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Jel Classification:C40 

Working Paper
Integrating Prediction and Attribution to Classify News

Recent modeling developments have created tradeoffs between attribution-based models, models that rely on causal relationships, and “pure prediction models†such as neural networks. While forecasters have historically favored one technology or the other based on comfort or loyalty to a particular paradigm, in domains with many observations and predictors such as textual analysis, the tradeoffs between attribution and prediction have become too large to ignore. We document these tradeoffs in the context of relabeling 27 million Thomson Reuters news articles published between 1996 ...
Finance and Economics Discussion Series , Paper 2022-042

Working Paper
Default Clustering Risk Premium and its Cross-Market Asset Pricing Implications

This study examines the market-implied premiums for bearing default clustering risk by analyzing credit derivatives contracts on the CDX North American Investment Grade (CDX.NA.IG) portfolio between September 2005 and March 2021. Our approach involves constructing a time series of reference tranche rates exclusively derived by single-name CDS spreads. The default clustering risk premium (DCRP) is captured by comparing the original and reference tranche spreads, with the former exceeding the latter when investors require greater compensation for correlated defaults at the portfolio level. The ...
Finance and Economics Discussion Series , Paper 2023-055

Speech
Remarks at the fifth Data Management Strategies and Technologies Workshop

Remarks at the Fifth Data Management Strategies and Technologies Workshop, Federal Reserve Bank of New York, New York City
Speech , Paper 129

Report
The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis

This paper examines point and density forecasts from the European Central Bank?s Survey of Professional Forecasters. We derive individual uncertainty measures along with individual point- and density-based measures of disagreement. We also explore the relationship between uncertainty and disagreement, as well as their roles in respondents? forecast performance and forecast revisions. We observe substantial heterogeneity in respondents? uncertainty and disagreement. In addition, there is little co-movement between uncertainty and disagreement, and forecast performance shows a more robust ...
Staff Reports , Paper 808

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