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The Science Of Algorithmic Trading And Portfolio Management

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The Science of Algorithmic Trading and Portfolio Management

The Science of Algorithmic Trading and Portfolio Management Book
Author : Robert Kissell
Publisher : Academic Press
Release : 2013-10-01
ISBN : 0124016936
Language : En, Es, Fr & De

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Book Description :

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. Helps readers design systems to manage algorithmic risk and dark pool uncertainty. Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.

Algorithmic Trading Methods

Algorithmic Trading Methods Book
Author : Robert Kissell
Publisher : Academic Press
Release : 2020-09-08
ISBN : 0128156317
Language : En, Es, Fr & De

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Book Description :

Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Trading and Portfolio Management. This edition includes new chapters on algorithmic trading, advanced trading analytics, regression analysis, optimization, and advanced statistical methods. Increasing its focus on trading strategies and models, this edition includes new insights into the ever-changing financial environment, pre-trade and post-trade analysis, liquidation cost & risk analysis, and compliance and regulatory reporting requirements. Highlighting new investment techniques, this book includes material to assist in the best execution process, model validation, quality and assurance testing, limit order modeling, and smart order routing analysis. Includes advanced modeling techniques using machine learning, predictive analytics, and neural networks. The text provides readers with a suite of transaction cost analysis functions packaged as a TCA library. These programming tools are accessible via numerous software applications and programming languages. Provides insight into all necessary components of algorithmic trading including: transaction cost analysis, market impact estimation, risk modeling and optimization, and advanced examination of trading algorithms and corresponding data requirements. Increased coverage of essential mathematics, probability and statistics, machine learning, predictive analytics, and neural networks, and applications to trading and finance. Advanced multiperiod trade schedule optimization and portfolio construction techniques. Techniques to decode broker-dealer and third-party vendor models. Methods to incorporate TCA into proprietary alpha models and portfolio optimizers. TCA library for numerous software applications and programming languages including: MATLAB, Excel Add-In, Python, Java, C/C++, .Net, Hadoop, and as standalone .EXE and .COM applications.

Hands On Machine Learning for Algorithmic Trading

Hands On Machine Learning for Algorithmic Trading Book
Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Release : 2018-12-31
ISBN : 1789342716
Language : En, Es, Fr & De

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Book Description :

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement learning models Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn Integrate machine learning models into a live trading strategy on Quantopian Evaluate strategies using reliable backtesting methodologies for time series Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

An Introduction to Algorithmic Finance Algorithmic Trading and Blockchain

An Introduction to Algorithmic Finance  Algorithmic Trading and Blockchain Book
Author : Satya Chakravarty,Palash Sarkar
Publisher : Emerald Group Publishing
Release : 2020-08-20
ISBN : 1789738938
Language : En, Es, Fr & De

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Book Description :

The purpose of the book is to provide a broad-based accessible introduction to three of the presently most important areas of computational finance, namely, option pricing, algorithmic trading and blockchain. This will provide a basic understanding required for a career in the finance industry and for doing more specialised courses in finance.

Python for Algorithmic Trading

Python for Algorithmic Trading Book
Author : Yves Hilpisch
Publisher : O'Reilly Media
Release : 2020-11-12
ISBN : 1492053325
Language : En, Es, Fr & De

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Book Description :

Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

Student Managed Investment Funds

Student Managed Investment Funds Book
Author : Brian Bruce
Publisher : Academic Press
Release : 2020-07-29
ISBN : 0128178671
Language : En, Es, Fr & De

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Book Description :

Student-Managed Investment Funds: Organization, Policy, and Portfolio Management, Second Edition, helps students work within a structured investment management organization, whatever that organizational structure might be. It aids them in developing an appreciation for day-to-day fund operations (e.g., how to get portfolio trade ideas approved, how to execute trades, how to reconcile investment performance), and it addresses the management of the portfolio and the valuation/selection process for discriminating between securities. No other book covers the "operational" related issues in SMIFs, like organizations, tools, data, presentation, and performance evaluation. With examples of investment policy statements, presentation slides, and organizational structures from other schools, Student-Managed Investment Funds can be used globally by students, instructors, and administrators alike. Addresses the basics of valuation as well as issues related to maintaining compliance, philosophy, performance measurement, and evaluation Provides explanations and examples about organizing a student-managed fund Reviews fundamental stock valuation approaches like multi-stage DDM, FCF, and price multiples

Algorithmic Trading

Algorithmic Trading Book
Author : Sophia Foster
Publisher : Unknown
Release : 2021-05-24
ISBN : 9781801567640
Language : En, Es, Fr & De

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Book Description :

Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Trading and Portfolio Management. This edition includes new chapters on algorithmic trading, advanced trading analytics, regression analysis, optimization, and advanced statistical methods. Increasing its focus on trading strategies and models, this edition includes new insights into the ever-changing financial environment, pre-trade and post-trade analysis, liquidation cost & risk analysis, and compliance and regulatory reporting requirements. Highlighting new investment techniques, this book includes material to assist in the best execution process, model validation, quality and assurance testing, limit order modeling, and smart order routing analysis. Includes advanced modeling techniques using machine learning, predictive analytics, and neural networks. The text provides readers with a suite of transaction cost analysis functions packaged as a TCA library. These programming tools are accessible via numerous software applications and programming languages.

Symposium proceedings XV International symposium Symorg 2016

Symposium proceedings   XV International symposium Symorg 2016 Book
Author : Ondrej Jaško,Sanja Marinković
Publisher : University of Belgrade, Faculty of Organizational Sciences
Release : 2016-06-03
ISBN : 8676803269
Language : En, Es, Fr & De

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Book Description :

Download Symposium proceedings XV International symposium Symorg 2016 book written by Ondrej Jaško,Sanja Marinković, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Machine Learning and Data Science Blueprints for Finance

Machine Learning and Data Science Blueprints for Finance Book
Author : Hariom Tatsat,Sahil Puri,Brad Lookabaugh
Publisher : "O'Reilly Media, Inc."
Release : 2020-10-01
ISBN : 1492073008
Language : En, Es, Fr & De

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Book Description :

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

PRICAI 2019 Trends in Artificial Intelligence

PRICAI 2019  Trends in Artificial Intelligence Book
Author : Abhaya C. Nayak,Alok Sharma
Publisher : Springer Nature
Release : 2019-08-22
ISBN : 3030298949
Language : En, Es, Fr & De

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Book Description :

This three-volume set LNAI 11670, LNAI 11671, and LNAI 11672 constitutes the thoroughly refereed proceedings of the 16th Pacific Rim Conference on Artificial Intelligence, PRICAI 2019, held in Cuvu, Yanuca Island, Fiji, in August 2019. The 111 full papers and 13 short papers presented in these volumes were carefully reviewed and selected from 265 submissions. PRICAI covers a wide range of topics such as AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim.

Environmental Social and Governance ESG Investing

Environmental  Social  and Governance  ESG  Investing Book
Author : John Hill
Publisher : Academic Press
Release : 2020-01-30
ISBN : 0128186933
Language : En, Es, Fr & De

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Book Description :

Environmental, Social, and Governance (ESG) Investing: A Balanced Analysis of the Theory and Practice of a Sustainable Portfolio presents a balanced, thorough analysis of ESG factors as they are incorporated into the investment process. An estimated 25% of all new investments are in ESG funds, with a global total of $23 trillion and the U.S. accounting for almost $9 trillion. Many advocate the sustainability goals promoted by ESG, while others prefer to maximize returns and spend their earnings on social causes. The core problem facing those who want to promote sustainability goals is to define sustainability investing and measure its returns. This book examines theories and their practical implications, illuminating issues that other books leave in the shadows. Provides a dispassionate examination of ESG investing Presents the historical arguments for maximizing returns and competing theories to support an ESG approach Reviews case studies of empirical evidence about relative returns of both traditional and ESG investment approaches

Optimal Sports Math Statistics and Fantasy

Optimal Sports Math  Statistics  and Fantasy Book
Author : Robert L. Kissell,James Poserina
Publisher : Academic Press
Release : 2017-04-06
ISBN : 0128052937
Language : En, Es, Fr & De

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Book Description :

Optimal Sports Math, Statistics, and Fantasy provides the sports community—students, professionals, and casual sports fans—with the essential mathematics and statistics required to objectively analyze sports teams, evaluate player performance, and predict game outcomes. These techniques can also be applied to fantasy sports competitions. Readers will learn how to: Accurately rank sports teams Compute winning probability Calculate expected victory margin Determine the set of factors that are most predictive of team and player performance Optimal Sports Math, Statistics, and Fantasy also illustrates modeling techniques that can be used to decode and demystify the mysterious computer ranking schemes that are often employed by post-season tournament selection committees in college and professional sports. These methods offer readers a verifiable and unbiased approach to evaluate and rank teams, and the proper statistical procedures to test and evaluate the accuracy of different models. Optimal Sports Math, Statistics, and Fantasy delivers a proven best-in-class quantitative modeling framework with numerous applications throughout the sports world. Statistical approaches to predict winning team, probabilities, and victory margin Procedures to evaluate the accuracy of different models Detailed analysis of how mathematics and statistics are used in a variety of different sports Advanced mathematical applications that can be applied to fantasy sports, player evaluation, salary negotiation, team selection, and Hall of Fame determination

Reform and Price Discovery at the Tokyo Stock Exchange From 1990 to 2012

Reform and Price Discovery at the Tokyo Stock Exchange  From 1990 to 2012 Book
Author : K. Kubota,H. Takehara
Publisher : Springer
Release : 2015-04-30
ISBN : 1137540397
Language : En, Es, Fr & De

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Book Description :

In the last two decades the Tokyo Stock Exchange implemented several important reforms in regulations, market trading mechanisms, and IT trading systems. In this book we analyze the impact of the evolution of the Tokyo Stock Exchange (TSE), at the same time discussing reforms in stock trading by related accounting standards and legal regulations. With daily stock return and market microstructure data, we analyze how these reforms have significantly influenced the pricing structure and price discovery process of traded stocks, as well as the trading style of institutional investors, individual investors, and high frequency traders. The research methodology we employ is primarily standard market microstructure tests as well as methods used in conventional empirical financial economics. We simultaneously use the most relevant concepts in these fields for our empirical tests and provide a comprehensive picture of trading, price discovery, pricing structure, and public vs. private information dissemination.

Machine Learning for Algorithmic Trading

Machine Learning for Algorithmic Trading Book
Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Release : 2020-07-31
ISBN : 1839216786
Language : En, Es, Fr & De

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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. Key Features Design, train, and evaluate machine learning algorithms that underpin automated trading strategies Create a research and strategy development process to apply predictive modeling to trading decisions Leverage NLP and deep learning to extract tradeable signals from market and alternative data Book 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 learn Leverage market, fundamental, and alternative text and image data Research and evaluate alpha factors using statistics, Alphalens, and SHAP values Implement machine learning techniques to solve investment and trading problems Backtest and evaluate trading strategies based on machine learning using Zipline and Backtrader Optimize portfolio risk and performance analysis using pandas, NumPy, and pyfolio Create a pairs trading strategy based on cointegration for US equities and ETFs Train a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes data Who 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.

Long Short Market Dynamics

Long Short Market Dynamics Book
Author : Clive M. Corcoran
Publisher : John Wiley & Sons
Release : 2007-02-06
ISBN : 0470065311
Language : En, Es, Fr & De

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Book Description :

Hedge funds are now the largest volume players in the capital markets. They follow a wide assortment of strategies but their activities have replaced and overshadowed the traditional model of the long only portfolio manager. Many of the traditional technical indicators and commonly accepted trading strategies have become obsolete or ineffective. The focus throughout the book is to describe the principal innovations that have been made within the equity markets over the last several years and that have changed the ground rules for trading activities. By understanding these changes the active trader is far better equipped to profit in today’s more complex and risky markets. Long/Short Market Dynamics includes: A completely new technique, Comparative Quantiles Analysis, for identifying market turning points is introduced. It is based on statistical techniques that can be used to recognize money flow and price/momentum divergences that can provide substantial profit opportunities. Power laws, regime shifts, self-organized criticality, phase transitions, network dynamics, econophysics, algorithmic trading and other ideas from the science of complexity are examined. All are described as concretely as possible and avoiding unnecessary mathematics and formalism. Alpha generation, portfolio construction, hedge ratios, and beta neutral portfolios are illustrated with case studies and worked examples. Episodes of financial contagion are illustrated with a proposed explanation of their origins within underlying market dynamics

Multi Asset Risk Modeling

Multi Asset Risk Modeling Book
Author : Morton Glantz,Robert Kissell
Publisher : Academic Press
Release : 2013-12-03
ISBN : 0124016944
Language : En, Es, Fr & De

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Book Description :

Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management. Covers all asset classes Provides mathematical theoretical explanations of risk as well as practical examples with empirical data Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities

Handbook of High Frequency Trading

Handbook of High Frequency Trading Book
Author : Greg N. Gregoriou
Publisher : Academic Press
Release : 2015-02-10
ISBN : 0128023627
Language : En, Es, Fr & De

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Book Description :

This comprehensive examination of high frequency trading looks beyond mathematical models, which are the subject of most HFT books, to the mechanics of the marketplace. In 25 chapters, researchers probe the intricate nature of high frequency market dynamics, market structure, back-office processes, and regulation. They look deeply into computing infrastructure, describing data sources, formats, and required processing rates as well as software architecture and current technologies. They also create contexts, explaining the historical rise of automated trading systems, corresponding technological advances in hardware and software, and the evolution of the trading landscape. Developed for students and professionals who want more than discussions on the econometrics of the modelling process, The Handbook of High Frequency Trading explains the entirety of this controversial trading strategy. Answers all questions about high frequency trading without being limited to mathematical modelling Illuminates market dynamics, processes, and regulations Explains how high frequency trading evolved and predicts its future developments

Machine Learning for Algorithmic Trading Second Edition

Machine Learning for Algorithmic Trading   Second Edition Book
Author : Stefan Jansen
Publisher : Unknown
Release : 2020-07-31
ISBN : 9781839217715
Language : En, Es, Fr & De

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Book Description :

Download Machine Learning for Algorithmic Trading Second Edition book written by Stefan Jansen, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Recent Advances and Applications in Alternative Investments

Recent Advances and Applications in Alternative Investments Book
Author : Zopounidis, Constantin,Kenourgios, Dimitris,Dotsis, George
Publisher : IGI Global
Release : 2020-02-07
ISBN : 1799824381
Language : En, Es, Fr & De

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Book Description :

In recent years, there has been a swell of investment opportunities in contemporary asset classes that have gained considerable attention, including cryptocurrencies, hedge funds, and private equity. These alternative investments provide the opportunity to enhance the diversification of financial portfolios and harvest risk premiums that traditional assets like stocks and bonds fail to provide. The emergence of these new properties has created the need to further understand the mechanics, risks, and returns of alternative investments. Recent Advances and Applications in Alternative Investments is a pivotal reference source that provides vital research on the emergence and development of complementary asset classes in the field of finance and investment. While highlighting topics such as carbon emission markets, renewable energy, and digital currencies, this publication explores modern investment strategies as well as the latest products and new types of risk. This book is ideally designed for managers, strategists, accountants, financial professionals, economists, brokers, investors, business practitioners, policymakers, researchers, and academicians seeking current research on contemporary developments in investment strategies and alternative assets.

Electronic and Algorithmic Trading Technology

Electronic and Algorithmic Trading Technology Book
Author : Kendall Kim
Publisher : Academic Press
Release : 2010-07-27
ISBN : 9780080548869
Language : En, Es, Fr & De

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Book Description :

Electronic and algorithmic trading has become part of a mainstream response to buy-side traders’ need to move large blocks of shares with minimum market impact in today’s complex institutional trading environment. This book illustrates an overview of key providers in the marketplace. With electronic trading platforms becoming increasingly sophisticated, more cost effective measures handling larger order flow is becoming a reality. The higher reliance on electronic trading has had profound implications for vendors and users of information and trading products. Broker dealers providing solutions through their products are facing changes in their business models such as: relationships with sellside customers, relationships with buyside customers, the importance of broker neutrality, the role of direct market access, and the relationship with prime brokers. Electronic and Algorithmic Trading Technology: The Complete Guide is the ultimate guide to managers, institutional investors, broker dealers, and software vendors to better understand innovative technologies that can cut transaction costs, eliminate human error, boost trading efficiency and supplement productivity. As economic and regulatory pressures are driving financial institutions to seek efficiency gains by improving the quality of software systems, firms are devoting increasing amounts of financial and human capital to maintaining their competitive edge. This book is written to aid the management and development of IT systems for financial institutions. Although the book focuses on the securities industry, its solution framework can be applied to satisfy complex automation requirements within very different sectors of financial services – from payments and cash management, to insurance and securities. Electronic and Algorithmic Trading: The Complete Guide is geared toward all levels of technology, investment management and the financial service professionals responsible for developing and implementing cutting-edge technology. It outlines a complete framework for successfully building a software system that provides the functionalities required by the business model. It is revolutionary as the first guide to cover everything from the technologies to how to evaluate tools to best practices for IT management. First book to address the hot topic of how systems can be designed to maximize the benefits of program and algorithmic trading Outlines a complete framework for developing a software system that meets the needs of the firm's business model Provides a robust system for making the build vs. buy decision based on business requirements