For the passed few years, bond funds have been becoming the most popular investment instrument for all investors. Because the values of those bonds invested by bond funds were not marked to market, the net asset values of bond funds may be greatly distorted. As the interest rates rise, most structured inverse-floating rate bonds invested by bond funds suffer enormous capital losses and greatly impact the bond fund yields. In order to protect the general public, the Financial Supervisory Commission (FSC) of R.O.C. requested all the bond funds to sell out all inverse-floating rate bonds at the fund company shareholders¡¦ expense to correct the distortion by the end of 2005. To understand the effect of these inverse-floating rate bonds on bond fund performance, this paper analyzes the relationship between the fund allocation and fund performance, using grouping analysis and rolling window method, to find out the most important factors affecting fund performance. Bond funds are found to generally allocate their asset in three categories - corporate bonds, government bond repurchases and short term deposits. It was found that how the fund allocates its asset has different effects to bond fund performance in different times. Before September 2005, funds with more corporate bonds performed better, but after September 2005, funds with more government bond repurchases performed better. There is no single asset allocation category always leads to superior fund performance. After further studying various bond funds portfolio rebalancing data, it is found that funds with better performance have smaller and slower portfolio adjustments after the FSC request. This may reflect a fact that the better funds are holding less structured products, such like inverse-floating rate bonds, so that they can maintain a better performance when reducing corporate fund holdings. Bond funds favored by the general public, indicated by having a greater increment in fund asset sizes during the period of April 2005 through August 2006, also show similar properties.

The New Basel Capital Accord (Basel II) provides added emphasis to the development of portfolio credit risk models. An important regulatory change in Basel II is the differentiated treatment in measuring capital requirements for the corporate exposures and retail exposures. Basel II allows agricultural loans to be categorized and treated as the retail exposures. However, portfolio credit risk model for agricultural loans is still in their infancy. Most portfolio credit risk models being used have been developed for corporate exposures, and are not generally applicable to agricultural loan portfolio. The objective of this study is to develop a credit risk model for agricultural loan portfolios. The model developed in this study reflects characteristics of the agricultural sector, loans and borrowers and designed to be consistent with Basel II, including consideration given to forecasting accuracy and model applicability. This study conceptualizes a theory of loan default for farm borrowers. A theoretical model is developed based on the default theory with several assumptions to simplify the model. An annual default model is specified using FDIC state level data over the 1985 to 2003. Five state models covering Iowa, Illinois, Indiana, Kansas, and Nebraska areestimated as a logistic function. Explanatory variables for the model are a three-year moving average of net cash income per acre from crops, net cash income per cwt from livestock, government payments per acre, the unemployment rate, and a trend. Net cash income generated by state reflects the five major commodities: corn, soybeans, wheat, fed cattle, and hogs. A simulation model is developed to generate the stochastic default rates by state over the 2004 to 2007 period, providing the probability of default and the loan loss distribution in a pro forma context that facilitates proactive decision making. The model also generates expected loan loss, VaR, and capital requirements. This study suggests two key conclusions helpful to future credit risk modeling efforts for agricultural loan portfolios: (1) net cash income is a significant leading indicator to default, and (2) the credit risk model should be segmented by commodity and geographical location.

Techn. Univ., Diss.--Berlin, 2006.

Includes bibliographical references (p. 36-38).

Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Operations Research." Includes bibliographical references (p. 93-98).

Zugl.: Sankt Gallen, Univ., Diss., 2010

Zugl.: Köln, Univ., Diss., 2009

Thesis (doctoral)--Universität St. Gallen, 1998.

This dissertation is a contribution to the pricing and portfolio choice theory in incomplete markets. It consists of three self-contained but interlinked essays. In the first essay, we present a utility-based methodology for the valuation and the risk management of mortgage-backed securities subject to totally unpredictable prepayment risk. Incompleteness stems from its embedded pre-payment option which affects the security's cash flow pattern. The prepayment time is constructed via deterministic or stochastic hazard rate. The relevant indifference price consists of a linear term, corresponding to the remaining outstanding balance, and a nonlinear one that incorporates the investor's risk aversion and the interest payments generated by the mortgage contract. The indifference valuation approach is also extended to the case of homogeneous mortgage pools. In the second essay, using forward optimality criteria, we analyze a portfolio choice problem when the local risk tolerance is time-dependent and asymptotically linear in wealth. This class corresponds to a dynamic extension of the traditional (static) risk tolerances associated with the power, logarithmic and exponential utilities. We provide explicit solutions for the optimal investment strategies and wealth processes in an incomplete non-Markovian market with asset prices modelled as Ito processes. The methodology allows for measuring the investment performance in terms of a benchmark and alter-native market views. In the last essay, we extend the forward investment performance approach to study the optimal portfolio choice problem in an incomplete market driven by jump processes. The asset price is modelled by a one-dimensional Lévy-Itô process. We prove the existence of a forward performance process by restricting the local risk tolerance functions to be time-independent and linear in wealth. This yields only three types of performance measurement criteria, namely, exponential, power and logarithmic. The optimal portfolios are constructed via stochastic feedback controls under these criteria. / text

Portfolio design is one of the central topics in finance. The original attempt dates back to the mean-variance model developed for a single period portfolio selection. To have a more realistic approach, multi-period selections were developed in order to manage uncertainties associated with the financial markets. This thesis presents a multi-period financial model proposed on the basis of the network flow structure with many planning advantages. This approach comprises two main steps, dynamic portfolio selection, and dynamic portfolio monitoring and rebalancing throughout the investment horizon. To build a realistic yet practical model that can capture the real characteristics of a portfolio a set of proper constraints is designed including restrictions on the size of the portfolio as well as the number of transactions, and consequently the management costs. The model is solved for two-stage financial planning problems to demonstrate the main advantages as well as characteristics of the presented approach.