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Working Paper
The Anatomy of Out-of-Sample Forecasting Accuracy
Rapach, David E.; Borup, Daniel; Goulet Coulombe, Philippe; Montes Schütte, Erik Christian; Schwenk-Nebbe, Sander (2022-11-07)
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
Central Bank Credibility During COVID-19: Evidence from Japan
Christensen, Jens H. E.; Spiegel, Mark M. (2021-12-21)
Japanese realized and expected inflation has been below the Bank of Japan’s two percent target for many years. We use the exogenous COVID-19 pandemic shock to examine the efficacy of monetary and fiscal policy responses for elevating inflation expectations from an arbitrage-free term structure model of nominal and real yields. We find that monetary and fiscal policy announcements during this period failed to lift inflation expectations, which instead declined notably and are projected to only slowly revert back to levels far below the announced target. Hence, our results illustrate the ...
Working Paper Series , Paper 2021-24

Discussion Paper
What Do Financial Conditions Tell Us about Risks to GDP Growth?
Boyarchenko, Nina; Adams, Patrick A.; http://fedora:8080/fcrepo/rest/objects/authors/; Liang, J. Nellie; Giannone, Domenico; Adrian, Tobias (2020-05-21)
The economic fallout from the COVID-19 pandemic has been sharp. Real U.S. GDP growth in the first quarter of 2020 (advance estimate) was -4.8 percent at an annual rate, the worst since the global financial crisis in 2008. Most forecasters predict much weaker growth in the second quarter, ranging widely from an annual rate of -15 percent to -50 percent as the economy pauses to allow for social distancing. Although growth is expected to begin its rebound in the third quarter absent a second wave of the pandemic, the speed of the recovery is highly uncertain. In this post, we estimate the risks ...
Liberty Street Economics , Paper 20200521

Working Paper
Bayesian Estimation of Time-Changed Default Intensity Models
Gordy, Michael B.; Szerszen, Pawel J. (2015-01-06)
We estimate a reduced-form model of credit risk that incorporates stochastic volatility in default intensity via stochastic time-change. Our Bayesian MCMC estimation method overcomes nonlinearity in the measurement equation and state-dependent volatility in the state equation. We implement on firm-level time-series of CDS spreads, and find strong in-sample evidence of stochastic volatility in this market. Relative to the widely-used CIR model for the default intensity, we find that stochastic time-change offers modest benefit in fitting the cross-section of CDS spreads at each point in time, ...
Finance and Economics Discussion Series , Paper 2015-2

Working Paper
Mining for Oil Forecasts
Calomiris, Charles W.; Cakir Melek, Nida; Mamaysky, Harry (2020-12-23)
In this paper, we study the usefulness of a large number of traditional determinants and novel text-based variables for in-sample and out-of-sample forecasting of oil spot and futures returns, energy company stock returns, oil price volatility, oil production, and oil inventories. After carefully controlling for small-sample biases, we find compelling evidence of in-sample predictability. Our text measures hold their own against traditional variables for oil forecasting. However, none of this translates to out-of-sample predictability until we data mine our set of predictive variables. Our ...
Research Working Paper , Paper RWP 20-20

Working Paper
Nothing is Certain Except Death and Taxes : The Lack of Policy Uncertainty from Expiring \"Temporary\" Taxes
Chang, Andrew C. (2018-06-22)
What is the policy uncertainty surrounding expiring taxes? How uncertain are the approvals of routine extensions of temporary tax policies? To answer these questions, I use event studies to measure cumulative abnormal returns (CARs) for firms that claimed the U.S. research and development (R&D) tax credit from 1996-2015. In 1996, the U.S. R&D tax credit was statutorily temporary but was routinely extended ten times until 2015, when it was made permanent. I take the event dates as both when these ten extensions of the R&D tax credit were introduced into committee and when the extensions were ...
Finance and Economics Discussion Series , Paper 2018-041

Working Paper
Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors
Fisher, Mark; Jensen, Mark J. (2018-02-01)
Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the out-of-sample behavior of the regime parameters. However, the hierarchical priors have been parametric. Their parametric nature leads to global shrinkage that biases the estimates of the parameter coefficient of extraordinary regimes toward the value of the average regime. To overcome this shrinkage, we model ...
FRB Atlanta Working Paper , Paper 2018-2

Report
Simple and reliable way to compute option-based risk-neutral distributions
Malz, Allan M. (2014-06-01)
This paper describes a method for computing risk-neutral density functions based on the option-implied volatility smile. Its aim is to reduce complexity and provide cookbook-style guidance through the estimation process. The technique is robust and avoids violations of option no-arbitrage restrictions that can lead to negative probabilities and other implausible results. I give examples for equities, foreign exchange, and long-term interest rates.
Staff Reports , Paper 677

Working Paper
Term Premium Variability and Monetary Policy
Mau, Ronald; Fuerst, Timothy S. (2016-05-06)
Two traditional explanations for the mean and variability of the term premium are: (i) time-varying risk premia on long bonds, and (ii) segmented markets between long- and short-term bonds. This paper integrates these two approaches into a medium-scale DSGE model. We consider two sources of business cycle variability: shocks to total factor productivity (TFP), and shocks to the marginal efficiency of investment (MEI). The ability of the risk approach to match the first moment of the term premium depends upon the relative importance of these two shocks. If MEI shocks are an important driver of ...
Working Papers (Old Series) , Paper 1611

Working Paper
Are Lemons Sold First? Dynamic Signaling in the Mortgage Market
Gerardi, Kristopher S.; Hartman-Glaser, Barney; Adelino, Manuel (2016-07-01)
A central result in the theory of adverse selection in asset markets is that informed sellers can signal quality and obtain higher prices by delaying trade. This paper provides some of the first evidence of a signaling mechanism through trade delays using the residential mortgage market as a laboratory. We find a strong relationship between mortgage performance and time to sale for privately securitized mortgages. Additionally, deals made up of more seasoned mortgages are sold at lower yields. These effects are strongest in the "Alt-A" segment of the market, where mortgages are often sold ...
FRB Atlanta Working Paper , Paper 2016-8

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