Download or read book Machine Learning and Causality The Impact of Financial Crises on Growth written by Mr.Andrew J Tiffin and published by International Monetary Fund. This book was released on 2019-11-01 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning and Causality The Impact of Financial Crises on Growth written by Mr.Andrew J Tiffin and published by International Monetary Fund. This book was released on 2019-11-01 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Predicting Fiscal Crises A Machine Learning Approach written by Klaus-Peter Hellwig and published by International Monetary Fund. This book was released on 2021-05-27 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Powering the Digital Economy Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Download or read book The Feasibility of Predicting Financial Crises using Machine Learning written by Julia Markhovski and published by GRIN Verlag. This book was released on 2024-03-26 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2024 in the subject Computer Science - Commercial Information Technology, grade: 1.0, Frankfurt School of Finance & Management, language: English, abstract: In a world characterized by increasingly complex financial markets, the prediction of financial crises is a constant challenge. This bachelor thesis investigates the use of machine learning, in particular regression algorithms, to analyze and predict financial crises based on macroeconomic data. By building six different regression models and optimizing them using cross-validation and GridSearch, the feasibility of using these technologies for accurate predictions is discussed. Although traditional models show limited effectiveness, the integration of machine learning, especially kNN algorithms, reveals significant potential for improving prediction accuracy. The paper highlights the importance of classification algorithms and provides crucial insights for application in real-world scenarios to provide valuable tools for policy and business decision makers.

Download or read book Identifying Financial Crises Using Machine Learning on Textual Data written by Mary Chen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Impact of Gray Listing on Capital Flows An Analysis Using Machine Learning written by Mizuho Kida and published by International Monetary Fund. This book was released on 2021-05-27 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Financial Action Task Force’s gray list publicly identifies countries with strategic deficiencies in their AML/CFT regimes (i.e., in their policies to prevent money laundering and the financing of terrorism). How much gray-listing affects a country’s capital flows is of interest to policy makers, investors, and the Fund. This paper estimates the magnitude of the effect using an inferential machine learning technique. It finds that gray-listing results in a large and statistically significant reduction in capital inflows.

Download or read book Essays on Theoretical and Empirical Models of Macroeconomics and Finance written by Ali R. Bagherpour and published by . This book was released on 2018 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents two chapters on empirical models of macroeconomics and finance, and one chapter on a theoretical model for conducting monetary policy. The first chapter applies machine learning algorithms to construct non-parametric, nonlinear predictions of mortgage loan default. I compile a large dataset with over 20 million loan observations from Fannie Mae and Freddie Mac, for the period 2001-2016 at the quarterly frequency. Different machine learning algorithms are applied to predict in sample (training sample), and to forecast out-of-sample (testing data). I find that the forecast performance of nonlinear and non-parametric algorithms are substantially better than the traditional logit model. Additionally, machine learning algorithms allow identification of the predictive power of specific variables. The results indicate that loan age is the most important predictor of loan default before and after the 2008 financial crisis. However, I find that market loan- to-value is the most effective predictor of mortgage loan default during the recent financial crisis. Finally, I use machine learning to formulate risk-based capital stress tests for Fannie Mae and Freddie Mac under different scenarios. I forecast their mortgage credit losses and associated capital needs during the financial crises. The results obtained are more accurate than those from the Federal Housing Enterprise Oversights (OFHEO), and other existing stress test studies. In the second, and third chapters, I tested the effectiveness of Monetary policy by empirical, and theoretical models. With the severity of the 2008 financial crisis, and apparent inefficacy of traditional monetary and fiscal policies, the Federal Reserve together with the U.S. government introduced unconventional policy measures. The Large Scale Asset Purchase (LSAP) and Troubled Asset Relief Program (TARP) are some of these policies introduced by the Federal Reserve and Department of Treasury. While these policies may have been important in preventing a deepening of the financial crisis and laying the foundation for the economic recovery, there were collateral effects on bank profitability. In this chapter, I study the impact of both the LSAP and TARP programs on banks? profit and risk taking using a large panel. The results indicate that these programs had a positive effect on banks? profit (Chapter 2). In chapter three, I use a small-scale DSGE model for the economy of Iran to analyze monetary policy. The model is extended to include housing and oil sectors. The model is adapted for the peculiarities of Iran's Central Bank, which uses money supply as a function of oil income and production growth. I study the reaction function of the model to technology, oil, and monetary shocks in this specific Iranian monetary policy framework. The results show that monetary shocks has only nominal effect on inflation but not on the real sector such as investment, consumption, or production. Also, positive oil income shocks lead to an increase in inflation instead of an increase in production.

Download or read book Fiscal Crises written by Mrs.Kerstin Gerling and published by International Monetary Fund. This book was released on 2017-04-03 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: A key objective of fiscal policy is to maintain the sustainability of public finances and avoid crises. Remarkably, there is very limited analysis on fiscal crises. This paper presents a new database of fiscal crises covering different country groups, including low-income developing countries (LIDCs) that have been mostly ignored in the past. Countries faced on average two crises since 1970, with the highest frequency in LIDCs and lowest in advanced economies. The data sheds some light on policies and economic dynamics around crises. LIDCs, which are usually seen as more vulnerable to shocks, appear to suffer the least in crisis periods. Surprisingly, advanced economies face greater turbulence (growth declines sharply in the first two years of the crisis), with half of them experiencing economic contractions. Fiscal policy is usually procyclical as countries curtail expenditure growth when economic activity weakens. We also find that the decline in economic growth is magnified if accompanied by a financial crisis.

Download or read book Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Global Waves of Debt written by M. Ayhan Kose and published by World Bank Publications. This book was released on 2021-03-03 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Prediction Learning and Games written by Nicolo Cesa-Bianchi and published by Cambridge University Press. This book was released on 2006-03-13 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Kingdom of Lesotho written by International Monetary Fund. African Dept. and published by International Monetary Fund. This book was released on 2024-09-11 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kingdom of Lesotho: Selected Issues

Download or read book The Promise of Fintech written by Ms.Ratna Sahay and published by International Monetary Fund. This book was released on 2020-07-01 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology is changing the landscape of the financial sector, increasing access to financial services in profound ways. These changes have been in motion for several years, affecting nearly all countries in the world. During the COVID-19 pandemic, technology has created new opportunities for digital financial services to accelerate and enhance financial inclusion, amid social distancing and containment measures. At the same time, the risks emerging prior to COVID-19, as digital financial services developed, are becoming even more relevant.

Download or read book Fiscal Policy and Long Term Growth written by International Monetary Fund and published by International Monetary Fund. This book was released on 2015-04-20 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper explores how fiscal policy can affect medium- to long-term growth. It identifies the main channels through which fiscal policy can influence growth and distills practical lessons for policymakers. The particular mix of policy measures, however, will depend on country-specific conditions, capacities, and preferences. The paper draws on the Fund’s extensive technical assistance on fiscal reforms as well as several analytical studies, including a novel approach for country studies, a statistical analysis of growth accelerations following fiscal reforms, and simulations of an endogenous growth model.

Download or read book Completing the Market Generating Shadow CDS Spreads by Machine Learning written by Nan Hu and published by International Monetary Fund. This book was released on 2019-12-27 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Understanding and Predicting Systemic Corporate Distress A Machine Learning Approach written by Ms. Burcu Hacibedel and published by International Monetary Fund. This book was released on 2022-07-29 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we study systemic non-financial corporate sector distress using firm-level probabilities of default (PD), covering 55 economies, and spanning the last three decades. Systemic corporate distress is identified by elevated PDs across a large portion of the firms in an economy. A machine-learning based early warning system is constructed to predict the onset of distress in one year’s time. Our results show that credit expansion, monetary policy tightening, overvalued stock prices, and debt-linked balance-sheet weaknesses predict corporate distress. We also find that systemic corporate distress events are associated with contractions in GDP and credit growth in advanced and emerging markets at different degrees and milder than financial crises.