NJ
United States
http://econweb.rutgers.edu/nswanson/
Rutgers University - Department of Economics
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reverse causation, exports, global business conditions, growth, investment
Convex loss function, Empirical processes, Forecast superiority, General loss function, Big data, Shrinkage, Latent Factors
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Market efficiency, expectations, news, data revision process
block bootstrap, density and conditional distribution, forecast accuracy testing, mean square error, parameter estimation error, parametric and nonparametric methods, prediction, rolling and recursive estimation scheme
Block bootstrap, density and conditional distribution, forecast accuracy testing, mean square error, parameter estimation error, parametric and nonparametric methods, prediction, rolling and recursive estimation scheme
Instrumental Variables, k-class Estimator, Local-to-zero Framework, Pathwise Asymptotics, Weak Instruments
prediction, independent component analysis, sparse principal component analysis, bagging, boosting, Bayesian model averaging, ridge regression, least angle regression, elastic net and non-negative garotte
diffusion index, factor, forecast, macroeconometrics, parameter estimation error, proxy
fractional integration, long memory, parameter estimation error, stock returns, long
Heteroskedasticity, instrumental variables, Jackknife estimation, local-to-zero framework, many instruments, pathwise asymptotics, weak instruments
Forecasting, Integrated Volatility, High-Frequency Data, Jumps, Realized Skewness, Cross-Sectional Stock Returns, Signed Jump Variation
Block bootstrap, recursive estimation scheme, reality check, nonlinear causality, parameter estimation error
prediction, bagging, boosting, Bayesian model averaging, ridge regression, least angle regression, elastic net and non-negative garotte
Confluent Hypergeometric Functions, Laplace Approximation, Local-to-zero Asymptotics, Weak Instruments
Block bootstrap, diffusion processes, parameter estimation error, simulated GMM, stochastic volatility
Diffusions, integrated volatility, realized volatility measures, kernels, microstructure noise, conditional confidence intervals, jumps, prediction
Forecasting, Latent common volatility factor, Dimension reduction, Factor-augmented regression, High-frequency data, High-dimensional data
Diffusions, integrated volatility, realized volatility measures, kernels, microstructure noise
Convex loss function, Empirical processes, Forecast superiority, General loss function
realized volatility, jump power variations, downside risk, semivariances, market microstructure, volatility forecasts, jump test
seasonal unit root, periodic autoregression, difference stationary, prediction, simulation
Sticky price, sticky information, predictive density, model selection
Financial econometrics, Integrated volatility, Nonparametric estimator, Continuous time model, Jumps, Co-jumps, Big data, High-frequency data
Sticky price, sticky information, empirical distribution, model selection
diffusion index, dimension reduction methods, emerging markets, factor model, forecasting, variable selection
Itô semi-martingale, realized volatility, jumps, multipower variation, tripower variation, truncated power variation, quarticity, infinite activity jumps
efficiency, robust estimation, empirical Bayes
block bootstrap, recursive estimation scheme, reality check, parameter estimation error
interest rate, multi-factor diffusion process, specification test, out-of-sample forecasts, block bootstrap
nowcasting, forecasting, factor model, MIDAS
diffusion index, factor loading stability, forecast failure, forecast stability, regression coefficients stability
block bootstrap, forecasting, recursive estimation scheme, rolling estimation scheme, model misspecification, nonlinear causality, parameter estimation error, prediction
endogeneity, instrumental variables, jackknife estimation, many moments, Hausman (1978) test
bias, efficiency, generically comprehensive tests, rationality
sticky price, sticky information, empirical distribution, model selection
File name: obes.pdf Size: 230K
File name: cbi039.pdf Size: 220K
diffusion model, jump intensity, jump size density, tricity
diffusion index, factor, forecast, macroeconometrics, monetary policy, parameter estimation error, proxy, federal reserve bank
File name: JTSA284.pdf Size: 140K
heteroskedasticity, instrumental variables, jackknife estimation, many instruments, weak instruments
Block bootstrap, diffusion processes, jumps, nonparametric simulated quasi maximum likelihood, parameter estimation error, recursive estimation, stochastic volatility
High-Frequency Jumps, Jump Spillover, Jump Risks, Excess Returns, ETFs, Great Recession, High-Frequency Data
forecasting, diffusion index, mixed frequency, recursive estimation, Kalman filter
File name: iere.pdf Size: 262K
endogeneity, instrumental variables, jackknife estimation, many moments, existence of moments
efficiency, real-time data set, unbiasedness, non-linearity, structural change
Instrumental Variables, Jackknife, Many Instruments, Heteroskedasticity
Bias, efficiency, generically comprehensive tests, rationality, preliminary, final, real-time data
Real-Time Forecasting, Dynamic Nelson-Siegel Model, Term Structure of Interest Rates, Realtime Dataset, FRED-MD, Real-Time Diffusion Index
multi-factor diffusion process, specification test, out-of-sample forecasts, conditional distribution, model selection, block bootstrap, jump process
Jump Test, Jump Intensity, Sequential Testing Bias, Fixed Time Span, Long Time Span, High-Frequency Data
Forecasting, Diffusion index, Mixed frequency data, Factor model, Recursive estimation, Kalman filter
fractional integration, long memory, parameter estimation error, stock returns, long horizon prediction
