Fat Tails in Power Prices

Spot power prices exhibit extreme price jumps and the tendency to oscillate around a long-term mean. Despite these well-known characteristics, electricity price models used for Monte Carlo simulations, VaR related measures, or derivatives valuation, often assume normally distributed residuals. In this paper, we examine the distributional characteristics of model residuals and show that the hypothesis of normality is rejected due to significant tail fatness and skewness. We then examine the Student-t distribution as a candidate fit for residuals and as an alternative distribution for random innovations in Monte Carlo simulations. The resulting price patterns clearly show that simulations based on the Student-t distribution resemble more closely actual power price patters. We then discuss the implications of our results for risk management.modelling;risk management;extreme value theory;Monte Carlo simulations;electricity price;spikes

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.Day-ahead electricity;Electricity prices;Energy markets;Panel models

Fat Tails in Power Prices

Spot power prices exhibit extreme price jumps and the tendency to oscillate around a long-term mean. Despite these well-known characteristics, electricity price models used for Monte Carlo simulations, VaR related measures, or derivatives valuation, often assume normally distributed residuals. In this paper, we examine the distributional characteristics of model residuals and show that the hypothesis of normality is rejected due to significant tail fatness and skewness. We then examine the Student-t distribution as a candidate fit for residuals and as an alternative distribution for random innovations in Monte Carlo simulations. The resulting price patterns clearly show that simulations based on the Student-t distribution resemble more closely actual power price patters. We then discuss the implications of our results for risk management

Being in Balance: Economic Efficiency in the Dutch Power Market

In this paper, we examine economic efficiency in the Dutch power market, an important pillar for successful creation of a competitive and non-discriminatory free power market. We examine historical time series of prices and volumes on the Dutch balancing market where energy companies are obliged to offer reserve capacity in order to offset power surpluses and deficits on the grid. We argue that these balancing prices and volumes are indicators for the level of economic efficiency. We find evidence that the level of economic efficiency has increased in the Dutch power market while the level of security of supply has maintained

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

Dealing with Electricity Prices

Christian Huurman was born in Dacca (Bangladesh) on 10 May 1977. From 1995 to 2001, Christian studied Business Administration at the Erasmus University. After obtaining his MSc degree in June 2001, he started his career as an assistant professor at the Strategic Management department of the RSM Erasmus University. During this period he taught several undergraduate courses. In November 2002 he moved to the Financial Management department of the RSM Erasmus University, where he worked as a PhD candidate on this Thesis. Christian Huurman has published in Economische Statistische Berichten and Energy Economics (forthcoming). He currently works for an investment bank in London as an associate at Institutional Securities.In het afgelopen decennium hebben vele landen wereldwijd hun electriciteitsindustrie gedereguleerd. Daardoor zijn er verschillende beurzen gecreëerd, elk met een eigen beleggingshorizon, waarop dagelijks stroom verhandeld wordt. Als gevolg daarvan is er veel voor de marktspelers veranderd en is de vraag relevant geworden op welke wijze met electriciteitsprijzen moet worden omgegaan. Omdat electriciteit niet opgeslagen kan worden, het consumptiepatroon grillig is en er geen substituut van electriciteit bestaat, worden stroomspotprijzen gekarakteriseerd door frequente- en extreme prijsschommelingen. Deze zijn niet terug te zien in de andere energie- of financiële markten. Het deregulatieproces heeft dan ook geleid tot een enorme toename in de vraag naar electriciteitsderivaten door marktspelers om dit prijsrisico te beheersen. Zo moeten eindgebruikers nadenken over hun consumptiepatroon en een passende stroomportfoliostrategie kiezen die consistent is met hun risicopreferentie. Alhoewel academisch onderzoek naar de derivatenwaardering en portfoliomanagementtheorie sterk ontwikkeld is, is er nog weinig bekend over de toepasbaarheid hiervan in electriciteitsmarkten (o.m. vanwege genoemde unieke karakteristieken van stroom(prijzen)). Het grootste gedeelte van het empirisch werk dient dan ook nog te moeten worden gedaan. We leveren hieraan in deze studie een bijdrage door het formuleren en toetsen van niet eerder geteste hypothesen. Ook passen we tijdreeksanalyse, extreme waardetheorie en paneldatamethodologie toe, om daarmee toevoegingen aan te dragen voor de traditionele (spot- en derivaten) prijsmodellering- en portfoliomanagementtheorie. Hiermee trachten we inzicht te krijgen in issues als marktefficiëntie, spotprijs-en forwardrisicopremiedynamiek en efficiëntie portfolioselectie. Data is verkregen van de meest actieve stroombeurzen wereldwijd.The 1990s witnessed the start of a worldwide deregulation process in the electricity industry. Since then, electricity prices have been based on the market rules of supply and demand. The non-storability of electricity, absence of substitutes, inelastic supply and patterns in electricity consumption, make that power prices are subject to mean-reversion, seasonality and frequent price jumps. These stylized facts are not as extreme as those observed in any other commodity- or financial market. The reforms have triggered the demand for electricity derivatives, and have led to the introduction of market places where electricity can be traded on spot or forward. These markets enable market players to allocate the price risk that they are exposed to, by selecting portfolios consisting of spot- and derivative contracts in accordance with their risk appetite. Although academic research on valuation of derivatives and portfolio theory is well-established, little is known about its applicability in electricity markets due to the aforementioned unique characteristics. The scientific contribution of this research is to extend the empirical methodology by conducting tests for untested hypotheses and propose alternative methodologies for (spot- and derivative) price modelling and portfolio management. We do so by using time-series analysis, extreme value theory, panel data models and portfolio theory. Data is obtained from the most active electricity exchanges in the world. We hereby provide answers to yet unresolved issues on market efficiency, spot price dynamics, forward risk premia dynamics and structuring of the sourcing portfolio

Non-excisional techniques for the treatment of intergluteal pilonidal sinus disease:a systematic review

Non-excisional techniques for pilonidal sinus disease (PSD) have gained popularity over the last years. The aim of this study was to review short and long-term outcomes for non-excisional techniques with special focus on the additive effect of treatment of the inner lining of the sinus cavity and the difference between primary and recurrent PSD. A systematic search was conducted in Embase, Medline, Web of Science Core Collection, Cochrane and Google Scholar databases for studies on non-excisional techniques for PSD including pit picking techniques with or without additional laser or phenol treatment, unroofing, endoscopic techniques and thrombin gelatin matrix application. Outcomes were recurrence rates, healing rates, complication rates, wound healing times and time taken to return to daily activities. In total, 31 studies comprising 8100 patients were included. Non-excisional techniques had overall healing rates ranging from 67 to 100%. Recurrence rates for pit picking, unroofing and gelatin matrix application varied from 0 to 16% depending on the follow-up time. Recurrence rates after additional laser, phenol and endoscopic techniques varied from 0 to 29%. Complication rates ranged from 0 to 16%, and the wound healing time was between three and forty-seven days. The return to daily activities varied from one to nine days. Non-excisional techniques are associated with fast recovery and low morbidity but recurrence rates are high. Techniques that attempt to additionally treat the inner lining of the sinus have worse recurrence rates than pit picking alone. Recurrence rates do not differ between primary and recurrent disease.</p

Graves Hyperthyroidism After Stopping Immunosuppressive Therapy in Type 1 Diabetic Islet Cell Recipients With Pretransplant TPO Autoantibodies

OBJECTIVE — After an initially successful islet cell transplantation, a number of patients return to C-peptide negativity, and therefore immunosuppressive therapy is discontinued. Some are then found to have developed Graves disease. We examined the risk of Graves disease after immunosuppression. RESEARCHDESIGNANDMETHODS — Immunosuppressive therapy was stopped in 13 type 1 diabetic islet cell recipients who had received one course of antithymocyte globulin and maintenance doses of mycophenolate mofetil and a calcineurin inhibitor. None had a history of thyroid disease. RESULTS — In four patients, clinical Graves hyperthyroidism was observed within 21 months after discontinuation and 30–71 months after the start of immunosuppressive therapy. All four patients exhibited a pretransplant positivity for thyroid peroxidase (TPO) autoantibod-ies, while the nine others were TPO negative pre- and posttransplantation. CONCLUSIONS — Type 1 diabetic recipients of islet cell grafts with pretransplant TPO autoantibody positivity exhibit a high risk for developing Graves hyperthyroidism after immu-nosuppressive therapy is discontinued for a failing graft. Diabetes Care 32:1817–1819, 2009 I slet cell transplantation has beenshown to reproducibly achieve meta-bolic correction in nonuremic type 1 diabetic patients (1,2). However, in the years following transplantation, several of them return to C-peptide negativity and thus to a discontinuation of their immu-nosuppressive therapy (2)