Mean reversion in the short horizon returns of UK portfolios

This paper will show that short horizon stock returns for UK portfolios are more predictable than suggested by sample autocorrelation co-efficients. Four capitalisation based portfolios are constructed for the period 1976–1991. It is shown that the first order autocorrelation coefficient of monthly returns can explain no more than 10% of the variation in monthly portfolio returns. Monthly autocorrelation coefficients assume that each weekly return of the previous month contains the same amount of information. However, this will not be the case if short horizon returns contain predictable components which dissipate rapidly. In this case, the return of the most recent week would say a lot more about the future monthly portfolio return than other weeks. This suggests that when predicting future monthly portfolio returns more weight should be given to the most recent weeks of the previous month, because, the most recent weekly returns provide the most information about the subsequent months' performance. We construct a model which exploits the mean reverting characteristics of monthly portfolio returns. Using this model we forecast future monthly portfolio returns. When compared to forecasts that utilise the autocorrelation statistic the model which exploits the mean reverting characteristics of monthlyportfolio returns can forecast future returns better than the autocorrelation statistic, both in and out of sample.

Human resource management in emerging markets:an introduction

The shifting of global economic power from mature, established markets to emerging markets (EMs) is a fundamental feature of the new realities in the global political economy. Due to a combination of reasons (such as scarcity of reliable information on management systems of EMs, the growing contribution of human resource management (HRM) towards organisational performance, amongst others), the understanding about the dynamics of management of HRM in the EMs context and the need for proactive efforts by key stakeholders (e.g., multinational and local firms, policy makers and institutions such as trade unions) to develop appropriate HRM practice and policy for EMs has now become more critical than ever. It is more so given the phenomenal significance of the EMs predicted for the future of the global economy. For example, Antoine van Agtmael predicts that: in about 25 years the combined gross national product (GNP) of emergent markets will overtake that of currently mature economies causing a major shift in the centre of gravity of the global economy away from the developed to emerging economies. (van Agtmael 2007: 10–11) Despite the present (late 2013 and early 2014) slowdown in the contribution of EMs towards the global industrial growth (e.g., Das, 2013; Reuters, 2014), EMs are predicted to produce 70 per cent of world GDP growth and a further ten years later, their equity market capitalisation is expected to reach US$ 80 trillion, 1.2 times more than the developed world (see Goldman Sachs, 2010).