A Factor Analysis of Bond Risk Premia

By Sydney C. Ludvigson, Serena Ng. 2009

185 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7f41dabeac68d59977afd192098fc2b397b291a9

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Citations in the corpus

Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, unknown): “This is in contrast to inference on the coeffi cients, where Pagan (1984), Bai and Ng (2009), Ludvigson and Ng (2011), and Gonçalves and Perron(2011) have shown that the generated regressors affect the sampling distribution.”
Principal Components Estimation and Identication of the Factors (2011, methodology): “For example, in diffusion index forecasting analysis of Stock and Watson (2002), the object of interest is the value of the dependent variable.”
Estimating latent asset-pricing factors (2018, background): “(12)Onatski (2012) studies weak factor models and shows the phase transition phenomena for weak factors estimated with PCA.”
Working Paper Series (2019, unknown): “Ludvigson and Ng (2011) updated the Stock-Watson data to 2007:12 and more broadly classified the data into 8 groups: (1) output and income, (2) labor market, (3) housing, (4) consumption, orders and inventories, (5) money and credit, (6) bond and exchange rates, (7) prices, and (8) stock market.”
State-Varying Factor Models of Large Dimensions (2018, methodology): “They have been successfully used in finance, for example, Ross (1976), Chamberlain and Rothschild (1983), and Ludvigson and Ng (2009), and in macro-economics, for example, Stock and Watson (2002) and Jurado, Ludvigson, and Ng (2015).”
Variable Selection in Predictive Regressions (2013, background): “For example, Ng and Perron (2001) show that the correct lag length need not yield a unit root test with the best size and/or power.”
Specification Test for Panel Data Models with Interactive Fixed Effects (2014, unknown): “Ludvigson and Ng (2009) investigate the empirical risk-return relation by using dynamic factor analysis for large datasets to summarize a large amount of economic information by few estimated factors.”
Forecasting US Recessions: The Role of Sentiment (2014, unknown): “We use a standard panel of macroeconomic and nancial series to estimate the common factors similar to Stock and Watson (2002a,b, 2006, 2010) and Ludvigson and Ng (2009, 2010).”
Principal components estimation and identification of static factors (2013, methodology): “For example, in diffusion index forecasting analysis of Stock and Watson (2002), the primary interest is the predicted value of the dependent variable.”