In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

The paper offers an alternative approach to analyzing stock market time series data. The purpose is to develop descriptive, more intuitive, and closer to reality analogs of the behavior of US stock market prices, as indexed by the S&P500 stock price index covering the period October 2003 to...

Topographic finance is the study of surfaces to describe financial systems in multiple dimensions. The problem with finance and economics is to describe accurately what is actually governing price dynamics. The price dynamics are behavioral and do not exhibit a rational maximization of a utility...

This paper develops a method of analyzing average value of a complex-valued function that can be represented as a Fourier series satisfying a few realistic restrictions. This method may be useful when Discrete Fourier transform is highly inefficient, and comparison with Hodrick-Prescott filter...

The classical theory about foreign exchange rate explains its fluctuations as the resulting of a random walk motion. In this paper, such a theory is put into question by performing Brock, Dechert and Scheinkman's (1987) test on the Austrian Schilling - US Dollars exchange rate for the period...

In this paper, we present an evolutionary model of industry dynamics yielding endogenous business cycles with 'Keynesian' features. The model describes an economy composed of firms and consumers/workers. Firms belong to two industries. The first one performs R&D and produces heterogeneous...

Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form (the SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that...

The Scaled Model of Error has gained considerable popularity during the past ten years as a device for computing probabilistic population forecasts of the cohort-component type. In this report we investigate how sensitive probabilistic population forecasts produced by means of the Scaled Model...

In this paper, we present an evolutionary model of industry dynamics yielding endogenous business cycles with 'Keynesian' features. The model describes an economy composed of firms and consumers/workers. Firms belong to two industries. The first one performs R&D and produces heterogeneous...