UNC Kenan-Flagler Business School Clinical Associate Professor of Finance Arzu Ozoguz discusses the SEC's anticipated new rules around sustainability.
We analyze the impact of the introduction of credit default swaps (CDSs) on real decision-making within the firm. Our structural model predicts that CDS introduction increases debt capacity more when uncertainty about the credit events that trigger CDS payment is lower.
We examine empirically and theoretically the relation between firms’ risk and distance to consumers in a production network. We document two novel facts: firms farther away from consumers have higher risk premiums and higher exposure to aggregate productivity. We quantitatively explain these findings using a general equilibrium model featuring a multilayer production process.
Scholars continue to debate whether voice and silence are opposites or distinct constructs. This ambiguity has prevented meaningful theoretical advancements about employees’ voice and silence at work. We draw on the behavioral activation and behavioral inhibition systems perspective to provide a conceptual framework for the independence of voice and silence and explicate how two key antecedents—perceived impact and psychological safety—more strongly relate to voice and silence, respectively. We further differentiate voice and silence by identifying their unique effects on employee burnout.
We analyze how Dodd-Frank-mandated risk retention affects the information investors extract from issuers’ retention choices in the CMBS market. We show that the required retention level is both binding and stringent.
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 swap spreads and model-implied default probabilities do not distinguish between such shocks.
We investigate whether institutional ownership (IO) plays a role in transmitting systemic risk through banks. We find robust evidence suggesting that IO is positively associated with future systemic risk. We find this relationship is stronger during economic downturns at the economy-wide level, as well as for banks demonstrating greater capital needs. Our results also suggest a trading mechanism through which active, and transient institutions in particular, play a role in propagating systemic risk.
We propose a new theory of systemic risk based on Knightian uncertainty (“ambiguity”). Because of uncertainty aversion, bad news on one asset class worsens investors’ expectations on other asset classes, so that idiosyncratic risk creates contagion, snowballing into systemic risk.
We show that blockchain can be more effective than pricing strategy in eliminating the post-purchase regret and improving social welfare.
Although the non-financial corporate sector accounts for the lion’s share of the post-Global Financial Crisis surge in emerging-market leverage, there is little systematic research on factors that impact corporate distress risk in emerging markets. Existing bankruptcy risk models developed using US data have low predictive power when applied to emerging market firms. We suggest that these models do not account for emerging market vulnerabilities to global shocks such as advanced economy monetary policy changes, US dollar movements, or shifts in global liquidity and risk-aversion.
Short selling is a risky business. Short sellers must identify mispriced securities, borrow shares in the equity lending market, postcollateral, and pay a loan fee each day until the position closes. In addition to the standard risks that many traders face, such as margin calls and regulatory changes, short sellers also face the risk of loan recalls and the risk of changing loan fees.
Since 1965, average idiosyncratic risk (IR) has never been lower than in recent years. In contrast to the high IR in the late 1990s that has drawn considerable attention in the literature, average market-model IR is 44% lower in 2013-2017 than in 1996-2000. Macroeconomic variables help explain why IR is lower, but using only macroeconomic variables leads to large prediction errors compared to using only firm-level variables. As a result of the dramatic change in the number and composition of listed firms since the late 1990s, listed firms are larger and older. Larger and older firms have lower idiosyncratic risk. Models that use firm char-acteristics to predict firm-level idiosyncratic risk estimated over 1963-2012 can largely or completely ex-plain why IR is low over 2013-2017. The same changes that bring about historically low IR lead to unusu-ally high market-model R-squareds.