Characteristics of a good customer reference for a process equipment supplier

Työn tavoitteena oli tutkia hyvän asiakasreferenssin ominaisuuksia suodatinvalmistaja Laroxin myynnin ja huollon sekä yrityksen asiakkaiden näkökulmasta. Larox voi käyttää saatua tietoa referenssien tehokkaampaan valintaan ja hyödyntämiseen. Kaksi internet-kyselyä toteutettiin, välineenä Webropol. Alustava kysely sunnattiin Laroxin myynnille ja huollolle. Kysely koostui viidestä kategoriasta asiakasreferenssejä, joiden tärkeyttä arvioitiin, sekä vapaista vastauksista. Tunnistettuja hyvän asiakasreferenssin ominaisuuksia ovat hyvä suhde referenssiasiakkaaseen, positiiviset jarehelliset suosittelut asiakkaalta, referenssilaitteen hyvä toimintakyky ja asiakas joka ymmärtää huollon tärkeyden. Pääkysely suunnattiin Laroxin asiakkaille. Tilastollisilla analyyseilla tutkittiin koetun riskin mallinmuuttujien välisiä yhteyksiä. Analyysit eivät paljastaneet merkittäviä riippuvuuksia asiakasreferenssin ominaisuuksien tärkeydessä eritaustaisten vastaajien tai tilannetekijöiden välillä, mutta asiakasreferenssin ominaisuuksien faktorit tukevat mallia. Referenssilaitteiden toimintakyky vaikuttaa tärkeimmältä ja huollon tärkeys on myös merkittävä.

Risks in R&D Collaboration between Small and Large Firms

The main aim of this thesis was to find out what kinds of risks arise from collabo-ration in R&D between small and large firms. The suitability and gain of some buyer/supplier risk frameworks in examining of R&D collaboration has been in-vestigated. A risk model has been based on the buyer/supplier risks models found in the literature. Its applicability has been tested empirically by means of theme interviews with firm representatives. The risk classification framework received some confirmation. But the study also showed that the theoretical framework was not completely adequate, as a new risk class arose from communication. Collaboration causes risks, and these risks should be taken into account when R&D collaboration is planned. The advantage of risk examination is the possibility to decrease failures and losses, and to in-crease possibilities for success and economical benefits. This study should be used as a managerial analysis tool in trying to understand the form and concept of risk in risk expectancy.

Riskianalyysi sisäisen valvonnan apuvälineenä

Tutkielman tavoitteena oli pyrkiä selvittämään Ilmatieteen laitoksen toiminnalliset ja taloudelliset riskit. Tämä toteutettiin Ilmatieteen laitoksen ulkoisten ja sisäisten sidosryhmien haastatteluiden perusteella. Riskeistä rakennettiin Ilmatieteen laitokselle riskianalyysimalli, jonka kautta riskejä voidaan laitoksessa systemaattisesti tarkastella. Riskianalyysin on myös tarkoitus toimia apuvälineenä laitoksen sisäistä valvontaa ja riskienhallintaa kehitettäessä. Riskianalyysissä riskejä arvioitiin riskiin sisältyvän kahden komponentin, todennäköisyyden ja seurausten, avulla. Näin saatiin riskit karkeasti vertailukelpoiseksi keskenään. Riskeistä muodostettiin ensin toimintokohtainen riskianalyysi, jonka jälkeen riskejä analysoitiin myös koko laitoksen tasolla. Riskejä ilmeni hyvin erilaisia: osaamiseen ja henkilöstöön liittyviä ja toisaalta pitkän tähtäimen strategisiin valintoihin liittyviä. Ilmatieteen laitoksen täytyy hallita toimintaansa ja toimintaympäristöönsä liittyvät muutokset ja olla uudistumiskykyinen. Täytyy myös huomata, että riskianalyysin lisäksi sisäisen valvonnan kehittämisessä on organisaation johdolla ja sisäisellä tarkastajalla tärkeä rooli.

Essays on pricing of risk and international linkage of Russian stock market

Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

Financier’s credit risk: A Performance-Based Classification Model

The purpose of this study is to view credit risk from the financier’s point of view in a theoretical framework. Results and aspects of the previous studies regarding measuring credit risk with accounting based scoring models are also examined. The theoretical framework and previous studies are then used to support the empirical analysis which aims to develop a credit risk measure for a bank’s internal use or a risk management tool for a company to indicate its credit risk to the financier. The study covers a sample of Finnish companies from 12 different industries and four different company categories and employs their accounting information from 2004 to 2008. The empirical analysis consists of six stage methodology process which uses measures of profitability, liquidity, capital structure and cash flow to determine financier’s credit risk, define five significant risk classes and produce risk classification model. The study is confidential until 15.10.2012.

Creating risk measurement model to project portfolio management in construction company

This thesis was carried out as a case study of a company YIT in order to clarify the sev-erest risks for the company and to build a method for project portfolio evaluation. The target organization creates new living environment by constructing residential buildings, business premises, infrastructure and entire areas worth for EUR 1.9 billion in the year 2013. Company has noted project portfolio management needs more information about the structure of project portfolio and possible influences of market shock situation. With interviews have been evaluated risks with biggest influence and most appropriate metrics to examine. The major risks for the company were evaluated by interviewing the executive staff. At the same time, the most appropriate risk metrics were considered. At the moment sales risk was estimated to have biggest impact on company‟s business. Therefore project port-folio evaluation model was created and three different scenarios for company‟s future were created in order to identify the scale of possible market shock situation. The created model is tested with public and descriptive figures of YIT in a one-year-long market shock and the impact on different metrics was evaluated. Study was conducted using con-structive research methodology. Results indicate that company has notable sales risk in certain sections of business portfolio.

How Is Credit Risk Estimated? Discussion and Evidence based on Cross-Industry Sample Utilizing the KMV Model

The purpose of this thesis is to focus on credit risk estimation. Different credit risk estimation methods and characteristics of credit risk are discussed. The study is twofold, including an interview of a credit risk specialist and a quantitative section. Quantitative section applies the KMV model to estimate credit risk of 12 sample companies from three different industries: automobile, banking and financial sector and technology. Timeframe of the estimation is one year. On the basis of the KMV model and the interview, implications for analysis of credit risk are discussed. The KMV model yields consistent results with the existing credit ratings. However, banking and financial sector requires calibration of the model due to high leverage of the industry. Credit risk is considerably driven by leverage, value and volatility of assets. Credit risk models produce useful information on credit worthiness of a business. Yet, quantitative models often require qualitative support in the decision-making situation.

Liquidity Risk in the Finnish Stock Market

This study explores the pricing of liquidity risk and its effect on stock returns in the Finnish stock market. In addition to that, it investigates whether there is a trend in liquidity risk. Finally, it analyzes whether the two chosen liquidity measures provide different results. The data consists of all the common shares listed in the Finnish stock market during the period of 1/1997–7/2015. To examine whether liquidity risk affects stock returns in the Finnish stock market, this study utilizes a conditional version of liquidity-adjusted capital asset pricing model (LCAPM) by Acharya and Pedersen (2005). Two recently proposed illiquidity measures – PQS and AdjILLIQ – are used in the empirical estimation to see whether there are differences in the results between the measures. The time-varying conditional liquidity risks are estimated by using a multivariate DCC-GARCH model, while the pricing of the liquidity risk is conducted by applying fixed effect panel regression. The results imply that investors in the Finnish stock market are willing to pay a premium to hedge from wealth shocks and having liquid assets during the declined market liquidity. However, investors are not willing to pay a premium for stocks with higher returns during illiquid markets. The total annualized illiquidity premiums found in the Finnish stock market are 1.77% and 1.04%, based on the PQS and AdjILLIQ measures, respectively. The study also shows that liquidity risk does not exhibit decreasing trend, and investors should consider liquidity risk in their portfolio diversification in the Finnish stock market.

Covariance Matrix Estimation and Mean-Variance Optimization in application to International Diversification

Tutkimus keskittyy kansainväliseen hajauttamiseen suomalaisen sijoittajan näkökulmasta. Tutkimuksen toinen tavoite on selvittää tehostavatko uudet kovarianssimatriisiestimaattorit minimivarianssiportfolion optimointiprosessia. Tavallisen otoskovarianssimatriisin lisäksi optimoinnissa käytetään kahta kutistusestimaattoria ja joustavaa monimuuttuja-GARCH(1,1)-mallia. Tutkimusaineisto koostuu Dow Jonesin toimialaindekseistä ja OMX-H:n portfolioindeksistä. Kansainvälinen hajautusstrategia on toteutettu käyttäen toimialalähestymistapaa ja portfoliota optimoidaan käyttäen kahtatoista komponenttia. Tutkimusaieisto kattaa vuodet 1996-2005 eli 120 kuukausittaista havaintoa. Muodostettujen portfolioiden suorituskykyä mitataan Sharpen indeksillä. Tutkimustulosten mukaan kansainvälisesti hajautettujen investointien ja kotimaisen portfolion riskikorjattujen tuottojen välillä ei ole tilastollisesti merkitsevää eroa. Myöskään uusien kovarianssimatriisiestimaattoreiden käytöstä ei synnytilastollisesti merkitsevää lisäarvoa verrattuna otoskovarianssimatrisiin perustuvaan portfolion optimointiin.

Profit at Risk as a Risk Management Tool in Deregulated Energy Markets

Euroopan energiamarkkinat ovat olleet viimeisen kymmenen vuoden aikana suurten muutosten alla. Markkinoiden kehitys on ollut huomattavaa myös Iso-Britanniassa, jossa sähkö- ja kaasumarkkinat ovat olleet avoinna kilpailulle jo muutamia vuosia. Ennen markkinoiden avautumista energiyhtiöt pystyivät siirtämään kaikki riskit suoraan asiakkaan kannettaviksi. Markkinoiden avautumisen myötä lisääntynyt kilpailu on kuitenkin pakottanut energiayhtiöitä ajanmukaistamaan näkemyksiään riskeistä. Riskitekijät, joista ei aiemmin tarvinnut välittää, on nyt pystyttävä tunnistamaan ja hallitsemaan. Tämä työ keskittyy hinta- ja volyymiriskien hallintaan. Rahoitusmarkkinoilla pitkään käytettyjä riskienhallintatyökaluja on otettu käyttöön myös energiamarkkinoilla. Energiamarkkinoiden piirteet poikkeavat kuitenkin rahoitusmarkkinoista, eikä näitä työkaluja voida ottaa käyttöön muutoksitta. Silti, jopa muutosten jälkeen rahoitusmarkkinoiden riskienhallitavälineet aliarvioivat energiamarkkinoiden hinta- ja volyymiriskejä. Tässä yhteydessä työssä esitetään Profit at Risk, PaR. PaR on skenaariopohjainen riskienhallinnan työkalu, joka on kehitetty erityisesti energiamarkkinoille ja täten huomioi niiden erikoispiirteet. Työn rungon muodostavat energiamarkkinoiden käyttäytyminen, hinta- ja volyymiriskitekijät sekä pohdinta miten hinta- ja volyymiriskeiltä voidaan suojautua ja miten niitä voidaan hallita. PaR-metodologiaa verrataan perinteisiin riskienhallintamenetelmiin ja työn tavoitteena on tuoda esiin ne tekijät, joiden ansiosta PaR on sopivampi työkalu energiamarkkinoiden riskienhallintaan kuin perinteiset menetelmät. Käytännön esimerkkinä työssä toimii Fortum Energy plus’n PaR –malli. Koska PaR on kehitetty erityisesti energiamarkkinoille, se huomioi täysin markkinoiden aiheuttamat hinta- ja volyymiriskit. Käytännön esimerkki kuitenkin osoittaa, että PaR menetelmästä ei ole riskienhallinnallista hyötyä ellei työkalun käyttäjällä ole täydellistä tietämystä niin energiamarkkinoista kuin markkinoiden muutoksiin vaikuttavien tekijöiden käyttäytymisestä.

Value at Risk in measuring market risk: Historical simulation

In this study the theoretical part was created to make comparison between different Value at Risk models. Based on that comparison one model was chosen to the empirical part which concentrated to find out whether the model is accurate to measure market risk. The purpose of this study was to test if Volatility-weighted Historical Simulation is accurate in measuring market risk and what improvements does it bring to market risk measurement compared to traditional Historical Simulation. Volatility-weighted method by Hull and White (1998) was chosen In order to improve the traditional methods capability to measure market risk. In this study we found out that result based on Historical Simulation are dependent on chosen time period, confidence level and how samples are weighted. The findings of this study are that we cannot say that the chosen method is fully reliable in measuring market risk because back testing results are changing during the time period of this study.

Time-varying Risk Premiums and Conditional Market Risk: Empirical Evidence from European Stock Markets

This study investigates the relationship between the time-varying risk premiums and conditional market risk in the stock markets of the ten member countries of Economy and Monetary Union. Second, it examines whether the conditional second moments change over time and are there asymmetric effects in the conditional covariance matrix. Third, it analyzes the possible effects of the chosen testing framework. Empirical analysis is conducted using asymmetric univariate and multivariate GARCH-in-mean models and assuming three different degrees of market integration. For a daily sample period from 1999 to 2007, the study shows that the time-varying market risk alone is not enough to explain the dynamics of risk premiums and indications are found that the market risk is detected only when its price is allowed to change over time. Also asymmetric effects in the conditional covariance matrix, which is found to be time-varying, are clearly present and should be recognized in empirical asset pricing analyses.

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.