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Author: Chenghu Ma
Publisher: World Scientific
ISBN: 184816632X
Category : Business & Economics
Languages : en
Pages : 818
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Book Description
This book provides a broad introduction to modern asset pricing theory. The theory is self-contained and unified in presentation. Both the no-arbitrage and the general equilibrium approaches of asset pricing theory are treated coherently within the general equilibrium framework. It fills a gap in the body of literature on asset pricing for being both advanced and comprehensive. The absence of arbitrage opportunities represents a necessary condition for equilibrium in the financial markets. However, the absence of arbitrage is not a sufficient condition for establishing equilibrium. These interrelationships are overlooked by the proponents of the no-arbitrage approach to asset pricing.This book also tackles recent advancement on inversion problems raised in asset pricing theory, which include the information role of financial options and the information content of term structure of interest rates and interest rates contingent claims.The inclusion of the proofs and derivations to enhance the transparency of the underlying arguments and conditions for the validity of the economic theory made it an ideal advanced textbook or reference book for graduate students specializing in financial economics and quantitative finance. The detailed explanations will capture the interest of the curious reader, and it is complete enough to provide the necessary background material needed to delve deeper into the subject and explore the research literature.Postgraduate students in economics with a good grasp of calculus, linear algebra, and probability and statistics will find themselves ready to tackle topics covered in this book. They will certainly benefit from the mathematical coverage in stochastic processes and stochastic differential equation with applications in finance. Postgraduate students in financial mathematics and financial engineering will also benefit, not only from the mathematical tools introduced in this book, but also from the economic ideas underpinning the economic modeling of financial markets.Both these groups of postgraduate students will learn the economic issues involved in financial modeling. The book can be used as an advanced text for Masters and PhD students in all subjects of financial economics, financial mathematics, mathematical finance, and financial engineering. It is also an ideal reference for practitioners and researchers in the subjects.
Author: Chenghu Ma
Publisher: World Scientific
ISBN: 184816632X
Category : Business & Economics
Languages : en
Pages : 818
Get Book Here
Book Description
This book provides a broad introduction to modern asset pricing theory. The theory is self-contained and unified in presentation. Both the no-arbitrage and the general equilibrium approaches of asset pricing theory are treated coherently within the general equilibrium framework. It fills a gap in the body of literature on asset pricing for being both advanced and comprehensive. The absence of arbitrage opportunities represents a necessary condition for equilibrium in the financial markets. However, the absence of arbitrage is not a sufficient condition for establishing equilibrium. These interrelationships are overlooked by the proponents of the no-arbitrage approach to asset pricing.This book also tackles recent advancement on inversion problems raised in asset pricing theory, which include the information role of financial options and the information content of term structure of interest rates and interest rates contingent claims.The inclusion of the proofs and derivations to enhance the transparency of the underlying arguments and conditions for the validity of the economic theory made it an ideal advanced textbook or reference book for graduate students specializing in financial economics and quantitative finance. The detailed explanations will capture the interest of the curious reader, and it is complete enough to provide the necessary background material needed to delve deeper into the subject and explore the research literature.Postgraduate students in economics with a good grasp of calculus, linear algebra, and probability and statistics will find themselves ready to tackle topics covered in this book. They will certainly benefit from the mathematical coverage in stochastic processes and stochastic differential equation with applications in finance. Postgraduate students in financial mathematics and financial engineering will also benefit, not only from the mathematical tools introduced in this book, but also from the economic ideas underpinning the economic modeling of financial markets.Both these groups of postgraduate students will learn the economic issues involved in financial modeling. The book can be used as an advanced text for Masters and PhD students in all subjects of financial economics, financial mathematics, mathematical finance, and financial engineering. It is also an ideal reference for practitioners and researchers in the subjects.
Author: Larry Harris
Publisher: OUP USA
ISBN: 9780195144703
Category : Business & Economics
Languages : en
Pages : 664
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Book Description
Focusing on market microstructure, Harris (chief economist, U.S. Securities and Exchange Commission) introduces the practices and regulations governing stock trading markets. Writing to be understandable to the lay reader, he examines the structure of trading, puts forward an economic theory of trading, discusses speculative trading strategies, explores liquidity and volatility, and considers the evaluation of trader performance. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).
Author: Stefan Jansen
Publisher: Packt Publishing Ltd
ISBN: 1839216786
Category : Business & Economics
Languages : en
Pages : 822
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Book Description
Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
Author: David Halsey
Publisher: John Wiley & Sons
ISBN: 1118283325
Category : Business & Economics
Languages : en
Pages : 228
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Book Description
A timely guide to profiting in markets dominated by high frequency trading and other computer driven strategies Strategies employing complex computer algorithms, and often utilizing high frequency trading tactics, have placed individual traders at a significant disadvantage in today's financial markets. It's been estimated that high-frequency traders—one form of computerized trading—accounts for more than half of each day's total equity market trades. In this environment, individual traders need to learn new techniques that can help them navigate modern markets and avoid being whipsawed by larger, institutional players. Trading the Measured Move offers a blueprint for profiting from the price waves created by computer-driven algorithmic and high-frequency trading strategies. The core of author David Halsey's approach is a novel application of Fibonnaci retracements, which he uses to set price targets and low-risk entry points. When properly applied, it allows traders to gauge market sentiment, recognize institutional participation at specific support and resistance levels, and differentiate between short-term and long-term trades at various price points in the market. Provides guidance for individual traders who fear they can't compete in today's high-frequency dominated markets Outlines specific trade set ups, including opening gap strategies, breakouts and failed breakout strategies, range trading strategies, and pivot trading strategies Reveals how to escape institutional strategies designed to profit from slower-moving market participants Engaging and informative, Trading the Measured Move will provide you with a new perspective, and new strategies, to successfully navigate today's computer driven financial markets
Author: Maria Zervou
Publisher: Packt Publishing Ltd
ISBN: 1837632901
Category : Computers
Languages : en
Pages : 456
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Book Description
Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable dataset Key Features Maximize the value of your data through effective data cleaning methods Enhance your data skills using strategies for handling structured and unstructured data Elevate the quality of your data products by testing and validating your data pipelines Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionProfessionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone. To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio. By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.What you will learn Ingest data from different sources and write it to the required sinks Profile and validate data pipelines for better quality control Get up to speed with grouping, merging, and joining structured data Handle missing values and outliers in structured datasets Implement techniques to manipulate and transform time series data Apply structure to text, image, voice, and other unstructured data Who this book is for Whether you're a data analyst, data engineer, data scientist, or a data professional responsible for data preparation and cleaning, this book is for you. Working knowledge of Python programming is needed to get the most out of this book.
Author: CFA Institute
Publisher: John Wiley & Sons
ISBN: 1119743699
Category : Business & Economics
Languages : en
Pages : 1335
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Book Description
Portfolio Management in Practice, Volume 1: Investment Management delivers a comprehensive overview of investment management for students and industry professionals. As the first volume in the CFA Institute’s new Portfolio Management in Practice series, Investment Management offers professionals looking to enhance their skillsets and students building foundational knowledge an essential understanding of key investment management concepts. Designed to be an accessible resource for a wide range of learners, this volume explores the full portfolio management process. Inside, readers will find detailed coverage of: Forming capital market expectations Principles of the asset allocation process Determining investment strategies within each asset class Integrating considerations specific to high net worth individuals or institutions into chosen strategies And more To apply the concepts outlined in the Investment Management volume, explore the accompanying Portfolio Management in Practice, Volume 1: Investment Management Workbook. The perfect companion resource, this workbook aligns chapter-by-chapter with Investment Management for easy referencing so readers can draw connections between theoretical content and challenging practice problems. Featuring contributions from the CFA Institute’s subject matter experts, Portfolio Management in Practice, Volume 1: Investment Management distills the knowledge forward-thinking professionals will need to succeed in today’s fast-paced financial world.
Author: Irene Aldridge
Publisher: John Wiley & Sons
ISBN: 1118416821
Category : Business & Economics
Languages : en
Pages : 326
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Book Description
A fully revised second edition of the best guide to high-frequency trading High-frequency trading is a difficult, but profitable, endeavor that can generate stable profits in various market conditions. But solid footing in both the theory and practice of this discipline are essential to success. Whether you're an institutional investor seeking a better understanding of high-frequency operations or an individual investor looking for a new way to trade, this book has what you need to make the most of your time in today's dynamic markets. Building on the success of the original edition, the Second Edition of High-Frequency Trading incorporates the latest research and questions that have come to light since the publication of the first edition. It skillfully covers everything from new portfolio management techniques for high-frequency trading and the latest technological developments enabling HFT to updated risk management strategies and how to safeguard information and order flow in both dark and light markets. Includes numerous quantitative trading strategies and tools for building a high-frequency trading system Address the most essential aspects of high-frequency trading, from formulation of ideas to performance evaluation The book also includes a companion Website where selected sample trading strategies can be downloaded and tested Written by respected industry expert Irene Aldridge While interest in high-frequency trading continues to grow, little has been published to help investors understand and implement this approach—until now. This book has everything you need to gain a firm grip on how high-frequency trading works and what it takes to apply it to your everyday trading endeavors.
Author: Long Cheng
Publisher: Springer
ISBN: 3030042219
Category : Computers
Languages : en
Pages : 590
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Book Description
The seven-volume set of LNCS 11301-11307 constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 5th volume, LNCS 11305, is organized in topical sections on prediction; pattern recognition; and word, text and document processing.
Author: Y. Zhang
Publisher: Springer
ISBN: 1137372591
Category : Business & Economics
Languages : en
Pages : 301
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Book Description
Stock Message Boards provides empirical data to reveal how online communication not only impacts stock returns, but also volatility, trading volume, and liquidity, as well as an investing firm's value and reputation.
Author: David Lee Kuo Chuen
Publisher: Elsevier
ISBN: 0323989748
Category : Business & Economics
Languages : en
Pages : 732
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Book Description
Handbook of Digital Currency: Bitcoin, Innovation, Financial Instruments, and Big Data, Second Edition offers readers new ways to learn about subjects outside their specialties and provides authoritative background and tools for those whose primary source of information is journal articles. Encompassing currencies, payment methods, and computer communication protocols, digital currencies are growing in use and importance. The book's comprehensive view of the field covers history, technical, IT, finance, economics, legal, tax, and the regulatory environment. For those coming from different backgrounds with different questions in mind, this new edition is an essential starting point. - Discusses all major strategies and tactics associated with digital currencies, their uses, and their regulations - Presents future scenarios for the growth of digital currencies - Offers seven new chapters covering such topics as side chains, sharding, privacy protection and CBDC, Libra and the convergence of technology, and much more
