The use of quantile trees in the prediction of the diameter distribution of a stand

Abstract

Quantile Estimation in Non-Stationary Streaming Data

We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.

Chasing performance persistence of hedge funds

The thesis examines the performance persistence of hedge funds using complement methodologies (namely cross-sectional regressions, quantile portfolio analysis and Spearman rank correlation test). In addition, six performance ranking metrics and six different combinations of selection and holding periods are compared. The data is gathered from HFI and Tremont databases covering over 14,000 hedge funds and time horizon is set from January 1996 to December 2007. The results suggest that there definitely exists performance persistence among hedge funds and the strength and existence of persistence vary among fund styles. The persistence depends on the metrics and combination of selection and prediction period applied. According to the results, the combination of 36-month selection and holding period outperforms other five period combinations in capturing performance persistence within the sample. Furthermore, model-free performance metrics capture persistence more sensitively than model-specific metrics. The study is the first one ever to use MVR as a performance ranking metric, and surprisingly MVR is more sensitive to detect persistence than other performance metrics employed.

Determinants of credit default swap spread: evidence from european credit derivatives market

Tämän tutkielman tavoitteena on selvittää, mitkä tekijät vaikuttavat yrityksen ja valtion velkakirjojen väliseen tuottoeroon. Strukturaalisten luottoriskin hinnoittelumallien mukaan luottoriskiin vaikuttavia tekijöitä ovat yrityksen velkaantumisaste, volatiliteetti ja riskitön korkokanta. Tavoitteena on erityisesti tutkia, kuinka hyvin nämä teoreettiset tekijät selittävät tuottoeroja ja onko olemassa muita tärkeitä selittäviä tekijöitä. Luottoriskinvaihtosopimusten noteerauksia käytetään tuottoerojen määrittämiseen. Selittävät tekijät koostuvat sekä yrityskohtaisista että markkinalaajuisista muuttujista. Luottoriskinvaihtosopimusten ja yrityskohtaisten muuttujien data on kerätty yhteensä 50 yritykselle Euroalueen maista. Aineisto koostuu kuukausittaisista havainnoista aikaväliltä 01.01.2003-31.12.2006. Empiiriset tulokset osoittavat, että strukturaalisten mallien mukaiset tekijät selittävät vain pienen osan tuottoeron muutoksista yli ajan. Toisaalta nämä teoreettiset tekijät selittävät huomattavasti paremmin tuottoeron vaihtelua yli poikkileikkauksen. Muut kuin teoreettiset tekijät pystyvät selittämään suuren osan tuottoeron vaihtelusta. Erityisen tärkeäksi tuottoeron selittäväksi tekijäksi osoittautui yleinen riskipreemio velkakirjamarkkinoilla. Tulokset osoittavat, että luottoriskin hinnoittelumalleja on kehitettävä edelleenniin, että ne ottaisivat huomioon yrityskohtaisten tekijöiden lisäksi myös markkinalaajuisia tekijöitä.

The Fed Model: International Analysis

The Fed model is a widely used market valuation model. It is often used only on market analysis of the S&P 500 index as a shorthand measure for the attractiveness of equity, and as a timing device for allocating funds between equity and bonds. The Fed model assumes a fixed relationship between bond yield and earnings yield. This relationship is often assumed to be true in market valuation. In this paper we test the Fed model from historical perspective on the European markets. The markets of the United States are also includedfor comparison. The purpose of the tests is to determine if the Fed model and the underlying assumptions come true on different markets. The various tests are made on time-series data ranging from the year 1973 to the end of the year 2008. The statistical methods used are regressions analysis, cointegration analysis and Granger causality. The empirical results do not give strong support for the Fed model. The underlying relationships assumed by the Fed model are statistically not valid in most of the markets examined and therefore the model is not valid in valuation purposes generally. The results vary between the different markets which gives reason to suspect the general use of the Fed model in different market conditions and in different markets.

Epävarmuuden vaikutus strategisiin alliansseihin vuosina 2000-2010

Tässä pro gradu –tutkielmassa perehdyttiin globaalin telekommunikaatiosektorin allianssitoimintaan vuosina 2000-2010. Tutkimuksen tavoitteena oli tarkastella kvantitatiivisin menetelmin yrityskohtaisen ja makrotaloudellisen epävarmuuden vaikutusta solmittujen allianssien rakenteeseen, muotoon ja osapuolten maantieteelliseen sijaintiin. Lisäksi oli tarkoitus tutkia, kuinka allianssien vuosittainen määrä ja niihin osallistuvien yritysten määrä muuttuu epävarmuuden vaihtelujen myötä. Tutkielman empiirisen rungon muodosti sekundaarinen data SDC Platinum ja Thomson Datastream –tietokannoista. Lopulliseen aineistoon sisältyi 50 maailman suurinta telekommunikaatioyritystä useasta eri maasta. Tilastollinen analyysi suoritettiin logistisen ja paneelidataregression avulla. Tutkielman viidestä hypoteesista vain kaksi vahvistuivat osittain. Kyseiset hypoteesit olettivat epävarmuuden kasvun negatiivista vaikutusta vertikaalisten ja kotimaisten allianssien suosioon yrityksen silmissä. Muut regressiomallit tuottivat ristiriitaisia ja tilastollisesti ei-merkitseviä tuloksia.

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.

Foreign Direct Investment, Clean Development Mechanism, and Environmental Management: A case of Sub-Saharan Africa

This doctoral dissertation explores the contribution of environmental management practices, the so-called clean development mechanism (CDM) projects, and foreign direct investment (FDI) in achieving sustainable development in developing countries, particularly in Sub- Saharan Africa. Because the climate change caused by greenhouse gas emissions is one of the most serious global environmental challenges, the main focus is on the causal links between carbon dioxide (CO2) emissions, energy consumption, and economic development in Sub-Saharan Africa. In addition, the dissertation investigates the factors that have affected the distribution of CDM projects in developing countries and the relationships between FDI and other macroeconomic variables of interest. The main contribution of the dissertation is empirical. One of the publications uses crosssectional data and Tobit and Poisson regressions. Three of the studies use time-series data and vector autoregressive and vector error correction models, while two publications use panel data and panel data estimation methods. One of the publications uses thus both timeseries and panel data. The concept of Granger causality is utilized in four of the publications. The results indicate that there are significant differences in the Granger causality relationships between CO2 emissions, energy consumption, economic growth, and FDI in different countries. It appears also that the causality relationships change over time. Furthermore, the results support the environmental Kuznets curve hypothesis but only for some of the countries. As to CDM activities, past emission levels, institutional quality, and the size of the host country appear to be among the significant determinants of the distribution of CDM projects. FDI and exports are also found to be significant determinants of economic growth.

The Determinants of Financial Leverage of Large Publicly Listed Companies - Evidence from Nordic Telecom Sector

This thesis examines the determinants of financial leverage ratio of large publicly listed companies within Nordic Telecom sector. The study is done as a case study and it covers 5 case companies headquartered in Nordic countries during period of 2002 - 2014 and by using restated values of quarterly observations from each case company’s interim reports. The chosen hypotheses are tested with multiple linear regressions firm by firm. The Findings of the study showed that uniqueness of Telecom sector and the region of our sample could not provide us unequivocal determinants of leverage ratio within the sector. However, e.g. Pecking order theory’s statement of Liquidity was widely confirmed by 3 out of 5 case companies which is worth to be taken into account in the big picture. The findings also showed that theories and earlier empirical evidence are confirmed by our case companies individually and non-systematically. Though Telecom sector is considered as quite unique industry and we did not discover absolute common relationships that would have held through all the Nordic case companies, we got unique and valuable evidence to conduct the research of this sector in future.

Pricing of Liquidity Risks in London Stock Exchange

This thesis aims to investigate pricing of liquidity risks in London Stock Exchange. Liquidity Adjusted Capital Asset Pricing Model i.e. LCAPM developed by Acharya and Pedersen (2005) is being applied to test the influence of various liquidity risks on stock returns in London Stock Exchange. The Liquidity Adjusted Capital Asset Pricing model provides a unified framework for the testing of liquidity risks. All the common stocks listed and delisted for the period of 2000 to 2014 are included in the data sample. The study has incorporated three different measures of liquidity – Percent Quoted Spread, Amihud (2002) and Turnover. The reason behind the application of three different liquidity measures is the multi-dimensional nature of liquidity. Firm fixed effects panel regression is applied for the estimation of LCAPM. However, the results are robust according to Fama-Macbeth regressions. The results of the study indicates that liquidity risks in the form of (i) level of liquidity, (ii) commonality in liquidity (iii) flight to liquidity, (iv) depressed wealth effect and market return as well as aggregate liquidity risk are priced at London Stock Exchange. However, the results are sensitive to the choice of liquidity measures.