Are foreign currency markets interdependent? evidence from data mining technologies

This study uses two data mining methodologies: Classification and Regression Trees (C&RT) and Generalized Rule Induction (GRI) to uncover patterns among daily cash closing prices of eight currency markets. Data from 2000 through 2009 is used, with the last year held out to test the robustness of the rules found in the previous nine years. Results from the two methodologies are contrasted. A number of rules which perform well in both the training and testing years are discussed as empirical evidence of interdependence among foreign currency markets. The mechanical rules identified in this paper can usefully supplement other types of financial modeling of foreign currencies.Foreign Currency Markets

Are oil, gold and the euro inter-related? time series and neural network analysis

This paper investigates inter-relationships among the price behavior of oil, gold and the euro using time series and neural network methodologies. Traditionally gold is a leading indicator of future inflation. Both the demand and supply of oil as a key global commodity are impacted by inflationary expectations and such expectations determine current spot prices. Inflation influences both short and long-term interest rates that in turn influence the value of the dollar measured in terms of the euro. Certain hypotheses are formulated in this paper and time series and neural network methodologies are employed to test these hypotheses. We find that the markets for oil, gold and the euro are efficient but have limited inter-relationships among themselves.Oil, Gold, the Euro, Relationships, Time-series Analysis, Neural Network Methodology

Quantitative Easing and the U.S. Stock Market: A Decision Tree Analysis

The Financial Crisis of 2007-09 caused the U.S. economy to experience a relatively long recession from December 2007 to June 2009. Both the U.S. government and the Federal Reserve undertook expansive fiscal and monetary policies to minimize both the severity and length of the recession.  Most notably, the Federal Reserve initiated three rounds of unconventional monetary policies known as Quantitative Easing.  These policies were intended to reduce long-term interest rates when the short term federal funds rates had reached the zero lower bound and could not become negative. It was argued that the lowering of longer-term interest rates would help the stock market and thus the wealth of consumers.  This paper investigates this hypothesis and concludes that quantitative easing has contributed to the observed increases in the stock market’s significant recovery since its crash due to the financial crisi

Are oil, gold and the euro inter-related? time series and neural network analysis

This paper investigates inter-relationships among the price behavior of oil, gold and the euro using time series and neural network methodologies. Traditionally gold is a leading indicator of future inflation. Both the demand and supply of oil as a key global commodity are impacted by inflationary expectations and such expectations determine current spot prices. Inflation influences both short and long-term interest rates that in turn influence the value of the dollar measured in terms of the euro. Certain hypotheses are formulated in this paper and time series and neural network methodologies are employed to test these hypotheses. We find that the markets for oil, gold and the euro are efficient but have limited inter-relationships among themselves

Are foreign currency markets interdependent? evidence from data mining technologies

This study uses two data mining methodologies: Classification and Regression Trees (C&RT) and Generalized Rule Induction (GRI) to uncover patterns among daily cash closing prices of eight currency markets. Data from 2000 through 2009 is used, with the last year held out to test the robustness of the rules found in the previous nine years. Results from the two methodologies are contrasted. A number of rules which perform well in both the training and testing years are discussed as empirical evidence of interdependence among foreign currency markets. The mechanical rules identified in this paper can usefully supplement other types of financial modeling of foreign currencies

Are foreign currency markets interdependent? evidence from data mining technologies

This study uses two data mining methodologies: Classification and Regression Trees (C&RT) and Generalized Rule Induction (GRI) to uncover patterns among daily cash closing prices of eight currency markets. Data from 2000 through 2009 is used, with the last year held out to test the robustness of the rules found in the previous nine years. Results from the two methodologies are contrasted. A number of rules which perform well in both the training and testing years are discussed as empirical evidence of interdependence among foreign currency markets. The mechanical rules identified in this paper can usefully supplement other types of financial modeling of foreign currencies

Are oil, gold and the euro inter-related? time series and neural network analysis

This paper investigates inter-relationships among the price behavior of oil, gold and the euro using time series and neural network methodologies. Traditionally gold is a leading indicator of future inflation. Both the demand and supply of oil as a key global commodity are impacted by inflationary expectations and such expectations determine current spot prices. Inflation influences both short and long-term interest rates that in turn influence the value of the dollar measured in terms of the euro. Certain hypotheses are formulated in this paper and time series and neural network methodologies are employed to test these hypotheses. We find that the markets for oil, gold and the euro are efficient but have limited inter-relationships among themselves

Nonlinear bivariate comovements of asset prices: Theory and tests

Comovements among asset prices have received a lot of attention for several reasons. For example, comovements are important in cross-hedging and cross-speculation; they determine capital allocation both domestically and in international mean–variance portfolios and also, they are useful in investigating the extent of integration among financial markets. In this paper we propose a new methodology for the non–linear modelling of bivariate comovements. Our approach extends the ones presented in the recent literature. In fact, our methodology outlined in three steps, allows the evaluation and the statistical testing of non-linearly driven comovements between two given random variables. Moreover, when such a bivariate dependence relationship is detected, our approach solves for a polynomial approximation. We illustrate our three–steps methodology to the time series of energy related asset prices. Finally, we exploit this dependence relationship and its polynomial approximation to obtain analytical approximations of the Greeks for the European call and put options in terms of an asset whose price comoves with the price of the underlying asset

Multi-fractality in foreign currency markets

(The paper won an award as "best runner-up article". The journal is cited in: ABI/Inform; EconLit

Searching for fractal structure in agricultural futures markets

(Rivista citata nei repertori: ABI/Inform, EBSCO, EconLit