Download or read book Adventures In Financial Data Science The Empirical Properties Of Financial And Economic Data Second Edition written by Graham L Giller and published by World Scientific. This book was released on 2022-06-27 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insights into the true nature of financial and economic data, and is a practical guide on how to analyze a variety of data sources. The focus of the book is on finance and economics, but it also illustrates the use of quantitative analysis and data science in many different areas. Lastly, the book includes practical information on how to store and process data and provides a framework for data driven reasoning about the world.The book begins with entertaining tales from Graham Giller's career in finance, starting with speculating in UK government bonds at the Oxford Post Office, accidentally creating a global instant messaging system that went 'viral' before anybody knew what that meant, on being the person who forgot to hit 'enter' to run a hundred-million dollar statistical arbitrage system, what he decoded from his brief time spent with Jim Simons, and giving Michael Bloomberg a tutorial on Granger Causality.The majority of the content is a narrative of analytic work done on financial, economics, and alternative data, structured around both Dr Giller's professional career and some of the things that just interested him. The goal is to stimulate interest in predictive methods, to give accurate characterizations of the true properties of financial, economic and alternative data, and to share what Richard Feynman described as 'The Pleasure of Finding Things Out.'

Download or read book Essays On Trading Strategy written by Graham L Giller and published by World Scientific. This book was released on 2023-08-17 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book directly focuses on finding optimal trading strategies in the real world and supports that with a well-defined theoretical foundation that allows trading strategy problems to be solved. Critically, it also delivers a menu of actual solutions that can be applied by traders with various risk profiles and objectives in markets that exhibit substantial tail risk. It shows how the Markowitz approach leads to excessive risk taking, and trader underperformance, in the real world. It summarizes the key features of Utility Theory, the deficiencies of the Sharpe Ratio as a statistic, and develops an optimal decision theory with fully developed examples for both 'Normal' and leptokurtotic distributions.

Download or read book Analysis of Financial Data written by Gary Koop and published by John Wiley & Sons. This book was released on 2006-01-09 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of Financial Data teaches the basic methods and techniques of data analysis to finance students, by showing them how to apply such techniques in the context of real-world empirical problems. Adopting a largely non-mathematical approach Analysis of Financial Data relies more on verbal intuition and graphical methods for understanding. Key features include: Coverage of many of the major tools used by the financial economist e.g. correlation, regression, time series analysis and methods for analyzing financial volatility. Extensive use of real data examples, which involves readers in hands-on computer work. Mathematical techniques at a level suited to MBA students and undergraduates taking a first course in the topic. Supplementary material for readers and lecturers provided on an accompanying website.

Download or read book Mergers Acquisitions and Other Restructuring Activities written by Donald M. DePamphilis and published by Academic Press. This book was released on 2003 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work includes updated cases and grounded models which reflect the theoretical underpinnings of the field. Expanded usage of key idea section headings enable the student to understand more easily the key point in each section of each chapter.

Download or read book Statistical Analysis of Financial Data in S Plus written by René Carmona and published by Springer Science & Business Media. This book was released on 2004-03-04 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book at the graduate textbook level to discuss analyzing financial data with S-PLUS. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. The book is aimed at undergraduate students in financial engineering; master students in finance and MBA's, and to practitioners with financial data analysis concerns.

Download or read book Financial Data Analytics with Machine Learning Optimization and Statistics written by Yongzhao Chen and published by John Wiley & Sons. This book was released on 2024-11-19 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential introduction to data analytics and Machine Learning techniques in the business sector In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs—especially of key results—and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. The book begins with a brief introduction to basic sampling theory and the fundamentals of simulation techniques, followed by a comparison between R and Python. It then discusses statistical diagnosis for financial security data and introduces some common tools in financial forensics such as Benford's Law, Zipf's Law, and anomaly detection. The statistical estimation and Expectation-Maximization (EM) & Majorization-Minimization (MM) algorithms are also covered. The book next focuses on univariate and multivariate dynamic volatility and correlation forecasting, and emphasis is placed on the celebrated Kelly's formula, followed by a brief introduction to quantitative risk management and dependence modelling for extremal events. A practical topic on numerical finance for traditional option pricing and Greek computations immediately follows as well as other important topics in financial data-driven aspects, such as Principal Component Analysis (PCA) and recommender systems with their applications, as well as advanced regression learners such as kernel regression and logistic regression, with discussions on model assessment methods such as simple Receiver Operating Characteristic (ROC) curves and Area Under Curve (AUC) for typical classification problems. The book then moves on to other commonly used machine learning tools like linear classifiers such as perceptrons and their generalization, the multilayered counterpart (MLP), Support Vector Machines (SVM), as well as Classification and Regression Trees (CART) and Random Forests. Subsequent chapters focus on linear Bayesian learning, including well-received credibility theory in actuarial science and functional kernel regression, and non-linear Bayesian learning, such as the Naïve Bayes classifier and the Comonotone-Independence Bayesian Classifier (CIBer) recently independently developed by the authors and used successfully in InsurTech. After an in-depth discussion on cluster analyses such as K-means clustering and its inversion, the K-nearest neighbor (KNN) method, the book concludes by introducing some useful deep neural networks for FinTech, like the potential use of the Long-Short Term Memory model (LSTM) for stock price prediction. This book can help readers become well-equipped with the following skills: To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisions To apply effective data dimension reduction tools to enhance supervised learning To describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.

Download or read book High frequency data analysis written by Nadine Hirte and published by GRIN Verlag. This book was released on 2004-06-23 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2003 in the subject Mathematics - Statistics, grade: 2.0 (B), European University Viadrina Frankfurt (Oder), language: English, abstract: Today the financial market becomes more complex and includes more competition. Reasons are trends like globalization, liberalization and lower-cost trading mechanism. The market microstructure research has the aim of an efficient market. It is focused on the structure of the financial market. The investigation becomes possible through the availability of high- frequency data. Those data exist especially in the United States and like that most of the research focuses this market. To explain the phenomena, which have been found adequate, models that fit the characteristics of high- frequency data have to be developed. The research is important to understand actions on the market as well as develop new efficient mechanism. One part of the market microstructure field is the bid-ask spread. It will be focus of this paper. In the first two parts it will be discussed theoretically. In the last part one model will be empirically analyzed and tested on its usefulness and validity. The second part of this paper explains the basic elements surrounding the research of bid-ask spread. Those are the financial market, market microstructure as well as high-frequency data. In the following part the bid-ask spread itself, approaches, researches and models focussing the spread will be discussed. The model of Roll (1984) will be explained in detail. The last part will be the empirical analysis of the model of Roll. It is analyzed with data from the NASDAQ.

Download or read book Empirical Science of Financial Fluctuations written by Hideki Takayasu and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial fluctuations were generally neglected in classical ecnomics and their basic statistical properties have only recently been elucidated in the emerging field of econophysics, a new science that analyzes data using methods developed by statistical physics, such as chaos, fractals, and phase transitions. This volume is the proceedings of a workshop at which leading international researchers in this discipline discussed their most recent results and examined the validity of the empirical laws of econophysics. Topics include stock market prices and foreign exchange rates, income distribution, market anomalies, and risk management. The papers herein relate econophysics to other models, present new models, and illustrate the mechanisms by which financial fluctuations occur using actual financial data. Containing the most recent econophysics results, this volume will serve as an indispensable reference for economic theorists and practitioners alike.

Download or read book The Statistical Mechanics of Financial Markets written by Johannes Voit and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: A careful examination of the interaction between physics and finance. It takes a look at the 100-year-long history of co-operation between the two fields and goes on to provide new research results on capital markets - taken from the field of statistical physics. The random walk model, well known in physics, is one good example of where the two disciplines meet. In the world of finance it is the basic model upon which the Black-Scholes theory of option pricing and hedging has been built. The underlying assumptions are discussed using empirical financial data and analogies to physical models such as fluid flows, turbulence, or superdiffusion. On this basis, new theories of derivative pricing and risk control can be formulated.

Download or read book The Financial Data Playbook written by Chris Conlan and published by . This book was released on 2021-08-06 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Financial Data Playbook is a compendium of thoughtful business lessons from a career financial machine learning engineer. It offers insights on how to navigate the business expectations and theoretical challenges of modern applied finance. Each argument is presented as a careful mathematical discussion that illustrates how investors, executives, and engineers think about and allocate resources to high-risk high-reward research and development projects. Readers will learn about: Measuring the business value of improving model accuracy Improving the accuracy and validity of investment performance simulations Estimating the amount of data required to improve a model Choosing the right model for the data Comparing the performance of modern and legacy methods Accounting for counter-party expectations to improve accuracy And more ... This book is written for finance and data business managers who want to maximize their financial data science R&D investment by understanding the opportunities and constraints presented by recent advances in financial machine learning.

Download or read book Resources in Education written by and published by . This book was released on 1998 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiscale Financial Data Analytics Mahb written by Tim Siu-Tang Leung and published by World Scientific Publishing Company. This book was released on 2025-06-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Download or read book Applications of Data Centric Science to Social Design written by Aki-Hiro Sato and published by Springer. This book was released on 2019-07-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intention behind this book is to illustrate the deep relation among human behavior, data-centric science, and social design. In fact, these three issues have been independently developing in different fields, although they are, of course, deeply interrelated to one another. Specifically, fundamental understanding of human behavior should be employed for investigating our human society and designing social systems. Insights and both quantitative and qualitative understandings of collective human behavior are quite useful when social systems are designed. Fundamental principles of human behavior, theoretical models of human behavior, and information cascades are addressed as aspects of human behavior. Data-driven investigation of human nature, social behavior, and societal systems are developed as aspects of data-centric science. As design aspects, how to design social systems from heterogeneous memberships is explained. There is also discussion of these three aspects—human behavior, data-centric science, and social design—independently and with regard to the relationships among them.

Download or read book Social Science Research written by Anol Bhattacherjee and published by CreateSpace. This book was released on 2012-04-01 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Download or read book Complexity in Financial Markets written by Matthieu Cristelli and published by Springer Science & Business Media. This book was released on 2013-08-28 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tools and methods from complex systems science can have a considerable impact on the way in which the quantitative assessment of economic and financial issues is approached, as discussed in this thesis. First it is shown that the self-organization of financial markets is a crucial factor in the understanding of their dynamics. In fact, using an agent-based approach, it is argued that financial markets’ stylized facts appear only in the self-organized state. Secondly, the thesis points out the potential of so-called big data science for financial market modeling, investigating how web-driven data can yield a picture of market activities: it has been found that web query volumes anticipate trade volumes. As a third achievement, the metrics developed here for country competitiveness and product complexity is groundbreaking in comparison to mainstream theories of economic growth and technological development. A key element in assessing the intangible variables determining the success of countries in the present globalized economy is represented by the diversification of the productive basket of countries. The comparison between the level of complexity of a country's productive system and economic indicators such as the GDP per capita discloses its hidden growth potential.

Download or read book Internet Finance And Digital Economy Advances In Digital Economy And Data Analysis Technology Proceedings Of The 2nd International Conference written by Faruk Balli and published by World Scientific. This book was released on 2023-08-24 with total page 1030 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, information technologies such as mobile payment, search engines, cloud computing and internet finance have developed rapidly. This has greatly impacted the structure of the financial market, and is set to bring about deep changes to the global financial industry. At the same time, the advent of the digital economy has brought about more challenges to the services and products of internet finance and financial supervision.This book contains the proceedings of the 2nd International Conference on Internet Finance and Digital Economy (ICIFDE 2022), which focus on how existing computer and information technology can be used to solve the problems of financial services in the era of digital economy. The chapters in this volume seek to provide technical solutions to the current digital financial transaction system, data processing in the digital economy and various forms of digital transactions or financing systems. Additionally, traditional research is combined with current cutting-edge technology in proposing new developments for the finance industry.

Download or read book Financial and Trade Globalization Greener Technologies and Energy Transition written by Magdalena Radulescu and published by Frontiers Media SA. This book was released on 2023-02-09 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: