Analysis of corporate social responsibility (CSR) performance and financial performance of selected mining companies

The global concern about sustainability has been growing and the mining industry is questioned about its environmental and social performance. Corporate social responsibility (CSR) is an important issue for the extractive industries. The main objective of this study was to investigate the relationship between CSR performance and financial performance of selected mining companies. The study was conducted by identifying and comparing a selection of available CSR performance indicators with financial performance indicators. Based on the result of the study, the relationship between CSR performance and financial performance is unclear for the selected group of companies. The result is mixed and no industry specific realistic way to measure CSR performance uniformly is available. The result as a whole is contradictory and varies at company level as well as based on the selected indicators. The result of this study confirms that the relationship between CSR performance and financial performance is complicated and difficult to determine. As an outcome, evaluation of benefits of CSR in the mining sector could better be analyzed based on different attributes.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.