Thierry Michel

An index of market shocks based on multiscale analysis

Abstract Financial markets are places of sudden and violent price movements. Nevertheless, financial crises lack a universally recognized way of assessing their gravity. This has motivated the measure recently proposed and applied to the exchange rates market by Zumbach et al (2000a Int. J. Theor. Appl. Finance 3 347–55). This measure relies on an analogy with geophysics: the scale of market shocks (SMS) is equivalent to the Richter scale used for earthquakes. More precisely, as a market is the place where economic agents—with different investment horizons—interact, the SMS definition is a weighted aggregation of volatility measures corresponding to these different horizons. In this paper, we implement and apply a similar measure to stock markets, and adapt it to take into account some extra features of these markets. The volatilities are first described, and then used to assess the market instability perceived by a market participant. The evolution of our index of market shocks (IMS)—after rescaling for easy interpretation—is presented using different computational methods. The IMS is then compared with another multiscale measure, the multifractal spectrum width, and we also investigate the links between the IMS and the daily close-to-close returns and volatility. Finally, we describe the recent turbulence on the French market using the IMS as an exploratory tool, concluding that the events of September 2001 proved to be a major shock compared to the Russian and Asian crises. * Paper presented at Applications of Physics in Financial Analysis (APFA) 3, 5–7 December 2001, Museum of London, UK.

Further Insights on the Puzzle of Technical Analysis Profitability

This paper extends current results concerning technical analysis efficiency on the foreign exchange market and attempts to determine whether filtering the raw exchange rate series with some trading rule significantly changes its characteristics. Because of the non-normality of exchange rate series, bootstrap methods are used on the main daily exchange rates since 1974 to show technical analysis performance. The technical analysis strategy tested generates returns whose distribution is significantly different from the basic series. The robustness of the results is tested in and out-of-sample and an explanation of the technical analysis performance based on its filtering properties is suggested.

Misalignments and Aggregated Volatility

This paper considers forecasting regressions of realized volatility on a misalignment measure defined by the temporary deviations from the common trend between the earning-price ratio and current inflation. Results show that this misalignment measure is useful to predict stock market volatility at monthly horizons. The analysis also suggests a threshold effect where only misalignments exceeding a certain level of overvaluation have a positive and significant impact on future volatility.