Search results for " Factor models"

showing 7 items of 7 documents

A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data

2008

The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We suggest the use of the principal component methodology of Stock and Watson [Stock, J.H., Watson, M.W., 2002. Macroeconomic forecasting using diffusion indices. Journal of Business and Economic Statistics, 20, 147–162] for the stochastic volatility factor model discussed by Harvey, Ruiz, and Shephard [Harvey, A.C., Ruiz, E., Shephard, N., 1994. Multivariate Stochastic Variance Models. Review of Economic Studies, 61, 247–264]. We provide theoretical and Monte Carlo results on this method and apply it to S&P data.

Economics and EconometricsMultivariate statisticsPrincipal componentsStochastic volatilityjel:C32jel:C33jel:G12Factor modelPrincipal component analysisEconometricsEconomicsStochastic volatility Factor models Principal componentsStochastic volatilityforecasting; stochastic volatility; large datasetFinanceFactor analysis
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Primary Commodity Prices: Co-movements, Common Factors and Fundamentals

2011

The behavior of commodities is critical for developing and developed countries alike. This paper contributes to the empirical evidence on the co-movement and determinants of commodity prices. Using nonstationary panel methods, we document a statistically significant degree of co-movement due to a common factor. Within a Factor Augmented VAR approach, real interest rate and uncertainty, as postulated by a simple asset pricing model, are both found to be negatively related to this common factor. This evidence is robust to the inclusion of demand and supply shocks, which both positively impact on the co-movement of commodity prices.

Commodity Prices Panel Estimation Factor Models.
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Interest rate co-movements, global factors and the long end of the term spread

2010

Interest Rates Panel Data Factor Models Terms Spread
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Interest rate co-movements, global factors and the long end of the term spread

2012

The disconnect between rising short and low long interest rates has been a distinctive feature of the 2000s. Both research and policy circles have argued that international forces, such as global monetary policy (e.g. Rogoff, 2006); international business cycles (e.g. Borio and Filardo, 2007); or a global savings glut (e.g Bernanke, 2005) may be responsible. In this paper, we employ recent advances in panel data econometrics to document the disconnect and link it explicitly to the existence of a global latent factor that dominates the long end of the term spread for the recent period; the saving glut story emerges as the most likely contender for the global factor.

InflationEconomics and Econometricsmedia_common.quotation_subjectYield (finance)jel:E43Short interest rates Long interest rateInternational economicsjel:C33Short and Long Interest Rates Financial Globalization Panel Data Factor Modelsjel:F36Factor modelsHGjel:F01Term (time)Interest ratejel:G15EconomicsEmerging marketsFinanceFinancial globalizationPanel dataPanel dataFactor analysismedia_commonFinancial globalizationJournal of Banking & Finance
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Co-movement of public spending in the G7

2010

Abstract The size of government in the G7 countries in the last fifty years follows a common pattern (see the left panel of Fig. 1 below): it grows in the first three decades, and then turns flat at the beginning of the nineties, for all countries alike. We highlight this common pattern in a dynamic factor model, and argue that a satisfactory explanation for it would be desirable.

Economics and EconometricsPublic spendingGovernmentPublic economicsMovement (music)Dynamic factorPolitical economyEconomicsDynamics of government size Dynamic factor modelsFinanceEconomics Letters
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Correlation, hierarchies, and networks in financial markets

2010

We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical trees, correlation based trees and networks from a correlation matrix. The hierarchical clustering and other procedures performed on the correlation matrix to detect statistically reliable aspects of the correlation matrix are seen as filtering procedures of the correlation matrix. We also discuss a method to associate a hierarchically nested factor model to a hierarchical tre…

Organizational Behavior and Human Resource ManagementEconomics and EconometricsPhysics - Physics and SocietyCorrelation based networkKullback–Leibler divergenceStability (learning theory)FOS: Physical sciencesKullback–Leibler distancePhysics and Society (physics.soc-ph)computer.software_genreHierarchical clusteringFOS: Economics and businessCorrelationMultivariate analysis Hierarchical clustering Correlation based networks Bootstrap validation Factor models Kullback–Leibler distancePortfolio Management (q-fin.PM)Bootstrap validationQuantitative Finance - Portfolio ManagementMathematicsFactor analysisStatistical Finance (q-fin.ST)Covariance matrixMultivariate analysiQuantitative Finance - Statistical FinanceHierarchical clusteringFactor modelTree (data structure)Physics - Data Analysis Statistics and ProbabilityData miningPortfolio optimizationcomputerData Analysis Statistics and Probability (physics.data-an)
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Primary commodity prices: co-movements, common factors and fundamentals

2011

The behavior of commodities is critical for developing and developed countries alike. This paper contributes to the empirical evidence on the co-movement and determinants of commodity prices. Using nonstationary panel methods, the authors document a statistically significant degree of co-movement due to a common factor. Within a Factor Augmented VAR approach, real interest rate and uncertainty, as postulated by a simple asset pricing model, are both found to be negatively related to this common factor. This evidence is robust to the inclusion of demand and supply shocks, which both positively impact on co-movement of commodity prices.

Economics and EconometricsSpot contractSupply shockFinancial economicsmedia_common.quotation_subjectCommodity prices Panel estimation Factor modelsjel:E30DevelopmentRelative priceCommodity Prices Panel Estimation Factor Modelsjel:F00Interest rateCommodity price indexEconomicsEconometricsCapital asset pricing modelEmerging MarketsMarkets and Market AccessCommoditiesCurrencies and Exchange RatesE-BusinessReal interest rateFutures contractmedia_common
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