Futures trading, spot price volatility and market efficiency: evidence from European real estate securities futures

In 2007 futures contracts were introduced based upon the listed real estate market in Europe. Following their launch they have received increasing attention from property investors, however, few studies have considered the impact their introduction has had. This study considers two key elements. Firstly, a traditional Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, the approach of Bessembinder & Seguin (1992) and the Gray’s (1996) Markov-switching-GARCH model are used to examine the impact of futures trading on the European real estate securities market. The results show that futures trading did not destabilize the underlying listed market. Importantly, the results also reveal that the introduction of a futures market has improved the speed and quality of information flowing to the spot market. Secondly, we assess the hedging effectiveness of the contracts using two alternative strategies (naïve and Ordinary Least Squares models). The empirical results also show that the contracts are effective hedging instruments, leading to a reduction in risk of 64 %.

Does the Future Price Help Forecast the Spot Price?

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Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

A comparison of electricity spot prices simulation using ARMA-GARCH and mean-reverting models

The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Commodity Future Price Premiums – Case EU ETS

The purpose of this thesis was to study commodity future price premiums and their nature on emission allowance markets. The EUA spot and future contracts traded on the secondary market during EU ETS Phase 2 and Phase 3 were selected for empirical testing. The cointegration of spot and future prices was examined with Johansen cointegration methodology. Daily interest rates with a similar tenor to the future contract maturity were used in the cost-of-carry model to calculate the theoretical future prices and to estimate the deviation from the fair value of future contracts, assumed to be explained by the convenience yield. The time-varying dependence of the convenience yield was studied by regression testing the correlation between convenience yield and the time to maturity of the future contract. The results indicated cointegration between spot and future prices, albeit depending on assumptions on linear trend and intercept in cointegration vector Dec-14 and Dec-15 contracts. The convenience yield correlates positively with the time-to-maturity of the future contract during Phase 2, but negatively during Phase 3. The convenience yield featured positive correlation with spot price volatility and negative correlation with future price volatility during both Phases 2 and 3.

Hydrologisen tilanteen ja tuulivoimatuotannon muutosten vaikutus vesiarvoihin pohjoismaisilla sähkön spot-markkinoilla

Vesivoimalla on merkittävä rooli pohjoismaisessa sähköntuotantojärjestelmässä. Spot-markkinoille tarjottavan vesivoiman hinta riippuu vaihtoehtoisen tuotannon hinnasta ja odotetusta vesivoimantuottajien käytettävissä olevasta veteen sitoutuneen potentiaalienergian määrästä. Hydrologisella tilanteella tarkoitetaan tässä tämän potentiaalienergian poikkeamaa normaalitasostaan. Viime vuosina tuulivoimatuotanto pohjoismaisella sähkömarkkina-alueella on kasvanut voimakkaasti, ja on tullut aiheelliseksi tarkastella, millaisia vaikutuksia tällä on vesivoimantuottajien toimintaan. Työssä määritellään vesivoimalle vaihtoehtoisen sähköntuotannon tuotantokustannus, joka pitkällä aikavälillä toimii vertailutasona, jonka perusteella vesivoimantuottajat määrittävät markkinoilla tarjontahinnan tuotannolleen. Tarkastellaan, kuinka hydrologisen tilanteen ja vaihtoehtoisen tuotannon tuotantokustannusten muutokset vaikuttavat vesiarvoon, joka on hinta, jolla hintariippuvaista eli säätyvää vesivoimaa tarjotaan spot-markkinoille. Todetaan, että hydrologisen tilanteen vahvistuminen ja vaihtoehtoisen tuotantokustannuksen aleneminen alentavat vesiarvoja. Todetaan lisäksi, että tuulivoima vaikuttaa sähkön hinnanmuodostukseen markkinoilla samankaltaisesti kuin hintariippumaton vesivoimatuotanto. Esitetään aikasarjamalli vesivoimatuotannon hintariippuvuuden mallintamiseksi. Vertaillaan vesivoimatuottajien toimintaa kahdella vesivoimatuotantoa sisältävällä hinta-alueella, joista toisella tuulivoimatuotanto on kasvanut voimakkaammin kuin toisella. Havaitaan, että molemmilla hinta-alueilla hydrologisen tilanteen vahvistuminen on alentanut ja heikkeneminen nostanut vesiarvoja. Lisäksi havaitaan, että alueella, jonka tuulivoimatuotanto on kasvanut enemmän, vesiarvot ovat laskeneet suhteessa alueen, jolla tuulivoimatuotanto on kasvanut vähemmän, vesiarvoihin. Tuulivoiman voidaan todeta syrjäyttäneen markkinoilta tuotantokustannuksiltaan kalliimpaa tuotantoa.

A trading strategy based on the lead–lag relationship between the spot index and futures contract for the FTSE 100

This paper examines the lead–lag relationship between the FTSE 100 index and index futures price employing a number of time series models. Using 10-min observations from June 1996–1997, it is found that lagged changes in the futures price can help to predict changes in the spot price. The best forecasting model is of the error correction type, allowing for the theoretical difference between spot and futures prices according to the cost of carry relationship. This predictive ability is in turn utilised to derive a trading strategy which is tested under real-world conditions to search for systematic profitable trading opportunities. It is revealed that although the model forecasts produce significantly higher returns than a passive benchmark, the model was unable to outperform the benchmark after allowing for transaction costs.

Short-term electricity price forecasting using wavelet and SVM techniques

In deregulated electricity market, modeling and forecasting the spot price present a number of challenges. By applying wavelet and support vector machine techniques, a new time series model for short term electricity price forecasting has been developed in this paper. The model employs both historical price and other important information, such as load capacity and weather (temperature), to forecast the price of one or more time steps ahead. The developed model has been evaluated with the actual data from Australian National Electricity Market. The simulation results demonstrated that the forecast model is capable of forecasting the electricity price with a reasonable forecasting accuracy.

An Analysis of Colombian Power Market Price Behavior from an Industrial Organization Perspective

We analyze the behavior of spot prices in the Colombian wholesale power market, using a series of models derived from industrial organization theory -- We first create a Cournot-based model that simulates the strategic behavior of the market-leader power generators, which we use to estimate two industrial organization variables, the Index of Residual Demand and the Herfindahl-Hirschman Index (HHI) -- We use these variables to create VAR models that estimate spot prices and power market impulse-response relationships -- The results from these models show that hydroelectric generators can use their water storage capability strategically to affect off-peak prices primarily, while the thermal generators can manage their capacity strategically to affect on-peak prices -- In addition, shocks to the Index of Residual Capacity and to the HHI cause spot price fluctuations, which can be interpreted as the generators´ strategic response to these shocks

Multidimensional Scaling Visualization using Parametric Similarity Indices

In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of ‘points’. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of “shapes”. This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

The importance and accuracy of wind power forecasts

Due to the global crisis o f climate change many countries throughout the world are installing the renewable energy o f wind power into their electricity system. Wind energy causes complications when it is being integrated into the electricity system due its intermittent nature. Additionally winds intennittency can result in penalties being enforced due to the deregulation in the electricity market. Wind power forecasting can play a pivotal role to ease the integration o f wind energy. Wind power forecasts at 24 and 48 hours ahead of time are deemed the most crucial for determining an appropriate balance on the power system. In the electricity market wind power forecasts can also assist market participants in terms o f applying a suitable bidding strategy, unit commitment or have an impact on the value o f the spot price. For these reasons this study investigates the importance o f wind power forecasts for such players as the Transmission System Operators (TSOs) and Independent Power Producers (IPPs). Investigation in this study is also conducted into the impacts that wind power forecasts can have on the electricity market in relation to bidding strategies, spot price and unit commitment by examining various case studies. The results o f these case studies portray a clear and insightful indication o f the significance o f availing from the information available from wind power forecasts. The accuracy o f a particular wind power forecast is also explored. Data from a wind power forecast is examined in the circumstances o f both 24 and 48 hour forecasts. The accuracy o f the wind power forecasts are displayed through a variety o f statistical approaches. The results o f the investigation can assist market participants taking part in the electricity pool and also provides a platform that can be applied to any forecast when attempting to define its accuracy. This study contributes significantly to the knowledge in the area o f wind power forecasts by explaining the importance o f wind power forecasting within the energy sector. It innovativeness and uniqueness lies in determining the accuracy o f a particular wind power forecast that was previously unknown.

Sähkön omatuotannon kannattavuustarkastelu

Tässä diplomityössä tutkitaan sähkön omatuotannon kannattavuutta M-realin Simpeleen tehtaiden voimalaitoksella. Erityisesti työssä arvioidaan lauhdesähköntuotannon kannattavuutta polttoaine- ja päästökustannuksista muodostuvien marginaalikustannusten osalta. Koska voimalaitoksen rakennusaste on varsin alhainen,sähköntuotannon kannattavuutta on tarkasteltu arvioimalla sähkön ja lämmön yhteistuotannon kustannuksia ja jakamalla syntyneet kustannukset suhdemenetelmän avulla eri tuotteille. Diplomityössä etsitään kustannustehokkain seospolttosuhde annettujen reunaehtojen puitteissa muodostamalla polttoaineista aiheutuvista kustannuksista laskentamalli, jota optimoidaan Microsoft Excelin Solver-toiminnolla. Lauhdesähköntuotannon marginaalikustannuksia verrataan Nord Poolin SPOT-tuntihintaan. Lauhdesähköntuotanto voimalaitoksella on kannattavaa, mikäli SPOT-tuntihinnan vuorokautinen keskiarvo ylittää lauhdesähköntuotannon marginaalikustannukset.

Sähkön markkinahintaa selittävät tekijät. Case: Nord Pool 2000-2005

Sähkön markkinahinta on saanut osakseen suurta huomiota viimeaikoina. Sähkömarkkinoiden vapautuminen ja päästökaupan avaaminen Euroopassa onentisestään nostanut sähkömarkkinoita näkyville lehdissä. Tämä tutkielma tutkii erilaisten tekijöiden vaikutusta sähkön markkinahintaan regressioanalyysin avulla. Edellä mainitun päästösopimusten markkinahinnan lisäksi tutkittiin kivihiilen sekä maakaasun markkinahintojen, lämpötilojen, jokien virtaamien, vesivarantojen täyttöasteiden sekä Saksan sähkömarkkinoiden hinnan vaikutusta sähkön markkinahintaan Nord Pool -sähköpörssissä. Työssä luotiin myös sähkön markkinahintaa ennustava malli. Kaikkien selittävien tekijöiden korrelaatiot olivat oletusten mukaiset ja regressioanalyysi onnistui selittämään yli 80 % sähkön markkinahinnan vaih-teluista. Merkittävimpiä selittäviä tekijöitä olivat vesivarannot sekä jokien virtaamat. Ennustavan mallin keskimääräinen suhteellinen virhe oli noin 10 %, joten ennustetarkkuus oli melko hyvä.

Kalenterianomaliat pohjoismaisilla sähkömarkkinoilla

Osakemarkkinoilta on jo useiden vuosien ajan julkaistu lukuisia tutkimuksia, joissa on esitetty havaintoja ajallisesta säännönmukaisuudesta osakkeiden hinnoissa, joita ei pystytä selittämään markkinakohtaisilla fundamenteilla. Nämä niin kutsutut kalenterianomaliat esiintyvät tyypillisesti ajallisissa käännepisteissä, kuten vuoden, kuukauden tai viikon vaihtuessa seuraavaksi. Myös erilaisten katkosten, kuten juhlapyhien, kaupankäyntirutiineissa on havaittu aiheuttavan anomalioita. Tutkimuksen tavoitteena oli tutkia osakemarkkinoilla havaittujen kalenterianomalioiden esiintymistä pohjoismaisilla sähkömarkkinoilla. Tutkitut anomaliat olivat viikonpäivä- kuukausi-, kuunvaihde- ja juhlapyhäanomalia. Näiden lisäksi tutkittiin tuottojen käyttäytymistä optioiden erääntymispäivien läheisyydessä. Yksittäisten tuotteiden sijasta tarkastelut suoritettiin sesonki- ja kvartaalituotteista muodostetuilla vuosituotteilla. Testauksessa käytettiin pienimmän neliösumman menetelmää, huomioidenheteroskedastisuuden, autokorrelaation ja multikollineaarisuuden vaikutukset. Pelkkien kalenterimuuttujien lisäksi testit suoritettiin regressiomalleilla, joissa lisäselittäjinä käytettiin spot-hintaa, päästöoikeuden hintaa ja/tai sade-ennusteita. Tarkastelujakso koostui vuosista 1998-2006.