Practical Trend Analysis
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Practical Trend Analysis
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Author : Michael C. Thomsett
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-05-20
Practical Trend Analysis written by Michael C. Thomsett and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-20 with Business & Economics categories.
Written for traders with a basic knowledge of trends and technical analysis, Practical Trend Analysis introduces advanced analytical tools for recognizing how risks evolve as trends proceed. Readers will learn how to use trend prediction to manage market risks far more effectively. Michael C. Thomsett provides insights on technical signals such as candlestick reversals, price gaps, and movement through resistance or support; distinguishing between strong and weak trends; objectively evaluating the health of a stock’s current price levels, trading breadth, and technical condition; and anticipating plateaus, slowdowns, or price reversals. He presents detailed coverage of trendlines and channel lines; patterns and confirmations of both reversals and continuations; broadening and narrowing trends, price jumps; and trends based on volume, moving averages, and momentum. Practical Trend Analysis will enable traders, both amateur and professional, to go far beyond mere trend "following." Michael C. Thomsett is a market expert, author, speaker, and coach. His many books include Stock Market Math, Candlestick Charting, and The Mathematics of Options.
Practical Trend Analysis
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Author : Michael C. Thomsett
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-05-20
Practical Trend Analysis written by Michael C. Thomsett and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-20 with Business & Economics categories.
Written for traders with a basic knowledge of trends and technical analysis, Practical Trend Analysis introduces advanced analytical tools for recognizing how risks evolve as trends proceed. Readers will learn how to use trend prediction to manage market risks far more effectively. Michael C. Thomsett provides insights on technical signals such as candlestick reversals, price gaps, and movement through resistance or support; distinguishing between strong and weak trends; objectively evaluating the health of a stock’s current price levels, trading breadth, and technical condition; and anticipating plateaus, slowdowns, or price reversals. He presents detailed coverage of trendlines and channel lines; patterns and confirmations of both reversals and continuations; broadening and narrowing trends, price jumps; and trends based on volume, moving averages, and momentum. Practical Trend Analysis will enable traders, both amateur and professional, to go far beyond mere trend "following." Michael C. Thomsett is a market expert, author, speaker, and coach. His many books include Stock Market Math, Candlestick Charting, and The Mathematics of Options.
A Technical Approach To Trend Analysis
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Author : Michael C. Thomsett
language : en
Publisher: FT Press
Release Date : 2015-06-24
A Technical Approach To Trend Analysis written by Michael C. Thomsett and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-24 with Business & Economics categories.
This is the only modern, action-oriented and practical guide to trend analysis and prediction for the professional trader. Unlike outdated competitive guides, it fully reflects today’s markets and charting sciences. Writing for traders with basic knowledge of trends and technical analysis, Michael C. Thomsett introduces advanced analytical tools for recognizing how risks evolve as trends proceed; distinguishing between strong and weak trends; objectively evaluating the health of a stock’s current price levels, trading breadth, and technical condition; and anticipating plateaus, slowdowns, or price reversals. Thomsett introduces trend prediction based on technical signals such as candlestick reversals, price gaps, and movement through resistance or support, enabling traders to go far beyond mere trend "following." You’ll learn techniques for gaining deeper insights into price change – and into valuable factors such as the angle of price change, trend duration, and offsetting price movements. You’ll find detailed coverage of trend theory, resistance, support, trendlines and channel lines; patterns and confirmations of both reversals and continuations; broadening and narrowing trends, price jumps; and trends based on volume, moving averages, and momentum. While other books focus solely on technical price movement, A Technical Approach to Trend Analysis will help you understand the trend itself – and use that insight to manage market risks far more effectively.
Practical Time Series Analysis
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Author : Dr. Avishek Pal
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-28
Practical Time Series Analysis written by Dr. Avishek Pal and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-28 with Computers categories.
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.
Forecasting Principles And Practice
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Author : Rob J Hyndman
language : en
Publisher: OTexts
Release Date : 2018-05-08
Forecasting Principles And Practice written by Rob J Hyndman and has been published by OTexts this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-08 with Business & Economics categories.
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Trading Price Action Trends
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Author : Al Brooks
language : en
Publisher: John Wiley & Sons
Release Date : 2025-09-03
Trading Price Action Trends written by Al Brooks and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-03 with Business & Economics categories.
A practical guide to profiting from institutional trading trends The key to being a successful trader is finding a system that works and sticking with it. Author Al Brooks has done just that. By simplifying his trading system and trading only 5-minute price charts he's found a way to capture profits regardless of market direction or economic climate. His first book, Reading Price Charts Bar by Bar, offered an informative examination of his system, but it didn't allow him to get into the real nuts and bolts of the approach. Now, with this new series of books, Brooks takes you step by step through the entire process. By breaking down his trading system into its simplest pieces: institutional piggybacking or trend trading (the topic of this particular book in the series), trading ranges, and transitions or reversals, this three book series offers access to Brooks' successful methodology. Price Action Trends Bar by Bar describes in detail what individual bars and combinations of bars can tell a trader about what institutions are doing. This is critical because the key to making money in trading is to piggyback institutions and you cannot do that unless you understand what the charts are telling you about their behavior. This book will allow you to see what type of trend is unfolding, so can use techniques that are specific to that type of trend to place the right trades. Discusses how to profit from institutional trading trends using technical analysis Outlines a detailed and original trading approach developed over the author's successful career as an independent trader Other books in the series include Price Action Trading Ranges Bar by Bar and Price Action Reversals Bar by Bar If you're looking to make the most of your time in today's markets the trading insights found in Price Action Trends Bar by Bar will help you achieve this goal.
Hydrologic Time Series Analysis
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Author : Deepesh Machiwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-05
Hydrologic Time Series Analysis written by Deepesh Machiwal 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 2012-03-05 with Science categories.
There is a dearth of relevant books dealing with both theory and application of time series analysis techniques, particularly in the field of water resources engineering. Therefore, many hydrologists and hydrogeologists face difficulties in adopting time series analysis as one of the tools for their research. This book fills this gap by providing a proper blend of theoretical and practical aspects of time sereies analysis. It deals with a comprehensive overview of time series characteristics in hydrology/water resources engineering, various tools and techniques for analyzing time series data, theoretical details of 31 available statistical tests along with detailed procedures for applying them to real-world time series data, theory and methodology of stochastic modelling, and current status of time series analysis in hydrological sciences. In adition, it demonstrates the application of most time series tests through a case study as well as presents a comparative performance evaluation of various time series tests, together with four invited case studies from India and abroad. This book will not only serve as a textbook for the students and teachers in water resources engineering but will also serve as the most comprehensive reference to educate researchers/scientists about the theory and practice of time series analysis in hydrological sciences. This book will be very useful to the students, researchers, teachers and professionals involved in water resources, hydrology, ecology, climate change, earth science, and environmental studies.
Optimal Mean Reversion Trading
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Author : Tim Leung (Professor of industrial engineering)
language : en
Publisher: World Scientific
Release Date : 2015-11-26
Optimal Mean Reversion Trading written by Tim Leung (Professor of industrial engineering) and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-26 with Business & Economics categories.
"Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications provides a systematic study to the practical problem of optimal trading in the presence of mean-reverting price dynamics. It is self-contained and organized in its presentation, and provides rigorous mathematical analysis as well as computational methods for trading ETFs, options, futures on commodities or volatility indices, and credit risk derivatives. This book offers a unique financial engineering approach that combines novel analytical methodologies and applications to a wide array of real-world examples. It extracts the mathematical problems from various trading approaches and scenarios, but also addresses the practical aspects of trading problems, such as model estimation, risk premium, risk constraints, and transaction costs. The explanations in the book are detailed enough to capture the interest of the curious student or researcher, and complete enough to give the necessary background material for further exploration into the subject and related literature. This book will be a useful tool for anyone interested in financial engineering, particularly algorithmic trading and commodity trading, and would like to understand the mathematically optimal strategies in different market environments."--
Practical Time Series Analysis
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Author : Aileen Nielsen
language : en
Publisher: O'Reilly Media
Release Date : 2019-09-20
Practical Time Series Analysis written by Aileen Nielsen and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance