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Essentials of Time Series for Financial Applications

Essentials of Time Series for Financial Applications
  • Author : Massimo Guidolin,Manuela Pedio
  • Publisher :Unknown
  • Release Date :2018-05-29
  • Total pages :434
  • ISBN : 9780128134108
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Summary : Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. Provides practical, hands-on examples in time-series econometrics Presents a more application-oriented, less technical book on financial econometrics Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction Features examples worked out in EViews (9 or higher)

Essentials of Stochastic Finance

Essentials of Stochastic Finance
  • Author : Albert N. Shiryaev
  • Publisher :Unknown
  • Release Date :1999
  • Total pages :834
  • ISBN : 9789810236052
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Summary : Readership: Undergraduates and researchers in probability and statistics; applied, pure and financial mathematics; economics; chaos.

Time Series

Time Series
  • Author : Ngai Hang Chan
  • Publisher :Unknown
  • Release Date :2002
  • Total pages :203
  • ISBN : STANFORD:36105111770926
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Summary : This title gives both conceptual and practical illustrations of financial time series. Examples and discussions in the later chapters of the book make recent developments in time series more accessible. Examples from finance are maximized as much as possible throughout the book.

Analysis of Financial Time Series

Analysis of Financial Time Series
  • Author : Ruey S. Tsay
  • Publisher :Unknown
  • Release Date :2005-09-15
  • Total pages :576
  • ISBN : 9780471746188
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Summary : Provides statistical tools and techniques needed to understandtoday's financial markets The Second Edition of this critically acclaimed text provides acomprehensive and systematic introduction to financial econometricmodels and their applications in modeling and predicting financialtime series data. This latest edition continues to emphasizeempirical financial data and focuses on real-world examples.Following this approach, readers will master key aspects offinancial time series, including volatility modeling, neuralnetwork applications, market microstructure and high-frequencyfinancial data, continuous-time models and Ito's Lemma, Value atRisk, multiple returns analysis, financial factor models, andeconometric modeling via computation-intensive methods. The author begins with the basic characteristics of financialtime series data, setting the foundation for the three maintopics: Analysis and application of univariate financial timeseries Return series of multiple assets Bayesian inference in finance methods This new edition is a thoroughly revised and updated text,including the addition of S-Plus® commands and illustrations.Exercises have been thoroughly updated and expanded and include themost current data, providing readers with more opportunities to putthe models and methods into practice. Among the new material addedto the text, readers will find: Consistent covariance estimation under heteroscedasticity andserial correlation Alternative approaches to volatility modeling Financial factor models State-space models Kalman filtering Estimation of stochastic diffusion models The tools provided in this text aid readers in developing adeeper understanding of financial markets through firsthandexperience in working with financial data. This is an idealtextbook for MBA students as well as a reference for researchersand professionals in business and finance.

Time Series Analysis and Its Applications

Time Series Analysis and Its Applications
  • Author : Robert H. Shumway,David S. Stoffer
  • Publisher :Unknown
  • Release Date :2014-01-15
  • Total pages :568
  • ISBN : 1475732627
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Summary :

Analysis of Financial Time Series

Analysis of Financial Time Series
  • Author : Ruey S. Tsay
  • Publisher :Unknown
  • Release Date :2010-10-26
  • Total pages :720
  • ISBN : 1118017099
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Summary : This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

Multivariate Time Series Analysis

Multivariate Time Series Analysis
  • Author : Ruey S. Tsay
  • Publisher :Unknown
  • Release Date :2013-11-11
  • Total pages :520
  • ISBN : 9781118617755
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Summary : An accessible guide to the multivariate time series toolsused in numerous real-world applications Multivariate Time Series Analysis: With R and FinancialApplications is the much anticipated sequel coming from one ofthe most influential and prominent experts on the topic of timeseries. Through a fundamental balance of theory and methodology,the book supplies readers with a comprehensible approach tofinancial econometric models and their applications to real-worldempirical research. Differing from the traditional approach to multivariate timeseries, the book focuses on reader comprehension by emphasizingstructural specification, which results in simplified parsimoniousVAR MA modeling. Multivariate Time Series Analysis: With R andFinancial Applications utilizes the freely available Rsoftware package to explore complex data and illustrate relatedcomputation and analyses. Featuring the techniques and methodologyof multivariate linear time series, stationary VAR models, VAR MAtime series and models, unitroot process, factor models, andfactor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce thepresented content • User-friendly R subroutines and research presentedthroughout to demonstrate modern applications • Numerous datasets and subroutines to provide readerswith a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbookfor graduate-level courses on time series and quantitative financeand upper-undergraduate level statistics courses in time series.The book is also an indispensable reference for researchers andpractitioners in business, finance, and econometrics.

Python for Finance

Python for Finance
  • Author : Yves Hilpisch
  • Publisher :Unknown
  • Release Date :2014-12-11
  • Total pages :606
  • ISBN : 9781491945384
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Summary : The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies

Practical Time Series Analysis

Practical Time Series Analysis
  • Author : Dr. Avishek Pal,Dr. PKS Prakash
  • Publisher :Unknown
  • Release Date :2017-09-28
  • Total pages :244
  • ISBN : 9781788294195
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Summary : Step by Step guide filled with real world practical examples. About This Book Get your first experience with data analysis with one of the most powerful types of analysis—time-series. Find patterns in your data and predict the future pattern based on historical data. Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide Who This Book Is For This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods. What You Will Learn Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project Develop an understanding of loading, exploring, and visualizing time-series data Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series Take advantage of exponential smoothing to tackle noise in time series data Learn how to use auto-regressive models to make predictions using time-series data Build predictive models on time series using techniques based on auto-regressive moving averages Discover recent advancements in deep learning to build accurate forecasting models for time series Gain familiarity with the basics of Python as a powerful yet simple to write programming language In Detail Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. Style and approach This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.

Communication Essentials for Financial Planners

Communication Essentials for Financial Planners
  • Author : John E. Grable,Joseph W. Goetz
  • Publisher :Unknown
  • Release Date :2017-02-02
  • Total pages :240
  • ISBN : 9781119350774
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Summary : Exploring the Human Element of Financial Planning Communication Essentials for Financial Planners tackles the counseling side of practice to help financial planners build more productive client relationships. CFP Board’s third book and first in the Financial Planning Series, Communication Essentials will help you learn how to relate to clients on a more fundamental level, and go beyond "hearing" their words to really listen and ultimately respond to what they're saying. Expert coverage of body language, active listening, linguistic signals, and more, all based upon academic theory. There is also an accompanied set of videos that showcase both good and bad communication and counseling within a financial planning context. By merging written and experiential learning supplemented by practice assignments, this book provides an ideal resource for any client-facing financial professional as well as any student on their pathway to CFP® certification. Counseling is a central part of a financial planner's practice, and attention to interpersonal communication goes a long way toward progressing in the field; this guide provides practical instruction on the proven techniques that make a good financial planner great. Build client relationships based on honesty and trust Learn to read body language and the words not spoken Master the art of active listening to help your clients feel heard Tailor your communications to suit the individual client's needs The modern financial planning practice is more than just mathematics and statistical analysis—at its heart, it is based on trust, communication, and commitment. While interpersonal skills have always been a critical ingredient for success, only recently has this aspect been given the weight it deserves with its incorporation into the certification process. Communication Essentials for Financial Planners provides gold-standard guidance for certification and beyond.

Essentials of Personal Financial Planning

Essentials of Personal Financial Planning
  • Author : Susan M. Tillery,Thomas N. Tillery
  • Publisher :Unknown
  • Release Date :2018-09-21
  • Total pages :456
  • ISBN : 9781119421207
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Summary : ESSENTIALS OF PERSONAL FINANCIAL PLANNING Essentials of Personal Financial Planning was written to challenge the status quo by promoting personal financial planning (PFP) as a profession, not as a sales tool to gather assets under management or facilitate sales of insurance products. The book takes a comprehensive and integrated approach to PFP for accounting students, allowing them to view the profession through the lens of a CPA – with integrity and objectivity. This book systematically introduces the essentials of all the major PFP topics (estate, retirement, investments, insurance, and tax), as well as: The PFP process, concepts and regulatory environment. Professional responsibilities of a CPA personal financial planner and the requirements of the Statement on Standards in PFP Services. Time value of money concepts. The book then builds on these foundational concepts, showing their interconnectivity and professional opportunities, to provide a deeper understanding of PFP and its application. After reading this book, students will be able to apply the knowledge and skills gained from this course to have an immediate and long-term positive impact for themselves and for the clients they serve.

Analysis of Financial Data

Analysis of Financial Data
  • Author : Gary Koop
  • Publisher :Unknown
  • Release Date :2006-01-09
  • Total pages :240
  • ISBN : IND:30000103007492
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Summary : 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.

Analysis of Financial Time Series

Analysis of Financial Time Series
  • Author : Ruey S. Tsay
  • Publisher :Unknown
  • Release Date :2016
  • Total pages :229
  • ISBN : 8126548932
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Summary :

Mathematical Foundations of Time Series Analysis

Mathematical Foundations of Time Series Analysis
  • Author : Jan Beran
  • Publisher :Unknown
  • Release Date :2018-03-23
  • Total pages :307
  • ISBN : 9783319743806
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Summary : This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.

Computational Finance

Computational Finance
  • Author : Argimiro Arratia
  • Publisher :Unknown
  • Release Date :2014-05-08
  • Total pages :301
  • ISBN : 9789462390706
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Summary : The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.

Financial Modeling Using Excel and VBA

Financial Modeling Using Excel and VBA
  • Author : Chandan Sengupta
  • Publisher :Unknown
  • Release Date :2004-02-26
  • Total pages :857
  • ISBN : 0471267686
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Summary : "Reviews all the necessary financial theory and concepts, and walks you through a wide range of real-world financial models" - cover.

Forecasting for Economics and Business

Forecasting for Economics and Business
  • Author : Gloria González-Rivera
  • Publisher :Unknown
  • Release Date :2016-12-05
  • Total pages :512
  • ISBN : 9781315510392
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Summary : For junior/senior undergraduates in a variety of fields such as economics, business administration, applied mathematics and statistics, and for graduate students in quantitative masters programs such as MBA and MA/MS in economics. A student-friendly approach to understanding forecasting. Knowledge of forecasting methods is among the most demanded qualifications for professional economists, and business people working in either the private or public sectors of the economy. The general aim of this textbook is to carefully develop sophisticated professionals, who are able to critically analyze time series data and forecasting reports because they have experienced the merits and shortcomings of forecasting practice.

Python for Data Analysis

Python for Data Analysis
  • Author : Wes McKinney
  • Publisher :Unknown
  • Release Date :2013
  • Total pages :452
  • ISBN : 9781449319793
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Summary : Presents case studies and instructions on how to solve data analysis problems using Python.

Technical Analysis of the Financial Markets

Technical Analysis of the Financial Markets
  • Author : John J. Murphy
  • Publisher :Unknown
  • Release Date :1999-01-01
  • Total pages :576
  • ISBN : 9781101659199
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Summary : John J. Murphy has now updated his landmark bestseller Technical Analysis of the Futures Markets, to include all of the financial markets. This outstanding reference has already taught thousands of traders the concepts of technical analysis and their application in the futures and stock markets. Covering the latest developments in computer technology, technical tools, and indicators, the second edition features new material on candlestick charting, intermarket relationships, stocks and stock rotation, plus state-of-the-art examples and figures. From how to read charts to understanding indicators and the crucial role technical analysis plays in investing, readers gain a thorough and accessible overview of the field of technical analysis, with a special emphasis on futures markets. Revised and expanded for the demands of today's financial world, this book is essential reading for anyone interested in tracking and analyzing market behavior.

The R Book

The R Book
  • Author : Michael J. Crawley
  • Publisher :Unknown
  • Release Date :2007-06-13
  • Total pages :950
  • ISBN : 0470515066
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Summary : The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis. Building on the success of the author’s bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines. Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities. Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.

Financial Mathematics

Financial Mathematics
  • Author : Giuseppe Campolieti,Roman N. Makarov
  • Publisher :Unknown
  • Release Date :2014-03-12
  • Total pages :829
  • ISBN : 9781439892428
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Summary : Versatile for Several Interrelated Courses at the Undergraduate and Graduate Levels Financial Mathematics: A Comprehensive Treatment provides a unified, self-contained account of the main theory and application of methods behind modern-day financial mathematics. Tested and refined through years of the authors’ teaching experiences, the book encompasses a breadth of topics, from introductory to more advanced ones. Accessible to undergraduate students in mathematics, finance, actuarial science, economics, and related quantitative areas, much of the text covers essential material for core curriculum courses on financial mathematics. Some of the more advanced topics, such as formal derivative pricing theory, stochastic calculus, Monte Carlo simulation, and numerical methods, can be used in courses at the graduate level. Researchers and practitioners in quantitative finance will also benefit from the combination of analytical and numerical methods for solving various derivative pricing problems. With an abundance of examples, problems, and fully worked out solutions, the text introduces the financial theory and relevant mathematical methods in a mathematically rigorous yet engaging way. Unlike similar texts in the field, this one presents multiple problem-solving approaches, linking related comprehensive techniques for pricing different types of financial derivatives. The book provides complete coverage of both discrete- and continuous-time financial models that form the cornerstones of financial derivative pricing theory. It also presents a self-contained introduction to stochastic calculus and martingale theory, which are key fundamental elements in quantitative finance.