Are European Financial Markets Integrated? An Approximate Factor Model Investigation

2004 ◽  
Author(s):  
Anthony Miloudi
Keyword(s):  
Financial Markets ◽  
Factor Model ◽  
Model Investigation ◽  
Approximate Factor Model

THE GENERALIZED DYNAMIC FACTOR MODEL: REPRESENTATION THEORY

2001 ◽  
Vol 17 (6) ◽  
pp. 1113-1141 ◽  
Author(s):  
Mario Forni ◽  
Marco Lippi
Keyword(s):  
Latent Variables ◽  
Factor Model ◽  
Companion Paper ◽  
Dynamic Factor ◽  
Dynamic Factor Model ◽  
Data Sets ◽  
Full Characterization ◽  
Approximate Factor Model ◽  
Firm Basis

This paper, along with the companion paper Forni, Hallin, Lippi, and Reichlin (2000, Review of Economics and Statistics 82, 540–554), introduces a new model—the generalized dynamic factor model—for the empirical analysis of financial and macroeconomic data sets characterized by a large number of observations both cross section and over time. This model provides a generalization of the static approximate factor model of Chamberlain (1983, Econometrica 51, 1181–1304) and Chamberlain and Rothschild (1983, Econometrica 51, 1305–1324) by allowing serial correlation within and across individual processes and of the dynamic factor model of Sargent and Sims (1977, in C.A. Sims (ed.), New Methods in Business Cycle Research, pp. 45–109) and Geweke (1977, in D.J. Aigner & A.S. Goldberger (eds.), Latent Variables in Socio-Economic Models, pp. 365–383) by allowing for nonorthogonal idiosyncratic terms. Whereas the companion paper concentrates on identification and estimation, here we give a full characterization of the generalized dynamic factor model in terms of observable spectral density matrices, thus laying a firm basis for empirical implementation of the model. Moreover, the common factors are obtained as limits of linear combinations of dynamic principal components. Thus the paper reconciles two seemingly unrelated statistical constructions.

A three-factor model investigation of foreign exchange-rate exposure

2010 ◽  
Vol 21 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Stephen P. Huffman ◽  
Stephen D. Makar ◽  
Scott B. Beyer
Keyword(s):  
Exchange Rate ◽  
Foreign Exchange ◽  
Factor Model ◽  
Foreign Exchange Rate ◽  
Model Investigation ◽  
Exchange Rate Exposure ◽  
Three Factor

A random-perturbation-based rank estimator of the number of factors

Biometrika ◽  
2020 ◽  
Author(s):  
Xinbing Kong
Keyword(s):  
Limit Theorem ◽  
Factor Model ◽  
Random Perturbation ◽  
Testing Procedure ◽  
Simulation Studies ◽  
Number Of Factors ◽  
Rank Estimator ◽  
Hypothesis Testing Procedure ◽  
Approximate Factor Model ◽  
New Hypothesis

Summary We introduce a random-perturbation-based rank estimator of the number of factors of a large-dimensional approximate factor model. An expansion of the rank estimator demonstrates that the random perturbation reduces the biases due to the persistence of the factor series and the dependence between the factor and error series. A central limit theorem for the rank estimator with convergence rate higher than root $n$ gives a new hypothesis-testing procedure for both one-sided and two-sided alternatives. Simulation studies verify the performance of the test.

scholarly journals A Test for the Number of Factors in an Approximate Factor Model

1993 ◽  
Vol 48 (4) ◽  
pp. 1263-1291 ◽  
Author(s):  
GREGORY CONNOR ◽  
ROBERT A. KORAJCZYK
Keyword(s):  
Factor Model ◽  
Number Of Factors ◽  
Approximate Factor Model

scholarly journals Identification of Global and Local Shocks in International Financial Markets via General Dynamic Factor Models*

2018 ◽  
Vol 17 (3) ◽  
pp. 462-494 ◽  
Author(s):  
Matteo Barigozzi ◽  
Marc Hallin ◽  
Stefano Soccorsi
Keyword(s):  
Financial Markets ◽  
Sovereign Debt ◽  
Factor Model ◽  
Debt Crisis ◽  
Factor Models ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Heterogeneous Effects ◽  
Global And Local ◽  
General Dynamic

AbstractWe employ a two-stage general dynamic factor model to analyze co-movements between returns and between volatilities of stocks from the U.S., European, and Japanese financial markets. We find two common shocks driving the dynamics of volatilities—one global shock and one United States–European shock—and four local shocks driving returns, but no global one. Co-movements in returns and volatilities increased considerably in the period 2007–2012 associated with the Great Financial Crisis and the European Sovereign Debt Crisis. We interpret this finding as the sign of a surge, during crises, of interdependencies across markets, as opposed to contagion. Finally, we introduce a new method for structural analysis in general dynamic factor models which is applied to the identification of volatility shocks via natural timing assumptions. The global shock has homogeneous dynamic effects within each individual market but more heterogeneous effects across them, and is useful for predicting aggregate realized volatilities.

scholarly journals Risk Management in Viet Nam Tourism Industry Under the Impact of a Two Factor Model During and After the Global Crisis

2019 ◽  
Vol 1 (2) ◽  
pp. p129
Author(s):  
Dinh Tran Ngoc Huy ◽  
Du Quoc Dao
Keyword(s):  
Financial Markets ◽  
Global Financial Crisis ◽  
Factor Model ◽  
Tourism Industry ◽  
Viet Nam ◽  
Tax Rates ◽  
Mean Values ◽  
Policy Suggestions ◽  
The Global Financial Crisis ◽  
The Impact

Over past few years, the global financial crisis shows certain influence on emerging financial markets including Viet nam. Therefore, this study chooses an analytical approach to give some systematic opinions on how much some certain determinants such as income tax and leverage, affect the level of market risk in listed tourism companies.First, it calculates equity and asset beta values in three different scenarios of changing tax rates and changing the level of financial leverage. Second, under 3 different scenarios of changing tax rates (20%, 25% and 28%), we recognized that there is not large disperse in equity beta values, estimated at 0,753 for current leverage situation.Third, by changing tax rates in 3 scenarios (25%, 20% and 28%), we recognized both equity and asset beta mean values have positive relationship with the increasing level of tax rate.Last but not least, this paper covers some ideas and policy suggestions.

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