Bank value and risk's portfolio interdependence and management ; Banko vertės ir rizikų portfelio sąveika ir valdymas

Gintautasg

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VILNIUS GEDIMINAS TECHNICAL UNIVERSITY Gintautas Garbanovas BANK VALUE AND RISK’S PORTFOLIO INTERDEPENDENCE AND MANAGEMENT SUMMARY OF DOCTORAL DISSERTATION SOCIAL SCIENCES, ECONOMICS (04S) VILNIUS 2010 Doctoral dissertation was prepared at Vilnius Gediminas Technical University in 1999–2010. The dissertation is defended as an external work. Scientific Consultant Prof Dr Habil Aleksandras Vytautas RUTKAUSKAS (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S). The dissertation is being defended at the Council of Scientific Field of Economics at Vilnius Gediminas Technical University: Chairman Prof Dr Habil Romualdas GINEVIČIUS (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S). Members: Prof Dr Habil Borisas MELNIKAS (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S), Prof Dr Habil Ona Gražina RAKAUSKIENĖ (Mykolas Romeris University, Social Sciences, Economics – 04S), Prof Dr Vytautas SNIEŠKA (Kaunas University of Technology, Social Sciences, Economics – 04S), Prof Dr Manuela TVARONAVIČIENĖ (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S). Opponents: Prof Dr Habil Artūras KAKLAUSKAS (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S), Prof Dr Habil Jonas MACKEVIČIUS (Vilnius University, Social Sciences, Economics – 04S).

Sujets

• Economics
• Risk management

Informations

• Publié par: vilnius_gediminas_technical_university
• Publié le: 01 janvier 2010
• Nombre de lectures: 38
• Poids de l'ouvrage: 3 Mo

Extrait

VILNIUS GEDIMINAS TECHNICAL UNIVERSITY

Gintautas Garbanovas

BANK VALUE AND RISK’S PORTFOLIO INTERDEPENDENCE AND MANAGEMENT

SUMMARY OF DOCTORAL DISSERTATION

SOCIAL SCIENCES, ECONOMICS (04S)

 

 

 

VILNIUS

 

 2010

 

Doctoral dissertation was prepared at Vilnius Gediminas Technical University in 1999–2010. The dissertation is defended as an external work. Scientific Consultant Prof Dr Habil Aleksandras Vytautas RUTKAUSKAS (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S).   The dissertation is being defended at the Council of Scientific Field of Economics at Vilnius Gediminas Technical University: Chairman Prof Dr Habil Romualdas GINEVIČIUS(Vilnius Gediminas Technical University, Social Sciences, Economics – 04S). Members: Prof Dr Habil Borisas MELNIKAS Gediminas Technical (Vilnius University, Social Sciences, Economics – 04S), Prof Dr Habil Ona Gražina RAKAUSKIEN- (Mykolas Romeris University, Social Sciences, Economics – 04S), Prof Dr Vytautas SNIEŠKA(Kaunas University of Technology, Social Sciences, Economics – 04S), Prof Dr Manuela TVARONAVIČIEN-(Vilnius Gediminas Technical University, Social Sciences, Economics – 04S). Opponents: Prof Dr Habil Artūras KAKLAUSKAS (Vilnius Gediminas Technical University, Social Sciences, Economics – 04S), Prof Dr Habil Jonas MACKEVIČIUS(Vilnius University, Social Sciences, Economics – 04S).   The dissertation will be defended at the public meeting of the Council of Scientific Field of Economics in the Senate Hall of Vilnius Gediminas Technical University at 2 p. m. on 24 November 2010. Address: Saultekio al. 11, LT-10223 Vilnius, Lithuania. Tel.: [phone]; fax [phone]; e-mail: [e-mail] The summary of the doctoral dissertation was   distributed on 22 October 2010. A copy of the doctoral dissertation is available for review at the Library of Vilnius Gediminas Technical University (Saultekio al. 14, LT-10223 Vilnius, Lithuania). © Gintautas Garbanovas, 2010

 

 

VILNIAUS GEDIMINO TECHNIKOS UNIVERSITETAS

Gintautas Garbanovas

BANKO VERTS IR RIZIKŲ PORTFELIO SĄVEIKA IR VALDYMAS

DAKTARO DISERTACIJOS SANTRAUKA

SOCIALINIAI MOKSLAI, EKONOMIKA (04S)

Vilnius

 

 2010

 

Disertacija   rengta   1999–2010   metais   Vilniaus   Gedimino   technikos universitete. Disertacija ginama eksternu. Mokslinis konsultantas prof. habil. dr. Aleksandras Vytautas RUTKAUSKAS (Vilniaus Gedimino technikos universitetas, socialiniai mokslai, ekonomika – 04S). Disertacija ginama Vilniaus Gedimino technikos universiteto Ekonomikos mokslo krypties taryboje: Pirmininkas prof. habil. dr. Romualdas GINEVIČIUS(Vilniaus Gedimino technikos universitetas, socialiniai mokslai, ekonomika – 04S). Nariai: prof. habil. dr. Borisas MELNIKAS(Vilniaus Gedimino technikos universitetas, socialiniai mokslai, ekonomika – 04S), prof. habil. dr. Ona Gražina RAKAUSKIEN- (Mykolo Romerio universitetas, socialiniai mokslai, ekonomika – 04S), prof. dr. Vytautas SNIEŠKA(Kauno technologijos universitetas, socialiniai mokslai, ekonomika – 04S), prof. dr. Manuela TVARONAVIČIEN- (Vilniaus Gedimino technikos universitetas, socialiniai mokslai, ekonomika – 04S). Oponentai: prof. habil. dr. Artūras KAKLAUSKAS(Vilniaus Gedimino technikos universitetas, socialiniai mokslai, ekonomika – 04S), prof. habil. dr. Jonas MACKEVIČIUS (Vilniaus universitetas, socialiniai mokslai, ekonomika 04S). –     Disertacija bus ginama viešame Ekonomikos mokslo krypties tarybos posdyje 2010 m. lapkričio 24 d. 14 val. Vilniaus Gedimino technikos universiteto senato posdžių salje. Adresas: Saultekio al. 11, LT-10223 Vilnius, Lietuva. Tel.: [phone]; faksas (8 5) 270 0112; el. paštas [e-mail] Disertacijos santrauka išsiuntinta 2010 m. spalio 22 d. Disertaciją galima peržiūrti Vilniaus Gedimino technikos universiteto bibliotekoje (Saultekio al. 14, LT-10223 Vilnius, Lietuva). VGTU leidyklos „Technika“ 1806-M mokslo literatūros knyga.   © Gintautas Garbanovas, 2010

 

 

 Introduction   Topicality of the Problem. A successful solution of risk mana ement roblems becomes the uarantee of the o erational success. Risk mana ement roblems, both worldwide and in Lithuania, become the ob ect of articular attention b both increasin the diversit of the risks under consideration and b develo in co nitive instruments. Durin the last decade a reat attention is aid to Value at Risk VaR method, which is bein examined, investi ated and on the basis of which new theories were created b the scientists all over the world. The classics of the Risk Mana ement theories, such as Markowitz, Merton, Black, Scholes are widel known, and their works have lon been the ob ect of s ecial attention not onl in science but also in the practice of the banking and financial markets. K. Dowd B. Schachter P. Joris R. A. Jarrow N. Oda, J. Murana a, J. Bessie and others were ones of the first who started to question Value at Risk. Foreign scholars only in recent years have published their first articles about the value of the company and the re ularit research on the risk factors of its activit . The scholars of Halle-Wittenber Universit German – L. Schiefner and R. Schmidt - ublished an article about the conce t of risk of the shareholder’s value Schiefner and Schmidt, 2003 . In the research, the authors determined com an 's cash flow distributions of the resent value b se aratin risk factors, creatin value calculation scheme and usin simulation models. Actuall , the authors limited themselves to model romotion for a com an ’s or individual project assessment and submitted it as aDecision Support System. It has already been a while that business value researches and bank value calculations have been carried out. The issues of the business value and bank value calculations are discussed by T. Copeland, T. Koller, J. Murri, S. Bennin , O. Sarig, D. Baur, M. Habib, R. Volkart, A. V. Rutkauskas, S. Eiva and others. The researches on the relationshi of risk and value have recentl become increasin l interestin for scientific societies. There are not man scholars dealin with risk assessment and risk mana ement issues in Lithuania. The Value at Risk methodology is interestin to P. Baršauskas, A. V. Rutkauskas, R. Ba donien, R. Rokuižien. Risk management roblems are investi ated b V. Valvonis M. Jasien, V. Aleknavičien. Business valuation issues are anal zed b D. Burkštaitien, V. Bo uslauskas. Statistical analysis and various simulation models are used by A. V. Rutkauskas, V. Jakštas.    

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  Object of the Research. Regularity of the bank value and risks in the bank operation, integrated value and risks processes management. Creation and use of the bank value models, witch enable to research for integrated bank value and bank risks processes, and gives possibilities evaluate bank value and bank risks proceses in quantitative mode, regularities and interdependences.   Aim and Tasks of the Work. of the work is based on the idea of Aim risk’s portfolio and company valuation on the discounted cash flow for the shareholders method, as well as on the Monte Carlo simulation methodology, to create the model of the bank value calculation and with the use of it to quantitatively research the interdependence and regularity of the bank's core values and risks. To achieve the aim of this work the followin ob ectives should be solved: 1.    literature about the main types of banking ze scientificTo anal risks and the princi les of their mana ement. 2.   To investigate scientific literature about the possibilities of VaR methodolo a lication. 3.   To anal ze scientific literature about the com onents of credit risk, its mana ement rinci les and techni ues, to examine the ossibilities of the credit risk measurement b the risk value. 4.    ze scientific literature about theTo anal of the bank's rinci les assessment, takin into consideration the risks, and develo the models of bank's value assessment and prediction while choosing ade uate methods of forecastin . 5.    consideration the risks, to create the model of bankTakin into assessment, a l it b investi atin the inter-relationshi between the value of the bank and risks ortfolio and to erform the research with this model as well as to anal ze the results. 6.    to check the bank valuation model based on historicalIn ractice, erformance indicators and to assess actual degree of risk of the risk factors in earlier eriods. 7.    of the value and risk with actTo conduct the research on the im bank value model and to analyze the results.   Methodolo o Research. was conducted on the basis of The stud methodolo of rather autonomousl o eratin subs stems in a s stem of interactin research in order to direct their interaction towards the aim of a common s stem. To s ecif the mentioned rinci le it should be asserted that the investigation was carried out according to the systematic methodology

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rinci le and covers the research of risk mana ement and a value as an ob ect of academic field, theor formation and develo ment in the li ht of new theories and ractical achievements of risks, value and risk mana ement. While addressin the issues raised b the thesis, a variet of scientific literature, internet, knowled e, ex ertise were used as well as other sources of anal sis and s nthesis methods re orts statistics and other data of lo ical mathematical and statistical re aration for decision-makin techniques develo ed b forecastin models, "Monte Carlo" simulation method. To solve the research tasks, the knowled e of the fields of economics, finance, mana ement, mathematics, statistics, etc. were used. To a l the model of the determination of the influence of bank's o erational risks on bank's valuation a commercial bank actin in Lithuania in the text referred to as the commercial bank was chosen; actual historical, financial, material and em irical data were used. In the thesis the followin theoretical and ractical data sources were anal zed and used: the law of the Re ublic of Lithuania, resolutions of the Government of the Re ublic of Lithuania, re ulator enactments a roved b the board of the Bank of Lithuania re ulator enactments approved by Ministry of Finance of the Republic of Lithuania, data b De artment of Statistics to the Government of the Re ublic of Lithuania, data b the Bank of Lithuania, the Bank for International Settlements BIS and documents a roved b the Basel Committee, financial accounts of commercial bank, works and re orts b forei n and Lithuanian researchers, anal sts, ractitioners, as well as articles published in periodicals on the issues of the thesis.   Scientific Novelt 1.   Ex erimentall im lemented idea of the bank's value and integrated management of risk. 2.   Created and practically applied model of the bank forecasting, based on the historical bank performance indicators, and bank’s assessment, based on forecast performance indicators. 3.   Created and practically applied model of the dependence of bank’s value on risk factors, which allows the assessment of the im pact of individual risk factors on bank’s value, with the evaluation of the interaction of those factors. This model is ada table to the calculation of an bank’s value and the research of its sensitivity to the risk factors. 4.    analAn innovative scheme for sensitivit is used: the sis de endence of the o ortunities of bank’s value distribution on the statistical dependency levels of bank risk factors.

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  Practical Value. uments and created schemes of Provided theoretical ar their ractical usa e are to be used for the inte rated bank value and risk mana ement, while determining common objectives of the bank value and risk mana ement. The stud allows a broader understandin of the bank’s value increase as a ke ob ective of the activit and bank's value dependence on the specific bank’s activit risk factors, which can be mana ed. The created in the scholarl work research model of the de endence of the bank’s value on bank risk indicators allows the assessment of the contribution of a s ecific risk factor to the increase or loss in value. The desi ned model of bank value calculation is suitable for the calculation of the value of an commercial bank and the investigation of the affect of any hypothetical scenario on the bank value.   Defended Propositions 1.   The integrated bank value and risk management are the hypothesis of effective current decisions of bank management and the stability uarantee of strate ic develo ment. 2.   While investi the atin ros bank’s ic develo ects, both strate ment and the ossibilit for current solutions shall be characterized through their efficiency, reliability and risk characteristics.   The Scope of the Scientific Work.The scientific work consists of the general characteristics of the dissertation, four chapters, conclusions, list of literature, list of publications and addenda. The total scope of the dissertation is 120 pages, 14 pictures, 9 tables and 4 addenda.   1. The Adequate Measurement Techniques of Risk. Risk Measurement by VaR.   In the study, the value at risk indicator was chosen as a risk measurement tool, which is understood as the maximum expected loss over some certain period of time at a certain level of reliabilit (Dowd, 1998). The measurement ca abilities of various t es of risk b the value at risk are examined in details. At the same time a reverse uestion, i.e. how the determinin arameters of the rocess have to chan e so that the value at risk chan es in a desired wa and scale, is not obvious and, moreover, uantitativel described rocess. So a roblem that resources for risk management shall be optimally allocated, should be naturally accepted.

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Thus with the hel of ex ert assessment there could be received the information which is necessar to o timall solve the roblem of risks ortfolio selection. In a iven case, the problem is formulated as a stochastic optimization task. Having used statistical data and expert assessment, it has been accepted that a one-litas investment in the measures aimed at avoiding possible losses in the individual risk strains has to ensure the effects described by normal distributions of effect probability, respectively: N(a 1 =0.75;S 1 =0.125),N(a 2 =0.95;S 2 =0.2),   N(a 3 =1.2;S 3 =0.35),N(1.42;0.41);  (1) Here, (a i ), (S i ) are the averages of the distribution probability of respective effects a i , and standard deviations S i . If we o erate onl the avera e values, the rovided schemes would rovide information about the o ortunities of rational allocation of resources. However in ractice it is often ex edient to be aware of all ossibilities as well as assessment of their reliabilit , so we have not onl standard “avera e deviation” ortfolio opportunities, but also quartiles, min and max portfolio options images.

100 90 80 70 60 Possibility 50 40 30 0.148 20 0.175 0.19 10 0.225 reisno Disp 0 0.255 0.294 Portfolio values Fig. 1.Geometr ca portfolio possibilities set – effective v ew o surface

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If we then take more detailed values of distributions in uartiles - deciles ercentiles – we will a roach to continuous set of uintile. Fi . 1 resents the eometric icture of such ossibilit when a set of uintile is e uivalent to ercentiles and each line of ercentile efficienc is u lifted to its ercentile hei ht. Thus, in Fi . 1 all ossible ortfolios value sets are outlined in three parameters: the possibility size, reliability and risk class of that possibility . As each set of portfolio possibilities is characterized by the above- mentioned three parameters - the magnitude of avoidable loss, avoidability guarantee, and risk – are linked to the considered possibility, the best option selection problem is complicated due to the fact that these parameters have even different dimensions: monetar unit – losses, the robabilit – avoidabilit uarantee ossibilit robabilit distribution – the risk of losses. Therefore to select the best options an adequate utility function is re uired. In case of success the utilit function can become functional, i.e. the rule that to ever ossibilit which is assessed in three parameters would give unambiguous assessment of the loss avoided.   2.   Credit Risk Measurement and Management Techniques. Credit Risk Measurement by VaR   Credit risk can be defined as the risk of loss, resulting from counterparty failure to erform a retroactive a ment. Credit risk has three basic com onents: - Insolvenc robabilit: the probability that the counterparty would fail to make a retroactive a ment. -The rate o recover art becomes insolvent. of funds if the other: recover   Borrowing Amountbe lost if the other party becomes: the amount that will - insolvent. It can, therefore, be asserted that the credit risk mana ement includes the followin ob ectives: to anal ze and measure these three credit risk com onents, and examine how financial institutions can influence those factors to reduce the credit risk. Some authors se arate credit risk into two com onents Oda, N. and Murana a, J., 1997 . The first: credit risk is the otential reduction of future cash flows from the current value of financial transactions, which is caused b the other art 's insolvenc . The second art of the credit risk is the otential loss due to the increase of insolvenc likelihood in the future. These authors ro ose their own methods of measurement, covering both credit risk components.

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It is ossible to create a s stem that would determine the maximum ossible amount that we could lose due to insolvenc i.e., value at insolvenc risk , but this indicator of the value at insolvenc risk i nores the risk of chan es in market rices. Traditional market value assesses these chan es in market rices; however, it underestimates the risk of insolvenc . In practice, there is a need to forecast losses for the two sources of risk. Although the theoretical grounds of insolvency risk integration into the value at risk is strong, there is a question of how much the efforts to determine the rate are worth - the combined risk of insolvenc lus the market value at risk. As stated b Dowd 1998 , the value at insolvenc risk will be ver little associated with value at market risk, thus the inte ration of two values at risk into a sin le value at risk will often ive a number which is onl sli htl reater than the real value at market risk. A numeric ex ression of the value at insolvenc risk is e ual to the value at market risk multi lied b the robabilit of insolvenc . However, an inte rated value at risk is si nificantl different from the real value at market risk in case of a significant probability of insolvency. It is still an open question of how much it is meaningful to integrate the value at insolvency risk into the value at risk at the current practice.   3. The Theoretical Modelling of the Bank’s Value Calculation   The paper presents the analysis of the bank value calculation methods and the simulation methods of bank's value, with the descri tion of their rinci les and o eration schemes. Methods and offers of how to more lo icall solve the uestion of bank value calculation while usin the models are resented. At the same time the uestions of the use of these models and their applicability in Lithuania are examined. Havin im lemented the investi ation when the value of bank’s share ca ital is calculated, it is possible to emphasize certain characteristics of the bank valuation. 1.   The described bank’s value identification model is theoretically correct and tested in trials. 2.   All values are calculated on the basis of the bank's business outlook for the future. 3.    of rofit loss indicatorsWhile forecastin , not onl determinants must be taken into consideration, but also the future structure of the balance sheet items. This is necessary in order to maintain the central bank's share capital requirements for banks and other prudential norms redictin the bank's business accounts. Consequently, a bank's operations forecasting model is required.

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