Equity Analysts Research Articles

Limits of bank regulation in financialised capitalism: lessons from the 2023 US banking crisis

ABSTRACT In this article I argue that banks continuously build new business models in financialised capitalism. Market value of these business models is regularly calculated and reported to the investors by investment banking expertise. What the US banking regulators, in their ex-post analysis, declared as unsustainable business models in the three failed banks – Silicon Valley Bank, Signature Bank, and First Republic Bank – in the Spring of 2023, had been promoted by equity analyst expertise as value-maximising ‘niche’ bank business models serving the disruptive technology start-ups after the Covid pandemic. The article argues that bank regulators’ power is severely constrained in financialised capitalism where stock market valuations of banks and equity-based remuneration of the executives are out of regulatory reach. Therefore financial stability mandate of central banks is undermined with significant risk to the society when business models of banks are legitimised by a financialised valuation regime that prioritises shareholder value creation.

The gender effects of COVID: evidence from equity analysts

The gender effects of COVID: evidence from equity analysts

Artificial intelligence innovation and stock price crash risk

AbstractThis study examines the association between artificial intelligence innovation (AII) and stock price crash risk (SPCR). AII serves as a governance mechanism that can bolster strength in internal controls, leading to increased financial transparency and thereby reducing the likelihood of future SPCR. The results hold after accounting for possible endogeneity issues Further, we find that monitoring through corporate governance mechanisms, level of following by equity analysts, and the reduced information asymmetry constitute important channels that mediate the association between AII and SPCR. Additionally, the relationship between AII and SPCR varies across corporate life cycle stages and workplace culture.

Predicting Analysts’ S and P 500 Earnings Forecast Errors and Stock Market Returns using Macroeconomic Data and Nowcasts

This study scrutinizes the quality of “bottom-up” forecasts of near-term S and P 500 Composite earnings, derived by aggregating analysts’ forecasts for individual firm-level earnings. We examine whether forecasts are broadly consistent with current macroeconomic conditions reflected in economists’ near-term outlook and other available data. To the contrary, we find that a simple macroeconomic model of aggregate S and P 500 earnings, coupled with GDP forecasts from the Blue Chip Survey and recent dollar exchange rate movements, can predict large and statistically significant errors in equity analysts’ bottom-up forecasts for S and P 500 earnings in the current quarter and the quarter ahead. This finding is robust to the requirement that our econometric model is calibrated using only data available at the time of forecast. Moreover, the discrepancy between the macro-model-based earnings forecasts and analysts’ forecasts has predictive power for 3-month-ahead stock returns

Do analysts play a monitoring role? Evidence from exogenous changes in litigation risk

AbstractThis paper examines whether securities litigation and sell‐side equity analysts play a substitutive versus complementary role as an external governance mechanism. We expect the 1999 ruling on the stricter interpretation of the Private Securities Litigation Reform Act to make it easier for firms headquartered in the Ninth Circuit to defend against securities class actions filed by shareholders, resulting in weaker protection from a litigation channel and stronger demand for analyst activity. Using a difference‐in‐differences research design, we find that analyst coverage increases as litigation risk decreases in the Ninth Circuit firms. Moreover, we find that analyst earnings forecast accuracy increases for firms in the Ninth Circuit following the ruling, consistent with analysts exerting greater efforts to perform their monitoring role. In cross‐sectional tests, we find that the substitution relation between litigation risk and analyst research is more pronounced in firms with a high level of ex‐ante litigation risk. We conduct extensive robustness tests, including another legal event exogenously increasing the risk of litigation, to gain confidence in our interpretations. We contribute to the literature by documenting causal evidence that analysts have greater incentives to provide meaningful equity research as gatekeepers in times of weaker investor protection by securities litigation.

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Different equity valuation models in theory provide identical estimates of equity intrinsic values if they are implemented with consistent assumptions. In practice, it is not unusual to obtain different value estimates from different models. Prior research on the comparison between multiples-based valuation model and flowsbased valuation models are quite limited. This research contributes to the literature by comparing the accuracy and reliability of three flows-based valuation models (discount dividend model, discounted free cash flow model, residual income valuation model) and multiples-based valuation model using one-year forward forecasted earning (PE1). For the analysis, all models are tested for bias, accuracy and explainability using t-tests, Wilcoxon tests and OLS regressions with a large sample of 40.547 observations from U.S public firms during the period from 2010 to 2020. Results show that PE1 value estimates are more accurate and reliable than that of flows-based models; and among flows-based models, residual income valuation model performs best. This research provides evidence for the performance and usage of such models to support sell-side equity analysts while making decisions of which model to use.

Gender, Competition, and Performance: International Evidence

Abstract Using a hand-collected sample of 18,269 equity analysts from 42 countries over the period of 2004 to 2019, we establish an intriguing negative association between a country’s institutional/economic development and its female share of equity analysts. We show that, in individualistic countries only, there is no gender gap in analyst forecast accuracy. We further show that female analysts are more skilled and more likely to drop out when underperforming in individualistic countries compared to peers in collectivistic countries. The evidence supports our hypothesis that the national cultural value of individualism encourages women to make career choices consistent with their general aversion to competition.

Quants and market anomalies

Sell-side quantitative equity research analysts (Quants) conduct econometric analyses of stock returns to uncover market anomalies and assist equity analysts and institutional clients with stock selection. We present novel evidence that establishes their role in helping analysts and mutual fund clients discover market anomalies and capital markets evolve toward greater pricing efficiency. Specifically, we find that analysts and mutual fund clients with greater access to Quants make recommendations and trades that reveal greater knowledge of anomalous cross-sectional return predictability. More importantly, cross-sectional return predictability is weaker in stocks that have higher coverage (ownership) by analysts (mutual fund clients) with access to Quants, and strengthens when quasi-exogenous brokerage house closures reduce the availability of Quants.

Does Alternative Data Improve Financial Forecasting? The Horizon Effect

ABSTRACTExisting research suggests that alternative data are mainly informative about short‐term future outcomes. We show theoretically that the availability of short‐term‐oriented data can induce forecasters to optimally shift their attention from the long term to the short term because it reduces the cost of obtaining short‐term information. Consequently, the informativeness of their long‐term forecasts decreases, even though the informativeness of their short‐term forecasts increases. We test and confirm this prediction by considering how the informativeness of equity analysts' forecasts at various horizons varies over the long run and with their exposure to social media data.

Impact of Stock Returns on Trading Volume in Indian Stocks: A Panel ARDL Approach

The purpose of this paper was to analyse the impact of stock returns on trading volume for the companies listed on BSE in India. This article attempted to analyse that whether there had been a significant impact of returns on the trading volume in the short-run and long-run. This study included a sample of 30 companies listed Sensex. To conduct this analysis, a two-stage methodology was employed. In the first stage, a panel autoregressive distributed lag (ARDL) approach was used to investigate the impact of stock returns on trading volume. In the second stage, the focus was on checking the cross-section short-run relationship in the sample by extending the ARDL estimation. The results showed that the short-run co-integration equation, all the variables have shown significant relationship. The returns have shown significant positive impact on trading volume in short-run whereas significant negative impact in the long-run. The lagged trading volume and stock returns have also shown significant positive impact on current trading volume. These findings have significant implications for investors, equity analysts and portfolio management firms for stock selection and trading patterns.

Learning from the Best: Can Artificial Intelligence Replicate Equity Analyst Skill?

Learning from the Best: Can Artificial Intelligence Replicate Equity Analyst Skill?

The Field of Investment Advice: The Social Forces That Govern Equity Analysts

ABSTRACT Literature on equity analysts presents a conundrum: analysts are seen as influential market participants, yet researchers widely criticize them for their bias and inaccuracy. Studies drawing from economic frames struggle to explain this. Therefore, we develop a new conceptualization that positions analysts as actors operating in a social field. Drawing on a qualitative study involving 70 interviews with analysts and portfolio managers, we offer two broad insights. First, we identify long-term interpersonal and interinstitutional ties between buy-side and sell-side actors which contribute to social inertia in the field. Second, we illustrate how sell-side analysts’ social environment is dichotomous, pushing some to converge with consensus estimates, while encouraging others to diverge. Taken as a whole, our findings contribute to the accounting literature by enriching our understanding of the social and institutional forces that govern analyst behavior.

Asian Paints: a valuation dilemma

Learning outcomes This case study will allow students to understand and analyse the process for conducting equity valuation by building a three-statement financial model, to understand and apply the workings of discounted cash flow (DCF) valuation methodology and its components, to apply the concepts related to the calculation of the weighted average cost of capital in the determination of discounting rate, to understand the terminal value calculation and assumptions thereof and to analyse the intrinsic valuation for the target company using the traditional multi-stage DCF model for investment decision-making. Case overview/synopsis In July 2019, Kapil Agarwal, an equity analyst operating out of Mumbai, India, was carefully looking over the financials of Asian Paints, a leading paints company in India. As an equity analyst, Kapil was constantly on the lookout for fundamentally strong but undervalued companies that could create long-term wealth for his equity fund. To decide upon the right valuation of Asian Paints, Kapil conducted fundamental analysis using the DCF method on the basis of available financial information. This case study puts students in an investment analyst role wherein they forecast financial statements and conduct DCF valuation for Asian Paints to discover potentially undervalued stocks for investment decision-making. Complexity academic level This case study is designed for use in an undergraduate or postgraduate programme in business management, particularly in a course on business valuation or investment management or security analysis. Supplementary materials Teaching notes are available for educators only. Subject code CSS 1: Accounting and Finance.

Text-Based Measure of Supply Chain Risk Exposure

Using textual analysis techniques, including seeded word embedding and bag-of-words-based content analysis, I develop a firm-level measure of supply chain risk exposure from a novel source of unstructured data—the discussion between managers and equity analysts on supply chain-related topics during firms’ quarterly earnings conference calls. I validate the measure by showing that (1) the measure exhibits intuitive variations over time and across firms, successfully capturing both routine and systematic supply chain risk events; and (2) the measure is about risk exposure, as it significantly correlates with realized and options-implied stock return volatility, even after controlling for well-known aggregate risk measures. I then demonstrate that the measure is specifically indicative of the supply chain component of risk exposure. (3) Consistent with theoretical predictions, firms facing higher supply chain risks have higher inventory buffers, particularly in raw materials and intermediate inputs, increased cash holdings in lieu of investments, and significantly lower trade credit received from suppliers. Moreover, (4) during unexpected risk episodes, such as the Tohoku earthquake, firms with higher ex ante risk exposure have worse operating and financial performance. These results indicate that the text-based measure provides a credible quantification of firm-level exposure to supply chain risks and can thus be reliably utilized as outcome or explanatory variables in empirical supply chain research. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4927 .

Pollution control bonds and environmental performance in energy utility firms: is there an incantation effect?

PurposeThis study aims to examine the effects of green financing through pollution control bonds (PCBs) on environmental performance.Design/methodology/approachThis study is based on a panel of 189 US energy utility firms observed over the period, 2011–2021 ; this study applies Generalized Method of Moments regressions.FindingsThis study found that PCBs positively affect environmental performance (aggregate measure, greenhouse emissions, waste landfill, waste incineration and waste recycling). These findings remain robust when this study considers alternative measures of PCBs and environmental performance, the quantile regression method and some firms’ attributes such as financial performance and firm age.Practical implicationsThe results indicate that US energy utility firms have to adopt more PCBs. This study helps researchers, practitioners, shareholders, bondholders, equity analysts and local authorities such as the California Pollution Control Financing Authority, municipalities and investors understand PCBs issuance, usefulness and relevance.Originality/valueTo the best of the authors’ knowledge, this study is the first to explore the effectiveness of PCBs in reducing pollution.

IMPACT OF COVID-19 ON PERFORMANCE ON INDIAN STOCK INDICES: A STUDY FOR NSE COMPOSITE AND SECTORAL INDICES

Purpose/Objective: The objective of the paper was to scrutinize the impact of COVID-19 on the performance of composite and sectoral indices of National Stock Exchange (NSE) of India. Methodology and Approach: The study included sample daily closing prices from July 2019 to December 2020 for two composite indices and nine sectoral indices of NSE. The sample was divided into three sub-samples to check the impact before, during and after (after the lockdown was lifted) the pandemic on the volatility of returns. The volatility measures were regressed using a dummy variable for COVID-19. Findings: The results showed that there was an increase in the volatility of returns of the indices during COVID-19 as compared to post-lockdown period. It was also found that the skewness of returns of the indices have become more negative in the post COVID (post-lockdown) period. Practical Implications /Conclusion: The findings of the study have significant implications and impacts regarding the decision making for equity analysts, portfolio management firms, investors and traders for assessing their investment in a better way and deciding their investments. The author believed that these results would magnify the volatility relations.

The Impact of Equity Analysts on ESG Performance: Evidence from an Exogenous Shock

This article investigates whether equity analysts promote or discourage environmental, social and governance (ESG) engagement by using an international sample of firms incorporated in 46 countries. To establish causality, we rely on two natural experiments, that is, brokerage mergers and closures, which generate an exogenous coverage termination. We find that the loss of an equity analyst results, on average, in an increase in the ESG score. This finding is consistent with the view that equity analysts exacerbate managerial myopia, encouraging listed firms’ managers to excessively focus on short-term outcomes. We also find that the impact of analyst loss on the ESG performance holds only for companies whose managers pay more attention to not miss earnings targets and for firms located in countries where the cultural orientation to long-term growth (rather than short-term results) is stronger. Finally, by decomposing the ESG score into its various sub-pillars, we observe that the impact of analyst loss is driven by the Environmental and Social dimensions, while no significant impact is found for the Governance dimension.

Intrafirm Knowledge Sharing in the Investment Research Industry

We study interdepartment knowledge sharing in an investment research setting where the benefits are potentially significant for the brokerage and the capital market, but so are the frictions impeding it. Using hand-collected data on equity analyst access to in-house debt research expertise, we find significant benefits to equity analysts in the form of improved ability to forecast cash flows and to anticipate credit rating downgrades. Moreover, we find evidence that access to management and research expertise underlie in-house debt analysts’ capacity to generate information beneficial to equity analysts. Finally, these benefits exist only in the presence of a collaborative brokerage culture or debt-equity analyst collocation, consistent with these factors promoting knowledge sharing in the investment research industry. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4809 .

Analyst Sentiment as a Factor Consideration

An equity analyst’s opinion of stocks summarizes how a variety of different forces (such as geopolitical, macroeconomic, country, industry, and company-specific) and their interaction may affect the future performance of a company. In this article, we constructed an analyst-sentiment factor that tracks changes in analyst expectations, and then examined its relationship with global equity performance. We also sought to define the analyst-sentiment factor and learn about its stability and performance. Our analysis revealed that analyst sentiment has been a robust and differentiated investment factor with strong associated risk premiums. It exhibited unique characteristics and information relative to traditional equity style factors such as value, quality, and momentum.

Why Do Analysts use a Zero Forecast for Other Comprehensive Income?

Accounting theory and accounting researchers stress the importance of clean surplus accounting and comprehensive income to corporate valuation. However, casual observation suggests that sell‐side equity analysts routinely ignore other comprehensive income (OCI) in their forecasts and instead focus on forecasting earnings (before OCI). Using a sample of analyst reports, I first confirm that analysts normally omit forecasts of OCI or comprehensive income from their reports, consistent with analysts forecasting OCI as zero. I then predict and find that a zero forecast for OCI generally produces lower forecasting errors than alternative time‐series models, such as a random walk or AR(1) model, suggesting a rational reason why analysts take this approach. Finally, I predict and find that although analysts’ point forecasts of future OCI are usually zero, their implied cost of equity estimates are consistent with analysts forecasting a positive variance for OCI.