Nagpurnanand Prabhala

Bio: Nagpurnanand Prabhala is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Initial public offering & Public sector. The author has an hindex of 28, co-authored 62 publications receiving 6197 citations. Previous affiliations of Nagpurnanand Prabhala include Yale University & Indian School of Business.

Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending

Abstract: We study the online market for peer-to-peer (P2P) lending, in which individuals bid on unsecured microloans sought by other individual borrowers. Using a large sample of consummated and failed listings from the largest online P2P lending marketplace - Prosper.com, we find that the online friendships of borrowers act as signals of credit quality. Friendships increase the probability of successful funding, lower interest rates on funded loans, and are associated with lower ex-post default rates. The economic effects of friendships show a striking gradation based on the roles and identities of the friends. We discuss the implications of our findings for the disintermediation of financial markets and the design of decentralized electronic markets.

Self-Selection Models in Corporate Finance

Abstract: Corporate finance decisions are not made at random, but are usually deliberate decisions by firms or their managers to self-select into their preferred choices. This chapter reviews econometric models of self-selection. The review is organized into two parts. The first part reviews econometric models of self-selection, focusing on the key assumptions of different models and the types of applications they may be best suited for. Part two reviews empirical applications of selection models in the areas of corporate investment, financing, and financial intermediation. We find that self-selection is a rapidly growing area in corporate finance, partly reflecting its recognition as a pervasive feature of corporate finance decisions, but more importantly, the increasing recognition of selection models as unique tools for understanding, modeling, and testing the role of private information in corporate finance.

Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending

Abstract: We study the online market for peer-to-peer P2P lending, in which individuals bid on unsecured microloans sought by other individual borrowers. Using a large sample of consummated and failed listings from the largest online P2P lending marketplace, Prosper.com, we find that the online friendships of borrowers act as signals of credit quality. Friendships increase the probability of successful funding, lower interest rates on funded loans, and are associated with lower ex post default rates. The economic effects of friendships show a striking gradation based on the roles and identities of the friends. We discuss the implications of our findings for the disintermediation of financial markets and the design of decentralized electronic markets. This paper was accepted by Sandra Slaughter, information systems.

Product Market Threats, Payouts, and Financial Flexibility

Abstract: We examine how product market threats influence firm payout policy and cash holdings. Using firms' product text descriptions, we develop new measures of competitive threats. Our primary measure, product market fluidity, captures changes in rival firms' products relative to the firm's products. We show that fluidity decreases firm propensity to make payouts via dividends or repurchases and increases the cash held by firms, especially for firms with less access to financial markets. These results are consistent with the hypothesis that firms' financial policies are significantly shaped by product market threats and dynamics.

Bowling alone: The collapse and revival of American community

Abstract: The present historical moment may seem a particularly inopportune time to review Bowling Alone, Robert Putnam's latest exploration of civic decline in America. After all, the outpouring of volunteerism, solidarity, patriotism, and self-sacrifice displayed by Americans in the wake of the September 11 terrorist attacks appears to fly in the face of Putnam's central argument: that \"social capital\" -defined as \"social networks and the norms of reciprocity and trustworthiness that arise from them\" (p. 19)'has declined to dangerously low levels in America over the last three decades. However, Putnam is not fazed in the least by the recent effusion of solidarity. Quite the contrary, he sees in it the potential to \"reverse what has been a 30to 40-year steady decline in most measures of connectedness or community.\"' As an example of how the current \"war on terrorism\" could generate a durable civic renewal, Putnam points to the burst in civic practices that occurred during and after World War II, which he says \"permanently marked\" the generation that lived through it and had a \"terrific effect on American public life over the last half-century.\" 3 If Americans can follow this example and channel their current civic

Answering the skeptics: yes, standard volatility models do provide accurate forecasts*

Abstract: A voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using ARCH and stochastic volatility models. While most of these studies have documented highly significant in-sample parameter estimates and pronounced intertemporal volatility persistence, traditional ex-post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts. Contrary to this contention, we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications. New methods for improved ex-post interdaily volatility measurements based on high-frequency intradaily data are also discussed.

Introductory Econometrics for Finance

Abstract: This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning package.

Econometric analysis of realized volatility and its use in estimating stochastic volatility models

Abstract: Summary. The availability of intraday data on the prices of speculative assets means that we can use quadratic variation-like measures of activity in financial markets, called realized volatility, to study the stochastic properties of returns. Here, under the assumption of a rather general stochastic volatility model, we derive the moments and the asymptotic distribution of the realized volatility error—the difference between realized volatility and the discretized integrated volatility (which we call actual volatility). These properties can be used to allow us to estimate the parameters of stochastic volatility models without recourse to the use of simulation-intensive methods.