Carl J. Ullrich

Forecasting Spot Price Volatility Using the Short-Term Forward Curve

We use high frequency real time spot prices and day-ahead forward prices from the Pennsylvania–New Jersey–Maryland wholesale electricity market to calculate, describe, and forecast spot price volatility. We introduce the concept of forward realized volatility calculated from day-ahead forward prices. Forward realized volatility improves forecasts of spot price volatility – in the sense of higher R2s and significantly lower forecast errors – when compared with forecasts based solely upon historical volatility. The largest forecast improvements obtained when the change in forward realized volatility is large in magnitude. Splitting total volatility into its continuous and jump components is crucial for forecasting volatility at weekly and monthly horizons.

Constrained Capacity and Equilibrium Forward Premia in Electricity Markets

This paper extends the equilibrium electricity pricing model in Bessembinder and Lemmon (2002). The new model accounts for constrained capacity, an important feature in electricity markets. Explicitly including a role for capacity allows the model to reproduce the price spikes observed in wholesale electricity markets using reasonable parameter values. The model implies that the equilibrium forward premium, defined to be the forward price minus the expected spot price, is decreasing in spot price variance when the expected spot price is low, but is increasing in the spot price variance when the expected spot price is high. I extend the empirical work in Longstaff and Wang (2004) and show that data from the Pennsylvania-New Jersey-Maryland (PJM) market support these model predictions.

Regulatory Uncertainty, Corporate Expectations, and the Postponement of Investment: The Case of Electricity Market Deregulation

We examine whether regulatory uncertainty encourages firms to delay capital investment decisions. The case of electricity market deregulation in the U.S is unique because the period of regulatory uncertainty is long-lived and there are data available on planned future investments. These previously unused expectational data provide unique insight into the broader effects of regulatory uncertainty. Relying on a real options modeling perspective, we hypothesize that industry participants reduced their investments in electric power-generating assets dramatically in the 1990s in response to increased regulatory uncertainty and then, just as dramatically, increased investment beginning in 2000 due to the resolution of some regulatory uncertainty. We provide empirical evidence that regulatory uncertainty is significantly and strongly negatively related to planned utility investments. This negative effect is 44% stronger for so-called green technologies.

Continuous-Time Models of Currency Volatility

How does currency return volatility evolve over time and what are the properties of volatility dynamics? What forms of non-linearities are admitted in the drift and diffusion functions? The purpose of this study is to estimate a large class of volatility processes and explore these issues using weekly observations on U.S. dollar-based Japanese yen and British pound options data. The approach is based on maximum-likelihood estimation that relies on closed-form density approximations (Ait-Sahalia, 1999; Ait-Sahalia, 2002). Based on volatility implied by currency options, the affine square root specification for the variance of variance function commonly adapted in the literature is misspecified. The constant elasticity of variance (CEV) specification provides a reasonable characterization of the variance of variance function. Unlike previous findings for equity volatility, extending the diffusion function beyond the CEV specification does not improve the fit of the model, regardless of the assumed form of the drift function.