Predicting Fiscal Crises A Machine Learning Approach
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Predicting Fiscal Crises A Machine Learning Approach
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Author : Klaus-Peter Hellwig
language : en
Publisher: International Monetary Fund
Release Date : 2021-05-27
Predicting Fiscal Crises A Machine Learning Approach written by Klaus-Peter Hellwig and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-27 with Business & Economics categories.
In this paper I assess the ability of econometric and machine learning techniques to predict fiscal crises out of sample. I show that the econometric approaches used in many policy applications cannot outperform a simple heuristic rule of thumb. Machine learning techniques (elastic net, random forest, gradient boosted trees) deliver significant improvements in accuracy. Performance of machine learning techniques improves further, particularly for developing countries, when I expand the set of potential predictors and make use of algorithmic selection techniques instead of relying on a small set of variables deemed important by the literature. There is considerable agreement across learning algorithms in the set of selected predictors: Results confirm the importance of external sector stock and flow variables found in the literature but also point to demographics and the quality of governance as important predictors of fiscal crises. Fiscal variables appear to have less predictive value, and public debt matters only to the extent that it is owed to external creditors.
Machine Learning And Causality The Impact Of Financial Crises On Growth
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Author : Mr.Andrew J Tiffin
language : en
Publisher: International Monetary Fund
Release Date : 2019-11-01
Machine Learning And Causality The Impact Of Financial Crises On Growth written by Mr.Andrew J Tiffin and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-01 with Computers categories.
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.
Predicting Imf Supported Programs A Machine Learning Approach
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Author : Tsendsuren Batsuuri
language : en
Publisher: International Monetary Fund
Release Date : 2024-03-08
Predicting Imf Supported Programs A Machine Learning Approach written by Tsendsuren Batsuuri and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-08 with Business & Economics categories.
This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF-supported programs, and evaluates model robustness with regard to different feature sets and time periods. ML models consistently outperform traditional methods in out-of-sample prediction of new IMF-supported arrangements with key predictors that align well with the literature and show consensus across different algorithms. The analysis underscores the importance of incorporating a variety of external, fiscal, real, and financial features as well as institutional factors like membership in regional financing arrangements. The findings also highlight the varying influence of data processing choices such as feature selection, sampling techniques, and missing data imputation on the performance of different ML models and therefore indicate the usefulness of a flexible, algorithm-tailored approach. Additionally, the results reveal that models that are most effective in near and medium-term predictions may tend to underperform over the long term, thus illustrating the need for regular updates or more stable – albeit potentially near-term suboptimal – models when frequent updates are impractical.
How To Assess Country Risk
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Author : International Monetary
language : en
Publisher: International Monetary Fund
Release Date : 2021-05-07
How To Assess Country Risk written by International Monetary and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-07 with Business & Economics categories.
The IMF’s Vulnerability Exercise (VE) is a cross-country exercise that identifies country-specific near-term macroeconomic risks. As a key element of the Fund’s broader risk architecture, the VE is a bottom-up, multi-sectoral approach to risk assessments for all IMF member countries. The VE modeling toolkit is regularly updated in response to global economic developments and the latest modeling innovations. The new generation of VE models presented here leverages machine-learning algorithms. The models can better capture interactions between different parts of the economy and non-linear relationships that are not well measured in ”normal times.” The performance of machine-learning-based models is evaluated against more conventional models in a horse-race format. The paper also presents direct, transparent methods for communicating model results.
Data Science For Economics And Finance
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Author : Sergio Consoli
language : en
Publisher: Springer Nature
Release Date : 2021-06-09
Data Science For Economics And Finance written by Sergio Consoli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-09 with Computers categories.
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Fiscal Crises The Role Of The Public Debt Investor Base And Domestic Financial Markets As Aggravating And Mitigating Factors
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Author : Ms. Rina Bhattacharya
language : en
Publisher: International Monetary Fund
Release Date : 2022-12-02
Fiscal Crises The Role Of The Public Debt Investor Base And Domestic Financial Markets As Aggravating And Mitigating Factors written by Ms. Rina Bhattacharya and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-02 with Business & Economics categories.
The paper evaluates the key drivers of fiscal crises in a sample of countries from all three income groups—advanced, emerging, and low-income countries, using fiscal crisis data recently developed by the IMF’s Fiscal Affairs Department. The empirical study focuses on three questions: (1) How does the composition of debtholders (domestic vs. foreign, resident vs. non-resident, or official vs. non-official) affect the probability of a fiscal crisis, after controlling for the level of public debt and other relevant variables?; (2) How does the development and size of the domestic financial sector affect the probability of a fiscal crisis?; and (3) How do changes in the debt level affect the probability of a fiscal crisis, for given compositions of the sovereign debt investor base and different levels of development and size of domestic financial markets? Our findings confirm the benefits of financial development, the danger of heavy reliance on a non-resident investor base, and also that emerging market economies have a lower debt carrying capacity compared to the full sample.
Prediction Learning And Games
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Author : Nicolo Cesa-Bianchi
language : en
Publisher: Cambridge University Press
Release Date : 2006-03-13
Prediction Learning And Games written by Nicolo Cesa-Bianchi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-13 with Computers categories.
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
Surrogate Data Models Interpreting Large Scale Machine Learning Crisis Prediction Models
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Author : Jorge Chan-Lau
language : en
Publisher: International Monetary Fund
Release Date : 2023-02-24
Surrogate Data Models Interpreting Large Scale Machine Learning Crisis Prediction Models written by Jorge Chan-Lau and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-24 with Business & Economics categories.
Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs model interpretability and their ability to provide adequate guidance in the design of crisis prevention and mitigation policies. This paper introduces surrogate data models as dimensionality reduction tools in large-scale crisis prediction models. The appropriateness of this approach is assessed by their application to large-scale crisis prediction models developed at the IMF. The results are consistent with economic intuition and validate the use of surrogates as interpretability tools.
Advancement In Business Analytics Tools For Higher Financial Performance
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Author : Gharoie Ahangar, Reza
language : en
Publisher: IGI Global
Release Date : 2023-08-08
Advancement In Business Analytics Tools For Higher Financial Performance written by Gharoie Ahangar, Reza and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-08 with Business & Economics categories.
The relentless growth of data in financial markets has boosted the demand for more advanced analytical tools to facilitate and improve financial planning. The ability to constructively use this data is limited for managers and investors without the proper theoretical support. Within this context, there is an unmet demand for combining analytical finance methods with business analytics topics to inform better investment decisions. Advancement in Business Analytics Tools for Higher Financial Performance explores the financial applications of business analytics tools that can help financial managers and investors to better understand financial theory and improve institutional investment practices. This book explores the value extraction process using more accurate financial data via business analytical tools to help investors and portfolio managers develop more modern financial planning processes. Covering topics such as financial markets, investment analysis, and statistical tools, this book is ideal for accountants, data analysts, researchers, students, business professionals, academicians, and more.
Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes
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Author : Cheng Few Lee
language : en
Publisher: World Scientific
Release Date : 2020-07-30
Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-30 with Business & Economics categories.
This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.