We examine the dynamic relationships between gold prices, stock price indices of gold mining companies and broad stock market indices. Evidence of cointegration between these variables is found. A vector error-correction model reveals that both gold and large-cap stock prices adjust to disturbances to restore the long-term relationship between the variables. Short-term unidirectional causal relationships are running from large-cap stock prices to gold mining company stock prices and from gold mining company stock prices to gold prices.
PurposeThe purpose of this paper is to evaluate firm financial success across a broad range of performance measures and identify areas of the performance spectrum for which positive results were most difficult to achieve. Simultaneously, the authors identify the firms that most frequently ranked among the top five in terms of composite financial performance.Design/methodology/approachThe dichotomous Rasch model was applied to 13 financial ratios for two industries for the years 2002‐2011. Of these ratios, the authors identify those that are consistent with the requirements of the Rasch model and suitable for ranking composite firm financial performance in each industry during the sample years. Ratio difficulty rankings are obtained, along with firm rankings reflecting managers' ability to achieve broad‐based financial success.FindingsFor the Foods and Aerospace/Defense industries during 2002‐2011, above average performance was most difficult to achieve in the areas of liquidity, financial leverage, and market valuation. Above average profitability and returns on investment seem to have been easier performance targets during this sample period. The authors also list the ticker symbols of firms with managers who consistently achieved top overall financial performance.Research limitations/implicationsThe performance data for each industry and time period have to fit the requirements of the Rasch model. In addition, it must be possible to translate continuous metric readings into binary measures without losing relevant information. Future research might explore the use of more sophisticated Rasch models, measures of non‐financial firm performance dimensions, additional industries and time periods.Practical implicationsThis research offers managers, investors and regulators a fresh perspective on the evaluation of firm financial performance and managerial ability.Social implicationsRasch models are widely used in the human sciences. Application of this methodology to firms offers a more comprehensive view of firm performance and may reveal factors relevant to firm valuation that have previously been ignored, thus possibly impacting the allocation of capital across firms and industries.Originality/valueTo the authors' knowledge, this research represents a first attempt to apply the Rasch approach to an evaluation of managerial ability as reflected in a firm's overall financial performance.
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