[Research Seminar 2019.07.23]The Rise of a Network: The Spillover of Political Patronage and Cronyism to the Private Sector

Abstract   The misallocation of government resources to the politically connected is considered to impose substantial economic costs. We document that preferential access for the politically connected extends to resources allocated by private sector firms. Following a presidential election in Korea in 2007, private banks appoint executives from the new president’s networks to establish links

[Research Seminar 2019.06.25] Investor Relations Executives in the Top Management Team

Abstract We examine the role of investor relations (IR) executives in the top management team and find that firms incorporating the IR function in their top management team are more likely to beat analysts’ estimates and exhibit more downward earnings guidance. We also provide evidence that these firms manage analysts’ expectations rather than manage earnings

[Research Seminar 2019.06.26] Do rating agencies deserve some credit? Evidence from transitory shocks to credit risk

Abstract We find that Credit Rating Agencies (CRAs) see through transitory shocks to credit risk that stem from transitory shocks to equity prices, while market-based measures of credit risk do not. For a given stock return, CRAs are significantly less likely to downgrade firms with transitory shocks than those with permanent shocks.  However, credit default

[Research Seminar 2019.05.28]Is AI an Invader That Threatens Humans? Complementary Effects Between Agents and AI on the Productivity of Call Center Agents

Abstract The promises of artificial intelligence (AI) co-exist with a skepticism that AI-based systems can live up to them.  In this study, we adopted a perspective of learning curves and examined (1) the impact of introducing AI-based systems on the task performance of call center agents and (2) the conditions that moderate the impact of

[Research Seminar 2019.04.03] Complex Emotions and Bitcoin Pricing

Abstract We examine how investor emotions and Bitcoin price influence each other using high- frequency data and NLP analysis. Emotions regarding Bitcoin are extracted from an online chatting window at one of the largest cryptocurrency exchanges in Korea. To control for global factors, we also analyze relative Bitcoin prices, Korean premium, and differences between Korean

[Research Seminar 2019.02.08]Impulse-Response Analysis with Proxy Variables

Abstract This paper suggests an efficient and simple regression-based approach for consistent estimation of dynamic effects of structural shocks in vector autoregressions (VAR) with proxy variables for the shocks. First, we show that given a serially uncorrelated proxy variable correlated only with current structural shock of interest, the existing Proxy Structural VAR (Proxy-SVAR) approach using

[Research Seminar 2019.02.08]Monetary Policy under Data Uncertainty: Interest-Rate Smoothing from a Cross-Country Perspective

Abstract Cross-country estimates of Taylor rules suggest that higher data uncertainty is associated with a more inertial behavior of interest rates. Data uncertainty is measured by the volatility of differences between real-time data and their revisions. Using a simple structural model with Kalman filter learning, I replicate the cross-country pattern of the inertial behavior. More

[Research Seminar 2019.01.29]A First Glimpse into the Short Side of Hedge Funds

Abstract We provide direct evidence about the profitability of hedge fund short trades in equities. We identify the opening and closing of short (and long) trades by combining data on institutional investors’ transactions and holdings. Hedge fund short sales covered within five trading days are highly profitable, but short positions kept open longer than five

[Research Seminar 2018.12.17]Linear time-varying regression with Copula-DCC-GARCH models for volatility

    Abstract This research provides a new linear time-varying regression with dynamic conditional correlation (DCC) estimated by Gaussian and Student-t copulas for forecasting financial volatility. Time-varying parameters will be estimated for non-parametric dependence by using copula functions with United States stock market data. We compare our model with Kim et al.’s (2016) linear time-varying

SBA Special Lecture / 경영학부 특강 개최(2018.12.04)