In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

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

/pdf/the-black-swan-the-impact-of-the-highly-improbable-578rzpihbf.pdf

The Black Swan: The Impact of the Highly Improbable

r 9HE purpose of this paper is to explore a hypothesis, based on acIcumulating evidence, regarding the character of inventions likely to issue from the research laboratories of the large industrial corporations. Simply put, this hypothesis may be stated as follows: with few exceptions, the large industrial laboratories are likely to be minor sources of major (radically new and commercially or militarily important) inventions; rather they are likely to be major sources of essentially "improvement" inventions. Put more precisely, the hypothesis states that the proportion of all minor inventions originating in the large industrial laboratories is likely to exceed the proportion of all major inventions originating in these laboratories. Note that the stress on the relative importance of these laboratories as sources of improvement inventions is not necessarily a denigration of the economic importance of this contribution. The cumulative effect of these improvement inventions may be, and often has been, of substantial importance over long periods of time for advancing technology, investment opportunities, and economic growth. The stress on improvement inventions as the principal product of the research laboratories of the large industrial corporations is meant simply to emphasize that, whatever the importance of their contributions, most of the latter is not likely to involve radically new inventive activity. I cannot claim originality for this hypothesis. After it suggested itself in the course of my investigations, I discovered that others, some of them in the most unlikely positions,2 had earlier said much the same thing. But, apart from occasional remarks, I can find no discussions attempting to explain or justify it. And because, if reasonably accurate, it has numerous ramifications, I have felt the need to set down an extended analysis of 1 I wish to thank members of the Seminar on Law and Technology, sponsored by the University of Wisconsin Law School under the auspices of the Ford Foundation, for their many helpful comments on this paper. Especially do I wish to thank Professors Jacob Schmookler, Robert Merrill, John Stedman, Harrison White, and John Heath. 2 See particularly the statement quoted below (p. 114) of D)r. Frank Jewett, former president of Bell Laboratories.

The journal of political economy

Measuring Business Cycles

This paper reviews the recent developments in the field of the variance-ratio (VR) tests of the random walk and martingale hypothesis. In particular, we present the conventional individual and multiple VR tests as well as their improved modifications based on power-transformed statistics, rank and sign tests, subsampling and bootstrap methods, among others. We also re-examine the weak-form efficiency for five emerging equity markets in Latin America.

Variance ratio tests of random walk: An overview

Large shocks and the September 11th terrorist attacks on international stock markets

This paper compares the GDP forecasting performance of alternative factor models based on monthly time series for the French economy. These models are based on static and dynamic principal components. The dynamic principal components are obtained using time and frequency domain methods. The forecasting accuracy is evaluated in two ways for GDP growth. First, we question whether it is more appropriate to use aggregate or disaggregate data (with three disaggregating levels) to extract the factors. Second, we focus on the determination of the number of factors obtained either from various criteria or from a fixed choice.

Olivier Darné

Papers

Variance ratio tests of random walk: An overview

Large shocks and the September 11th terrorist attacks on international stock markets

Are Disaggregate Data Useful for Factor Analysis in Forecasting French GDP

Variance-ratio tests of random walk: an overview

Unit roots and infrequent large shocks: new international evidence on output