Forecasting bank loans loss-given-default

With the advent of the new Basel Capital Accord, banking organizations are invited to estimate credit risk capital requirements using an internal ratings based approach. In order to be compliant with this approach, institutions must estimate the expected loss-given-default, the fraction of the credit exposure that is lost if the borrower defaults. This study evaluates the ability of a parametric fractional response regression and a nonparametric regression tree model to forecast bank loan credit losses. The out-of-sample predictive ability of these models is evaluated at several recovery horizons after the default event. The out-of-time predictive ability is also estimated for a recovery horizon of one year. The performance of the models is benchmarked against recovery estimates given by historical averages. The results suggest that regression trees are an interesting alternative to parametric models in modeling and forecasting loss-given-default.Loss-given-default, Forecasting, Bank loans, Fractional response regression, Regression trees

The structure of international stock market returns

The behavior of international stock market returns in terms of their distributional properties, serial dependence, long-memory and conditional volatility is examined. A factor analysis is employed to identify the underlying dimensions of the returns. The analysis reveals the existence of meaningful factors when these are estimated from the empirical properties of a large set of international equity indices. Furthermore, the factor scores discriminate very well the stock markets according to size and level of development.International stock markets; Serial dependence; Long-memory; Conditional volatility; Factor analysis.

Recurrence quantification analysis of global stock markets

This study investigates the presence of deterministic dependencies in international stock markets using recurrence plots and recurrence quantification analysis (RQA). The results are based on a large set of free float-adjusted market capitalization stock indices, covering a period of 15 years. The statistical tests suggest that the dynamics of stock prices in emerging markets is characterized by higher values of RQA measures when compared to their developed counterparts. The behavior of stock markets during critical financial events, such as the burst of the technology bubble, the Asian currency crisis, and the recent subprime mortgage crisis, is analyzed by performing RQA in sliding windows. It is shown that during these events stock markets exhibit a distinctive behavior that is characterized by temporary decreases in the fraction of recurrence points contained in diagonal and vertical structures.Recurrence plot, Recurrence quantification analysis, Nonlinear dynamics, International stock markets

A class of cubic Rauzy Fractals

In this paper, we study arithmetical and topological properties for a class of Rauzy fractals ${\mathcal R}_a$ given by the polynomial $x^3- ax^2+x-1$ where $a \geq 2$ is an integer. In particular, we prove the number of neighbors of ${\mathcal R}_a$ in the periodic tiling is equal to $8$. We also give explicitly an automaton that generates the boundary of ${\mathcal R}_a$. As a consequence, we prove that ${\mathcal R}_2$ is homeomorphic to a topological disk

Carbon budgets from global to regional scales: current challenges and future perspectives

EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-343

Nonparametric models of financial leverage decisions

This paper investigates the properties of nonparametric decision tree models in the analysis of financial leverage decisions. This approach presents two appealing features: the relationship between leverage ratios and the explanatory variables is not predetermined but is derived according to information provided by the data, and the models respect the bounded and fractional nature of leverage ratios. The analysis shows that tree models suggest relationships between explanatory variables and the relative amount of issued debt that parametric models fail to capture. Furthermore, the significant relationships found by tree models are in most cases in accordance with the effects predicted by the pecking-order theory. The results also show that two-part tree models can accommodate better the distinct effects of explanatory variables on the decision to issue debt and on the amount of debt issued by firms that do resort to debt.Capital structure, Fractional regression, Decision trees, Two-part models

A Multivariate Training Technique with Event Reweighting

An event reweighting technique incorporated in multivariate training algorithm has been developed and tested using the Artificial Neural Networks (ANN) and Boosted Decision Trees (BDT). The event reweighting training are compared to that of the conventional equal event weighting based on the ANN and the BDT performance. The comparison is performed in the context of the physics analysis of the ATLAS experiment at the Large Hadron Collider (LHC), which will explore the fundamental nature of matter and the basic forces that shape our universe. We demonstrate that the event reweighting technique provides an unbiased method of multivariate training for event pattern recognition.Comment: 20 pages, 8 figure