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Jel Classification:C22 

Working Paper
The Anatomy of Out-of-Sample Forecasting Accuracy

We develop metrics based on Shapley values for interpreting time-series forecasting models, including“black-box” models from machine learning. Our metrics are model agnostic, so that they are applicable to any model (linear or nonlinear, parametric or nonparametric). Two of the metrics, iShapley-VI and oShapley-VI, measure the importance of individual predictors in fitted models for explaining the in-sample and out-of-sample predicted target values, respectively. The third metric is the performance-based Shapley value (PBSV), our main methodological contribution. PBSV measures the ...
FRB Atlanta Working Paper , Paper 2022-16

Working Paper
Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book

An extensive empirical literature documents a generally negative correlation, named the ?leverage effect,? between asset returns and changes of volatility. It is more challenging to establish such a return-volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and test for a discontinuous leverage effect ? i.e. a relation between contemporaneous jumps in prices and volatility ? in high-frequency data with market microstructure noise. We present local tests and estimators for price jumps and volatility jumps. Five years of transaction data from ...
Working Papers , Paper 2017-12

Report
Revisiting useful approaches to data-rich macroeconomic forecasting

This paper analyzes the properties of a number of data-rich methods that are widely used in macroeconomic forecasting, in particular principal components (PC) and Bayesian regressions, as well as a lesser-known alternative, partial least squares (PLS) regression. In the latter method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the covariance between a target variable and these common components is maximized. Existing studies have focused on modelling the target variable as a function of a finite set of unobserved common factors that ...
Staff Reports , Paper 327

Working Paper
The Role of the Prior in Estimating VAR Models with Sign Restrictions

Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identified VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Specifically, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of ...
Working Papers , Paper 2030

Report
Bank Capital and Real GDP Growth

We find evidence that bank capital matters for the distribution of future GDP growth but not its central tendency. Growth in the aggregate bank capital ratio compresses the tails of expected GDP growth, a relationship that is particularly robust in reducing the probability of the worst GDP outcomes. These results suggest a role for regulation to mitigate financial crises, with an additional 100 basis points of bank capital reducing the probability of negative GDP growth by 10 percent at the one-year horizon, even controlling for credit growth and financial conditions, and without a ...
Staff Reports , Paper 950

Working Paper
exuber: Recursive Right-Tailed Unit Root Testing with R

This paper introduces the R package exuber for testing and date-stamping periods of mildly explosive dynamics (exuberance) in time series. The package computes test statistics for the supremum ADF test (SADF) of Phillips, Wu and Yu (2011), the generalized SADF (GSADF) of Phillips, Shi and Yu (2015a,b), and the panel GSADF proposed by Pavlidis, Yusupova, Paya, Peel, Martínez-García, Mack and Grossman (2016); generates finite-sample critical values based on Monte Carlo and bootstrap methods; and implements the corresponding date-stamping procedures. The recursive least-squares algorithm that ...
Globalization Institute Working Papers , Paper 383

Working Paper
Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance?but still mean reverting?behavior is commonly found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a fully parametric Bayesian estimator, robust to nonstationarity, is designed for the fractionally integrated, autoregressive, stochastic volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters ...
FRB Atlanta Working Paper , Paper 2015-12

Working Paper
Real-Time Forecasting with a Large, Mixed Frequency, Bayesian VAR

We assess point and density forecasts from a mixed-frequency vector autoregression (VAR) to obtain intra-quarter forecasts of output growth as new information becomes available. The econometric model is specified at the lowest sampling frequency; high frequency observations are treated as different economic series occurring at the low frequency. We impose restrictions on the VAR to account explicitly for the temporal ordering of the data releases. Because this type of data stacking results in a high-dimensional system, we rely on Bayesian shrinkage to mitigate parameter proliferation. The ...
Working Papers , Paper 2015-30

Working Paper
Inference in Long-Horizon Regressions

I develop new results for long-horizon predictive regressions with overlapping observations. I show that rather than using auto-correlation robust standard errors, the standard t-statistic can simply be divided by the square root of the forecasting horizon to correct for the effects of the overlap in the data; this is asymptotically an exact correction and not an approximate result. Further, when the regressors are persistent and endogenous, the long-run OLS estimator suffers from the same problems as does the short-run OLS estimator, and it is shown how similar corrections and test ...
International Finance Discussion Papers , Paper 853

Working Paper
The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility

We propose a novel approach to decompose realized jump measures by type of activity (finite/infinite) and sign, and also provide noise-robust versions of the ABD jump test (Andersen et al., 2007b) and realized semivariance measures. We find that infinite (finite) jumps improve the forecasts at shorter (longer) horizons; but the contribution of signed jumps is limited. As expected, noise-robust measures deliver substantial forecast improvements at higher sampling frequencies, although standard volatility measures at the 300-second frequency generate the smallest MSPEs. Since no single model ...
Working Papers , Paper 1902

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