Estimating tail risk measures such as Value at Risk (VaR) and Conditional Tail Expectation (CTE) is a vital component in financial and actuarial risk management. The CTE is a preferred risk measure, due to coherence and a widespread acceptance in actuarial community. In particular we focus on the estimation of the CTE using both parametric and nonparametric approaches. In parametric case the conditional tail expectation and variance are analytically derived for the exponential distribution family and its transformed distributions. For small i.i.d. samples the exact bootstrap (EB) and the influence function are used as nonparametric methods in estimating the bias and the the variance of the empirical CTE. In particular, it is shown that the bias is corrected using the bootstrap for the CTE case. In variance estimation the influence function of the bootstrapped quantile is derived, and can be used to estimate the variance of any bootstrapped L-estimator without simulations, including the VaR and the CTE, via the nonparametric delta method. An industry model are provided by applying theoretical findings on the bias and the variance of the estimated CTE. Finally a new capital allocation method is proposed. Inspired by the allocation of the solvency exchange option by Sherris (2006), this method resembles the CTE allocation in its form and properties, but has its own unique features, such as managerbased decomposition. Through a numerical example the proposed allocation is shown to fail the no undercut axiom, but we argue that this axiom may not be aligned with the economic reality.

Estimating tail risk measures such as Value at Risk (VaR) and Conditional Tail Expectation (CTE) is a vital component in financial and actuarial risk management. The CTE is a preferred risk measure, due to coherence and a widespread acceptance in actuarial community. In particular we focus on the estimation of the CTE using both parametric and nonparametric approaches. In parametric case the conditional tail expectation and variance are analytically derived for the exponential distribution family and its transformed distributions. For small i.i.d. samples the exact bootstrap (EB) and the influence function are used as nonparametric methods in estimating the bias and the the variance of the empirical CTE. In particular, it is shown that the bias is corrected using the bootstrap for the CTE case. In variance estimation the influence function of the bootstrapped quantile is derived, and can be used to estimate the variance of any bootstrapped L-estimator without simulations, including the VaR and the CTE, via the nonparametric delta method. An industry model are provided by applying theoretical findings on the bias and the variance of the estimated CTE. Finally a new capital allocation method is proposed. Inspired by the allocation of the solvency exchange option by Sherris (2006), this method resembles the CTE allocation in its form and properties, but has its own unique features, such as managerbased decomposition. Through a numerical example the proposed allocation is shown to fail the no undercut axiom, but we argue that this axiom may not be aligned with the economic reality.

No description available.

This thesis studies the change process of risk management practices associated with the implementation of Enterprise Risk Management (ERM) and the extent to which it can lead to changes in capital allocation practices. The study develops a theoretical framework to study risk management changes, which draws on structuration theory (Giddens, 1979, 1984) and institutional theory, particularly the institutional framework of Burns and Scapens (2000), as well as new institutional sociology theory. A two-stage empirical study was undertaken in non-life insurance companies. The first stage was a field study of 10 listed non-life insurance companies, while the second stage was a case study of a large non-life insurance company. Multiple data collection methods were used including semi-structured interviews, documentary evidence, annual reports, and publicly available data. Findings show internal, coercive, and normative pressures have mainly driven the ERM adoption decision. The literature supports the impact of coercive, mimetic, and normative pressures on the trend toward ERM in financial industries. However, the study finds that internal pressures related to achieving the company's objectives are either equal to or surpass the external pressures. The study also provides empirical evidence of the changes in risk management practices, which include capital allocation change process associated with ERM implementation. Effective capital allocation requires the incorporation of ERM elements in the whole process of allocating capital. Furthermore, new capital allocation routines and institutions are produced. The study shows that the risk-based capital allocation method is intra- and extra-institutionalised at the company level. The main contribution of this thesis is to identify the nature of ERM adoption and implementation in insurance companies. More specifically, this study provides a better understanding of the institutional forces driving ERM adoption and offers empirical evidence on ERM implementation and the change in risk management practices (routines) within nonlife insurance companies. Moreover, this study avoids the limitations of previous research that was based on surveys, and it does so by conducting an exploratory field study and explanatory case study to address the changes in risk management practices. Practices and process need to be located in their institutional context and hence cannot be reflected in surveys.

none

Companiesissuing insurance cover, in return for insurance premiums, face the payments ofclaims occurring according to a loss distribution. Hence, capital must be heldby the companies so that they can guarantee the fulfilment of the claims ofeach line of insurance. The increased incidence of insurance insolvencymotivates the birth of new legislations as the European Solvency II Directive.Companies have to determine the required amount of capital and the optimalcapital allocation across the different lines of insurance in order to keep therisk of insolvency at an adequate level. The capital allocation problem may betreated in different ways, starting from the insurance company balance sheet.Here, the running process and efficiency of four methods are evaluated andcompared so as to point out the characteristics of each of the methods. TheValue-at-Risk technique is straightforward and can be easily generated for anyloss distribution. The insolvency put option principle is easily implementableand is sensitive to the degree of default. The capital asset pricing model isone of the oldest reliable methods and still provides very helpful intermediateresults. The Myers and Read marginal capital allocation approach encouragesdiversification and introduces the concept of default value. Applications ofthe four methods to some fictive and real insurance companies are provided. Thethesis further analyses the sensitivity of those methods to changes in the economiccontext and comments how insurance companies can anticipate those changes.

In this thesis, we aim at a quantitative understanding of extreme risks. We use heavy-tailed distribution functions to model extreme risks, and use various tools, such as copulas and MRV, to model dependence structures. We focus on modeling as well as quantitatively estimating certain measurements of extreme risks. We start with a credit risk management problem. More specifically, we consider a credit portfolio of multiple obligors subject to possible default. We propose a new structural model for the loss given default, which takes into account the severity of default. Then we study the tail behavior of the loss given default under the assumption that the losses of the obligors jointly follow an MRV structure. This structure provides an ideal framework for modeling both heavy tails and asymptotic dependence. Using HRV, we also accommodate the asymptotically independent case. Multivariate models involving Archimedean copulas, mixtures and linear transforms are revisited. We then derive asymptotic estimates for the Value at Risk and Conditional Tail Expectation of the loss given default and compare them with the traditional empirical estimates. Next, we consider an investor who invests in multiple lines of business and study a capital allocation problem. A randomly weighted sum structure is proposed, which can capture both the heavy-tailedness of losses and the dependence among them, while at the same time separates the magnitudes from dependence. To pursue as much generality as possible, we do not impose any requirement on the dependence structure of the random weights. We first study the tail behavior of the total loss and obtain asymptotic formulas under various sets of conditions. Then we derive asymptotic formulas for capital allocation and further refine them to be explicit for some cases. Finally, we conduct extreme risk analysis for an insurer who makes investments. We consider a discrete-time risk model in which the insurer is allowed to invest a proportion of its wealth in a risky stock and keep the rest in a risk-free bond. Assume that the claim amounts within individual periods follow an autoregressive process with heavy-tailed innovations and that the log-returns of the stock follow another autoregressive process, independent of the former one. We derive an asymptotic formula for the finite-time ruin probability and propose a hybrid method, combining simulation with asymptotics, to compute this ruin probability more efficiently. As an application, we consider a portfolio optimization problem in which we determine the proportion invested in the risky stock that maximizes the expected terminal wealth subject to a constraint on the ruin probability.

After the promulgation of Financial Holding Company Law at the end of year 2001, the law has liberated the limitation of operations across banking, brokerage, and insurance. In order to cope with the future market competition, these institutions formed in total of 14 financial holding companies (FHCs) through self raising, merging, or acquisition. This research is aiming at the 14 FHCs and their subsidiary banks, security brokerages, and insurance companies, through applying financial ratio analysis to measure the synergy of FHCs¡¦ merging and acquisition. The sources of synergy are divided into three dimensions : operations, markets, and finance. A total of eight years of financial data is collected, including two parts: four years of pre-founding of FHCs from 1998 to 2001 and four years after founding the FHCs from 2002 to 2005. In-depth interview is conducted to look for the differences of operation performance and effect of increasing shareholder wealth after the FHCs merging and acquisition. The conclusions of this study are presented as following¡G 1.Market Synergy Dimension: The revenue increased after founding the FHCs shows that the market synergy exists and fits to expectation. FHCs could operate across fields including banking, brokerage, and insurance to provide cross selling chance for finance products. 2.Operational Synergy Dimension: The operating costs and operating costs ratio are increased after founding the FHCs. Because the FHCs do not reach the economy of scale, the unit operation cost is high and the organization of FHCs becomes large and needs more communication, which makes the decision making process inefficient, the management efficiency still needs to be improved. 3.Financial Synergy Dimension: The profit after tax and ROE are decreased after founding the FHCs, which are mainly contributed from inefficient use of financial resources and human resources as a whole group. 4.Synergy was hard to be seen within short term, which needed three to four years to make it possible. After merging or acquisition, FHCs need some time to reduce the conflicts between its subsidiaries and to conduct more efficient resource application to form FHCs synergy. 5.Market Evaluation: The market value of whole FHCs increases which increases the shareholder¡¦s wealth. This research provides the solution for increasing operation costs, including the following three points: 1.Converging the operation process. 2.Increasing economy of scale. 3.Enforcing the management efficiency.

Insurance companies or other financial institutions face financial risks during their various activites. Risk capital is allocated in order to cover these risks. The goal of capital allocation is to redistribute this capital to various constituents of the firm with respect to their riskiness. The thesis deals with risk measures and allocation methods. Special emphasis is put on the notions of coherent risk measures and coherent allocation methods. Conditions of coherence are checked for certain allocation methods. The thesis also deals with practical calculation of allocations to individual risks using allocation methods. 1

In this thesis, we use a wide cross-sectional sample of both privately held and publicly listed European banks over the period 1999 to 2008 to analyse the role played by bank shareholder incentives in the performance of banks and, ultimately, on the capital allocation efficiency of the economy as a whole. In our first essay, we use the entire range of Bankscope and Amadeus Top 250,000 to construct the portfolios of shareholders who hold equity stakes in banks for each year. We show that about 62 per cent of the ultimate largest shareholders of banks are diversified investors, holding on average equity investments from thirteen companies in their portfolio. We exploit this heterogeneity to investigate the impact of their portfolio diversification on bank risk-taking. Our results show that the relationship between portfolio diversification and bank risk-taking is both statistically significant and economically sizeable. Overall, these findings contribute to the literature by providing novel evidence on the characteristics of bank shareholders’ portfolios and by studying an explicit channel through which shareholders’ incentives for risk-taking affect the banks’ risk. In our second essay, we build on our previous evidence to further investigate whether the level of diversification of bank shareholders has any effect on the efficiency of capital allocation in the economy. We aggregate our data at regional level, using information on the address where companies and banks have their headquarters and identify regions based on Eurostat Nomenclature of Territorial Units for Statistics (NUTS) definitions. Our results indicate that capital appears to be allocated more efficiently in regions where banks are controlled by (more) diversified shareholders. In particular, a change in value-added growth increases capital investment by approximately 8 per cent of its mean in regions where banks are controlled by undiversified shareholders, while it increases capital investment by almost 21 per cent in regions where banks are controlled by shareholders with diversified portfolios. These findings contribute to the literature by studying a specific novel channel through which financial development, in the form of bank shareholders’ diversification, affects the real economy. Lastly, in our third essay we combine our detailed micro-level data on ownership with commercial loans market data from Dealscan to evaluate evidence of related lending in Western European banks. In doing so, we are able to explicitly identify related loans and provide original evidence of related lending and preferential lending terms. We show that 14 per cent of banks in our sample engage in related lending, and that firms borrowing from their related banks have lower costs and higher access to credit. Given these findings, we then proceed to analyse the effect of related lending in bank performance. Our tests show that banks participating in related lending experience an increase in average returns of 11 per cent. Results are both statistically significant and economically sizeable. Overall, our findings contribute to the literature by providing evidence in support the information asymmetry view of related lending, suggesting that in countries with strong rule of law related lending may become a relevant mechanism for informational capital accumulation for banks, allowing them to make more profitable lending decisions.