This thesis examines the economic consequences of the adoption of international pension accounting standard IAS19 Revised (IAS19R) on pension asset allocation decisions by applying a difference-in-differences with propensity score matching method. The publication of IAS19R in 2011 marked a fundamental change to pension reporting in financial statements. In particular, it had a significant impact on (1) how sponsor firms recognise net pension assets/liabilities on the balance sheet, (2) the calculation and recognition of pension expenses, (3) the presentation of re-measurement (actuarial gains and losses), treatment of which had been heavily debated by academics and practitioners, and (4) disclosure requirements for pension schemes, which had been criticised as “excessive” under IAS19. This research examines the “real effect” of IAS19R adoption on management investment decisions. Using a difference-in-differences with propensity score matching method, the results suggest that, on average, UK sponsor firms affected by IAS19R have reduced their risk taking in pension investments post-IAS19R, both over time and compared with a control sample of unaffected US firms (matched by propensity score matching). The results of sensitivity analysis also suggest that UK sponsor firms tried to avoid the expensive liquidity costs of asset re-allocation by switching their pension plan asset allocations gradually during the period around the publication and adoption of IAS19R. Furthermore, the outcomes of sensitivity tests suggest a positive relationship between equity investment levels, and firms’ leverage and cash flow risk, consistent with the “risk-shifting” hypothesis documented in the previous literature. The thesis also applies a manual textual analysis on the comment letters sent by industrial firms to the IASB to provide their opinions on the IAS19R Exposure Draft. The analysis describes and tabulates the arguments raised by these firms on three main amendment areas of IAS19: recognition, presentation and disclosure. Based on this description, this part aims to motivate the empirical research mentioned previously and shed light on the other potential consequences of IAS19R adoption. These consequences include: the management of funding might be driven by accounting rules rather than management rules; the increasing volatility of balance sheet; de-risking in the pension plan portfolio following the adoption of IAS19R; the diminishing of financial statement “true and fair view” and its usefulness due to the abolition of expected rate of return and excessive requirements on pension disclosure. Furthermore, the study also suggests that the lobbying behaviour of these firms on the standard setting process is consistent with the predictions of Positive Accounting Theory.

This thesis examines the performance of currency-only portfolios with different strategies, in out-of-sample analysis. I first examine a number of passive portfolio strategies into currency market in out-of-sample analysis. The strategies I applied in this chapter include sample-based mean-variance portfolio and its extension, minimum variance portfolio, and equally-weighted risk contribution model. Moreover, I consider GDP portfolio and Trade portfolio as market value portfolio for currency market. With naïve portfolio, there are 12 different asset allocation models. In my out-of-sample analysis, naïve portfolio performs reasonably well among all 12 portfolios, and transaction cost does not seriously affect the results prior to transaction cost analysis. The results are robust across different estimation windows and perspectives of investors from different countries. Next, more portfolio strategies are examined to compare with naïve portfolio in currency market. The first portfolio strategy called ‘optimal constrained portfolio’ in this chapter is derived from the idea of maximising the quadratic utility function. In addition, the timing strategies, a set of simple active portfolio strategies, are also considered. In my out-of-sample analysis with rolling sample approach, naïve portfolio can be beaten by all the strategies discussed in this chapter. In chapter six, the characteristics of currency are exploited to construct a currency only portfolio. Firstly, the pre-sample test proves that the characteristics, both fundamental and financial, are relevant to the portfolio construction. I then examine the performance of parametric portfolio policies. The results show that while fundamental characteristics can bring investor benefits of active portfolio management, financial characteristics cannot. Moreover, I find the relationship between characteristics of currency and weights of optimal portfolio. The overall results show that currencies can be thought of as an asset in their own right to construct optimal portfolios, which have better performance than naïve portfolio, if suitable strategies are used. In addition, ‘lesser’ currencies, indeed, bring significant benefits to the investors.

The industrial gas industry represents a multi-billion dollar global market and provides essential product to manufacturing and service organizations that drive the global economy. In this dissertation, we focus on improving distribution efficiency in the industrial gas industry by addressing the strategic level problem of bulk tank allocation (BTA) while considering the effects of important operational issues. The BTA problem determines the preferred size of bulk tanks to assign to customer sites to minimize recurring gas distribution costs and initial tank installation costs. The BTA problem has a unique structure which includes a resource allocation problem and an underlying vehicle routing problem with split deliveries. In this dissertation, we provide an exact solution approach that solves the BTA problem to optimality and recommends tank allocations, provides a set of delivery routes, and determines delivery amounts to customers on each delivery route within reasonable computational time. The exact solution approach is based on a branch-and-price algorithm that solves problem instances with up to 40 customers in reasonable computational time. Due to the complexity of the problem and the size of industry representative problems, the solution approaches published in the literature rely on heuristics that require a set of potential routes as input. In this research, we investigate and compare three alternative route generation algorithms using data sets from an industry partner. When comparing the routes generation algorithms, a sweep-based heuristic was the preferred heuristic for the data sets evaluated. The existing BTA solution approaches in the literature also assume a single bulk tank can be allocated at each customer site. While this assumption is valid for some customers due to space limitations, other customer sites may have the capability to accommodate multiple tanks. We propose two alternative mathematical models to explore the possibility and potential benefits of allocating multiple tanks at designated customer site that have the capacity to accommodate more than one tank. In a case study with 20 customers, allowing multiple tank allocation yield 13% reduction in total costs. In practice, industrial gas customer demands frequently vary by time period. Thus, it is important to allocate tanks to effectively accommodate time varying demand. Therefore, we develop a bulk tank allocation model for time varying demand (BTATVD) which captures changing demands by period for each customer. Adding this time dimension increases complexity. Therefore, we present three decomposition-based solution approaches. In the first two approaches, the problem is decomposed and a restricted master problem is solved. For the third approach, a two phase periodically restricting heuristic approach is developed. We evaluate the solution approaches using data sets provided by an industrial partner and solve the problem instances with up to 200 customers. The results yield approximately 10% in total savings and 20% in distribution cost savings over a 7 year time horizon. The results of this research provide effective approaches to address a variety of distribution issues faced by the industrial gas industry. The case study results demonstrate the potential improvements for distribution efficiency. / Ph. D.

Thesis (MBA)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: In this study investors were informed of the benefits of diversification and the reduction of systematic risk when property is included in an asset allocation portfolio. It also provided investors with information that will assist them in deciding on asset class allocations, specifically including real estate within a mixed-asset portfolio for both the short and long term. The method applied to answer the research questions started with a detailed literature review in order to gain a thorough understanding of the topic. The second part involved a quantitative approach. The South African Property Index (SAPI), All Share Index (ALSI) and All Bond Index (ALBI) total returns were analysed using descriptive statistics in order to gain knowledge about the return (mean) and risk (standard deviation) performances of the three asset data series. The final part analysed the allocation weights of assets in a mixed portfolio to determine the optimal portfolio weights to either reduce risk or enhance returns. It was found for the period under review that property quarterly returns outperformed equity and bonds. The compound annual growth rate for the period was calculated and it was found that property had a growth rate of 26.1 per cent, equity a growth rate of 17.9 per cent and bonds a growth rate of 10.9 per cent. The risk rate for property was also determined and it was higher than for equity and bonds. The study also found a correlation between bonds and properties, meaning that adding bonds to a real estate portfolio would not give much diversification benefit. Equity to bonds had a negative correlation, showing diversification benefits of adding bonds to an equity portfolio. However, equity to property had a low correlation, meaning that adding property to an equity portfolio would reduce portfolio risk and increase returns. Should an investor not want to be exposed to more risk than simply holding one asset, namely bonds, a portfolio gives substantially higher returns without increasing the risk The study also observed the changes in the asset class returns during certain economic activities. Bonds were found to be the most resistant of the three asset classes and equity the most affected.

<p>This dissertation consists of two essays on household portfolio choice. The first essay is entitled 'Household Portfolio Choice and Retirement'. In this first essay, I empirically examine the portfolio decisions of households as they transition into retirement. I document a novel stylized fact: holding household characteristics constant, singles maintain a relatively constant share of risky assets in their financial portfolios as they transition into retirement. On the other hand, couples decrease their share of risky assets significantly. I analyze this difference in behavior, and show that it is not driven by retirement-related background risks for couples relative to singles. Instead, I show that the heterogeneity within couples can be explained by the within-couple difference in spouses' individual risk aversion levels, and that the results are consistent with a net increase in couples' effective household-level risk aversion after retirement. Further, exploiting heterogeneity in couples' relative retirement dates, I show that husbands' and wives' respective retirement events are associated with very different (opposite-signed) persistent effects on the risky share of couples' portfolios. Moreover, I show that the relative magnitude of these persistent effects is consistent with the importance of each spouse's labor income within the household before retirement. Overall, the evidence is consistent with the outcome of a household bargaining game in which wives demand a smaller share of risky assets than their husbands, with each spouse losing some bargaining power after retiring.</p><p>In the second essay, entitled 'Household Bargaining and Asset Allocation', we empirically examine the effect of intra-household bargaining on household portfolio choice over the life cycle. We find that fluctuations in the distribution of intra-household bargaining power are associated with significant asset allocation shifts between risky and comparatively safer asset classes in households' portfolios. Our results are robust to alternative risky asset definitions, including investments in stocks, real estate, and holdings in private business, as well as to alternative control specifications. We find that the implied effect of intra-household bargaining is economically large in magnitude, with changes in bargaining power driving within-household variation in risky asset shares comparable to changes in labor income and wealth over the life cycle.</p> / Dissertation

The thesis evaluates the benefit of allowing for long memory volatility dynamics in forecasts of the variance-covariance matrix for asset allocation. First, I compare the forecast performance of multivariate long memory conditional volatility models (the long memory EWMA, long memory EWMA-DCC, FIGARCH-DCC and Component GARCH-DCC models) with that of short memory conditional volatility models (the short memory EWMA and GARCH-DCC models), using the asset allocation framework of Engle and Colacito (2006). The research reports two main findings. First, for longer horizon forecasts, long memory volatility models generally produce forecasts of the covariance matrix that are statistically more accurate and informative, and economically more useful than those produced by short memory volatility models. Second, the two parsimonious long memory EWMA models outperform the other models – both short memory and long memory – in a majority of cases across all forecast horizons. These results apply to both low and high dimensional covariance matrices with both low and high correlation assets, and are robust to the choice of estimation window. The research then evaluates the application of multivariate long memory conditional volatility models in dynamic asset allocation, applying the volatility timing procedure of Fleming et al. (2001). The research consistently identifies the economic gains from incorporating long memory volatility dynamics in investment decisions. Investors are willing to pay to switch from the static to the dynamic strategies, and especially from the short memory volatility timing to the long memory volatility timing strategies across both short and long investment horizons. Among the long memory conditional volatility models, the two parsimonious long memory EWMA models, again, generally produce the most superior portfolios. When transaction costs are taken into account, the gains from the daily rebalanced dynamic portfolios deteriorate; however, it is still worth implementing the dynamic strategies at lower rebalancing frequencies. The results are robust to estimation error in expected returns, the choice of risk aversion coefficients and the use of a long-only constraint. To control for estimation error in forecasts of the long memory high dimensional covariance matrix, the research develops a dynamic long memory factor (the Orthogonal Factor Long Memory, or OFLM) model by embedding the univariate long memory EWMA model of Zumbach (2006) into an orthogonal factor structure. The factor-structured OFLM model is evaluated against the six above multivariate conditional volatility models in terms of forecast performance and economic benefits. The results suggest that the OFLM model generally produces impressive forecasts over both short and long forecast horizons. In the volatility timing framework, portfolios constructed with the OFLM model consistently dominate the static and other dynamic volatility timing portfolios in all rebalancing frequencies. Particularly, the outperformance of the factor-structured OFLM model to the fully estimated LM-EWMA model confirms the advantage of the factor structure in reducing estimation error. The factor structure also significantly reduces transaction costs, making the dynamic strategies more feasible in practice. The dynamic factor long memory volatility model also consistently produces more superior portfolios than those produced by the traditional unconditional factor and the dynamic factor short memory volatility models.

The purpose of this thesis is to analyze real estate investments from the vantage point of an institutional multi asset investor perspective, both in terms of the potential benefits real estate can bring as well as the challenges it can pose. The thesis consists of six papers and approaches the research question from three distinct perspectives. The quantitative papers consists of paper 1 and 5. Paper 1 analyses the portfolio characteristics of domestic and international real estate in a mean variance framework over seven investor domiciles. It is found that the optimal allocation to real estate is in the range of 15-25 percent depending on domicile of the investor. The fifth paper expands the analysis in paper one by expanding the data. Furthermore, the analysis is extended to investigate how the structure of the real estate portfolio can support a diversification objectives best. Papers 2, 3 and 4 are the market related papers. Paper 2 compares the suggested allocation weights with the allocation to real estate of institutions in four countries, and finds that the actual allocation is significantly lower and that all investor domiciles have a significant home bias. The third paper discusses changes in the institutional framework of real estate markets and the size of the investment universe. Paper 4 discusses various entry points to the real estate market, and how an investor can utilize these in order to adjust the characteristics of the real estate portfolio. The sixth and last paper is qualitative, and investigates how institutions managing pension capital handle real estate. ​ / <p>QC 20161115</p>

D.Comm. / Copulas provide a useful way to model different types of dependence structures explicitly. Instead of having one correlation number that encapsulates everything known about the dependence between two variables, copulas capture information on the level of dependence as well as whether the two variables exhibit other types of dependence, for example tail dependence. Tail dependence refers to the instance where the variables show higher dependence between their extreme values. A copula is defined as a multivariate distribution function with uniform marginals. A useful class of copulas is known as Archimedean copulas that are constructed from generator functions with very specific properties. The main aim of this thesis is to construct multivariate Archimedean copulas by nesting different bivariate Archimedean copulas using the vine construction approach. A characteristic of the vine construction is that not all combinations of generator functions lead to valid multivariate copulas. Established research is limited in that it presents constraints that lead to valid multivariate copulas that can be used to model positive dependence only. The research in this thesis extends the theory by deriving the necessary constraints to model negative dependence as well. Specifically, it ensures that the multivariate copulas that are constructed from bivariate copulas that capture negative dependence, will be able to capture negative dependence as well. Constraints are successfully derived for trivariate copulas. It is, however, shown that the constraints cannot easily be extended to higher-order copulas. The rules on the types of dependence structures that can be nested are also established. A number of practical applications in the financial markets where copula theory can be utilized to enhance the more established methodologies, are considered. The first application considers trading strategies based on statistical arbitrage where the information in the bivariate copula structure is utilised to identify trading opportunities in the equity market. It is shown that trading costs adversely affect the profits generated. The second application considers the impact of wrong-way risk on counterparty credit exposure. A trivariate copula is used to model the wrong-way risk. The aim of the analysis is to show how the theory developed in this thesis should be applied where negative correlation is present in a trivariate copula structure. Approaches are considered where conditional and unconditional risk driver scenarios are derived by means of the trivariate copula structure. It is argued that by not allowing for wrong-way risk, a financial institution’s credit pricing and regulatory capital calculations may be adversely affected. The final application compares the philosophy behind cointegration and copula asset allocation techniques to test which approach produces the most profitable index-tracking portfolios over time. The copula asset allocation approach performs well over time; however, it is very computationally intensive.

Understanding stock-bond return correlation is a key facet in asset mix, asset allocation and in an investor’s portfolio optimisation strategy. For the last couple of decades, several studies have probed this cardinal relationship. While initial literature tries to understand the fundamental pattern of co-movements, later studies aim to model the economic state variables influencing such time-varying volatility behaviour of stock-bond returns. This study provides a systematic literature review in the field of stock and bond return correlation. The review investigates the existing literature in three key dimensions. First, it examines the effect of macro-economic variables on SB return co-movements. Second, it illustrates the effect of financial integration on the asset correlation dynamics. Third, it reviews the existing models that are employed to estimate the dynamic relationship. In addition to the systematic review, I conduct an empirical analysis of stock-bond return co-movements on U.S. capital market. Both the literature and the empirical investigation substantiate my claims on existing research gaps and respective scope for further research. Evidence shows that existing models impose strong restrictions on past stock-bond return variance dynamics and yield inconclusive results. I, therefore, propose an alternative method, i.e. copula function approach, to model stock and bond time-varying co-movements. Since the previous studies largely focus on developed economies, I suggest an empirically investigation of emerging economies as well. This will allow me to examine the effect of financial integration on the dynamic asset return correlation. Apart from this academic contribution, the study provides an illustration of the economic implications which relate to portfolio optimization and minimal-risk hedge ratio.

The domestic life insurance industry at present is in the steep competition situation. With the fund accumulated rapidly, which investment strategy the life insurance company should take is very important. Law of Insurance 146th puts the restriction on the investment upper limit of the life insurance company. This research will discuss the influence of this investment restriction on life insurance companies¡¦ asset allocation by the samples of Cathay Life Insurance and Shin Kong Life Insurance, and also evaluate the performances of these two life insurance companies. Moreover, under the investment restriction, this research compares the investment rates of return between the optimal portfolios by different portfolio performance measures and the actual portfolios of the two life insurance companies and also shows that which portfolio performance measure is more suitable for life insurance companies to contribute to the decision-making of the life insurance companies about asset allocation. This research utilizes the Efficient Frontier that is inferred from the Markowitz¡¦s portfolio selection model to apply on the Sharpe measure and the IRp measure to achieve the research¡¦s goal mentioned above. The conclusions of this research are as follows: 1. Evaluated by the Sharpe measure, whether there is the investment restriction or not, the difference is small¡FEvaluated by the IRp measure, then there is the higher expected rate of return and better diversification with no investment restriction. 2.The actual rates of return of Cathay Life Insurance and Shin Kong Life Insurance are below the expected rates of returns of their portfolio evaluated be the Sharpe measure and the IRp measure. Moreover, This two measures show that Cathay Life Insurance has the better investment performance then Shin Kong Life Insurance. 3. Under the investment restriction, the differences between the expected rates of return of the optimal portfolio whether by the Sharpe measure or the IRp measure and the investment rates of return of the actual portfolio of these two companies are caused by the influence of the macro economy. 4. If there is no investment restriction, the optimal portfolio of the IRp measure has the better diversification that fits the conservative character of the life insurance companies.