Optimizing counterparty credit risk portfolio by reducing exposure at default variance

Rahoitusyhtiöt pitävät omaa pääomaa taseessa harvinaisen suuria markkinamuutoksia varten ja tämän pääoman määrä on ohjattu valvontaviranomaisten toimesta. Euroopassa Basel akordi antaa suuntaviivat näille säädöksille. 2007 vuoden finanssikriisin jälkeen rahoitusyhtiöt sekä valvojat ovat olleet entistä kiinnostuneempia pääoman riittävyydestä. Tutkimuksia riskistä, säädöksistä ja pääomavaateen madaltamisesta on tehty aikaisemmin, mutta tässä tutkimuksessa keskitytään vaateen jatkuvan muutoksen suuruuteen. Tutkimus sisältää hypoteettisen vastapuoliriski portfolion, jossa on mukana valuuttajohdannaisia. Tätä portfoliota simuloidaan eri tavoin, jotta nähtäisiin kuinka suuri vaikutus portfolion koostumuksella voi olla pääomavaateen varianssiin. Jos tämä muuttuja on merkittävä, pitäisikö rahoitusyhtiöiden yrittää pienentää muutosta, jotta yhtiöiden varapääoman määrää voitaisiin alentaa? Tutkimuksessa on myös haastateltu Suomen johtavia vastapuoliriski asiantuntijoita, jotta nähtäisiin rahoitusalan oma näkemys asian merkittävyydestä. Tutkimusmenetelminä toimivat haastattelut sekä numeerinen analyysi hypoteettisella portfoliolla. Kaupat tähän vastapuoliriski portfolioon on luotu 14 vuoden ajalle ja se sisältää ainoastaan valuuttajohdannaisia viidessä eri valuutassa. Riski lasketaan markkina-arvo menetelmällä, joista lasketaan VaR-mallilla tulevaisuuden riski nettoutuksen kera. Portfolion rakennetta muutetaan simuloinneissa, jotta nähtäisiin vaikutus tulevaisuuden riskeille, joita käytetään edustamaan pääomavaateen määrää ja sen vaihtelua yli ajan. Portfolioiden riskejä lasketaan myös rasituskokeiden avulla, jotta tuloksista saataisiin mahdollisimman todenmukaisia. Analyyttinen osuus tutkimuksesta näyttää sen, että tämän kaltainen optimointi on suuresti riippuvainen alkuperäisestä portfoliosta, jonka määrittää yleisesti rahoitusyhtiön myyntistrategia. Yleisesti ottaen pääomavaateen varianssin muutos voi simuloinneissa olla melko suurta, varsinkin jos mukaan huomioidaan rasitus testit, puuttuvat tuotteet sekä muut pääomavaateen laskentaan huomioitavat seikat. Haastatteluissa saatiin selville millainen optimointi voisi olla mahdollista todellisuudessa. Huomattiin myös että tämän kaltainen ajattelumalli on jo huomattu alalla ennestään. Jon Gregory jopa mainitsi, että jotkin rahoitusyhtiöt ovat enemmän kiinnostuneita muutosten pienentämisestä kuin itse pääomavaateen suuruudesta. Näyttääkin siltä, että tämän aihepiiri vaatisi entistä enemmän tutkimusta, sillä sitä ei ennestään vielä ole, ja rahoitusyhtiöt ovat jo alkaneet etsimään uusia keinoja selvitäkseen rahoitusalalla, joka on yhä entisestään kilpailullisempi.

A Project Portfolio Tool for Forecasting Small Projects Profitability

The case company in this study is a large industrial engineering company whose business is largely based on delivering a wide-range of engineering projects. The aim of this study is to create and develop a fairly simple Excel-based tool for the sales department. The tool’s main function is to estimate and visualize the profitability of various small projects. The study also aims to find out other possible and more long-term solutions for tackling the problem in the future. The study is highly constructive and descriptive as it focuses on the development task and in the creation of a new operating model. The developed tool focuses on estimating the profitability of the small orders of the selected project portfolio currently on the bidding-phase (prospects) and will help the case company in the monthly reporting of sales figures. The tool will analyse the profitability of a certain project by calculating its fixed and variable costs, then further the gross margin and operating profit. The bidding phase of small project is a phase that has not been covered fully by the existing tools within the case company. The project portfolio tool can be taken into use immediately within the case company and it will provide fairly accurate estimate of the profitability figures of the recently sold small projects.

Bank Income Diversification and its Impact on Profitability and Risk: Evidence from Nordic Markets

Financial industry has recently encountered many changes in the business environment. Increased regulation together with growing competition is forcing commercial banks to rethink their business models. In order to maintain profitability in the new environment, banks are focusing more into activities that yield noninterest income. This is a shift away from the traditional intermediation function of banks. This study aims to answer the question if the shift from traditional income yielding activities to more innovative noninterest activities is logical in terms of profitability and risk in Nordics. This study also aims to answer the question if diversification within the noninterest income categories has impact on profitability and risk and if there are certain categories of noninterest income that are better than others in terms of profitability and risk in Nordics. Results show that diversification between interest and noninterest activities and increase in the share of noninterest income have a negative impact on the risk adjusted returns and risk profile. Results also show that further diversification within the noninterest income categories has negative impact on risk adjusted profitability and risk while an increase of the share of commission and fee income category of total noninterest income has a positive impact on risk adjusted profitability and risk. Results are logical and in line with previous research (De Young & Roland, 2001; Stiroh, 2004). Results provide useful information to banks and help them better evaluate outcomes of different income diversification strategies.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Model to Build a Service Quality Centric Customer Reference Portfolio in a Software as a Service Company

The goal of the master’s thesis was to develop a model to build a service quality centric customer reference portfolio for a software as a service company. The case company is Meltwater Finland Oy that leverages customer references externally but there is no systematic model to produce good quality customer references that are in line with the company strategy. The project was carried out as a case study, where the primary source of information were seventeen internal interviews with the employees of the case company. The theory part focuses on customer references as assets and service quality in software as a service industry. In the empirical part the research problem is solved. As a result of the case study, the model to build a service quality centric customer reference portfolio was created and further research areas were suggested.

Understanding the portfolio in the secondary school classroom

Four secondary school teachers were involved in this case study. Individual interviews, group reflective sessions, and participant portfolios were transcribed verbatim and analyzed. The use of the portfolio in the secondary school classroom was then discussed in relation to emergent themes. These themes included teacher attitude, portfolio structure, portfolio purpose, challenges, effect, and professional development. Teachers were able to individualize the portfolio structure to meet both program and students' needs. The portfolio structure enabled both teachers and students to assume control over the learning process. The portfolio informed teachers about their teaching. This, in tum, challenged them to reflect on their teaching practices and enabled them to redesign curriculum implementation. A collaborative professional development structure fostered a learning environment that enabled teachers to experience success, despite the challenges that they inevitably encountered. These findings were related to contemporary literature. Finally, implications for theory and practice related to portfolio use in the secondary school classroom and professional development for secondary school teachers were considered.

Using First Nations Children's Literature in the Classroom: Portfolio of Learning

A portfolio was developed to encourage teachers of Aboriginal children to include First Nations mentor texts into their daily teaching practices. The artifacts within the portfolio have been produced in accordance with guiding beliefs about how students, specifically First Nations students, learn. The portfolio supports the notion that Aboriginal children need to encounter representations of their own culture, histories and beliefs within the literature in order to be successful in school. The use of First Nations children’s literature in the classroom was explored with an emphasis on how using this literature will assist in improving literacy levels and the self-esteem of First Nations students.

Diversification Limited by Absence of Short Sales: the Chinese Case.

Rapport de recherche

Sequential Machine learning Approaches for Portfolio Management

Cette thèse envisage un ensemble de méthodes permettant aux algorithmes d'apprentissage statistique de mieux traiter la nature séquentielle des problèmes de gestion de portefeuilles financiers. Nous débutons par une considération du problème général de la composition d'algorithmes d'apprentissage devant gérer des tâches séquentielles, en particulier celui de la mise-à-jour efficace des ensembles d'apprentissage dans un cadre de validation séquentielle. Nous énumérons les desiderata que des primitives de composition doivent satisfaire, et faisons ressortir la difficulté de les atteindre de façon rigoureuse et efficace. Nous poursuivons en présentant un ensemble d'algorithmes qui atteignent ces objectifs et présentons une étude de cas d'un système complexe de prise de décision financière utilisant ces techniques. Nous décrivons ensuite une méthode générale permettant de transformer un problème de décision séquentielle non-Markovien en un problème d'apprentissage supervisé en employant un algorithme de recherche basé sur les K meilleurs chemins. Nous traitons d'une application en gestion de portefeuille où nous entraînons un algorithme d'apprentissage à optimiser directement un ratio de Sharpe (ou autre critère non-additif incorporant une aversion au risque). Nous illustrons l'approche par une étude expérimentale approfondie, proposant une architecture de réseaux de neurones spécialisée à la gestion de portefeuille et la comparant à plusieurs alternatives. Finalement, nous introduisons une représentation fonctionnelle de séries chronologiques permettant à des prévisions d'être effectuées sur un horizon variable, tout en utilisant un ensemble informationnel révélé de manière progressive. L'approche est basée sur l'utilisation des processus Gaussiens, lesquels fournissent une matrice de covariance complète entre tous les points pour lesquels une prévision est demandée. Cette information est utilisée à bon escient par un algorithme qui transige activement des écarts de cours (price spreads) entre des contrats à terme sur commodités. L'approche proposée produit, hors échantillon, un rendement ajusté pour le risque significatif, après frais de transactions, sur un portefeuille de 30 actifs.