The Science of Algorithmic Trading and Portfolio Management

• Author : Robert Kissell
• Publisher : Academic Press
• Release : 01 October 2013

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

• Author : Robert L. Kissell
• Publisher : Academic Press
• Release : 08 September 2020

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,

• Author : Satya Chakravarty,Palash Sarkar
• Publisher : Emerald Group Publishing
• Release : 20 August 2020

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.

• Author : Yves Hilpisch
• Publisher : O'Reilly Media
• Release : 12 November 2020

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

• Author : Brian Bruce
• Publisher : Academic Press
• Release : 29 July 2020

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

• Author : Morton Glantz,Robert Kissell
• Publisher : Academic Press
• Release : 03 December 2013

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

• Author : Ondrej Jaško,Sanja Marinković
• Publisher : University of Belgrade, Faculty of Organizational Sciences
• Release : 03 June 2016

• Author : Abhaya C. Nayak,Alok Sharma
• Publisher : Springer Nature
• Release : 22 August 2019

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.

• Author : Robert L. Kissell,James Poserina
• Publisher : Academic Press
• Release : 06 April 2017

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

• Author : John Hill
• Publisher : Academic Press
• Release : 30 January 2020

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

• Author : Stefan Jansen
• Publisher : Packt Publishing Ltd
• Release : 31 December 2018

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook 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

• Author : Andrew Pole
• Publisher : John Wiley & Sons
• Release : 07 July 2011

While statistical arbitrage has faced some tough times?as markets experienced dramatic changes in dynamics beginning in 2000?new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Pole?s own research and experience running a statistical arbitrage hedge fund for eight years?in partnership with a group whose own history stretches back to the dawn of what was first called pairs trading?this unique guide provides detailed

• Author : Kendall Kim
• Publisher : Academic Press
• Release : 27 July 2010

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

• Author : Clive M. Corcoran
• Publisher : John Wiley & Sons
• Release : 06 February 2007

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

• Author : Sophia Foster
• Publisher : Unknown
• Release : 24 May 2021

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,