Pricing of the time-change risks

We develop an equilibrium endowment economy with Epstein-Zin recursive utility and a Lévy time-change subordinator, which represents a clock that connects business and calendar time. Our setup provides a tractable equilibrium framework for pricing non-Gaussian jump-like risks induced by the time-change, with closed-form solutions for asset prices. Persistence of the time-change shocks leads to predictability of consumption and dividends and time-variation in asset prices and risk premia in calendar time. In numerical calibrations, we show that the risk compensation for Lévy risks accounts for about one-third of the overall equity premium.     

Bidding asymmetries in multi-unit auctions: Implications of bid function equilibria in the British spot market for electricity

This paper introduces and tests Bid Function Equilibria (BFE) in the British spot market for electricity. BFE extend von der Fehr and Harbord's (1993) multi-unit auction model of wholesale electricity markets by allowing firms to have heterogeneous costs for different generating units. Pure-strategy equilibria in BFE predict asymmetric bidding by producers: a single firm (the “price-setter") bids strategically while other firms (“non-price-setters") bid their costs. We test for asymmetries in firms' bid functions in the British spot market between 1993 and 1995 and find strong empirical support for the theory. We conclude that BFE have important implications for the design and governance of electricity markets.     

Risk,jumps, and diversification

We test for price discontinuities, or jumps, in a panel of high-frequency intraday stock returns and an equiweighted index constructed from the same stocks. Using a new test for common jumps that explicitly utilizes the cross-covariance structure in the returns to identify non-diversifiable jumps, we find strong evidence for many modest-sized, yet highly significant, cojumps that simply pass through standard jump detection statistics when applied on a stock-by-stock basis. Our results are further corroborated by a striking within-day pattern in the significant cojumps, with a sharp peak at the time of regularly scheduled macroeconomic news announcements.     

Leverage and Volatility Feedback Effects in High-Frequency Data

We examine the relationship between volatility and past andfuture returns using high-frequency aggregate equity index data.Consistent with a prolonged "leverage" effect, we find the correlationsbetween absolute high-frequency returns and current and pasthigh-frequency returns to be significantly negative for severaldays, whereas the reverse cross-correlations are generally negligible.We also find that high-frequency data may be used in more accuratelyassessing volatility asymmetries over longer daily return horizons.Furthermore, our analysis of several popular continuous-timestochastic volatility models clearly points to the importanceof allowing for multiple latent volatility factors for satisfactorilydescribing the observed volatility asymmetries.     

Risk and return: Long-run relations,fractional cointegration,and return predictability

Univariate dependencies in market volatility, both objective and risk neutral, are best described by long-memory fractionally integrated processes. Meanwhile, the ex post difference, or the variance swap payoff reflecting the reward for bearing volatility risk, displays far less persistent dynamics. Using intraday data for the Standard & Poor's 500 and the volatility index (VIX), coupled with frequency domain methods, we separate the series into various components. We find that the coherence between volatility and the volatility-risk reward is the strongest at long-run frequencies. Our results are consistent with generalized long-run risk models and help explain why classical efforts of establishing a naïve return-volatility relation fail. We also estimate a fractionally cointegrated vector autoregression (CFVAR). The model-implied long-run equilibrium relation between the two variance variables results in nontrivial return predictability over interdaily and monthly horizons, supporting the idea that the cointegrating relation between the two variance measures proxies for the economic uncertainty rewarded by the market.     

Realized jumps on financial markets and predicting credit spreads

This paper extends the jump detection method based on bipower variation to identify realized jumps on financial markets and to estimate parametrically the jump intensity, mean, and variance. Finite sample evidence suggests that the jump parameters can be accurately estimated and that the statistical inferences are reliable under the assumption that jumps are rare and large. Applications to equity market, treasury bond, and exchange rate data reveal important differences in jump frequencies and volatilities across asset classes over time. For investment grade bond spread indices, the estimated jump volatility has more forecasting power than interest rate factors and volatility factors including option-implied volatility, with control for systematic risk factors. The jump volatility risk factor seems to capture the low frequency movements in credit spreads and comoves countercyclically with the price–dividend ratio and corporate default rate.     

Socially optimal and equilibrium distributions of office activity: Models with exogenous and endogenous contacts

Two models of the location of office activities within a city are developed. In the first model, the pattern of interoffice contacts is specified exogenously as has been traditional in the literature. In the second model the contact patterns as well as the distribution of firms are endogenous. For both models, the market equilibrium distribution of office activities is not socially optimal. Two sources for this market failure are identified in these models: (1) agglomeration economies and (2) transactional externalities arising from firm interdependence and mobility.