Assessing Credit with Equity: A CEV Model with Jump to Default

Unlike in structural and reduced-form models, we use equity as a liquid and observable primitive to analytically value corporate bonds and credit default swaps. Restrictive assumptions on the firmâs capital structure are avoided. Default is parsimoniously represented by equity value hitting the zero barrier. Default can be either predictable, according to a CEV process that yields a positive probability of diffusive default and enables the leverage effect, or unpredictable, according to a Poisson-process jump that implies non-zero credit spreads for short maturities. Easy cross-asset hedging is enabled. By means of a carefully specified pricing kernel, we also enable analytical credit-risk management under possibly systematic jump-to-default risk.Equity, Corporate Bonds, Credit Default Swaps, Constant-Elasticity-of-Variance (CEV) Diffusion, Jump to Default

CoCo Bonds - What drives their yields compared to benchmarks and on a standalone basis?

The need for uniform banking regulations was recognized in the mid nineteen thirties by several countries. The global financial crisis beginning in 2007 was the trigger event for the third and as of today last Basel accord. In 2009 the first draft of Basel III was already submitted, featuring stricter capital rules and marking the first incentive to issue CoCo bonds by the regulator. The combination of a young market and the lack of comparable securities leads to a shortage in statistical evaluations, analysing the drivers of the CoCo market. The high importance of such data is explainable by the big market size and the investors need for transparency, to evaluate potential risks when deciding to invest in CoCo bonds. The drivers of CoCo bonds are analysed over the last 3.5 years and compared to benchmark indices. The impact the factors have will be displayed and discussed for all indicators, macro, market and bond-specific indicators subsequently. It was found that equity markets influence CoCo markets in a strong manner. Specifically, equity indices like EURO STOXX 50 and EURO STOXX banks can explain relevant parts of the variance of the yield. Also, non-bank related indices have an even bigger explanatory factor for yields variance in a single regression analysis. On the other hand, the influence of the single equity price of the issuing banks is rather small, underlining reaction on systemic events and market movements. Stating the influence of equity markets on CoCo bonds, an unexplainable detachment of both markets was detected, which took place over the last six months. Separately, a clear relation between distance to trigger and yields was established with a linear and non-linear model

Modelling of and empirical studies on portfolio choice, option pricing, and credit risk

This thesis develops and applies a statistical spanning test for mean-coherent regular risk portfolios. Similarly in spirt to Huberman and Kandel (1987), this test can be implemented by means of a simple semi-parametric instrumental variable regression, where instruments have a direct link with a stochastic discount factor. Applications to different asset classes are studied. The results are compared to the conventional mean-variance approach. The second part of the thesis concerns option pricing under stochastic volatility and credit risk modelling. It is shown that modelling dynamics of the implied prices of volatility risk can improve out-of-sample option pricing performance. Finally, an equity-based structural model of credit risk with a constant elasticity of volatility assumption is discussed. This model might be particularly suitable for analysis of high yield fixed income instruments, where correlation between credit spreads and equity returns is substantial.

Does green improve portfolio optimisation?

Our study uses the GARCH-EVT-copula model to develop out-of-sample forecasts for diverse asset classes, including a green asset. To construct optimal portfolios, we apply four different portfolio allocation techniques: equal weighting, minimum variance, global minimum variance (GMV), and certainty equivalence tangency (CET) criteria. The results demonstrate that the GMV portfolio outperforms other portfolios in risk measures. Further, backtesting evidence shows that the portfolio containing a green asset performs better than the benchmark for short horizons. The results have implications for fund managers and policymakers since green asset provides valuable diversification benefits and further the cause of sustainable development

Macroeconomic Volatility and Sovereign Asset-Liability Management

For most developing countries, the predominant source of sovereign wealth is commodity related export income. However, over-reliance on commodity related income exposes countries to significant terms of trade shocks due to excessive price volatility. The spillovers are pro-cyclical fiscal policies and macroeconomic volatility problems that if not adequately managed, could have catastrophic economic consequences including sovereign bankruptcy. The aim of this study is to explore new ways of solving the problem in an asset-liability management framework for an exporting country like Ghana. Firstly, I develop an unconditional commodity investment strategy in the tactical mean-variance setting for deterministic returns. Secondly, in continuous time, shocks to return moments induce additional hedging demands warranting an extension of the analysis to a dynamic stochastic setting whereby, the optimal commodity investment and fiscal consumption policies are conditioned on the stochastic realisations of commodity prices. Thirdly, I incorporate jumps and stochastic volatility in an incomplete market extension of the conditional model. Finally, I account for partial autocorrelation, significant heteroskedastic disturbances, cointegration and non-linear dependence in the sample data by adopting GARCH-Error Correction and dynamic Copula-GARCH models to enhance the forecasting accuracy of the optimal hedge ratios used for the state-contingent dynamic overlay hedging strategies that guarantee Pareto efficient allocation. The unconditional model increases the Sharpe ratio by a significant margin and noticeably improves the portfolio value-at-risk and maximum drawdown. Meanwhile, the optimal commodities investment decisions are superior in in-sample performance and robust to extreme interest rate changes by up to 10 times the current rate. In the dynamic setting, I show that momentum strategies are outperformed by contrarian policies, fiscal consumption must account for less than 40% of sovereign wealth, while risky investments must not exceed 50% of the residual wealth. Moreover, hedging costs are reduced by as much as 55% while numerically generating state-dependent dynamic futures hedging policies that reveal a predominant portfolio strategy analogous to the unconditional model. The results suggest buying commodity futures contracts when the country’s current exposure in a particular asset is less than the model implied optimal quantity and selling futures contracts when the actual quantity exported exceeds the benchmark.Open Acces

Modelling of and Empirical Studies on Portfolio Choice, Option Pricing, and Credit Risk.

This thesis develops and applies a statistical spanning test for mean-coherent regular risk portfolios. Similarly in spirt to Huberman and Kandel (1987), this test can be implemented by means of a simple semi-parametric instrumental variable regression, where instruments have a direct link with a stochastic discount factor. Applications to different asset classes are studied. The results are compared to the conventional mean-variance approach. The second part of the thesis concerns option pricing under stochastic volatility and credit risk modelling. It is shown that modelling dynamics of the implied prices of volatility risk can improve out-of-sample option pricing performance. Finally, an equity-based structural model of credit risk with a constant elasticity of volatility assumption is discussed. This model might be particularly suitable for analysis of high yield fixed income instruments, where correlation between credit spreads and equity returns is substantial.

Convertible arbitrage: risk, return and performance

This study explores the risk and return characteristics of convertible arbitrage, a dynamic trading strategy employed by hedge funds. To circumvent biases in reported hedge fund data, a simulated convertible bond arbitrage portfolio is constructed. The returns from this portfolio are highly correlated with convertible arbitrage hedge fund indices and the portfolio serves as a benchmark o f fund performance. Default and term structure risk factors are defined and estimated which are highly significant in explaining the returns of the hedge fund indices and the returns of the simulated portfolio, and when specified with a convertible bond arbitrage risk factor in a linear factor model, these factors explain a large proportion of the risk in convertible arbitrage hedge fund indices. The residuals of the hedge fund indices estimated from this model are serially correlated, and a lag of the hedge fund index return is specified correcting fo r the serial correlation and the coefficient o f this term is also interpretable as a measure o f illiq u id ity risk. A linear multi-factor model, incorporating several lags o f the risk factors is specified to estimate individual fund performance. Estimates o f abnormal performance from this model provide evidence that convertible arbitrageurs generate abnormal returns between 2.4% and 4.2% per annum. The convertible arbitrage hedge fund indices and individual hedge fund returns used to evaluate performance generally exhibit negative skewness and excess kurtosis. Residual Augmented Least Squares (RALS), an estimation technique which explicitly incorporates higher moments is used to robustly estimate multi-factor models o f convertible arbitrage hedge fund index returns. Functions o f the hedge fund index residuals are specified as common skewness and kurtosis risk factors in a multifactor analysis of individual fund performance. Results from this analysis provide evidence that failing to specify third and fourth moment risk factors w ill bias upward estimates o f convertible arbitrage individual hedge fund performance by 0.60% per annum. Theoretical non-linearity in the relationship between convertible arbitrage hedge fund index returns and default and term structure risk factor is then modelled using Logistic Smooth Transition Autoregressive (LSTAR) models

Uniform CPA examination questions May 1974 to November 1975

https://egrove.olemiss.edu/aicpa_exam/1140/thumbnail.jp