In this paper we combine the Symbolic Time Series methods (Daw et. al., 2003) with the nearest neighbour single linkage clustering algorithm (Mantegna, 1999) to describe dynamics and structure of a set of stocks. We start with a partition of the time series state space; we label each piece of the...

During the financial crisis, stock returns became more correlated, increasing the R-square of market models estimated during that time. However, the overall increase in volatility also increased the standard error of these models. As a result, conventional event studies tend to find too many...

In this paper we empirically analyze the phenomena of indebtedness of the main companies belonging to the Spanish hotel industry. In particular, we introduce a method to analyze the structure and dynamics of the largest companies in this sector. The method combines the Pearson correlation...

Enormous quantity of information affects stock returns every day producing their almost random behavior. Nonetheless some information can be recovered by using symbolic methods and constructing Minimal Spanning Trees (MST) and Hierarchical Trees (HT). The introduced method is applied to the main...

Financial Markets can be modeled as complex systems. The Hugh quantity and different information affecting these markets is a remarked characteristic. However some of this information can be recover by constructing a topology of the market. We develop a symbolic method in order to study...

Macroeconomic data is often noisy, contradictory and lagging. These limitations render the data difficult to integrate into a robust quantitative investment strategy that generates excess returns. This paper outlines a new approach to macro investing that removes these inherent limitations in...

In this paper we describe a method to analyze the structure and dynamics of the 30 largest North American companies. The method combines the tools of Symbolic Time Series Analysis with the nearest neighbor single linkage clustering algorithm. Data symbolization allows to obtain a metric distance...

This paper, prepared for the Invited Symposium "Financial Econometrics" at the 7th WCES, Tokyo, August 1995, surveys the subject of Econometrics of option pricing, and more precisely try to offer versatile tools to model the source of the prediction errors in option pricing.