a linear model displays poor fit, we find that entropy balancing significantly improves accrual model specification by reducing coefficient bias relative to linear and propensity-score matched models. Consistent with entropy balancing retaining sufficient power, we find that its estimates detect seeded accrual manipulations and explain variation in accruals around equity issuances.

Buying is easier than shorting for many equity investors. Combining this arbitrage asymmetry with the arbitrage risk represented by idiosyncratic volatility (IVOL) explains the negative relation between IVOL and average return. The IVOL-return relation is negative among overpriced stocks but positive among underpriced stocks, with mispricing determined by combining 11 return anomalies. Consistent with arbitrage asymmetry, the negative relation among overpriced stocks is stronger, especially for stocks less easily shorted, so the overall IVOL-return relation is negative. Further supporting our explanation, high investor sentiment weakens the positive relation among underpriced stocks and, especially, strengthens the negative relation among overpriced stocks.

Investor stock market response has received a great deal of attention in the marketing literature. However, firms are not faceless corporations; individuals such as CEOs set their strategies. Upper echelon and strategic leadership theories hold that chosen strategies derive from these individuals’ opinions, which are a function of their personalities, demographics, experiences, and values. Building on recent literature, the authors propose how CEO characteristics can influence innovation and stock returns. Investors are motivated by cash flow expectations—in particular, the prospect of increasing and accelerating future cash flows, reducing associated risks, and increasing residual value. This systematic review focuses on four main characteristics—personality, demographics, experience and compensation—to arrive at a set of propositions on innovation and stock returns. After reviewing the extensive literature on CEO characteristics, the authors outline the emerging findings on CMO characteristics; propose future research directions on CEO and CMO characteristics, innovations, and stock returns; and offer implications for practice.

We examine firm value and performance implications of the growing trend of nontechnology companies engaging in activities relating to digital technologies. We measure digital activities in firms based on the disclosure of digital words in the business description section of 10-Ks. Digital activities are associated with a market-to-book ratio 8%–26% higher than industry peers, and only 25% of the differences in market-to-book is explained by accounting capitalization restrictions. To control for selection bias, we implement lagged dependent variable and IV regressions, and our market-to-book findings are robust to these specifications. Portfolios formed on digital activity disclosure earn a Daniel et al. The Journal of Finance 52 (3): 1035–1058 ( 1997 )-adjusted return of 30% over a three-year horizon and a monthly alpha of 44-basis-points. On the other hand, we find weak evidence of near-term, positive improvements in fundamental performance, as we find some evidence of interim productivity increases but declines in sales growth conditional on digital activities.

Using estimators of the variation of positive and negative returns (realized semivariances) and high-frequency data for the S&P 500 Index and 105 individual stocks, this paper sheds new light on the predictability of equity price volatility. We show that future volatility is more strongly related to the volatility of past negative returns than to that of positive returns and that the impact of a price jump on volatility depends on the sign of the jump, with negative (positive) jumps leading to higher (lower) future volatility. We show that models exploiting these findings lead to significantly better out-of-sample forecast performance.

Many studies have focused on the relationship between companies with strong environmental, social, and governance (ESG) characteristics and corporate financial performance. However, these have often struggled to show that positive correlations—when produced—can in fact explain the behavior. The authors of this article provide a link between ESG information and the valuation and performance of companies, by examining three transmission channels within a standard discounted cash flow model—which they call the cash-flow channel, the idiosyncratic risk channel, and the valuation channel. They tested each of these transmission channels using Morgan Stanley Capital International ESG Ratings data and financial variables. This showed that companies’ ESG information was transmitted to their valuation and performance, both through their systematic risk profile (lower costs of capital and higher valuations) and their idiosyncratic risk profile (higher profitability and lower exposures to tail risk). The research suggests that changes in a company’s ESG characteristics may be a useful financial indicator. ESG ratings may also be suitable for integration into policy benchmarks and financial analyses. TOPICS: ESG investing, security analysis and valuation, risk management

Advancements in conversational Artificial Intelligence (AI) have led to rapid growth in firms’ use of AI chatbots in customer service roles. While the shareholder wealth effects of AI chatbots have yet to be investigated, recent findings suggest that AI investment may contribute negatively to firm value. This cautionary evidence, and the growing prevalence of AI chatbots, underscore that a clear understanding of their impact on firm value is urgently needed. An event study of 153 AI chatbot announcements demonstrates that implementation of AI customer service chatbots generates a .22% abnormal stock return, indicating investors respond favorably to this practice. Importantly, B2B (vs. B2C) firms have substantially more to gain from implementing AI chatbot customer service. However, we find chatbot anthropomorphism interacts with customer type, as investors respond less (more) favorably to anthropomorphized chatbots used in B2B (B2C) customer service roles. Two additional studies provide support for this pattern of findings.