Shimon Kogan

Predicting Risk from Financial Reports with Regression

We address a text regression problem: given a piece of text, predict a real-world continuous quantity associated with the texts meaning. In this work, the text is an SEC-mandated financial report published annually by a publicly-traded company, and the quantity to be predicted is volatility of stock returns, an empirical measure of financial risk. We apply well-known regression techniques to a large corpus of freely available financial reports, constructing regression models of volatility for the period following a report. Our models rival past volatility (a strong baseline) in predicting the target variable, and a single model that uses both can significantly outperform past volatility. Interestingly, our approach is more accurate for reports after the passage of the Sarbanes-Oxley Act of 2002, giving some evidence for the success of that legislation in making financial reports more informative.

Information Content of Public Firm Disclosures and the Sarbanes-Oxley Act

We find evidence that public firm disclosure, in the form of Management Discussion and Analysis (Sections 7 and 7a of annual reports), is more informative about the firms future risk following the passage of the Sarbanes-Oxley Act of 2002. Employing a novel text regression, we are able to predict, out of sample, firm return volatility using the Management Discussion and Analysis section from annual 10-K reports (which contains forward-looking views of the management). Using the relative performance of the text model as a proxy for the informativeness of reports, we show that the MD&A sections are significantly more informative after the passage of SOX. We further show that this additional information is associated with a reduction in share illiquidity, suggesting that the information divulged was new to investors. Finally, we find that the increase in informativeness of MD&A reports is most pronounced for firms with higher costs of adverse selection.

Business Microloans for U.S. Subprime Borrowers

We show that business microloans to U.S. subprime borrowers have a very large impact on subsequent firm success. Using data on startup loan applicants from a lender that employed an automated algorithm in its application review, we implement a regression discontinuity design assessing the causal impact of receiving a loan on firms. Startups receiving funding are dramatically more likely to survive, enjoy higher revenues and create more jobs. Loans are more consequential for survival among subprime business owners with more education and less managerial experience.A lot. Using data on startup loan applicants from a U.S. lender that employed an automated algorithm in its application review, we implement a regression discontinuity design assessing the causal impact of receiving a loan on entrepreneurial success. Obtaining a loan has a strong effect on the future financial position of startups. Startups receiving funding are dramatically more likely to survive, enjoy higher revenues and create more jobs. Loans are more consequential for survival among entrepreneurs with more education and less managerial experience. Access to credit creates a skewed firm size distribution by enabling quite small firms to succeed. We would like to thank Catherine Meyrat, Nelly Rojas-Moreno, and Duangkamol Phuengpanyalert for their guidance about institutional details. We also thank Rosy Manzanarez, Alejandra Garcia, and Siddharth Subramanian for their research support. We are grateful for comments from seminar participants at Instituto de Empresa, NYU Stern, Rutgers, UCLA and Wharton. Garmaise gratefully acknowledges support from the Harold and Pauline Price Center. Contact information: cesare.fracassi@mccombs.utexas.edu, mark.garmaise@anderson.ucla.edu, shimon.kogan@austin.utexas.edu, gnativid@stern.nyu.edu. Small entrepreneurial firms represent a strikingly large portion of the American economy. Basic indicators such as GDP growth, job creation, innovation rate, and wealth accumulation all depend to a great extent on the success of newly founded organizations constantly revitalizing U.S. markets. Given the collective size and dynamism of this sector of the economy, the role of financial institutions in funding nascent firms has become a central area of research and debate. In this paper we consider two main questions. First, to what extent do formal loans matter for entrepreneurial success in the U.S.? Second, what types of entrepreneurs experience the greatest benefits from receiving this credit? On the first issue of the importance of credit, consider a potential loan to a small firm from a given lender. It may be argued that this funding will have a large impact on the firm’s success, as loans constitute a major source of entrepreneurial financing (Robb and Robinson (2012)), and early-stage credit may enable entrepreneurial ventures to invest in value-creating opportunities and achieve necessary scale. On the other hand, there are reasons to suggest that the effect of the loan will be minimal. Specifically, there is evidence that entrepreneurs who cannot obtain bank financing are of relatively low quality (Kerr and Nanda (2009), Cetorelli (2009) and Andersen and Nielsen (2012)). In that case, good firms that are rejected by this one lender will find financing elsewhere, while poor firms that do receive a loan will be unlikely to succeed in any event. Moreover, there are indications that liquidity constraints do not matter much for entrepreneurial firm creation (Hurst and Lusardi (2004)) and some surveys suggest that small firms are unlikely to be financially constrained (Angelini and Generale (2008)). Further, there has been considerable debate on whether financial constraints matter for small-firm growth trajectories in developed economies, as financial capital may be substituted for by other available factors (e.g., Carpenter and Petersen (2002) and Beck, Demirguc-Kunt, and Maksimovic (2005)) and entrepreneurs may For example, the U.S. Census reports that there were 22.6 million nonfarm sole proprietorships and 3.1 million partnerships in 2008, together accounting for 42.4% of all business net income in that year.

Aggregate Sentiment and Investment: An Experimental Study

Sentiment indices, such as measures of consumer confidence, are often discussed as potential indicators of future investment, consumption and growth. However, documenting a causal relationship between consumer confidence and output — and understanding the precise nature of the relationship — using field data has been challenging. We rely on the high degree of control afforded by a laboratory setting to experimentally test a simple model of investment with complementarities and time-varying fundamentals. Our experiment manipulates the presence of aggregate confidence measures to test both how they reflect available information and how they influence future output. We find that an aggregate sentiment measure can be as effective as a highly precise exogenous public signal in coordinating behavior on more efficient equilibria. Furthermore, our analysis indicates that the confidence measure also impacts expectations by influencing beliefs about aggregate investment.

Information Environment and the Geography of Firms and Investors

We develop a model linking stock ownership and returns to the distribution of private information and quality of public information. Supporting the model, we find that the firm’s information environment affects investors’ propensity to hold and trade its stocks, but its effects hinge on investors’ access to private information. Nearby investors with potential access decrease their holdings when private information becomes more dispersed and public information quality improves, whereas distant investors display opposite patterns. Tests exploiting exogenous shocks to firms’ information environments indicate these relations are causal. Moreover, firms’ information environments and proximity to potential investors jointly explain stock returns.