Lasso Regressions And Forecasting Models In Applied Stress Testing
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Lasso Regressions And Forecasting Models In Applied Stress Testing
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Author : Mr.Jorge A. Chan-Lau
language : en
Publisher: International Monetary Fund
Release Date : 2017-05-05
Lasso Regressions And Forecasting Models In Applied Stress Testing written by Mr.Jorge A. 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 2017-05-05 with Business & Economics categories.
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.
Smart Trends In Computing And Communications
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Author : Tomonobu Senjyu
language : en
Publisher: Springer Nature
Release Date :
Smart Trends In Computing And Communications written by Tomonobu Senjyu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Imf Research Bulletin Summer 2017
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Author : International Monetary Fund. Research Dept.
language : en
Publisher: International Monetary Fund
Release Date : 2017-08-11
Imf Research Bulletin Summer 2017 written by International Monetary Fund. Research Dept. 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 2017-08-11 with Business & Economics categories.
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.
Sains Data
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Author : Hartatik
language : id
Publisher: Kaizen Media Publishing
Release Date : 2023-03-20
Sains Data written by Hartatik and has been published by Kaizen Media Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-20 with Language Arts & Disciplines categories.
Sains Data telah menjadi bidang yang semakin populer di era digital saat ini, di mana data yang tersedia semakin banyak dan kompleks. Bab 1 membahas pengantar sains data, termasuk apa itu sains data, mengapa sains data penting, dan bagaimana sains data berkaitan dengan teknologi lainnya. Bab 2 juga penting bagi data scientists karena membahas keterampilan lunak yang diperlukan untuk sukses dalam pekerjaan ini. Ini termasuk keterampilan interpersonal, manajemen proyek, dan kemampuan presentasi yang efektif. Sebagai seorang data scientist, Anda akan bekerja dengan berbagai jenis data. Bab 3 memberikan pengantar tentang data, termasuk jenis data dan cara mereka disimpan dan dikelola. Bab 4 membahas platform cloud big data, yang merupakan teknologi kunci untuk menyimpan dan mengolah data secara efektif. Kemudian, Bab 5 dan Bab 6 membahas dua aspek penting dari sains data: pra-pemrosesan data dan penyusunan data. Dalam bab-bab ini, Anda akan belajar tentang alat dan teknik untuk membersihkan dan mempersiapkan data untuk pemodelan. Setelah data Anda siap, Anda dapat mulai membangun model. Bab 7 dan Bab 8 membahas strategi penyetelan model dan pengukuran kinerja. Bab 9 hingga Bab 15 membahas berbagai teknik pemodelan, termasuk model regresi, metode regulasi, pohon keputusan, dan jaringan syaraf tiruan. Bab ini membahas detail teknis untuk membantu Anda memahami dan mengimplementasikan model yang efektif. Dalam keseluruhan buku, Anda akan belajar tentang berbagai aspek sains data, mulai dari keterampilan lunak hingga teknik pemodelan. Dengan pemahaman ini, Anda dapat mengembangkan keterampilan yang diperlukan untuk menjadi seorang data scientist yang sukses dan berkontribusi dalam memecahkan masalah dunia nyata.
Applied Economic Forecasting Using Time Series Methods
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Author : Eric Ghysels
language : en
Publisher: Oxford University Press
Release Date : 2018-03-23
Applied Economic Forecasting Using Time Series Methods written by Eric Ghysels and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-23 with Business & Economics categories.
Economic forecasting is a key ingredient of decision making both in the public and in the private sector. Because economic outcomes are the result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast precision and reliability can be enhanced by the use of proper econometric models and methods, this innovative book provides an overview of both theory and applications. Undergraduate and graduate students learning basic and advanced forecasting techniques will be able to build from strong foundations, and researchers in public and private institutions will have access to the most recent tools and insights. Readers will gain from the frequent examples that enhance understanding of how to apply techniques, first by using stylized settings and then by real data applications--focusing on macroeconomic and financial topics. This is first and foremost a book aimed at applying time series methods to solve real-world forecasting problems. Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as forecast evaluation and combination. Several chapters cover univariate time series models, vector autoregressive models, cointegration and error correction models, and Bayesian methods for estimating vector autoregressive models. A collection of special topics chapters study Threshold and Smooth Transition Autoregressive (TAR and STAR) models, Markov switching regime models, state space models and the Kalman filter, mixed frequency data models, nowcasting, forecasting using large datasets and, finally, volatility models. There are plenty of practical applications in the book and both EViews and R code are available online at authors' website.
Completing The Market Generating Shadow Cds Spreads By Machine Learning
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Author : Nan Hu
language : en
Publisher: International Monetary Fund
Release Date : 2019-12-27
Completing The Market Generating Shadow Cds Spreads By Machine Learning written by Nan Hu 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 2019-12-27 with Business & Economics categories.
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.
Applied Predictive Modeling
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Author : Max Kuhn
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-05-17
Applied Predictive Modeling written by Max Kuhn and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-17 with Medical categories.
Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
Bayesian And Frequentist Regression Methods
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Author : Jon Wakefield
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-04
Bayesian And Frequentist Regression Methods written by Jon Wakefield and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-04 with Mathematics categories.
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.
Disrupting Finance
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Author : Theo Lynn
language : en
Publisher: Springer
Release Date : 2018-12-06
Disrupting Finance written by Theo Lynn and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-06 with Business & Economics categories.
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.
Data Science For Economics And Finance
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Author : Sergio Consoli
language : en
Publisher: Springer Nature
Release Date : 2021
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 with Application software 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.