Simulating the dynamics of silver market using computational market dynamics

Traditional econometric approaches in modeling the dynamics of equity and commodity markets, have, made great progress in the past decades. However, they assume rationality among the economic agents and and do not capture the dynamics that produce extreme events (black swans), due to deviation from the rationality assumption. The purpose of this study is to simulate the dynamics of silver markets by using the novel computational market dynamics approach. To this end, the daily data from the period of 1st March 2000 to 1st March 2013 of closing prices of spot silver prices has been simulated with the Jabłonska-Capasso-Morale(JCM) model. The Maximum Likelihood approach has been employed to calibrate the acquired data with JCM. Statistical analysis of the simulated series with respect to the actual one has been conducted to evaluate model performance. The model captures the animal spirits dynamics present in the data under evaluation well.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.

From Fluid Dynamics to Human Psychology.What Drives Financial Markets Towards Extreme Events

For decades researchers have been trying to build models that would help understand price performance in financial markets and, therefore, to be able to forecast future prices. However, any econometric approaches have notoriously failed in predicting extreme events in markets. At the end of 20th century, market specialists started to admit that the reasons for economy meltdowns may originate as much in rational actions of traders as in human psychology. The latter forces have been described as trading biases, also known as animal spirits. This study aims at expressing in mathematical form some of the basic trading biases as well as the idea of market momentum and, therefore, reconstructing the dynamics of prices in financial markets. It is proposed through a novel family of models originating in population and fluid dynamics, applied to an electricity spot price time series. The main goal of this work is to investigate via numerical solutions how well theequations succeed in reproducing the real market time series properties, especially those that seemingly contradict standard assumptions of neoclassical economic theory, in particular the Efficient Market Hypothesis. The results show that the proposed model is able to generate price realizations that closely reproduce the behaviour and statistics of the original electricity spot price. That is achieved in all price levels, from small and medium-range variations to price spikes. The latter were generated from price dynamics and market momentum, without superimposing jump processes in the model. In the light of the presented results, it seems that the latest assumptions about human psychology and market momentum ruling market dynamics may be true. Therefore, other commodity markets should be analyzed with this model as well.

Added Value of Combining Value and Momentum Indicators in the Swiss Stock Market

The purpose of the thesis is to examine the added value of combining value and momentum indicators in the Swiss stock exchange. Value indicators employed are P/E, EV/EBITDA, P/CF, P/B ja P/S. Momentum indicators examined are 52-week high, acceleration rate, 12-month past return and 6-month past return. The thesis examines whether the composite value measures based on the above mentioned ratios can add value and whether the inclusion of momentum can further improve the risk return profile of the value portfolios. The data is gathered from the Swiss equity market during the sample period from May 2001 to May 2011. Previous studies have shown that composite value measures can somewhat add value to the value portfolio strategy. Similarly, recent academic literature have found evidence that momentum works well as a timing indicator for time to entry to value stocks. This study indicates that the added value of composite value measures exists. It also shows that momentum combined to acceleration rate can significantly improve the risk adjusted performance of value-only portfolios.

The Anchoring Bias of Investors and the 52-Week High Momentum Strategy in the OMX Helsinki Stock Exchange: Psychological Approach to Market Efficiency

The behavioural finance literature expects systematic and significant deviations from efficiency to persist in securities markets due to behavioural and cognitive biases of investors. These behavioural models attempt to explain the coexistence of intermediate-term momentum and long-term reversals in stock returns based on the systematic violations of rational behaviour of investors. The study investigates the anchoring bias of investors and the profitability of the 52-week momentum strategy (GH henceforward). The relatively highly volatile OMX Helsinki stock exchange is a suitable market for examining the momentum effect, since international investors tend to realise their positions first from the furthest security markets by the time of market turbulence. Empirical data is collected from Thomson Reuters Datastream and the OMX Nordic website. The objective of the study is to provide a throughout research by formulating a self-financing GH momentum portfolio. First, the seasonality of the strategy is examined by taking the January effect into account and researching abnormal returns in long-term. The results indicate that the GH strategy is subject to significantly negative revenues in January, but the strategy is not prone to reversals in long-term. Then the predictive proxies of momentum returns are investigated in terms of acquisition prices and 52-week high statistics as anchors. The results show that the acquisition prices do not have explanatory power over the GH strategy’s abnormal returns. Finally, the efficacy of the GH strategy is examined after taking transaction costs into account, finding that the robust abnormal returns remain statistically significant despite the transaction costs. As a conclusion, the relative distance between a stock’s current price and its 52-week high statistic explains the profits of momentum investing to a high degree. The results indicate that intermediateterm momentum and long-term reversals are separate phenomena. This presents a challenge to current behavioural theories, which model these aspects of stock returns as subsequent components of how securities markets respond to relevant information.

Performance of value and momentum strategies in the Swedish stock market

This thesis investigates the performance of value and momentum strategies in the Swedish stock market during the 2000-2015 sample period. In addition the performance of some value and value-momentum combination is examined. The data consists of all the publicly traded companies in the Swedish stock market between 2000-2015. P/E, P/B, P/S, EV/EBITDA, EV/S ratios and 3, 6 and 12 months value criteria are used in the portfolio formation. In addition to single selection criteria, combination of P/E and P/B (aka. Graham number), the average ranking of the five value criteria and EV/EBIT – 3 month momentum combination is used as a portfolio-formation criterion. The stocks are divided into quintile portfolios based on each selection criterion. The portfolios are reformed once a year using the April’s price information and previous year’s financial information. The performance of the portfolios is examined based on average annual return, the Sharpe ratio and the Jensen alpha. The results show that the value-momentum combination is the best-performing portfolio both during the whole sample period and during the sub-period that started after the 2007-financial crisis.

Arvo- ja momentum-strategioiden yhdistäminen Suomen osakemarkkinoilla

Tämän tutkielman tavoitteena on selvittää pystytäänkö momentum-strategiaa hyödyntämällä parantamaan arvostrategian tuottoja Suomen osakemarkkinoilla. Yhdistetyn arvo- ja momentum-strategian lisäksi tutkitaan myös arvosrategian menestystä. Tutkimuksessa arvostusmittareina on käytetty P/E-, P/B-, P/CF-, P/S-, P/D-, EV/EBITDA-lukuja sekä kolmea näistä muodostettua yhdistelmätunnuslukua. Tutkimusaineisto koostuu Suomen osakemarkkinoilla julkisesti noteerattujen osakkeiden tuottoaikasarjoista vuosilta 1992-2008. Osakkeet on järjestetty tunnuslukujen ja momentum-indikaattorien perusteella kolmeen tertiiliportfolioon. Sijoitusten pitoaikana on käytetty yhtä ja kolmea vuotta. Portfolioista on raportoitu keskimääräisen vuosituoton lisäksi riskikorjattu tuotto Sharpen luvulla ja Jensenin alfalla mitattuna sekä näiden tilastollinen merkitsevyys. Tulosten perusteella voidaan päätellä, ettei momentum-strategian avulla pystytä parantamaan arvostrategian tuottoja Suomen osakemarkkinoilla. Arvostrategia menestyi kuitenkin erittäin hyvin etenkin yhdistelmätunnuslukujen sekä P/D-, EV/EBITDA- ja P/E-lukujen osalta.

Momentum-anomalia ja siihen perustuvat sijoitusstrategiat Yhdysvaltojen osakemarkkinoilla

Tutkielmassa lähestytään osakemarkkinoilla havaittua poikkeavuutta, momentum-anomaliaa, sekä sen ilmenemistä ja selittyvyyttä Yhdysvaltojen osakemarkkinoiden olosuhteissa. Lisäksi tutkielma sisältää lyhyen katsauksen kansainvälisesti ilmenevään momentumiin kuin myös sen muodostumiseen vaikuttaviin tekijöihin. Työn tutkimusongelmana on, selittyykö Yhdysvaltojen osakemarkkinoilla ilmenevä momentum-anomalia selkeämmin behaviorististen vai makrotaloudellisten riskitekijöiden muodostamien mallien avulla. Kuten aiempi tutkimus on havainnut, myös tässä tutkielmassa oletuksena on, että behavioristis-perusteiset tekijät omaavat suuremman selitysvoiman, kuin makrotaloudellisten riskitekijöiden -perusteiset mallit. Yksittäisiin tekijöihin keskittymisen ohella on tarkoitus havainnoida momentum-anomalian ilmentymisen riippuvuus markkinasuhdanteista, jolloin syntyviä momentumin tuottoja tarkastellaan sekä korkea-, että matalasuhdannemarkkinoiden olosuhteissa.

Performance Comparison of Behavioral Finance -based Investment Strategies in the Finnish Stock Market 1996-2010

In this thesis traditional investment strategies (value and growth) are compared to modern investment strategies (momentum, contrarian and GARP) in terms of risk, performance and cumulative returns. Strategies are compared during time period reaching from 1996 to 2010 in the Finnish stock market. Used data includes all listed main list stocks, dividends and is adjusted in case of splits, and mergers and acquisitions. Strategies are tested using different holding periods (6, 12 and 36 months) and data is divided into tercile portfolios based on different ranking criteria. Contrarian and growth strategies are the only strategies with improved cumulative returns when longer holding periods are used. Momentum (52-week high price1) and GARP strategies based on short holding period have the best performance and contrarian and growth strategies the worst. Momentum strategies (52-week high price) along with short holding period contrarian strategies (52-week low price2) have the lowest risk. Strategies with the highest risk are both growth strategies and two momentum strategies (52-week low price). The empirical results support the efficiency of momentum, GARP and value strategies. The least efficient strategies are contrarian and growth strategies in terms of risk, performance and cumulative returns. Most strategies outperform the market portfolio in all three measures. 1 Stock ranking criterion (current price/52-week highest price) 2 Stock ranking criterion (current price/52-week lowest price)

Observations of Industry Momentum Effect in European Equity Indices

This thesis examines the existence and nature of momentum effect in European equity indices. A set of predefined indicators is used to compose momentum portfolios and different holding periods are used to test the strategies over variable time periods as well as under different economical conditions. The data consists of daily closing prices of STOXX Europe 600 index and its 18 super sector indices. Over the study period we follow the performances of a long position in the Winner portfolio, a position in the market neutral zero-cost portfolio and also a position in the risk-controlled zero-cost portfolio. The investment ratio of the risk-controlled zero-cost portfolio is negatively correlated with the realized market volatility. The results show that momentum effect is present in European industries and is most prominent in the short-term. Indicators that are based on short-term performance tend predict the over- and underperformers for the 1-month holding period more reliably than any other indicator/holding period combination. The examination of the strategies under different economical conditions shows that the market neutral approach can create significant returns in times of recession but in times of economic boom the long position in Winner portfolio outperforms the market neutral portfolio by an extensive margin.

Pricing anomalies in the Finnish stock market

The aim of this thesis is to examine whether the pricing anomalies exists in the Finnish stock markets by comparing the performance of quantile portfolios that are formed on the basis of either individual valuation ratios, composite value measures or combined value and momentum indicators. All the research papers included in the thesis show evidence of value anomalies in the Finnish stock markets. In the first paper, the sample of stocks over the 1991-2006 period is divided into quintile portfolios based on four individual valuation ratios (i.e., E/P, EBITDA/EV, B/P, and S/P) and three hybrids of them (i.e. composite value measures). The results show the superiority of composite value measures as selection criterion for value stocks, particularly when EBITDA/EV is employed as earnings multiple. The main focus of the second paper is on the impact of the holding period length on performance of value strategies. As an extension to the first paper, two more individual ratios (i.e. CF/P and D/P) are included in the comparative analysis. The sample of stocks over 1993- 2008 period is divided into tercile portfolios based on six individual valuation ratios and three hybrids of them. The use of either dividend yield criterion or one of three composite value measures being examined results in best value portfolio performance according to all performance metrics used. Parallel to the findings of many international studies, our results from performance comparisons indicate that for the sample data employed, the yearly reformation of portfolios is not necessarily optimal in order to maximally gain from the value premium. Instead, the value investor may extend his holding period up to 5 years without any decrease in long-term portfolio performance. The same holds also for the results of the third paper that examines the applicability of data envelopment analysis (DEA) method in discriminating the undervalued stocks from overvalued ones. The fourth paper examines the added value of combining price momentum with various value strategies. Taking account of the price momentum improves the performance of value portfolios in most cases. The performance improvement is greatest for value portfolios that are formed on the basis of the 3-composite value measure which consists of D/P, B/P and EBITDA/EV ratios. The risk-adjusted performance can be enhanced further by following 130/30 long-short strategy in which the long position of value winner stocks is leveraged by 30 percentages while simultaneously selling short glamour loser stocks by the same amount. Average return of the long-short position proved to be more than double stock market average coupled with the volatility decrease. The fifth paper offers a new approach to combine value and momentum indicators into a single portfolio-formation criterion using different variants of DEA models. The results throughout the 1994-2010 sample period shows that the top-tercile portfolios outperform both the market portfolio and the corresponding bottom-tercile portfolios. In addition, the middle-tercile portfolios also outperform the comparable bottom-tercile portfolios when DEA models are used as a basis for stock classification criteria. To my knowledge, such strong performance differences have not been reported in earlier peer-reviewed studies that have employed the comparable quantile approach of dividing stocks into portfolios. Consistently with the previous literature, the division of the full sample period into bullish and bearish periods reveals that the top-quantile DEA portfolios lose far less of their value during the bearish conditions than do the corresponding bottom portfolios. The sixth paper extends the sample period employed in the fourth paper by one year (i.e. 1993- 2009) covering also the first years of the recent financial crisis. It contributes to the fourth paper by examining the impact of the stock market conditions on the main results. Consistently with the fifth paper, value portfolios lose much less of their value during bearish conditions than do stocks on average. The inclusion of a momentum criterion somewhat adds value to an investor during bullish conditions, but this added value turns to negative during bearish conditions. During bear market periods some of the value loser portfolios perform even better than their value winner counterparts. Furthermore, the results show that the recent financial crisis has reduced the added value of using combinations of momentum and value indicators as portfolio formation criteria. However, since the stock markets have historically been bullish more often than bearish, the combination of the value and momentum criteria has paid off to the investor despite the fact that its added value during bearish periods is negative, on an average.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.