The Center performs and disseminates research on the most important and pressing issues in risk and portfolio management in financial markets.

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Who we are

The UC Berkeley Center for Risk Management Research was established on July 1, 2013 as the successor to the Coleman Fung Risk Management Research Center. (more)

Site News

Konstantin Magin’s Risk Center working paper

Konstantin Magin’s Risk Center working paper (# 2009-01 and 2013-04), “Equity Risk Premium and Insecure Property Rights,” has been published in Economic Theory Bulletin. The final publication is available here.

CDAR website

The Consortium for Data Analytics in Risk (CDAR) is an industry partnership working in close collaboration with the Risk Center, and funded by State Street Bank and Trust. The CDAR website went live on 8/28/15.

Yuriy Gorodnichenko and Michael Weber

Yuriy Gorodnichenko and Michael Weber’s Risk Center working paper, “Are Sticky Prices Costly? Evidence from the Stock Market” has been published by the American Economic Review, available here.

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Presentations and Speaking Engagements

Alex Shkolnik will present “Systemic Risk in the Repo Market” at the upcoming Consortium for Systemic Risk Meeting (CSRA) December 15th Meeting

Alex Shkolnik presented “Systemic Risk in the Repo Market” at the Consortium for Systemic Risk Meeting (CSRA) on December 15th, 2015

Samim Ghamami’s – “Efficient Monte Carlo Counterparty Credit Risk Pricing and Measurement” to appear in the September issue of Journal of Credit Risk.

Samim Ghamami’s – “Efficient Monte Carlo Counterparty Credit Risk Pricing and Measurement” appeared in the September 2015 issue of Journal of Credit Risk.

Samim Ghamami presents “Static Models of Central Counterparty Risk” and will be a panel discussion participant on counterparty credit risk at the Quant Congress USA – July 16-18 2014, New York.

Samim Ghamami presented “Static Models of Central Counterparty Risk” and was a panel discussion participant on counterparty credit risk at the Quant Congress USA– July 16-18 2014, New York.

Lisa discusses the Monty Hall problem on Numberphile, a mathematical YouTube series produced by British filmmaker Brady Haran. A follow-up video featuring Brady adds to the discussion.

Director of Research Lisa Goldberg featured in a Numberphile Video on the Monty Hall Problem
Wednesday, May 28, 2014

Lisa discussed the Monty Hall problem on Numberphile, a mathematical YouTube series produced by British filmmaker Brady Haran. A follow-up video featuring Brady adds to the discussion.

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Newest Working Papers

Comparative Statics in Finite Horizon Finance Economies with Stochastic Taxation

Comparative Statics in Finite Horizon Finance Economies with Stochastic Taxation
Konstantin Magin

This paper studies comparative statics of Financial Markets (FM) equilibria in the finite horizon General Equilibrium with Incomplete Markets (GEI) model with respect to changes in stochastic tax rates imposed on agent’s endowments and dividends. We show that under reasonable assumptions, without assuming CRRA and identical agents, an increase in the current dividend tax rate unambiguously reduces current asset prices. The paper also finds that there exists a bound B such that for a coefficient of relative risk aversion less than B, an increase in a future dividend tax rate reduces current price of tradable assets. At the same time, for a coefficient of relative risk aversion greater than B, an increase in a future dividend tax rate boosts the current price of tradable assets. Finally, for a coefficient of relative risk aversion equal to B, an increase in a future dividend tax rate leaves current consumption and current price of tradable assets unchanged. As a special case, under additional assumptions, B is equal to 1. Also, under reasonable assumptions, an increase in the current endowment tax rate reduces current asset prices, while an increase in a future endowment tax rate boosts current asset prices. more…

 

Examining US REITs Pricing Bubbles: An Application of the CCAPM with Stochastic Taxation and Money Supply

Examining US REITs Pricing Bubbles: An Application of the CCAPM with Stochastic Taxation and Money Supply
Robert H. Edelstein and Konstantin Magin

This paper examines three issues relating to US REITs pricing. First, using a modified Consumption Capital Asset Pricing Model (CCAPM) with stochastic taxation and money supply, we compute the fundamental values for United States Real Estate Investment Trusts (REITs) for our data sample, 1972-2013. Our empirical analysis for US REIT pricing is statistically consistent with the CCAPM with stochastic taxation and monetary policy. Second, for our purposes, for publicly traded equity REITs, we define a bubble at a point in time to be the difference between the actual stock market price and the fundamental value derived from our theoretical model. United States REITs have, among other corporate structural features, special rules governing dividend distributions and corporate taxation treatment that make them an especially attractive and preferred vehicle for testing for the presence of pricing bubbles. Our study suggests that during the sample time horizon, United States REITs experienced many price bubbles, some of which were quite large. Third, our empirical results imply that monetary policy, in the short run, plays a role in the formation of these pricing bubbles. more…

Infinite Horizon CCAPM with Stochastic Taxation and Monetary Policy

Infinite Horizon CCAPM with Stochastic Taxation and Monetary Policy
Konstantin Magin

This paper derives the infinite horizon CCAPM with heterogeneous agents, stochastic dividend taxation and monetary policy. I find that under reasonable assumptions on assets’ dividends and probability distributions of the future dividend taxes and consumption, the model implies the constant price/after-tax dividend ratios. I also obtain that the higher current and expected dividend tax rates imply lower current asset prices. Finally, contrary to popular belief, monetary policy is neutral, in the long run, with respect to the real equilibrium asset prices. more…

Generic Existence of Equilibria in Finite Horizon Finance Economies with Stochastic Taxation

Generic Existence of Equilibria in Finite Horizon Finance Economies with Stochastic Taxation
Konstantin Magin

The paper proves the existence of equilibria in the finite horizon general equilibrium with incomplete markets (GEI) model with insecure property rights. Insecure property rights come in the form of the stochastic taxes imposed on agents’ endowments and assets’ dividends. This paper finds that under reasonable assumptions, Financial Markets (FM) equilibria exist for most of the stochastic tax rates. Moreover, sufficiently small changes in stochastic taxation preserve the existence and completeness of FM equilibria. more…

Understanding Systematic Risk: A High-Frequency Approach

Understanding Systematic Risk: A High-Frequency Approach
Markus Pelger

Under a large dimensional approximate factor model for asset returns, I use high-frequency data for the S&P 500 firms to estimate the latent continuous and jump factors. I estimate four very persistent continuous systematic factors for 2007 to 2012 and three from 2003 to 2006. These four continuous factors can be approximated very well by a market, an oil, a finance and an electricity portfolio. The value, size and momentum factors play no significant role in explaining these factors. For the time period 2003 to 2006 the finance factor seems to disappear. There exists only one persistent jump factor, namely a market jump factor. Using implied volatilities from option price data, I analyze the systematic factor structure of the volatilities. There is only one persistent market volatility factor, while during the financial crisis an additional temporary banking volatility factor appears. Based on the estimated factors, I can decompose the leverage effect, i.e. the correlation of the asset return with its volatility, into a systematic and an idiosyncratic component. The negative leverage effect is mainly driven by the systematic component, while it can be non-existent for idiosyncratic risk. more…

Large-Dimensional Factor Modeling Based on High-Frequency Observations

Large-Dimensional Factor Modeling Based on High-Frequency Observations
Markus Pelger

This paper develops a statistical theory to estimate an unknown factor structure based on financial high-frequency data. I derive a new estimator for the number of factors and derive consistent and asymptotically mixed-normal estimators of the loadings and factors under the assumption of a large number of cross-sectional and high-frequency observations. The estimation approach can separate factors for normal “continuous” and rare jump risk. The estimators for the loadings and factors are based on the principal component analysis of the quadratic covariation matrix. The estimator for the number of factors uses a perturbed eigenvalue ratio statistic. The results are obtained under general conditions, that allow for a very rich class of stochastic processes and for serial and cross-sectional correlation in the idiosyncratic components. more…

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