We analyze the usefulness of accounting information on tax loss carryforwards and negative performance to predict earnings and cash flows. We use hand-collected information on tax loss carryforwards and the corresponding deferred taxes from the International Financial Reporting Standards tax...

The scale of distribution network construction is huge and the differences in construction areas are significant. The accuracy of investment strategies would directly affect the effectiveness of upgrading distribution networks. In response to the current subjectivity and lack of precision in the...

This paper compares the ability of the log periodic power law (LPPL) procedure and the supremum augmented Dickey Fuller (supremum ADF) tests to confirm or reject the presence of bubbles in various time series simulations. We develop a time stamping method for the LPPL procedure and derive a more...

In this paper, we propose a general data-driven framework that unifies the valuation and risk measurement of financial derivatives, which is especially useful in markets with thinly-traded derivatives. We first extract the empirical characteristic function from market-observable time series for...

Our aim in this article is to predict local airline market shares in the United States at the company level combining traditional economic indicators (at the national and local levels) with Google search engine requests. We resort both to simple econometric models and to more sophisticated...

We simulate a simplified version of the price process including bubbles and crashes proposed in Kreuser and Sornette (2018). The price process is defined as a geometric random walk combined with jumps modelled by separate, discrete distributions associated with positive (and negative) bubbles....

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...

Dynamic Time Warping (DTW) is a widely used algorithm in speech recognition for measuring similarity between two time series. This non-parametric technique overcomes the problems associated with Pearson's correlation coefficient by allowing a non-linear mapping of one sequence to another...

This paper tackles a core question of portfolio management: How ‘active' is an active portfolio? To answer this question holistically, we generalise the idea of Active Share by keeping the same calculation methodology but substituting in different types of portfolio and benchmark ‘weights'....