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    Essays on financial risk modelling : a thesis presented in fulfilment of the requirements for the degree of Doctor of Philosophy in Finance, School of Economics and Finance, Massey University, Auckland, New Zealand
    (Massey University, 2024-08-08) Nguyen, Thao Thac Thanh
    In today’s highly interconnected financial landscape, the risk of shock spillover is a critical factor contributing to increased systemic risk and impacting the global financial stability. Research on spillover effects has gained significant attention from both academics and practitioners. This thesis aims to contribute to this strand of the literature by conducting three studies that employ a variety of connectedness methods to investigate several underexplored issues within the field of financial risk management. These essays delve further into the evolution of these spillover effects during times of extreme financial uncertainty and aim to identify the key drivers of these spillovers. Essay One investigates the high-frequency spillover of volatility shocks across major oil-dependent foreign exchange markets, considering the impact of the oil market’s volatility regime. Essay Two examines the return shock spillover between European sectoral credit default swap and the natural gas markets. This investigation is conducted across different quantiles of return distributions, with a special focus on understanding the effects of the ongoing Russian-Ukrainian war on this spillover. Essay Three scrutinizes spillover effects of inflation shocks under normal economic conditions and extreme inflationary conditions between the U.S. and emerging markets. The essay further unveils the determinants of the inflation spillovers among the sample markets.
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    Risk management portfolios in New Zealand dairy farming : a dissertation presented in partial fulfilment of the requirements for the degree of PhD in Agribusiness at Massey University, Manawatu, New Zealand
    (Massey University, 2022) Khatami, Koohyar
    New Zealand’s dairy farming sector has changed dramatically over the last two decades. As a result of growth in global demand, dairy farms have become more intensive in production, more capital-intensive and have more debt. These changes increase the vulnerability of the dairy farmers to risks and uncertainties arising from various sources such as input prices, output prices, climatic conditions, and policy changes. In response to these uncertainties, dairy farmers utilise various sets of risk management strategies, henceforth known as portfolios of risk management strategies. Previous studies have created a solid foundation for understanding dairy farms’ responses to risk. In particular, they found that debt management and planning for capital spending are the two most important risk management strategies for New Zealand dairy farmers. However, little is known about what entails debt management and planning for capital spending from farmers’ perspective. Hence, little is known about the diversity of risk management portfolios that New Zealand dairy farmers utilise to manage risks. By extending the definition of portfolio of risk management strategies into the financial risk management space, this study was one of the first studies that provides a synthesis of farm business risk management and farm financial risk management through the perspective of a risk management portfolio. Six portfolios of risk management strategies were identified, each of which has a different mix of risk management strategies and implications for the overall business strategy. The results also showed that a range of farm and farmers characteristics shape NZ dairy farmers’ portfolio of risk management strategies. The range and complexity of financial management strategies identified in this study suggest that traditional financial management literature can benefit from insights gained from the empirical studies. The results provided the industry people such as rural consultants, policy makers, and banking sector much-needed insights into the risk management portfolios used by dairy farmers.
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    Essays in hedge fund performance : a thesis presented in fulfilment of the requirement for the degree of Doctor of Philosophy in Finance at Massey University, Palmerston North, New Zealand
    (Massey University, 2018) Yuen, Mui Kuen
    Over the last decade, hedge funds domiciled in the Asia Pacific has been one of the fastest growing sectors in the global hedge fund universe both in terms of the number of funds and assets under management (AUM). The issue of the sustainability of hedge fund risk-adjusted performance (alpha) has become more relevant given the rapidly increasing inflows in hedge funds in this region. The first part of this thesis investigates the alpha generating of the hedge funds domiciled in the Asia Pacific based on a recent sample compiled from the Eurekahedge, TASS, and Morningstar databases covering both the up and down markets and including the latest financial crisis. I find a positive average alpha in the cross-section for the majority of strategies and a positive and significant alpha for roughly half of all funds. Moreover, the alpha of three-quarter of the strategy indices is positive and significant in the time series. A comparison of the stepwise regression factor model and the widely used factor model proposed by Fung and Hsieh (2004a) reveals that the estimated alpha is robust with respect to the choice of the factor model. In contrast to prior research I find little evidence of a decreasing hedge fund alpha over time except dedicated short bias strategy. The second part of this thesis examines the issue of performance persistence in relation hedge funds domiciled in the Asia Pacific. Evidence of performance persistence indicates active selection is likely to enhance the expected return, particularly relevant for hedge fund investors. The second sub period that includes the global financial crisis of 2007 to 2010 result only weak evidence of performance. Over the full sample period, the results illustrate only weak evidence of persistence. Lastly, the thesis relates the survival of hedge funds domiciled in the Asia Pacific to the hedge fund characteristics. Given certain hedge fund characteristics such as age, size, performance, standard deviation, leverage, management and performance fees, high water mark provisions, redemption frequency, lockup provisions, minimum investment requirements, and whether the fund is listed on an exchange, I question whether attrition of hedge funds can be predicted. The results show larger, better performing funds with lower redemption frequency has a higher likelihood of survival irrespective of the model used.
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    An examination of bank risk measures and their relationship to systemic risk measurement : a dissertation presented in partial fulfilment of the requirements for the degree of Doctoral of Philosophy in Finance at Massey University, Manawatu (Turitea), New Zealand
    (Massey University, 2018) Li, Xiping
    This research explores ways of measuring bank risk, both individual bank risk and systemic risk, with the main focus on z-score. Z-score is a popular indicator of individual bank risk-taking. Despite its popularity among academics, there is a lack of consensus on a standard way to construct a time-varying z-score measure. Meanwhile, in the post-GFC period, increasing attention has been given to macro-prudential policy and its role in mitigating systemic risk. This research discusses major challenges in existing approaches to the construction of time-varying z-score measure. It empirically compares these approaches using quarterly data of New Zealand banks. Both conceptual discussions and empirical analyses support the use of a rolling window in the computation of time-varying z-score, which is consistent with changing bank risk profiles through time. This research is also the first study to propose a risk-weighted z-score measure. This research further proposes a new systemic risk measure based on z-score, which is developed on the concept of Leave-One-Out (LOO) approach. The systemic risk contribution of an individual bank can be captured by the variation of risk-taking of a banking system when excluding the particular bank. The LOO z-score measure can be computed using accounting information only, and is therefore applicable to both listed and unlisted banks. Empirical analysis on the LOO z-score measure in assessing banks’ systemic risk contribution is first applied to the New Zealand and Australian markets, and then extended to an international sample including 17 countries. The LOO z-score measure is proved to be useful for assessing banks’ systemic risk contribution, with a positive rank correlation with Marginal Expected Shortfall (MES) and Delta Conditional Value-at-Risk (ΔCoVaR). The LOO z-score measure provides a new approach to assess systemic risk contribution using accounting data, which can be used as a complement to market-based approaches. This measure is especially useful for systemic risk analyses of banks with limited or even no share market data at all, which is the key advantage. The ability to include both listed and unlisted banks in the evaluation of systemic risk is fundamental in macro-prudential policy frameworks.
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    Extending value at risk to a corporate setting : an application to Fonterra Cooperative : a thesis presented in partial fulfillment of the requirements for the degree of Master of Business Studies in Finance at Massey University
    (Massey University, 2005) Cahan, Jared M
    This paper demonstrates the development and application of a corporate Value-at-Risk model. Using the RiskMetrics Group's CorporateMetrics as a starting point we show how the framework can be modified to meet the specific needs of Fonterra Cooperative, a major New Zealand dairy exporter. We develop a Monte-Carlo simulation model that uses univariate ARIMA and multivariate Vector Error Correction (VECM) forecast models to estimate the Value-at-Risk on Fonterra Group Treasury's interest rate and FX hedge portfolio over a 15-month period.
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    Estimating and evaluating the Archimedean-copula-based models in financial risk management : a dissertation submitted in fulfillment of the requirements for the degree of Doctor of Philosophy in Financial Economics, Massey University, Auckland, New Zealand
    (Massey University, 2008) Xu, Qing
    Copula is used to model multivariate data, as it accounts for the dependence structure and provides a flexible representation of the multivariate distribution. Recently a large number of Archimedean copulas have been proposed to deal with various dependence aspects in financial risk management, which invokes several new questions in some important yet under-researched areas. These questions, therefore, need further investigation. This dissertation comprises three essays and probes into three untouched questions all involving the Archimedean-copula-based models. The first essay studies whether the Archimedean-copula-based portfolio value-at-risk (PVaR) model outperforms the Gaussian-copula-based PVaR model in out-of-sample forecasting. My empirical findings in this essay show that the Archimedean-copula-based PVaR model, especially the Clayton copula-based model, has better forecasting performance than the Gaussian-copula-based PVaR model in most cases m both the in-sample and out-of-sample periods. In addition, the data snooping problem (i.e., model risk) associated with the copula-based PVaR model is also explored. The second essay examines the question of how to evaluate the non-Gaussian multivariate density forecasts. In this essay, I propose a test procedure, by using the likelihood ratio test based on the Kullback-Leibler information criterion, to evaluate the Archimedean-copula-based multivariate density forecasts, and apply the procedure to foreign exchange markets. The test procedure is not only conducive to fully ranking competing sophisticated models with the non-Gaussian-distributed multivariate densities, but also allows for model misspecification in both marginal and copula functions under the null and the alternative hypothesis. The third essay focuses on this question: Will the PVaR estimation be improved if the Archimedean copula model takes into account conditional asymmetric tail dependence and time-varying investors' heterogeneous beliefs? I use the conditional skewed-t distribution (as the marginal function) to represent time-varying investors' heterogeneous beliefs, and employ three two-parameter Archimedean copulas to investigate dynamic asymmetric tail dependence between two of three Asian developed futures markets. My results provide strong evidence that such conditional copula models can improve the PVaR estimation and so a greater amount of diversification benefits can be reaped at a higher confidence level.