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

The financial market turmoil in 2007 and 2008 has led to the most severe financial crisis since the Great Depression and threatens to have large repercussions on the real economy The bursting of the housing bubble forced banks to write down several hundred billion dollars in bad loans caused by mortgage delinquencies At the same time, the stock market capitalization of the major banks declined by more than twice as much While the overall mortgage losses are large on an absolute scale, they are still relatively modest compared to the $8 trillion of US stock market wealth lost between October 2007, when the stock market reached an all-time high, and October 2008 This paper attempts to explain the economic mechanisms that caused losses in the mortgage market to amplify into such large dislocations and turmoil in the financial markets, and describes common economic threads that explain the plethora of market declines, liquidity dry-ups, defaults, and bailouts that occurred after the crisis broke in summer 2007 To understand these threads, it is useful to recall some key factors leading up to the housing bubble The US economy was experiencing a low interest rate environment, both because of large capital inflows from abroad, especially from Asian countries, and because the Federal Reserve had adopted a lax interest rate policy Asian countries bought US securities both to peg the exchange rates at an export-friendly level and to hedge against a depreciation of their own currencies against the dollar, a lesson learned from the Southeast Asian crisis of the late 1990s The Federal Reserve Bank feared a deflationary period after the bursting of the Internet bubble and thus did not counteract the buildup of the housing bubble At the same time, the banking system underwent an important transformation The

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Deciphering the Liquidity and Credit Crunch 2007-2008

This paper surveys the most important developments in multivariate ARCH-type modelling. It reviews the model specifications, the inference methods, and the main areas of application of these models in financial econometrics.

Multivariate GARCH Models: A Survey

The Analysis of Time Series: An Introduction, 4th edn. By C. Chatfield. ISBN 0 412 31820 2. Chapman and Hall, London, 1989. 242 pp. £13.50.

The Analysis of Time Series: An Introduction

A rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high-frequency returns coupled with simple modeling procedures. Building on recent theoretical results in Barndorff-Nielsen and Shephard (2004a, 2005) for related bi-power variation measures, the present paper provides a practical and robust framework for non-parametrically measuring the jump component in asset return volatility. In an application to the DM/$ exchange rate, the S&P500 market index, and the 30-year U.S. Treasury bond yield, we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process. Moreover, many jumps appear directly associated with specific macroeconomic news announcements. Separating jump from non-jump movements in a simple but sophisticated volatility forecasting model, we find that almost all of the predictability in daily, weekly, and monthly return volatilities comes from the non-jump component. Our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling, forecasting, and pricing the continuous and jump components of the total return variation process.

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Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility

Policy makers aim to avoid banking crises, and although they can to some extent control domestic conditions, internationally transmitted crises are difficult to tackle. This paper identifies international contagion in banking during the 2007–2009 crisis for 54 economies. We identify three channels of contagion – systematic, idiosyncratic and volatility – and find evidence for these in 45 countries. Banking crises are overwhelmingly associated with the presence of both systematic and idiosyncratic contagion. The results reveal that crisis shocks transmitted from a foreign jurisdiction via idiosyncratic contagion increase the likelihood of a systemic crisis in the domestic banking system by almost 37 percent, whereas increased exposure via systematic contagion does not necessarily destabilize the domestic banking system. Thus while policy makers and regulatory authorities are rightly concerned with the systematic transmission of banking crises, reducing the potential for idiosyncratic contagion can importantly reduce the consequences for the domestic economy.

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Contagion and Banking Crisis - International Evidence for 2007-2009

The global financial crisis (2007-2009) saw sharp declines in stock markets around the world, affecting both advanced and emerging markets. In this paper we test for the existence of equity market contagion originating from the US to advanced and emerging markets during the crisis period. Using a latent factor model, we provide strong evidence of contagion effects in both advanced and emerging equity markets. In the aggregate equity market indices, contagion from the US explains a large portion of the variance in stock returns in both advanced and emerging markets. However, in the financial sector indices we find less evidence of contagion than in the aggregate indices, and this is particularly the case for the advanced markets. The results suggest that contagion effects are not strongly related to high levels of global integration.

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Equity Market Contagion During the Global Financial Crisis: Evidence from the World's Eight Largest Economies

Dungey and Pagan (2000) present a SVAR model of the Australian economy which models macroeconomic outcomes as transitory deviations from a deterministic trend. In this paper we extend that model in two directions. First, we relate it to an emerging literature on Dynamic Stochastic General Equilibrium modelling of small open economies. Second, we allow for both transitory and permanent components in the series and show how this modification has an impact on the design of macroeconomic models.

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Extending a SVAR model of the Australian economy

Tests for contagion in financial returns using correlation analysis are seriously affected by the size of the “noncrisis” and “crisis” periods. Typically the crisis period contains relatively few observations, which seriously affects the power of the test.

Testing for contagion using correlations: some words of caution

https://eprints.utas.edu.au/17213/1/2013-15_Working_Paper_Equity_Market_Contagion_09102013.pdf

Mardi Dungey

Papers

Contagion and Banking Crisis - International Evidence for 2007-2009

Equity Market Contagion During the Global Financial Crisis: Evidence from the World's Eight Largest Economies

Extending a SVAR model of the Australian economy

Testing for contagion using correlations: some words of caution

Equity market contagion during the global financial crisis: Evidence from the world's eight largest economies