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A perennial question in international finance is to what extent stock returns are influenced by country-location, as opposed to industry-affiliation, factors. This paper develops a novel methodology to measure these effects, in which portfolios mimicking "pure" country and industry factors are first constructed and their joint dynamics then modeled as regime-switching processes. Estimation using global firm-level data allows us to identify well-defined volatility states over the past thirty years and shows that the contribution of the industry factor becomes systematically more prominent during high global volatility states, while the country factor contribution declines. Using the model's estimates, we find that portfolio diversification possibilities vary considerably across economic states.
Econometrics --- Finance: General --- Investments: Stocks --- Public Finance --- Portfolio Choice --- Investment Decisions --- International Financial Markets --- Pension Funds --- Non-bank Financial Institutions --- Financial Instruments --- Institutional Investors --- Financial Markets and the Macroeconomy --- General Financial Markets: General (includes Measurement and Data) --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- National Government Expenditures and Related Policies: General --- Finance --- Investment & securities --- Econometrics & economic statistics --- Public finance & taxation --- Stocks --- Market capitalization --- Stock markets --- Time series analysis --- Public expenditure review --- Financial institutions --- Financial markets --- Expenditure --- Econometric analysis --- Financial services industry --- Stock exchanges --- Expenditures, Public --- United States
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Regime switching models can match the tendency of financial markets to often change their behavior abruptly and the phenomenon that the new behavior of financial variables often persists for several periods after such a change. While the regimes captured by regime switching models are identified by an econometric procedure, they often correspond to different periods in regulation, policy, and other secular changes. In empirical estimates, the regime switching means, volatilities, autocorrelations, and cross-covariances of asset returns often differ across regimes, which allow regime switching models to capture the stylized behavior of many financial series including fat tails, heteroskedasticity, skewness, and time-varying correlations. In equilibrium models, regimes in fundamental processes, like consumption or dividend growth, strongly affect the dynamic properties of equilibrium asset prices and can induce non-linear risk-return trade-offs. Regime switches also lead to potentially large consequences for investors' optimal portfolio choice.
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Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance.--
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The World Economic Outlook (WEO) is a key source of forecasts of global economic conditions. It is therefore important to review the performance of these forecasts against both actual outcomes and alternative forecasts. This paper conducts a series of statistical tests to evaluate the quality of the WEO forecasts for a very large cross section of countries, with particular emphasis on the recent recession and recovery. It assesses whether forecasts were unbiased and informationally efficient, and characterizes the process whereby WEO forecasts get revised as the time to the point of the forecast draws closer. Finally, the paper assess whether forecasts can be improved by combining WEO forecasts with the Consensus forecasts. The results suggest that the performance of the WEO forecasts is similar to that of the Consensus forecasts. While WEO forecasts for many variables in many countries meet basic quality standards in some, if not all, dimensions, the paper raises a number of concerns with current forecasting performance.
Economic development. --- Economic forecasting -- Evaluation. --- Electronic books. -- local. --- International economic relations. --- Business & Economics --- Economic Theory --- Economic forecasting --- Evaluation. --- Economic policy, Foreign --- Economic relations, Foreign --- Economics, International --- Foreign economic policy --- Foreign economic relations --- Interdependence of nations --- International economic policy --- International economics --- New international economic order --- Economics --- Development, Economic --- Economic growth --- Growth, Economic --- Forecasting --- Economic policy --- International relations --- Economic sanctions --- Economic indicators --- Statics and dynamics (Social sciences) --- Development economics --- Resource curse --- Exports and Imports --- Inflation --- Macroeconomics --- Current Account Adjustment --- Short-term Capital Movements --- Forecasting and Simulation: Models and Applications --- Price Level --- Deflation --- Forecasting and Other Model Applications --- Economic Forecasting --- Current account balance --- Current account --- GDP forecasting --- Balance of payments --- National income --- Prices --- United States
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