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Lasso Regressions And Forecasting Models In Applied Stress Testing
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Book Synopsis Lasso Regressions and Forecasting Models in Applied Stress Testing by : Mr.Jorge A. Chan-Lau
Download or read book Lasso Regressions and Forecasting Models in Applied Stress Testing written by Mr.Jorge A. Chan-Lau and published by International Monetary Fund. This book was released on 2017-05-08 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model selection and forecasting in stress tests can be facilitated using machine learning techniques. These techniques have proved robust in other fields for dealing with the curse of dimensionality, a situation often encountered in applied stress testing. Lasso regressions, in particular, are well suited for building forecasting models when the number of potential covariates is large, and the number of observations is small or roughly equal to the number of covariates. This paper presents a conceptual overview of lasso regressions, explains how they fit in applied stress tests, describes its advantages over other model selection methods, and illustrates their application by constructing forecasting models of sectoral probabilities of default in an advanced emerging market economy.
Book Synopsis Smart Trends in Computing and Communications by : Tomonobu Senjyu
Download or read book Smart Trends in Computing and Communications written by Tomonobu Senjyu and published by Springer Nature. This book was released on with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :International Monetary Fund. Research Dept. Publisher :International Monetary Fund ISBN 13 :1484315448 Total Pages :19 pages Book Rating :4.4/5 (843 download)
Book Synopsis IMF Research Bulletin, Summer 2017 by : International Monetary Fund. Research Dept.
Download or read book IMF Research Bulletin, Summer 2017 written by International Monetary Fund. Research Dept. and published by International Monetary Fund. This book was released on 2017-08-11 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Summer 2017 issue of the IMF Research Bulletin highlights new research such as recent IMF Working Papers and Staff Discussion Notes. The Research Summaries are “Structural Reform Packages, Sequencing, and the Informal Economy (by Zsuzsa Munkacsi and Magnus Saxegaard) and “A Broken Social Contract, Not High Inequality Led to the Arab Spring” (by Shantayanan Devarajan and Elena Ianchovichina). The Q&A section features “Seven Questions on Fintech” (by Tommaso Mancini-Griffoli). The Bulletin also includes information on recommended titles from IMF Publications and the latest articles from the IMF Economic Review.
Book Synopsis Applied Economic Forecasting Using Time Series Methods by : Eric Ghysels
Download or read book Applied Economic Forecasting Using Time Series Methods written by Eric Ghysels and published by Oxford University Press. This book was released on 2018 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic forecasting is a key ingredient of decision making in the public and private sectors. This book provides the necessary tools to solve real-world forecasting problems using time-series methods. It targets undergraduate and graduate students as well as researchers in public and private institutions interested in applied economic forecasting.
Book Synopsis Completing the Market: Generating Shadow CDS Spreads by Machine Learning by : Nan Hu
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.
Book Synopsis Interpretable Machine Learning by : Christoph Molnar
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Book Synopsis Bayesian and Frequentist Regression Methods by : Jon Wakefield
Download or read book Bayesian and Frequentist Regression Methods written by Jon Wakefield and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.
Download or read book Disrupting Finance written by Theo Lynn and published by Springer. This book was released on 2018-12-06 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry.
Book Synopsis Stress Testing at the IMF by : Mr.Tobias Adrian
Download or read book Stress Testing at the IMF written by Mr.Tobias Adrian and published by International Monetary Fund. This book was released on 2020-02-05 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper explains specifics of stress testing at the IMF. After a brief section on the evolution of stress tests at the IMF, the paper presents the key steps of an IMF staff stress test. They are followed by a discussion on how IMF staff uses stress tests results for policy advice. The paper concludes by identifying remaining challenges to make stress tests more useful for the monitoring of financial stability and an overview of IMF staff work program in that direction. Stress tests help assess the resilience of financial systems in IMF member countries and underpin policy advice to preserve or restore financial stability. This assessment and advice are mainly provided through the Financial Sector Assessment Program (FSAP). IMF staff also provide technical assistance in stress testing to many its member countries. An IMF macroprudential stress test is a methodology to assess financial vulnerabilities that can trigger systemic risk and the need of systemwide mitigating measures. The definition of systemic risk as used by the IMF is relevant to understanding the role of its stress tests as tools for financial surveillance and the IMF’s current work program. IMF stress tests primarily apply to depository intermediaries, and, systemically important banks.
Book Synopsis Real Estate Modelling and Forecasting by : Chris Brooks
Download or read book Real Estate Modelling and Forecasting written by Chris Brooks and published by Cambridge University Press. This book was released on 2010-04-15 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.
Book Synopsis Data Science for Economics and Finance by : Sergio Consoli
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.
Book Synopsis Stress-testing the Banking System by : Mario Quagliariello
Download or read book Stress-testing the Banking System written by Mario Quagliariello and published by Cambridge University Press. This book was released on 2009-10-15 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stress tests are used in risk management by banks in order to determine how certain crisis scenarios would affect the value of their portfolios, and by public authorities for financial stability purposes. Until the first half of 2007, interest in stress-testing was largely restricted to practitioners. Since then, the global financial system has been hit by deep turbulences, including the fallout from sub-prime mortgage lending. Many observers have pointed out that the severity of the crisis has been largely due to its unexpected nature and have claimed that a more extensive use of stress-testing methodologies would have helped to alleviate the repercussions of the crisis. This book analyses the theoretical underpinnings, as well as the practical aspects, of applying such methodologies. Building on the experience gained by the economists of many national and international financial authorities, it provides an updated toolkit for both practitioners and academics.
Book Synopsis Interconnectedness and Contagion Analysis: A Practical Framework by : Mrs.Jana Bricco
Download or read book Interconnectedness and Contagion Analysis: A Practical Framework written by Mrs.Jana Bricco and published by International Monetary Fund. This book was released on 2019-10-11 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of interconnectedness and contagion is an important part of the financial stability and risk assessment of a country’s financial system. This paper offers detailed and practical guidance on how to conduct a comprehensive analysis of interconnectedness and contagion for a country’s financial system under various circumstances. We survey current approaches at the IMF for analyzing interconnectedness within the interbank, cross-sector and cross-border dimensions through an overview and examples of the data and methodologies used in the Financial Sector Assessment Program. Finally, this paper offers practical advice on how to interpret results and discusses potential financial stability policy recommendations that can be drawn from this type of in-depth analysis.
Book Synopsis Machine Learning with R by : Brett Lantz
Download or read book Machine Learning with R written by Brett Lantz and published by Packt Publishing Ltd. This book was released on 2019-04-15 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve real-world data problems with R and machine learning Key Features Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.6 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R. What you will learn Discover the origins of machine learning and how exactly a computer learns by example Prepare your data for machine learning work with the R programming language Classify important outcomes using nearest neighbor and Bayesian methods Predict future events using decision trees, rules, and support vector machines Forecast numeric data and estimate financial values using regression methods Model complex processes with artificial neural networks — the basis of deep learning Avoid bias in machine learning models Evaluate your models and improve their performance Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow Who this book is for Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.
Book Synopsis Limit Order Books by : Frédéric Abergel
Download or read book Limit Order Books written by Frédéric Abergel and published by Cambridge University Press. This book was released on 2016-05-09 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: A limit order book is essentially a file on a computer that contains all orders sent to the market, along with their characteristics such as the sign of the order, price, quantity and a timestamp. The majority of organized electronic markets rely on limit order books to store the list of interests of market participants on their central computer. A limit order book contains all the information available on a specific market and it reflects the way the market moves under the influence of its participants. This book discusses several models of limit order books. It begins by discussing the data to assess their empirical properties, and then moves on to mathematical models in order to reproduce the observed properties. Finally, the book presents a framework for numerical simulations. It also covers important modelling techniques including agent-based modelling, and advanced modelling of limit order books based on Hawkes processes. The book also provides in-depth coverage of simulation techniques and introduces general, flexible, open source library concepts useful to readers studying trading strategies in order-driven markets.
Book Synopsis Statistical Learning with Sparsity by : Trevor Hastie
Download or read book Statistical Learning with Sparsity written by Trevor Hastie and published by CRC Press. This book was released on 2015-05-07 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underl
Book Synopsis Economic Forecasting by : Graham Elliott
Download or read book Economic Forecasting written by Graham Elliott and published by Princeton University Press. This book was released on 2016-04-05 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and integrated approach to economic forecasting problems Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike
