On Option Price Information Content and Extraction of Implied Probability Distributions

In this study we used market settlement prices of European call options on stock index futures to extract implied probability distribution function (PDF). The method used produces a PDF of returns of an underlying asset at expiration date from implied volatility smile. With this method, the assumption of lognormal distribution (Black-Scholes model) is tested. The market view of the asset price dynamics can then be used for various purposes (hedging, speculation). We used the so called smoothing approach for implied PDF extraction presented by Shimko (1993). In our analysis we obtained implied volatility smiles from index futures markets (S&P 500 and DAX indices) and standardized them. The method introduced by Breeden and Litzenberger (1978) was then used on PDF extraction. The results show significant deviations from the assumption of lognormal returns for S&P500 options while DAX options mostly fit the lognormal distribution. A deviant subjective view of PDF can be used to form a strategy as discussed in the last section.

Comovement of stock price risk in strategic alliance — Case: mobile internet

The focus of this study has been comovement of stock price risk level between two companies as they form strategic alliance. Thus the main reason has been to shed more light to possible increased risk level that the stockholder confronts when a company he owns forms a strategic alliance with another company. This study has centralized to interfirm cooperation between mobile and internet companies, which have furthered the development of mobile internet. The study has been divided into theoretical and empirical part. In theoretical part the main concepts riskiness of a stock (volatility), comovement and strategic alliance have been run through. In empirical part seven strategic alliances formed by mobile internet companies have been examined. Based on this, strategic alliance seems to increase comovement of stock price risk in some degree. This comovement seems to be stronger when core businesses or operating environments of cooperating companies differ more from each other.

Commodity Price Driven Risk Management from Viewpoint of High Grade Steel Alloys

The study of price risk management concerning high grade steel alloys and their components was conducted. This study was focused in metal commodities, of which nickel, chrome and molybdenum were in a central role. Also possible hedging instruments and strategies for referred metals were studied. In the literature part main themes are price formation of Ni, Cr and Mo, the functioning of metal exchanges and main hedging instruments for metal commodities. This section also covers how micro and macro variables may affect metal prices from the viewpoint of short as well as longer time period. The experimental part consists of three sections. In the first part, multiple regression model with seven explanatory variables was constructed to describe price behavior of nickel. Results were compared after this with information created with comparable simple regression model. Additionally, long time mean price reversion of nickel was studied. In the second part, theoretical price of CF8M alloy was studied by using nickel, ferro-chrome and ferro-molybdenum as explanatory variables. In the last section, cross hedging possibilities for illiquid FeCr -metal was studied with five LME futures. Also this section covers new information concerning possible forthcoming molybdenum future contracts as well. The results of this study confirm, that linear regression models which are based on the assumption of market rationality, are not able to reliably describe price development of metals at issue. Models fulfilling assumptions for linear regression may though include useful information of statistical significant variables which have effect on metal prices. According to the experimental part, short futures were found to incorporate the most accurate information concerning the price movements in the future. However, not even 3M futures were able to predict turning point in the market before the faced slump. Cross hedging seemed to be very doubtful risk management strategy for illiquid metals, because correlations coefficients were found to be very sensitive for the chosen time span.

Suljetun jäähdytysvesiverkon mallinnus

Työssä selvitettiin Neste Oil Porvoon jalostamon tuotantolinja 2 jäähdytysvesiverkon tilaa. Jäähdytysvesiverkon hydraulinen malli päivitettiin ja verifioitiin painemittauksin. Mallia tarkennettiin säätöventtiilien mallinnuksen sekä virhelähteiden tarkastelun perusteella havaituin muutoksin. Mallin verifioinnissa havaittiin huomattavia eroja mallin ja mitattujen paineiden välillä. Tämä johti mallin tarkempaan tarkasteluun, sekä virhelähteiden ja niiden vaikutusten selvittämiseen. Putkivarusteiden mallinnusmenetelmiä, sekä mallinnusperiaatteita vertailtiin keskenään. Koska jäähdytysveden kokonaiskierto oli riittämätön, tarkasteltiin kolmea vaihtoehtoa riittävän kiertovesimäärän aikaansaamiseksi. Nykyisten kiertovesipumppujen rinnanoperointi, sekä riittävän suureksi skaalatun pumpun käyttö simuloitiin. Kolmantena tapauksena arvioitiin lämmönvaihdinkohtaisen kuristussuunnitelman vaikutus putkiston painehäviöön, sekä putkistolle sopiva kiertovesipumppu. Vaihtoehdoille laskettiin suuntaa-antavat investointi- ja käyttökustannukset. Tarkastelun perusteella riittävän suureksi skaalattu pumppu todettiin kannattavimmaksi pienen hintaeron, sekä luotettavamman jäähdytysvesikierron käyttövarmuuden vuoksi. Työssä onnistuttiin tuottamaan yleispätevää tietoa suljetun jäähdytysvesiverkon hydrauliseen mallinnukseen vaikuttavista tekijöistä, sekä niiden vaikutuksesta mallin tarkkuuteen. Selvityksen perusteella tarkasteltua mallia saatiin tarkemmaksi.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Economical potential of controlling charging of electric vehicles by using price signal

The number of electric vehicles grows continuously and the implementation of charging electric vehicles is an important issue for the future. Increasing amount of electric vehicles can cause problems to distribution grid by increasing peak load. Currently charging of electric vehicles is uncontrolled, but as the amount of electric vehicles grows, smart charg-ing (controlled charging) will be one possible solution to handle this situation. In this thesis smart charging of electric vehicles is examined from electricity retailers` point of view. The purpose is to find out plausible saving potentials of smart charging, when it´s controlled by price signal. Saving potential is calculated by comparing costs of price signal controlled charging and uncontrolled charging.

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.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Regime-Switching in the Impact of Oil Price Shocks on Stock Market Volatility: Evidence from Oil-Importing and Oil-Exporting Countries

Research has highlighted the adequacy of Markov regime-switching model to address dynamic behavior in long term stock market movements. Employing a purposed Extended regime-switching GARCH(1,1) model, this thesis further investigates the regime dependent nonlinear relationship between changes in oil price and stock market volatility in Saudi Arabia, Norway and Singapore for the period of 2001-2014. Market selection is prioritized to national dependency on oil export or import, which also rationalizes the fitness of implied bivariate volatility model. Among two regimes identified by the mean model, high stock market return-low volatility regime reflects the stable economic growth periods. The other regime characterized by low stock market return-high volatility coincides with episodes of recession and downturn. Moreover, results of volatility model provide the evidence that shocks in stock markets are less persistent during the high volatility regime. While accelerated oil price rises the stock market volatility during recessions, it reduces the stock market risk during normal growth periods in Singapore. In contrast, oil price showed no significant notable impact on stock market volatility of target oil-exporting countries in either of the volatility regime. In light to these results, international investors and policy makers could benefit the risk management in relation to oil price fluctuation.