Early analysis of Bitcoin concluded that it did not meet the economic conditions to be classified as a currency. Since this conclusion, interest in Bitcoin has increased substantially. We investigate whether the introduction of futures trading in Bitcoin is able to resolve the issues that stopped Bitcoin from being considered a currency. Our analysis shows that spot volatility has increased following the appearance of futures contracts, that futures contracts are not an effective hedging instrument, and that price discovery is driven by uninformed investors in the spot market. We therefore argue that the conclusion that Bitcoin is a speculative asset rather than a currency is not altered by the introduction of futures trading.

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We use a sample survey to analyse the capital-budgeting practices of Australian listed companies. We find that NPV, IRR and Payback are the most popular evaluation techniques. Real options techniques have gained a toehold in capital budgeting but are not yet part of the mainstream. Discounting is typically by the weighted average cost of capital, assumed constant for the life of the project, and with the same discount rate across divisions. The WACC is usually based on target weights for debt and equity. The CAPM is widely used, while other asset pricing models are not. The discount rate is reviewed regularly and is updated as conditions change. In most companies, project analysis takes no account of the value of imputation tax credits. Australian corporate practice is generally consistent with the practice of Australian price regulators, except that regulators take into account the value of imputation tax credits when computing the cost of capital.

This paper investigates the financial market effects of recent cybercriminality in cryptocurrency markets. Hacking events are found to increase both the price volatility of the targeted cryptocurrency and broad cross-cryptocurrency correlations. Further, cybercrime events significantly reduce price discovery sourced within the hacked currency relative to other cryptocurrencies. Finally, abnormal returns in the hours prior to the cybercrime event, revert to zero when news is publicly announced.

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The majority of classification models developed have used a pool of financial ratios combined with statistical variable selection techniques to maximize the accuracy of the classifier constructed. Rather than follow this approach, this article seeks to provide an explicit economic basis for the selection of variables for inclusion in bankruptcy models. This search to develop an economic theory of bankruptcy augments the existing bankruptcy prediction literature. Variables which occur in bankruptcy probability expressions derived from the solution of a stochastic optimizing model of firm behaviour are 'proxied' by variables constructed from financial statement data. The random nature of the lifetime of a single firm provides the rationale for the use of duration or hazard-based statistical methods in the validation of the derived bankruptcy probability expressions. Results of the validation exercise confirm that the majority of variables included in the empirical hazard formulation behave in a way that is consistent with the model of the firm. The results highlight the need for developments in the measurement of earnings dispersion.

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