Completing the Market: Generating Shadow CDS Spreads by Machine Learning
Title | Completing the Market: Generating Shadow CDS Spreads by Machine Learning PDF eBook |
Author | Nan Hu |
Publisher | International Monetary Fund |
Pages | 37 |
Release | 2019-12-27 |
Genre | Business & Economics |
ISBN | 1513524089 |
We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms’ accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient Boosting and Random Forest) strongly outperform other estimators, and Bagging particularly stands out in terms of accuracy. Traditional credit risk models using OLS techniques have the lowest out-of-sample prediction accuracy. The results suggest that the non-linear machine learning methods, especially the ensemble methods, add considerable value to existent credit risk prediction accuracy and enable CDS shadow pricing for companies missing those securities.
Completing the Market: Generating Shadow CDS Spreads by Machine Learning
Title | Completing the Market: Generating Shadow CDS Spreads by Machine Learning PDF eBook |
Author | Nan Hu |
Publisher | International Monetary Fund |
Pages | 37 |
Release | 2019-12-27 |
Genre | Business & Economics |
ISBN | 1513525182 |
We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms’ accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient Boosting and Random Forest) strongly outperform other estimators, and Bagging particularly stands out in terms of accuracy. Traditional credit risk models using OLS techniques have the lowest out-of-sample prediction accuracy. The results suggest that the non-linear machine learning methods, especially the ensemble methods, add considerable value to existent credit risk prediction accuracy and enable CDS shadow pricing for companies missing those securities.
Popular Mechanics
Title | Popular Mechanics PDF eBook |
Author | |
Publisher | |
Pages | 140 |
Release | 2000-01 |
Genre | |
ISBN |
Popular Mechanics inspires, instructs and influences readers to help them master the modern world. Whether it’s practical DIY home-improvement tips, gadgets and digital technology, information on the newest cars or the latest breakthroughs in science -- PM is the ultimate guide to our high-tech lifestyle.
The Advocate
Title | The Advocate PDF eBook |
Author | |
Publisher | |
Pages | 104 |
Release | 2004-08-17 |
Genre | |
ISBN |
The Advocate is a lesbian, gay, bisexual, transgender (LGBT) monthly newsmagazine. Established in 1967, it is the oldest continuing LGBT publication in the United States.
Machine Learning and Causality: The Impact of Financial Crises on Growth
Title | Machine Learning and Causality: The Impact of Financial Crises on Growth PDF eBook |
Author | Mr.Andrew J Tiffin |
Publisher | International Monetary Fund |
Pages | 30 |
Release | 2019-11-01 |
Genre | Computers |
ISBN | 1513518305 |
Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example—assessing the impact of a hypothetical banking crisis on a country’s growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond.
The Fundamental Determinants of Credit Default Risk for European Large Complex Financial Institutions
Title | The Fundamental Determinants of Credit Default Risk for European Large Complex Financial Institutions PDF eBook |
Author | Jiri Podpiera |
Publisher | International Monetary Fund |
Pages | 34 |
Release | 2010-06-01 |
Genre | Business & Economics |
ISBN | 1455200573 |
This paper attempts to identify the fundamental variables that drive the credit default swaps during the initial phase of distress in selected European Large Complex Financial Institutions (LCFIs). It uses yearly data over 2004 - 08 for 29 European LCFIs. The results from a dynamic panel data estimator show that LCFIs’ business models, earnings potential, and economic uncertainty (represented by market expectations about the future risks of a particular LCFI and market views on prospects for economic growth) are among the most significant determinants of credit risk. The findings of the paper are broadly consistent with those of the literature on bank failure, where the determinants of the latter include the entire CAMELS structure - that is, Capital Adequacy, Asset Quality, Management Quality, Earnings Potential, Liquidity, and Sensitivity to Market Risk. By establishing a link between the financial and market fundamentals of LCFIs and their CDS spreads, the paper offers a potential tool for fundamentals-based vulnerability and early warning system for LCFIs.
Global Waves of Debt
Title | Global Waves of Debt PDF eBook |
Author | M. Ayhan Kose |
Publisher | World Bank Publications |
Pages | 403 |
Release | 2021-03-03 |
Genre | Business & Economics |
ISBN | 1464815453 |
The global economy has experienced four waves of rapid debt accumulation over the past 50 years. The first three debt waves ended with financial crises in many emerging market and developing economies. During the current wave, which started in 2010, the increase in debt in these economies has already been larger, faster, and broader-based than in the previous three waves. Current low interest rates mitigate some of the risks associated with high debt. However, emerging market and developing economies are also confronted by weak growth prospects, mounting vulnerabilities, and elevated global risks. A menu of policy options is available to reduce the likelihood that the current debt wave will end in crisis and, if crises do take place, will alleviate their impact.