Following the definition of systemic risk by the Financial Stability Board, the International Monetary Fund and the Bank for International Settlements, this paper proposes a method able to simultaneously address the two dimensions in which this risk materializes: namely the cross-sectional and...

This paper applies non linear methods to analyze and predict the daily open S&P index which is one of the most important stock index in the world .The aim of the analysis is to quantitatively show if the corresponding time series is a deterministic chaotic one and if one or more days ahead...

Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs. Certificates can be modeled using a bond component and a derivative component, typically an options strategy. The pricing of certificates is typically performed...

The Heston model is one of the most used techniques for estimating the fair value and the risk measures associated with investment certificates. Typically, the pricing engine implements a significant number of projections of the underlying until maturity, it calculates the pay-off for all the...

This paper demonstrates the use of Random Regression Forests (RRF) for optimal lag selection. Using an extended sample of 144 data series, of various data types with different frequencies and sample sizes, we perform optimal lag selection using RRF and compare the results with seven...

Managing the trade-off between volume and margin is among the most fundamental challenges for dealers in a securities market. We attempt to overcome this trade-off by incorporating predictions for buyer- and seller-initiated trades when submitting limit orders. Using the Avellaneda-Stoikov model...

This paper presents a short discussion on the lag phenomenon. Lag-length selection is an important issue since all inferences in VAR models depend on the correct model specification. In contemporary econometric modelling, impulse response functions (IRFs) are used to describe the lagged...

This paper proposes a novel method for assessing the predictability of energy market time series, by predicting the entropy of the series. According to conventional entropy-based analysis where the entropy is always ex-post estimated), high entropy values characterize unpredictable series, while...

Using virtual stock markets with artificial interacting software in- vestors, aka agent-based models (ABMs), we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By op- timizing...

In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of Brock and Hommes 1998, we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a...