Person: Siriwardane, Emil
Loading...
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Siriwardane
First Name
Emil
Name
Siriwardane, Emil
5 results
Search Results
Now showing 1 - 5 of 5
Publication The Probability of Rare Disasters: Estimation and Implications(2015-11-10) Siriwardane, EmilI analyze a rare disasters economy that yields a measure of the risk neutral probability of a macroeconomic disaster, p*t . A large panel of options data provides strong evidence that p*t is the single factor driving option-implied jump risk measures in the cross section of firms. This is a core assumption of the rare disasters paradigm. A number of empirical patterns further support the interpretation of p*t as the risk-neutral likelihood of a disaster. First, standard forecasting regressions reveal that increases in p*t lead to economic downturns. Second, disaster risk is priced in the cross section of U.S. equity returns. A zero-cost equity portfolio with exposure to disasters earns risk-adjusted returns of 7.6% per year. Finally, a calibrated version of the model reasonably matches the: (i) sensitivity of the aggregate stock market to changes in the likelihood of a disaster and (ii) loss rates of disaster risky stocks during the 2008 financial crisis.Publication Structural GARCH: The Volatility-Leverage Connection(2015-07-21) Engle, Robert; Siriwardane, EmilWe propose a new model of volatility where financial leverage amplifies equity volatility by what we call the “leverage multiplier.” The exact specification is motivated by standard structural models of credit; however, our parameterization departs from the classic Merton (1974) model and can accommodate environments where the firm’s asset volatility is stochastic, asset returns can jump, and asset shocks are non-normal. In addition, our specification nests both a standard GARCH and the Merton model, which allows for a statistical test of how leverage interacts with equity volatility. Empirically, the Structural GARCH model outperforms a standard asymmetric GARCH model for approximately 74 percent of the financial firms we analyze. We then apply the Structural GARCH model to two empirical applications: the leverage effect and systemic risk measurement. As a part of our systemic risk analysis, we define a new measure called “precautionary capital” that uses our model to quantify the advantages of regulation aimed at reducing financial firm leverage.Publication Concentrated Capital Losses and the Pricing of Corporate Credit Risk(2015-07-21) Siriwardane, EmilUsing proprietary credit default swap (CDS) data from 2010 to 2014, I show that capital fluctuations for sellers of CDS protection are an important determinant of CDS spread movements. I first establish that markets are dominated by a handful of net protection sellers, with five sellers accounting for nearly half of all net selling. In turn, a reduction in their total capital increases CDS spreads. Capital fluctuations of the largest five sellers account for over 10 percent of the time-series variation in spread changes, a significant amount given that observable firm and macroeconomic factors account for less than 17 percent of variation during this time period. I then demonstrate that the concentration of sellers creates fragility — higher concentration results in more volatile risk premiums. I also employ a number of complementary approaches to address identification, such as using the 2011 Japanese tsunami as an exogenous shock to the risk bearing capacity of CDS traders. My findings are consistent with asset pricing models with limited investment capital, but also suggest that both the level and distribution of capital are crucial for accurately describing price dynamics.Publication Precautionary Savings in Stocks and Bonds(2017-03-23) Pflueger, Carolin; Siriwardane, Emil; Sunderam, AdityaWe document a strong and robust relation between the one-year real rate and precautionary savings motives, as measured by the stock market. Our novel proxy for precautionary savings, based on the difference in valuations between low- and high-volatility stocks, explains 37% of variation in the real rate. In addition, the real rate forecasts returns on the low-minus-high volatility portfolio, though it appears unrelated with measures of the quantity of risk. Our results suggest that precautionary savings motives, and thus the real rate, are driven by time-varying attitudes towards risk. We rationalize these findings in a stylized model with segmented investor clienteles and habit formation.Publication Concentrated Capital Losses and the Pricing of Corporate Credit Risk - Online Appendix(2015-07-21) Siriwardane, EmilThis is the online appendix to "Concentrated Capital Losses and the Pricing of Corporate Credit Risk". In this appendix, I provide additional stylized facts about the CDS market regarding: (i) the size of the market, (ii) the concentration of net buyers and sellers within each reference entity, (iii) the commonality of net buyers and sellers across reference entities, (iv) who purchases and sells protection, (v) the network structure of the CDS trading network, and (vi) the role of dealers in the CDS market. In addition, I discuss why the role of dealers as prime brokers does not impact the stylized facts and results presented throughout the paper.