Generalized Factor Models: A Bayesian Approach

There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors.

Understanding Sources of the Change in International Business Cycles

Macroeconomic activity has become less volatile over the past three decades in most G7 economies. Current literature focuses on the characterization of the volatility reduction and explanations for this so called "moderation" in each G7 economy separately. In opposed to individual country analysis and individual variable analysis, this paper focuses on common characteristics of the reduction and common explanations for the moderation in G7 countries. In particular, we study three explanations: structural changes in the economy, changes in common international shocks and changes in domestic shocks. We study these explanations in a unified model structure. To this end, we propose a Bayesian factor structural vector autoregressive model. Using the proposed model, we investigate whether we can find common explanations for all G7 economies when information is pooled from multiple domestic and international sources. Our empirical analysis suggests that volatility reductions can largely be attributed to the decline in the magnitudes of the shocks in most G7 countries while only for the U.K., the U.S. and Italy they can partially be attributed to structural changes in the economy. Analyzing the components of the volatility, we also find that domestic shocks rather than common international shocks can account for a large part of the volatility reduction in most of the G7 countries. Finally, we find that after mid-1980s the structure of the economy changes substantially in five of the G7 countries: Germany, Italy, Japan, the U.K. and the U.S..

The Role of Monetary Policy Uncertainty in Corporate Decisions

The paper emphasizes the role of monetary policy uncertainty in understanding the common dynamics in corporate behavior. Building on common statistical properties of the corporate events, we extract the common pattern (factor) and the common variance (volatility) from five corporate event waves. Using the extracted common factor and the common volatility, this study examines the effect of monetary policy uncertainty on corporate decisions. We hypothesize and explore this explanation of how commonalities between the corporate event waves are formed. The Fed’s actions can result in higher monetary policy uncertainty, which can increase the uncertainty about the outcomes of the major firm activities. The findings from the econometric analyses suggest that monetary policy uncertainty has a significant influence on the dynamics of corporate event waves

A Framework for Minimizing the Tracking Error in an Indexed Portfolio Through Efficient Tax Management

This paper presents a framework for an investor to minimize a loss function that includes the total costs from tracking errors, capital tax losses, and transaction costs. Using this framework, we analyze optimal trading decisions and suggest a trading rule called the “x-percent rule,” which minimizes the loss function. According to this trading rule, once the price of a stock position in the portfolio drops x percent from its purchase price, the portfolio manager sells that position and reinvests in another stock from the same sector. Numerically, the proposed framework is applied to simulated asset returns based on parameters calibrated from historical U.S. stock market returns

Understanding sources of the change in international business cycles

Macroeconomic activity has become less volatile over the past three decades in most G7 economies. Current literature focuses on the characterization of the volatility reduction and explanations for this so called "moderation" in each G7 economy separately. In opposed to individual country analysis and individual variable analysis, this paper focuses on common characteristics of the reduction and common explanations for the moderation in G7 countries. In particular, we study three explanations: structural changes in the economy, changes in common international shocks and changes in domestic shocks. We study these explanations in a unified model structure. To this end, we propose a Bayesian factor structural vector autoregressive model. Using the proposed model, we investigate whether we can find common explanations for all G7 economies when information is pooled from multiple domestic and international sources. Our empirical analysis suggests that volatility reductions can largely be attributed to the decline in the magnitudes of the shocks in most G7 countries while only for the U.K., the U.S. and Italy they can partially be attributed to structural changes in the economy. Analyzing the components of the volatility, we also find that domestic shocks rather than common international shocks can account for a large part of the volatility reduction in most of the G7 countries. Finally, we find that after mid-1980s the structure of the economy changes substantially in five of the G7 countries: Germany, Italy, Japan, the U.K. and the U.S.

Generalized factor models : a bayesian approach

There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors

UNDERSTANDING SOURCES OF THE CHANGE IN INTERNATIONAL BUSINESS CYCLES

Macroeconomic activity has become less volatile over the past three decades in most G7 economies. Current literature focuses on the characterization of the volatility reduction and explanations for this so called “moderation ” in each G7 economy separately. In opposed to individual country analysis and individual variable analysis, this paper focuses on common characteristics of the reduction and common explanations for the moderation in G7 countries. In particular, we study three explanations: structural changes in the economy, changes in common international shocks and changes in domestic shocks. We study these explanations in a unified model structure. To this end, we propose a Bayesian factor structural vector autoregressive model. Using the proposed model, we investigate whether we can find common explanations for all G7 economies when information is pooled from multiple domestic and international sources. Our empirical analysis suggests that volatility reductions can largely be attributed to the decline in the magnitudes of the shocks in most G7 countries while only for the U.K., the U.S. and Italy they can partially be attributed to structural changes in the economy. Analyzing the components of the volatility, we also find that domestic shocks rather than common international shocks can account for a large part of the volatility reduction in most of the G7 countries. Finally, we find that after mid-1980s the structure of th

GENERALIZED FACTOR MODELS: A BAYESIAN APPROACH

There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors

A Bayesian Generalized Factor Model with Comparative Analysis (Genellestirilmis Faktor Modellerinin Bayesyen Yaklasimi ve Karsilastirmali Analizi)

This paper has two major objectives. First, we develop and implement a Bayesian generalized factor model that allows for non-orthogonality of the idiosyncratic factors and the flexibility of cross-sectional and time series dimensions. Second, we evaluate the significance of the orthogonality assumption in factor models, a controversial assumption discussed in the recent literature. To this end, we propose a simple methodology to choose the generalized factor model that best determines the idiosyncratic correlations and provide a comparative analysis between the classical and generalized factor models. The proposed methodology is applied to both the simulated data and the foreign exchange rate data.Factor model, Bayesian time series, MCMC simulation, Model selection.

A New Core Inflation Indicator for Turkey (Turkiye Ekonomisi Icin Yeni Bir Cekirdek Enflasyon Gostergesi)

This paper has two main objectives. The first objective is to propose a new indicator of core inflation, which is obtained by cleaning month on month relative price fluctuations from overall price changes and idiosyncratic dynamics. We use a factor model with the subcomponents of CPI inflation to extract this new core indicator. The second objective is to evaluate the performance of this new indicator and two widely used core indicators for Turkey, H and I, by the help of four criteria designed to assess the informativeness and the predictive power of these series for the analysis of overall inflation. The results suggest that the new indicator, Fcore, is a good measure of core inflation and a useful tool for policy analysis. Moreover, the core indicator H is a more informative measure of core inflation compared to core indicator I.Inflation, Core inflation, Factor model, Bayesian time series