Regime Jumps in Electricity Prices

Electricity prices are known to be very volatile and subject to frequent jumps due to system breakdown, demand shocks, and inelastic supply. As many international electricity markets are in some state of deregulation, more and more participants in these markets are exposed to these stylised facts. Appropriate pricing, portfolio, and risk management models should incorporate these facts. Authors have introduced stochastic jump processes to deal with the jumps, but we argue and show that this specification might lead to problems with identifying the true mean-reversion within the process. Instead, we propose using a regime jump model that disentangles mean-reversion from jump behaviour. This model resembles more closely the true price path of electricity prices

Revisiting Uncovered Interest Rate Parity: Switching Between UIP and the Random Walk

In this paper, we examine in which periods uncovered interest rate parity was likely to hold. Empirical research has shown mixed evidence on UIP. The main finding is that it doesn’t hold, although some researchers were not able to reject UIP in periods with large interest differentials or high volatility. In this paper, we introduce a switching regime framework in which we assume that the exchange rate can switch between a UIP regime and a random walk regime. Our empirical results provide evidence that exchange rate movements were consistent with UIP over some periods, but not all. Consistent with the existing literature we also show that in periods with large interest differentials or increased exchange rate volatility, the exchange rate is more likely to follow UIP

Regime jumps in electricity prices

Many countries are liberalizing their energy markets. Participants in these markets are exposed to market risk due to the characteristics of electricity price dynamics. Electricity prices are known to be mean-reverting very volatile and subject to frequent spikes. Models that describe the dynamics of electricity prices should incorporate these characteristics. In order to capture the price spikes, many researchers have introduced stochastic jump processes, but we argue and show that this specification might lead to potential problems with specifying the true amount of mean-reversion within the process. In this paper, we propose a regime-switching model that models price spikes separated from normal mean-reverting prices

Guaranteeing benefits in generational pension plans

In this paper we analyze the possibilities of intergenerational risk sharing in a generational DB pension fund. Each generation is subject to discretionary investment, indexation and contribution policies, thereby losing intergenerational diversification gains. Intergenerational risk sharing is repaired by introducing contingent claims on the generational surplus or deficit. We find that in some circumstances the values of these options can be substantial

Hourly Electricity Prices in Day-Ahead Markets

This paper focuses on the characteristics of hourly electricity prices in day-ahead markets. In these markets, quotes for day-ahead delivery of electricity are submitted simultaneously for all hours in the next day. The same information set is used for quoting all hours of the day. The dynamics of hourly electricity prices does not behave as a time series process. Instead, these prices should be treated as a panel in which the prices of 24 cross-sectional hours vary from day to day. This paper introduces a panel model for hourly electricity prices in day-ahead markets and examines their characteristics. The results show that hourly electricity prices exhibit hourly specific mean-reversion and that they oscillate around an hourly specific mean price level. Furthermore, a block structured cross-sectional correlation pattern between the hours is apparent

Do Exchange Rates Move in Line With Uncovered Interest Parity?

According to uncovered interest rate Parity (UIP), the expected relative change in an exchange rate is equal to the difference between interest rates between the two currencies. Empirically, UIP is frequently rejected. In this paper, we examine whether exchange rates have at least any tendency to move in the direction predicted by UIP and whether exchange rates tend to move more in line with UIP in periods with large interest rate differentials

Electricity Portfolio Management: Optimal Peak / Off-Peak Allocations

Electricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to allocate optimal positions in peak and off-peak forward contracts. It is shown that the optimal allocations are based on the difference in risk premiums per unit of day-ahead risk as a measure of relative costs of hedging risk in the day-ahead markets. The outcomes of the model are then applied to show 1) whether it is optimal to purchase a baseload consumption profile with a baseload forward contract and 2) that, under reasonable assumptions, risk taking by the purchaser is rewarded by lower expected costs

Hedging Exposure to Electricity Price Risk in a Value at Risk Framework

This paper deals with the question how an electricity end-consumer or distribution company should structure its portfolio with energy forward contracts. This paper introduces a one period framework to determine optimal positions in peak and off-peak contracts in order to purchase future consumption volume. In this framework, the end-consumer or distribution company is assumed to minimize expected costs of purchasing respecting an ex-ante risk limit defined in terms of Value at Risk. Based on prices from the German EEX market, it is shown that a risk-loving agent is able to obtain lower expected costs than for a risk-averse agent

A Range-Based Multivariate Model for Exchange Rate Volatility

In this paper we present a parsimonious multivariate model for exchange rate volatilities based on logarithmic high-low ranges of daily exchange rates. The multivariate stochastic volatility model divides the log range of each exchange rate into two independent latent factors, which are interpreted as the underlying currency specific components. Due to the normality of logarithmic volatilities the model can be estimated conveniently with standard Kalman filter techniques. Our results show that our model fits the exchange rate data quite well. Exchange rate news seems to be very currency-specific and allows us to identify which currency contributes most to both exchange rate levels and exchange rate volatilities

An empirical application of stochastic volatility models

This paper studies the empirical performance of stochastic volatility models for twenty years of weekly exchange rate data for four major currencies. We concentrate on the effects of the distribution of the exchange rate innovations for both parameter estimates and for estimates of the latent volatility series. The density of the log of squared exchange rate innovations is modelled as a flexible mixture of normals. We use three different estimation techniques: quasi-maximum likelihood, simulated EM, and a Bayesian procedure. The estimated models are applied for pricing currency options. The major findings of the paper are that: (1) explicitly incorporating fat-tailed innovations increases the estimates of the persistence of volatility dynamics; (2) the estimation error of the volatility time series is very large; (3) this in turn causes standard errors on calculated option prices to be so large that these prices are rarely significantly different from a model with constant volatility