Machine learning has been growing in importance in empirical accounting research. In this opinion piece, I review the unique challenges of going beyond prediction and leveraging these tools into generalizable conceptual insights. Taking as springboard "Machine learning improves accounting...

Spanish Abstract: En el presente trabajo se valora una opción call estándar y una opción call asiática promedio aritmético europea estrike fijo, asumiendo que el movimiento Browniano se ajusta a una distribución logística. Los resultados obtenidos se comparan con los obtenidos cuando se...

Spanish Abstract: En el presente trabajo se valora una opción call estándar y una opción call asiática promedio aritmético europea estrike fijo, usando por primera vez el método numérico estocástico de Taylor 1.5. Los resultados obtenidos se comparan con los métodos numéricos...

Recent advances in machine learning are finding commercial applications across many industries, not least the finance industry. This paper focuses on applications in one of the core functions of finance, the investment process. This includes return forecasting, risk modelling and portfolio...

In an exchange economy with recursive preferences (Epstein and Zin, 1989), we propose a novel nonparametric generalized method of moment (GMM) series approach to estimate unknown policy functions which are recursively specified in a system of nonlinear conditional expectation models...

In this article, we study the algorithmic calculation of present values greeks for callable exotic instruments. The speed of greeks evaluations becomes important with recent initial margin rules, including the ISDA standard model SIMM, requiring sensitivity calculations for non-cleared deals...

In modelling macroeconomic time series, often a monthly indicator of global real economic activity is used. We propose a new indicator, named World steel production, and compare it to other existing indicators, precisely the Kilian's index of global real economic activity and the index of OECD...

To avert the impending global Cyber-Finance Insurance Crisis based upon large-scale commercial reliance upon quantitative models with inherent model risks, tail risks, and systemic risks in current form, this post-doctoral thesis makes the following key contributions: Develops the first known...

This work contributes to the literature over time-changed processes in two directions. Firstly, this is the first thorough study of theoretical properties of Lévy processes, subordinated by a self-excited random clock. The process observed on this new time scale, called clustered Lévy process,...

This paper proposed an optimisation mechanism in the currency overlay portfolios construction process, an area that has not been explored in the literature that tend to focus on pre-determined fixed weights, such as the trading volume of currencies from the survey of the Bank for International...