Squeaky Wheel Optimization

We describe a general approach to optimization which we term `Squeaky Wheel' Optimization (SWO). In SWO, a greedy algorithm is used to construct a solution which is then analyzed to find the trouble spots, i.e., those elements, that, if improved, are likely to improve the objective function score. The results of the analysis are used to generate new priorities that determine the order in which the greedy algorithm constructs the next solution. This Construct/Analyze/Prioritize cycle continues until some limit is reached, or an acceptable solution is found. SWO can be viewed as operating on two search spaces: solutions and prioritizations. Successive solutions are only indirectly related, via the re-prioritization that results from analyzing the prior solution. Similarly, successive prioritizations are generated by constructing and analyzing solutions. This `coupled search' has some interesting properties, which we discuss. We report encouraging experimental results on two domains, scheduling problems that arise in fiber-optic cable manufacturing, and graph coloring problems. The fact that these domains are very different supports our claim that SWO is a general technique for optimization

Investor Expectations and Systematic Risk

This study refines the estimation of beta risk within the Capital Asset Pricing Model (CAPM) framework. Evidence is provided that the link between ex-ante risk and ex-post returns is strengthened by more accurately reflecting the formation of investor expectations. An adaptive expectations approach is employed as an estimation technique consistent with the behavioural patterns of investors. Finally, the study compares the capability of risk estimates from both the standard CAPM and adaptive expectation methods to account for future asset returns in Australia.Asset Pricing; Adaptive Expectations; Australia.

Institutional Homogeneity and Choice in Superannuation

In this analysis of institutional investor performance, two questions are addressed. First, what degree of similarity is observed within the market place for retail superannuation funds? Second, what are the implications of homogenous behaviour for member choice policy? The answers from this study are as follows: as an industry, institutional investors destroyed value for superannuation investors for the period 1991 through 2003, under-performing passive portfolio returns by around 60 basis points per annum. Moreover, we find there is a great deal of clustering around this average underperformance. It also appears as though funds have similar risk characteristics which are, on average, defensive. The findings suggest that the products offered by those competing in this market are very similar in nature, hence limiting the potency of choice policy in Australia.Superannuation, underperformance

HACking at Non-linearity: Evidence from Stocks and Bonds

The implicit assumption of linearity is an important element in empirical finance. This study presents a hypothesis testing approach which examines the linear behaviour of the conditional mean between stock and bond returns. Conventional tests detect spurious non-linearity in the conditional mean caused by heteroskedasticity and/or autocorrelation. This study re-states these tests in a heteroskedasticity and autocorrelation consistent (HAC) framework and we find that stock and bond returns are indeed linear-in-the-mean in both univariate and bivariate settings. This study contends that previous research may have detected spurious non-linearity due to size distortions caused by heteroskedasticity and autocorrelation, rather than the presence of genuine non-linearity.linearity, nonlinear, heteroskedasticity-robust tests, autocorrelation-robust tests

Australia’s Retail Superannuation Fund Industry: Structure, Conduct and Performance

In this analysis of Australiaâs superannuation arrangements it is our conjecture that the structure and conduct of the retail superannuation industry in Australia directly impacts performance, resulting in the delivery of costly funds management products which add minimal value for investors over the long term. In this study, we take the perspective of an investor faced with selecting a retail superannuation fund, and explore the extent to which various differentiating characteristics (such as style, rating and cost) provide insights into fund quality which uses a variety of asset pricing models for the period 1991 through 2003. The results of this study, suggest that investors cannot garner superior risk-adjusted returns through reliance on such characteristics.Superannuation funds, Australia; Performance evaluation

Forecasting multivariate volatility in larger dimensions: some practical issues

The importance of covariance modelling has long been recognised in the field of portfolio management and large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating whether simpler moving average based correlation forecasting methods have equal predictive accuracy as their more complex multivariate GARCH counterparts for large dimensional problems. We find simpler forecasting techniques do provide equal (and often superior) predictive accuracy in a minimum variance sense. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set (Hansen, Lunde, and Nason (2003)) are used to compare methods, whilst portfolio weight stability and computational time are also considered.Volatility, multivariate GARCH, portfolio allocation

Stochastic Index Numbers: A Review

The stochastic approach is a new way of viewing index numbers in which uncertainty and statistical ideas play a central role. Rather than just providing a single number for the rate of inflation, the stochastic approach provides the whole probability distribution of inflation. This paper reviews the key elements of the approach and then discusses some previously overlooked links with Fisher’s early work contained in his book The Making of Index Numbers. We then consider some more recent developments, including Diewert’s well-known critique of the stochastic approach, and provide responses to his criticisms. We also provide a review of Theil’s work on the stochastic approach, and present and extend Diewert’s work on this topic within the context of the Country Product Dummy method which measures price levels internationally.

Discretised Non-Linear Filtering for Dynamic Latent Variable Models: with Application to Stochastic Volatility

Filtering techniques are often applied to the estimation of dynamic latent variable models. However, these techniques are often based on a set assumptions which restrict models to be specified in a linear state-space form. Numerical filtering techniques have been propsed that avoid invoking such restrictive assumptions, thus permitting a wider class of latent variable models to be considered. This paper proposes an accurate yet computationally efficient numerical filtering algorithm (based on a discretisation of the state space) for estimating the general class of dynamic latent variable models. The empirical performance of this algorithm is considered within the context of the stochastic volatility model. It is found that the proposed algorithm outperforms a number of accepted procedures in terms of volatility forecastiNon-linear filtering, latent variable models, stochastic volatility, volatilitry forecasting