Submitted by Bruno Zaneti (blzaneti@gmail.com) on 2013-07-22T13:27:12Z No. of bitstreams: 1 ZANETI_Dissertacao-MPAgro_vF.pdf: 1353030 bytes, checksum: 129d2405b05986f5310256b86efdbd18 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-07-22T13:41:28Z (GMT) No. of bitstreams: 1 ZANETI_Dissertacao-MPAgro_vF.pdf: 1353030 bytes, checksum: 129d2405b05986f5310256b86efdbd18 (MD5) / Made available in DSpace on 2013-07-22T14:05:04Z (GMT). No. of bitstreams: 1 ZANETI_Dissertacao-MPAgro_vF.pdf: 1353030 bytes, checksum: 129d2405b05986f5310256b86efdbd18 (MD5) Previous issue date: 2013-06-21 / Este trabalho objetiva analisar e contribuir com o gerenciamento de riscos de preços dentro da indústria sucroenergética brasileira, mais especificamente da região Centro-Sul do país, que é a maior processadora de cana-de-açúcar de todo o mundo. Esta indústria tem características peculiares, tanto quanto às formas de comercialização de seus produtos finais – notadamente o açúcar e o etanol – quanto de sua estrutura de custos, onde a cana-de-açúcar representa algo da ordem de 70% do custo total de produção destes produtos. Assim, a proposição aqui implícita passa por uma abordagem específica para o gerenciamento de riscos de preços destas empresas, definindo como principal fator de risco o distanciamento entre os preços das vendas de açúcar travados em mercado organizado de futuros frente aos preços do açúcar apurados dentro da metodologia Consecana e que formam os preços do principal insumo produtivo destas empresas, a cana-de-açúcar. Assim, com uma abordagem empírica é feita uma análise sobre uma amostra de 1.138 ações de fixações de preços ocorridas durante o ano-safra 2012-13, revelando um comportamento de atuação no mercado futuro por parte destas empresas de maximização do valor da firma. Além disso, serão identificados os principais fatores idiossincráticos e sistêmicos que influenciam o retorno que estas empresas obtêm da comercialização de açúcar para o exterior, bem como os fatores que influenciam a tomada de decisão por parte destas empresas. / This work aims to analyze and contribute the prices risk management in the Brazilian sugarcane industry, more specifically the Center-South region of the country, which is the largest processor of sugarcane in the world. This industry has unique characteristics, so as to the ways these firms sell their ended products – notably sugar and ethanol – as its structure of costs, where sugarcane accounts for around 70% of the total cost of production of these products. Thus, the proposition here passes through a specific approach for managing price risks in these firms, defining the major risk they are exposed as the gap between the prices of sugar they sell in futures market and the sugar prices calculated within the Consecana methodology to serve as input for the prices of sugarcane, their main production feedstock. To achieve that it is made an analysis on a sample of 1,138 price fixation actions occurred during the 2012-13 crop, revealing a firm value maximizing behavior. Furthermore, the proposed models will help identify the main idiosyncratic and systemic factors that influence the return these firms obtain from their actions in futures markets as well as the main factors that influence the decision process of hedging within these firms.

This thesis aims to identify main driving market risk factors of different strategies implemented by hedge funds by looking at correlation coefficients, implementing Principal Component Analysis and analyzing "loadings" for first three principal components, which explain the largest portion of the variation of hedge funds' returns. In the next step, a stepwise regression through iteration process includes and excludes market risk factors for each strategy, searching for the combination of risk factors which will offer a model with the best "fit", based on The Akaike Information Criterion - AIC and Bayesian Information Criterion - BIC. Lastly, to avoid counterfeit results and overcome model uncertainty issues a Bayesian Model Average - BMA approach was taken. Key words: Hedge Funds, hedge funds' strategies, market risk, principal component analysis, stepwise regression, Akaike Information Criterion, Bayesian Information Criterion, Bayesian Model Averaging Author's e-mail: aleksaradosavcevic@gmail.com Supervisor's e-mail: mp.princ@seznam.cz

This diploma thesis deals with external audit of banks in Czech Republic. The main objective of this thesis is to describe in detail the techniques, strategy and methods which are used by the external auditor during the engagement and to compare them with those used in internal audit. The main emphasis during the stage of interim audit is put on control of risk management activities. The first part of this diploma thesis is devoted to theoretical issues and legal aspects of audit profession. Specific characteristics of banking institutions audit including major risks and the scope of external auditor's activities are described in the second chapter of the thesis. Third part describes the main stages, used methodology and the process of external audit of banking institutions. Last chapter is devoted to a brief description of the internal auditor's activities in the bank and their comparison with the external audit.

The goal of my thesis "Audit of a bank" is to identify and describe the area of external and internal audit in banking and to focus on specifics of bank audit in comparison to external audit of commercial enterprise. The first part is focused on audit of financial statements. In the second part are described the specifics of banking segment. Third part describes internal audit and cooperation between external and internal audit. In the last part there are described methods applied during the audit of the bank.

This diploma thesis introduces the measures of network connectedness in the context of asset pricing. It proposes an asset pricing model in which the factor of connectedness is included as one of the risk factors together with the three Fama-French factors. The goal of the analysis is to examine whether the con- nectedness represents a signifcant risk factor that should be considered while determining the risk premium of the portfolio in diferent sectors in the market. Using the realized volatilities and returns of 496 assets of SP 500 index over the period 2005 - 2018, that are divided into 11 sectors, we frstly determine the linkages of connectedness between the assets in the same sector. Applying Fama-MacBeth two-step regression model, we explore the signifcance of the connectedness factor for the determination of the risk premium. We argue that the sector overall connectedness represents a signifcant risk in most of the sec- tors and should be therefore taken into account by the investors in all sectors. Moreover, the total directional connectedness that captures the spillover of shocks to one asset from the other assets in the sector, is a signifcant risk fac- tor that should increase the risk premium of the portfolio, especially in sectors such as the fnancial, health care, consumer...

Since the financial crisis of 2008, the risk awareness has increased in the -financial sector. Companies are regulated with regards to risk exposure. These regulations are driven by the Basel Committee that formulates broad supervisory standards, guidelines and recommends statements of best practice in banking supervision. In these regulations companies are regulated with own funds requirements for market risks. This thesis constructs an internal model for risk management that, according to the "Capital Requirements Regulation" (CRR) respectively the "Fundamental Review of the Trading Book" (FRTB), computes the regulatory capital requirements for market risks. The capital requirements according to CRR and FRTB are compared to show how the suggested move to an expected shortfall (ES) based model in FRTB will affect the capital requirements. All computations are performed with data that have been provided from a power trading company to make the results fit reality. In the results, when comparing the risk capital requirements according to CRR and FRTB for a power portfolio with only linear assets, it shows that the risk capital is higher using the value-at-risk (VaR) based model. This study shows that the changes in risk capital mainly depend on the different methods of calculating the risk capital according to CRR and FRTB respectively and minor on the change of risk measure. / I samband med finanskrisen 2008 har riskmedvetenheten ökat i den finansiella sektorn. Företag regleras mot riskexponering av föreskrifter som drivs av Baselkommittén, de utformar tillsynsstandarder och riktlinjer samt rekommenderar åtgärder av bästa praxis. I dessa föreskrifter regleras företag av kapitalbaskrav mot marknadsrisker. I det här examensarbetet beskrivs processen för att ta fram en intern riskmodell, enligt "Capital Requirements Regulation"(CRR) respektive Fundamental Review of the Trading Book"(FRTB), för att beräkna de lagstadgade kapitalkraven mot marknadsrisker. Kapitalbaskraven enligt regelverken jämförs för att förstå hur det föreslagna bytet till en expected shortfall (ES) baserad modell i FRTB kommer att påverka kapitalbaskraven. I alla beräkningar anv änds data från ett elhandelsföretag för att göra resultaten mer intressanta och verklighetsanpassade. I resultatdelen, vid jämförelse av riskkapitalkraven enligt CRR och FRTB för en energiportfölj med endast linjära tillgångar kan det ses att riskkapitalet blir högre med en value-at-risk (VaR) baserad modell. Den viktigaste upptäckten med detta är att skillnaden i riskkapitalkraven inte främst beror på de olika riskmåtten utan snarare de olika metoderna för att beräkna riskkapitalet enligt CRR och FRTB.

The Own Risk and Solvency Assessment, ORSA, is referred to as the heart of the regulation to be for European insurance companies - Solvency II. The aim of the ORSA process is to provide an overall and holistic view of the insurer’s risks by analyzing their current financial status and business strategy at hand. There is no predefined way to implement this process, which means that the companies are forced to develop a model themselves, as they see fit. In collaboration with a regional insurance company in Sweden we develop a structure and framework for an ORSA-model, flexible enough to be used by similar insurers yet standardized enough to overcome the issue of constrained resources within these smaller organizations. We apply a risk-factor based approach and tie together a balance sheet projection and stress testing, designed to be further developed as the individual insurer see fit. The suggested approach yields partially satisfying results and we consider the model to be particularly well-suited for assessing risk in the context of the small, non-life insurer. / Den egna risk- och solvensutvärderingen, ORSA, kallas hjärtat av det kommande regelverket för europeiska försäkringsbolag - Solvens II. Syftet med ORSA-processen är att ge en övergripande helhetsbild av försäkringsgivarens risker genom att analysera deras finansiella ställning och affärsstrategi. Det finns inget fördefinierat sätt att genomföra denna process, vilket innebär att företagen tvingas att utveckla en modell på egen hand, på ett sätt som de finner lämpligt. I samarbete med ett regionalt försäkringsbolag i Sverige utvecklar vi en struktur och en grund för en ORSA-modell. En modell som är tillräckligt flexibel för att kunna användas av liknande försäkringsgivare men samtidigt standardiserad nog att lösa problemet med begränsade resurser i dessa mindre organisationer. Vi tillämpar en riskfaktor-baserad metod, prognostiserar resultat- och balansräkning för bolaget och utför stresstester. Metoden är utformad för att utvecklas vidare av den enskilde försäkringsgivaren så som de finner lämpligt. Den föreslagna metoden ger delvis tillfredsställande resultat och vi anser att det är en grund väl lämpad att använda som utgångspunkt för att konstruera riskmätningsmetoder för små, skadeförsäkringsbolag.

Bakgrund: Kommuninvest är en medlemsorganisation som finansierar en stor andel av den svenska kommunsektorns upplåning. Detta möjliggörs genom att Kommuninvest emitterar obligationer på finansiella marknader för att sedan låna ut kapital till kommunerna. Finansiella institut som Kommuninvest hanterar en rad olika risker i sin verksamhet och eftersom det saknas tidigare forskning angående Kommuninvests exponering mot och hantering av marknadsrisk är detta intressant att studera för att fylla kunskapsluckan. Det är också intressant eftersom kommunerna är en viktig aktör i det svenska samhället och Kommuninvest spelar en stor roll i den kommunala upplåningen. Syfte: Syftet med denna studie är att analysera Kommuninvests marknadsriskexponering när de lånar upp pengar på den finansiella marknaden för att låna ut dessa till medlemskommunerna, samt att analysera företagets marknadsriskhantering. Syftet är också att analysera hur marknadsriskexponeringen och marknadsriskhanteringen påverkar medlemskommunerna. Genomförande: Studien är designad som en fallstudie. Fallet har definierats som Kommuninvests marknadsriskexponering och -hantering. Det empiriska materialet utgörs av nio semistrukturerade intervjuer och en dokumentstudie. Det empiriska materialet har använts för att kunna dra slutsatser om Kommuninvests marknadsriskexponering och -hantering samt dessas potentiella påverkan på medlemskommunerna. Slutsats: Flera slutsatser kan dras från denna studie. Kommuninvest hedgar främst sin marknadsrisk med derivat och naturlig matchning. Den monetära effekten på låneportföljen konstateras vara relativt liten. Räntemarginalen är så pass låg att de små kommunerna väljer att alltid låna av Kommuninvest och de stora väljer att göra det ibland. Kommunerna i studien har över lag högt förtroende för Kommuninvest och majoritet upplever att de inte påverkas så mycket av bolagets riskexponering eller riskhantering. Denna studie bidrar med ny kunskap om Kommuninvests marknadsriskexponering och -hantering till det företagsekonomiska forskningsfältet såväl som till de svenska kommunerna. / Background: Kommuninvest is a member organisation that finances a large part of the borrowing of Swedish local governments. This is made possible by emitting bonds on the financial markets and then lending capital to the local governments. Financial institutions like Kommuninvest deal with several different risks and since no previous research has been conducted on the subject of the market risk exposure and the market risk management of Kommuninvest, this is a pertinent case to study in order to fill the gap. It is also a pertinent case since the local governments of Sweden are a very important part of the society and since Kommuninvest plays a great role in the borrowing of these local governments. Aim: The aim of this study is to analyse the market risk exposure of Kommuninvest when the company borrows capital on the financial markets to lend to their members, Swedish local governments, as well as to analyse the market risk management of the company. A secondary aim is to analyse how the market risk exposure and the market risk management affect the local governments that are members of Kommuninvest. Completion: The study is designed as a case study. The case has been defined as The market risk exposure and market risk management of Kommuninvest. The empirical data consists of nine semi-structured interviews and one document study. The empirical data is used to draw conclusions about the market risk exposure and the market risk management of Kommuninvest, as well as their potential effects on the Swedish local governments that are members of Kommuninvest. Conclusion: Several conclusions can be drawn from this study. Kommuninvest primarily hedges its market risk with derivates and natural hedges. The monetary effect on the loan portfolio is found to be relatively small. The interest margin is low enough so that the small local governments choose to always borrow from Kommuninvest, and the big local governments choose to sometimes do so. The local governments that participated in the study generally have high confidence in Kommuninvest and most of them experience that they are not very affected by the company’s risk exposure or risk management. This study contributes with new knowledge about the market risk exposure and market risk management of Kommuninvest to the research field as well as to the Swedish local governments.

In this thesis, we set out to model the market risk exposure for 251 stocks in the S&P 500 index, during a ten-year period between 2011-04-30 and 2021-03-31. The study brings to light a model not often mentioned in the scientific literature focused on market risk estimation, the linear mixed model. The linear mixed model makes it possible to model a time-varying market risk, as well as adding structure to the idiosyncratic risk, which is often assumed to be a stationary process. The results show that the mixed model is able to produce more accurate estimates for the market risk, compared to the baseline, which is here defined as a CAPM model. The success of the mixed model, which we in the study will refer to as the ADAPT model (adaptive APT), most certainly lies in its ability to create a hierarchical regression model. This makes it possible to not just view the set of observations as a single population, but let us group the observations into different clusters and in such a way makes it possible to construct a time-varying exposure. In the last part of the thesis, we highlight possible improvements for future works, which could make the estimation even more accurate and also more efficient.

In dieser Dissertation werden neue Methoden zur Erfassung zweier Risikoarten entwickelt. Markrisiko ist definiert als das Risiko, auf Grund von Wertrückgängen in Wertpapierportfolios Geld zu verlieren. Systemisches Risiko bezieht sich auf das Risiko des Zusammenbruchs eines Finanzsystems, das durch die Notlage eines einzelnen Finanzinstituts entsteht. Im Zuge der Finanzkrise 2007–2009 realisierten sich beide Risiken, was weltweit zu hohen Verlusten für Investoren, Unternehmen und Steuerzahler führte. Vor diesem Hintergrund besteht sowohl bei Finanzinstituten als auch bei Regulierungsbehörden Interesse an neuen Ansätzen für das Risikomanagement. Die Gemeinsamkeit der in dieser Dissertation entwickelten Methoden besteht darin, dass unterschiedliche Quantilsregressionsansätze in neuartiger Weise für das Finanzrisikomanagement verwendet werden. Zum einen wird nichtparametrische Quantilsregression mit Extremwertmethoden kombiniert, um extreme Markpreisänderungsrisiken zu prognostizieren. Das resultierende Value at Risk (VaR) Prognose- Modell für extremeWahrscheinlichkeiten wird auf internationale Aktienindizes angewandt. In vielen Fällen schneidet es besser ab als parametrische Vergleichsmodelle. Zum anderen wird ein Maß für systemisches Risiko, das realized systemic risk beta, eingeführt. Anders als bereits existierende Messgrößen erfasst es explizit sowohl Risikoabhängigkeiten zwischen Finanzinstituten als auch deren individuelle Bilanzmerkmale und Finanzsektor-Indikatoren. Um die relevanten Risikotreiber jedes einzelnen Unternehmens zu bestimmen, werden Modellselektionsverfahren für hochdimensionale Quantilsregressionen benutzt. Das realized systemic risk beta entspricht dem totalen Effekt eines Anstiegs des VaR eines Unternehmens auf den VaR des Finanzsystems. Anhand von us-amerikanischen und europäischen Daten wird gezeigt, dass die neue Messzahl sich gut zur Erfassung und Vorhersage systemischen Risikos eignet. / This thesis develops new methods to assess two types of financial risk. Market risk is defined as the risk of losing money due to drops in the values of asset portfolios. Systemic risk refers to the breakdown risk for the financial system induced by the distress of individual companies. During the financial crisis 2007–2009, both types of risk materialized, resulting in huge losses for investors, companies, and tax payers all over the world. Therefore, considering new risk management alternatives is of interest for both financial institutions and regulatory authorities. A common feature of the models used throughout the thesis is that they adapt quantile regression techniques to the context of financial risk management in a novel way. Firstly, to predict extreme market risk, nonparametric quantile regression is combined with extreme value theory. The resulting extreme Value at Risk (VaR) forecast framework is applied to different international stock indices. In many situations, its performance is superior to parametric benchmark models. Secondly, a systemic risk measure, the realized systemic risk beta, is proposed. In contrast to exististing measures it is tailored to account for tail risk interconnections within the financial sector, individual firm characteristics, and financial indicators. To determine each company’s relevant risk drivers, model selection techniques for high-dimensional quantile regression are employed. The realized systemic risk beta corresponds to the total effect of each firm’s VaR on the system’s VaR. Using data on major financial institutions in the U.S. and in Europe, it is shown that the new measure is a valuable tool to both estimate and forecast systemic risk.