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We measure \"good\" and \"bad\" variance premia that capture risk compensations for the realized variation in positive and negative market returns, respectively. The two variance premium components jointly predict excess returns over the next one and two years with statistically significant positive (negative) coefficients on the good (bad) component. The [R.sup.2]s reach about 10% for aggregate equity and portfolio returns and 20% for corporate bond returns. To explain the new empirical evidence, we develop a model that highlights the differential impact of upside and downside risk on equity and variance risk premia.

We investigate Morningstar's new qualitative, forward-looking analyst ratings, which reflect independent analysts' expectations of a fund's future performance. We find relatively higher flows to funds receiving higher ratings, suggesting that the average investor values the analyst's subjective views when allocating their wealth. Performance tests show that investors would have earned significantly higher returns over our sample period by investing in funds with the highest analyst conviction. These results suggest that independent research that expands the information set to include qualitative elements may help investors make better investment allocation decisions.

Changing economic conditions over the past two decades have created incentives for sell-side analysts to both provide their institutional clients tiered services and to streamline their written research process. One manifestation of these changes is an increased likelihood of analysts' issuing earnings forecasts for multiple firms on the same day. We identify this bundling property and show that bundling has increased steadily over time. We provide field evidence that the practice is a cost-saving measure, a natural by-product of analysts focusing on thematic research, and a reflection of forecast updating that occurs in advance of important events. Our empirical analyses show that bundled forecasts are less accurate, less bold, and less informative to investors than non-bundled forecasts. We also find that analysts who produce bundled forecasts provide valuable specialized services to their institutional clients. Our findings ultimately demonstrate that forecast bundling has important implications for the properties of analysts' forecasts.

Economists commonly suppose that persons have probabilistic expectations for uncertain events, yet empirical research measuring expectations was long rare. The inhibition against collection of expectations data has gradually lessened, generating a substantial body of recent evidence on the expectations of broad populations. This paper first summarizes the history leading to development of the modern literature and overviews its main concerns. I then describe research on three subjects that should be of direct concern to macroeconomists: expectations of equity returns, inflation expectations, and professional macroeconomic forecasters. I also describe work that questions the assumption that persons have well defined probabilistic expectations and communicate them accurately in surveys. Finally, I consider the evolution of thinking about expectations formation in macroeconomic policy analysis. I favorably observe the increasing willingness of theorists to study alternatives to rational expectations assumptions, but I express concern that models of expectations formation will proliferate in the absence of empirical research to discipline thinking. To make progress, I urge measurement and analysis of the revisions to expectations that agents make following occurrence of unanticipated shocks.

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.

We explore the impact of corporate social responsibility (CSR) ratings on sell-side analysts' assessments of firms' future financial performance. We suggest that when analysts perceive CSR as an agency cost they produce pessimistic recommendations for firms with high CSR ratings. Moreover, we theorize that, over time, the emergence of a stakeholder focus shifts the analysts' perceptions of CSR. Using a large sample of publicly traded U.S. firms over 15 years, we confirm that, in the early 1990s, analysts issue more pessimistic recommendations for firms with high CSR ratings. However, analysts progressively assess these firms more optimistically over time. Furthermore, we find that analysts of highest status are the first to shift the relation between CSR ratings and investment recommendation optimism.

Standalone corporate social responsibility (CSR) reports vary considerably in the content of information released due to their voluntary nature. In this study, we develop a disclosure score based on the tone, readability, length, and the numerical and horizon content of CSR report narratives, and examine the relationship between the CSR disclosure scores and analyst forecasts. We find that CSR reporters with high disclosure scores are associated with more accurate forecasts, whereas low score CSR reporters are not associated with more accurate forecasts than firms who do not issue CSR reports. The findings are robust to controlling for firm characteristics including CSR activity ratings and financial narratives. The findings are driven by experienced CSR reporters rather than first-time CSR reporters. Together, our findings suggest that the content of CSR reports helps to improve analyst forecast accuracy, and this relationship is more pronounced for CSR reports with more substantial content.

This study examines analyst information intermediary roles using a textual analysis of analyst reports and corporate disclosures. We employ a topic modeling methodology from computational linguistic research to compare the thematic content of a large sample of analyst reports issued promptly after earnings conference calls with the content of the calls themselves. We show that analysts discuss exclusive topics beyond those from conference calls and interpret topics from conference calls. In addition, we find that investors place a greater value on new information in analyst reports when managers face greater incentives to withhold value-relevant information. Analyst interpretation is particularly valuable when the processing costs of conference call information increase. Finally, we document that investors react to analyst report content that simply confirms managers’ conference call discussions. Overall, our study shows that analysts play the information intermediary roles by discovering information beyond corporate disclosures and by clarifying and confirming corporate disclosures. The Internet appendix is available at https://doi.org/10.1287/mnsc.2017.2751 . This paper was accepted by Suraj Srinivasan, accounting.

This paper examines the joint time series of the S&P 500 index and its options with a two-factor Hawkes jump-diffusion model that captures jump propagation (i.e., the phenomenon in which the strike of one jump substantially raises the probability for more to follow). The propagation effect uncovered from the joint data is severe but short lived. On average, this component takes up more than two-thirds of the total jump risks. Our jump specification proves crucial not only in reconciling the dynamics implied from the joint data, but also in explaining the time series of option-implied volatility skew.

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