The theory of precautionary saving is shown in this paper to be isomorphic to the Arrow-Pratt theory of risk aversion, making possible the application of a large body of knowledge about risk aversion to precautionary saving, and more generally, to the theory of optimal choice under risk In particular, a measure of the strength of precautionary saving motive analogous to the Arrow-Pratt measure of risk aversion is used to establish a number of new propositions about precautionary saving, and to give a new interpretation of the Oreze-Modigliani substitution effect

Precautionary Saving in the Small and in the Large

Features of Financial Returns Modelling Price Volatility Forecasting Standard Deviations The Accuracy of Autocorrelation Estimates Testing the Random Walk Hypothesis Forecasting Trends in Prices Evidence Against the Efficiency of Futures Markets Valuing Options Appendix: A Computer Program for Modelling Financial Time Series.

Modelling Financial Time Series

http://www.lem.sssup.it/Diks_Panchenko_2005.pdf

A new statistic and practical guidelines for nonparametric Granger causality testing

http://www.cs.cas.cz/mp/papers07/causality-IT-final.pdf

Causality detection based on information-theoretic approaches in time series analysis

The key to successful stock market forecasting is achieving best results with minimum required input data. Given stock market model uncertainty, soft computing techniques are viable candidates to capture stock market nonlinear relations returning significant forecasting results with not necessarily prior knowledge of input data statistical distributions. This paper surveys more than 100 related published articles that focus on neural and neuro-fuzzy techniques derived and applied to forecast stock markets. Classifications are made in terms of input data, forecasting methodology, performance evaluation and performance measures used. Through the surveyed papers, it is shown that soft computing techniques are widely accepted to studying and evaluating stock market behavior.

Surveying stock market forecasting techniques - Part II: Soft computing methods

In this paper, we have tested for volatility spillovers between stock returns and exchange rate changes for six countries, namely the US, the UK, Japan, Germany, Canada and France. Our findings can be summarised as follows. (a) Evidence of spillovers from stock returns to exchange rate changes is found for all countries except Germany. These results suggest that the asset approach to exchange rate determination is valid when formulated in terms of the second moments of the exchange rate distribution for these countries. (b) The spillovers from stock returns to exchange rate changes are symmetric in nature. (c) Volatility spillovers from exchange rate changes to stock returns are insignificant for all countries. The non-presence of spillovers from exchange rate changes to stock returns is in line with previous research which has focused on the first moments of the relevant distributions. (d) The correlation coefficient between the EGARCH filtered stock returns and exchange rate changes is negative and significant for all countries, indicating that there is a significant contemporaneous relationship between stock returns and exchange rate changes. (e) Volatility spillovers from stock returns spillovers to exchange rates have increased since the October 1987 crash, perhaps because financial markets have become more closely integrated during this period. Â© Blackwell Publishers Ltd. 2000.

Volatility Spillovers Between Stock Returns and Exchange Rate Changes: International Evidence

The paper employs the multivariate trace statistic [Pcirc]z, the Johansen method, and the recently proposed Bierens nonparametric approach to test for pairwise cointegration between the US and each of the six largest European equity markets, namely those of the UK, Germany, France, Switzerland, Italy, and the Netherlands. The analysis covers the period 03/01/83–29/11/96. The results from these tests are robust and consistent in suggesting that the US market is not pairwise cointegrated with any of the European markets, which is in contrast to previous evidence on the linkages between the US and European markets. This finding implies that there exist potential long-run benefits in risk reduction from diversifying in US stocks and stocks in any of the major European markets.

Linkages between the us and european equity markets : further evidence from cointegration tests

This paper examines the issue of volatility spillovers across the three largest European stock markets, namely London, Frankfurt and Paris. The Exponential Generalized Autoregressive Conditional Heteroscedasticity model is used to capture potential asymmetric effects of innovations on volatility. During the period from 01/01/84 to 07/12/93, reciprocal spillovers are found to exist between London and Paris, and between Paris and Frankfurt, and unidirectional spillovers from London to Frankfurt. In almost all cases, spillovers are asymmetric in the sense that bad news in one market has a greater effect on the volatility of another market than good news. An analysis for the pre-crash (01/01/84 – 15/09/87) and post-crash (15/11/87 – 07/12/93) periods suggests that more spillovers and spillovers with higher intensity exist during the latter period. These findings suggest that these markets became more interdependent during the post-crash period.

Volatility spillovers across equity markets: European evidence

https://commons.ln.edu.hk/cgi/viewcontent.cgi?article=1026&context=capswp

Angelos Kanas

Papers

Volatility Spillovers Between Stock Returns and Exchange Rate Changes: International Evidence

Linkages between the us and european equity markets : further evidence from cointegration tests

Volatility spillovers across equity markets: European evidence

Testing for a nonlinear relationship among fundamentals and exchange rates in the ERM

Comparing linear and nonlinear forecasts for stock returns