• Corpus ID: 13215609

No 978 , June 2010 Visual Predictions of Currency Crises : A Comparison of Self-Organizing Maps with Probit Models

@inproceedings{Sarlin2010No9,
  title={No 978 , June 2010 Visual Predictions of Currency Crises : A Comparison of Self-Organizing Maps with Probit Models},
  author={Peter Sarlin},
  year={2010}
}
Throughout the 1990s, four global waves of financial turmoil occurred. The beginning of the 21st century has also suffered from several crisis episodes, including the severe subprime crisis. However, to date, the forecasting results are still disappointing. This paper examines whether new insights can be gained from the application of the SelfOrganizing Map (SOM) – a non-parametric neural network-based visualization tool. In this paper, we present a SOM model for prediction of currency crises… 

SOM-based data analysis of speculative attacks' real effects

Self-Organizing Maps are used to search for meaningful associations between speculative attacks' real effects and 28 variables that characterize the economic, financial, legal, and socio-political structure of the country at the onset of the attack.

Are Emerging Market Currency Crises Predictable? - a Test

This paper analyzes the predictability of emerging market currency crises by comparing the often used probit model to a new method, namely a multi-layer perceptron artificial neural network (ANN)

Predicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach

Recent episodes of financial crisis have revived interest in developing models able to signal their occurrence in timely manner. The literature has developed both parametric and non-parametric

Self-organizing neural networks for the analysis and representation of data: Some financial cases

The present work shows the capabilities of self-organizing feature maps for the analysis and representation of financial data and for aid in financial decision-making.

Predicting Currency Crisis Contagion from East Asia to Russia and Brazil: An Artificial Neural Network Approach

Studies dealing with currency crisis prediction are often vulnerable to data mining and perform poorly when tested on out-of-sample data. This paper suggests an artificial neural network approach to

Predicting currency crises:: The indicators approach and an alternative

A Visualization and Clustering Approach to Analyzing the Early Warning Signals of Currency Crises

Financial crises are not uncommon and their consequences are often severe, thus they constitute an important and interesting field of economics research. In the 1990s alone, four waves of financial

Are Currency Crises Predictable? A Test

This paper evaluates three models for predicting currency crises that were proposed before 1997. The idea is to answer the question: if we had been using these models in late 1996, how well armed

What Caused the Asian Crises: An Early Warning System Approach

type="main" xml:lang="en"> We estimate a simple probit model of the probability of balance-of-payments crises over a panel of developing countries through 1995. We then forecast crisis probabilities

Indicators of Financial Crises Do Work! An Early-Warning System for Six Asian Countries

Indicators of financial crisis generally do not have a good track record. This paper presents an early warning system for six countries in Asia, in which indicators do work.We distinguish three types
...