Suchergebnisse

AbstractJumps in the paths of efficient asset prices have important economic implications. Motivated by the issue of testing for jumps based on noisy high‐frequency data, we develop a novel spot volatility estimator, which is obtained by minimizing the sum of some Huber loss functions, and use it as an ingredient for jump detection. This type of estimators is uniformly consistent in estimating the spot volatilities of the efficient price at numerous time points. We further demonstrate the consistency of the proposed jump test based on the property of the novel spot volatility estimator. We show that in finite samples, the proposed volatility estimator and the test perform favorably compared to some competitors through Monte Carlo simulations. We also illustrate our methodology with the stock prices of Apple and Microsoft.

In this paper we analyse the short-term spot price of European Union Allowances (EUAs), which is of particular importance in the transition of energy markets and for the development of new risk management strategies. We use daily spot market data from the second trading period of the EU ETS. Emphasis is given to short-term forecasting of prices and volatility. Due to the characteristics of the price process, such as volatility modelling, breaks in the volatility process and heavy-tailed distributions, we investigate the use of Markov switching GARCH (MS-GARCH) models. We find that these models distinguish well between states, and that the volatility processes in the states are clearly different. Our findings support the use of MS-GARCH models for risk management, especially because their forecasting ability is better than other Markov switching or simple GARCH models.

This paper analyses the volatility of wholesale electricity markets for five markets in Europe. Using GARCH models after filtering outliers, significant asymmetric effects and volatility persistence have been documented. Moreover, empirical evidence is provided on a significant relation between volume and volatility which can be both positive or negative depending on the specific market.

We propose a non-parametric procedure for estimating the realized spot volatility of a price process described by an Itô semimartingale with Lévy jumps. The procedure integrates threshold jump elimination technique of Mancini (2009) with a frame (Gabor) expansion of the realized trajectory of spot volatility. We show that the procedure converges in probability in L²([0; T]) for a wide class of spot volatility processes, including those with discontinuous paths. Our analysis assumes the time interval between price observations tends to zero; as a result, the intended application is for the analysis of high frequency financial data. We investigate practical tests of market efficiency that are not subject to the joint-hypothesis problem inherent in tests that require the specification of an equilibrium model of asset prices. The methodology we propose simplify the testing procedure considerably by reframing the market efficiency question into one about the existence of a local martingale measure. As a consequence, the need to directly verify the no dominance condition is completely avoided. We also investigate market efficiency in the large financial market setting with the introduction of notions of asymptotic no dominance and market efficiency that remain consistent with the small market theory. We obtain a change of numeraire characterization of asymptotic market efficiency and suggest empirical tests of inefficiency in large financial markets. We argue empirically that the U.S. treasury futures market is informational inefficient. We show that an intraday strategy based on the assumption of cointegrated treasury futures prices earns statistically significant excess return over the equally weighted portfolio of treasury futures. We also provide empirical backing for the claim that the same strategy, financed by taking a short position in the 2-Year treasury futures contract, gives rise to a statistical arbitrage.