This paper is concerned with modelling time series by single hidden layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...

It is now an accepted fact that the majority of financial markets worldwide are neither normal nor constant, and South Africa is no exception. One idea that can be used to understand such markets and has been gaining popularity recently is that of regimes and regime-switching models. In this...

Risk factors and systematic factor strategies are fast becoming an integral part of the global asset management landscape. In this report, we provide an introduction to, and critique of, the factor investing paradigm in a South African setting. We initially discuss the general factor...

The performance of dynamic trading and investment strategies can be difficult to predict. Although not without its problems, analysis of the historical performance of a strategy can provide valuable insight into its general risk and return properties. Furthermore, historical analysis allows one...

This research addresses a simple but important unanswered question in the factor investing literature: how do the factor exposures of equity factor strategies decay over time? The answer to this question has two important practical consequences. Firstly, understanding how a strategy’s factor...

The proliferation of factor investing strategies in recent years has highlighted the idea that a portfolio can harvest improved risk-adjusted returns through timed exposure to risk factors during times of elevated risk premia. While there is a large body of research on such risk factors and risk...

In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on statistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model...

This paper is concerned with modelling time series by single hidden layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...

The main goal of this paper is to better understand the behavior of credit spreads in the past and the potential risk of unexpected future credit spread changes. One important consideration to note regarding credit spreads is the fact that bond spreads contain a liquidity premium, which...

One of the most important factors to control for the achievements of investment portfolio returns is risk. If we only think that a 100% positive return is needed to recover a portfolio loss of 50%, we can understand why. With the advent of the exponential growth of technology usage in markets,...