The Science Of Algorithmic Trading And Portfolio Management

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The Science of Algorithmic Trading and Portfolio Management

Robert Kissell
The Science of Algorithmic Trading and Portfolio Management Book PDF

Author : Robert Kissell
Publisher : Academic Press
Page : 496 pages
File Size : 54,6 Mb
Release : 2013-10-01
Category : Business & Economics
ISBN : 9780124016934

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The Science of Algorithmic Trading and Portfolio Management by Robert Kissell Pdf

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

Robert Kissell
Algorithmic Trading Methods Book PDF

Author : Robert Kissell
Publisher : Academic Press
Page : 614 pages
File Size : 54,6 Mb
Release : 2020-09-08
Category : Business & Economics
ISBN : 9780128156315

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Algorithmic Trading Methods by Robert Kissell Pdf

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

Machine Learning for Algorithmic Trading

Stefan Jansen
Machine Learning for Algorithmic Trading Book PDF

Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Page : 822 pages
File Size : 51,9 Mb
Release : 2020-07-31
Category : Business & Economics
ISBN : 9781839216787

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Machine Learning for Algorithmic Trading by Stefan Jansen Pdf

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.

Statistical Arbitrage

Andrew Pole
Statistical Arbitrage Book PDF

Author : Andrew Pole
Publisher : John Wiley & Sons
Page : 230 pages
File Size : 51,9 Mb
Release : 2011-07-07
Category : Business & Economics
ISBN : 9781118160732

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Statistical Arbitrage by Andrew Pole Pdf

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 insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.

Algorithmic Trading

Ernie Chan
Algorithmic Trading Book PDF

Author : Ernie Chan
Publisher : John Wiley & Sons
Page : 230 pages
File Size : 40,7 Mb
Release : 2013-05-21
Category : Business & Economics
ISBN : 9781118746912

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Algorithmic Trading by Ernie Chan Pdf

Praise for Algorithmic TRADING “Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded. This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers.” —DAREN SMITH, CFA, CAIA, FSA, Managing Director, Manager Selection & Portfolio Construction, University of Toronto Asset Management “Using an excellent selection of mean reversion and momentum strategies, Ernie explains the rationale behind each one, shows how to test it, how to improve it, and discusses implementation issues. His book is a careful, detailed exposition of the scientific method applied to strategy development. For serious retail traders, I know of no other book that provides this range of examples and level of detail. His discussions of how regime changes affect strategies, and of risk management, are invaluable bonuses.” —ROGER HUNTER, Mathematician and Algorithmic Trader

Quantitative Portfolio Management

Michael Isichenko
Quantitative Portfolio Management Book PDF

Author : Michael Isichenko
Publisher : John Wiley & Sons
Page : 306 pages
File Size : 42,5 Mb
Release : 2021-09-10
Category : Business & Economics
ISBN : 9781119821212

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Quantitative Portfolio Management by Michael Isichenko Pdf

Discover foundational and advanced techniques in quantitative equity trading from a veteran insider In Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage, distinguished physicist-turned-quant Dr. Michael Isichenko delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn patterns of asset returns from historical data, generate and combine multiple forecasts, manage risk, build a stock portfolio optimized for risk and trading costs, and execute trades. In this important book, you’ll discover: Machine learning methods of forecasting stock returns in efficient financial markets How to combine multiple forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as “benign overfitting” in machine learning The theoretical and practical aspects of portfolio construction, including multi-factor risk models, multi-period trading costs, and optimal leverage Perfect for investment professionals, like quantitative traders and portfolio managers, Quantitative Portfolio Management will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data science, machine learning, and optimization to the stock market.

Python for Finance and Algorithmic Trading

Lucas INGLESE
Python for Finance and Algorithmic Trading Book PDF

Author : Lucas INGLESE
Publisher : Unknown
Page : 285 pages
File Size : 44,5 Mb
Release : 2021-09-25
Category : Electronic
ISBN : 9798451749241

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Python for Finance and Algorithmic Trading by Lucas INGLESE Pdf

The financial sector is undergoing significant restructuring. Traders and portfolio managers are increasingly becoming financial data scientists. Banks, investment funds, and fintech are increasingly automating their investments by integrating machine learning and deep learning algorithms into their decision-making process. The book presents the benefits of portfolio management, statistics, and machine learning applied to live trading with MetaTrader 5. *Learn portfolio management technics and how to implement your optimization criterion *How to backtest a strategy using the most valuable metrics in trading *Import data from your broker to be as close as possible to the market *Learn statistical arbitrage through pair trading strategies *Generate market predictions using machine learning, deep learning, and time series analysis *Learn how to find the best take profit, stop loss, and leverage for your strategies *Combine trading strategies using portfolio management to increase the robustness of the strategies *Connect your Python algorithm to your MetaTrader 5 and run it with a demo or live trading account *Use all codes in the book for live trading or screener if you prefer manual trading

Hands-On Machine Learning for Algorithmic Trading

Stefan Jansen
Hands On Machine Learning for Algorithmic Trading Book PDF

Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Page : 668 pages
File Size : 53,7 Mb
Release : 2018-12-31
Category : Computers
ISBN : 9781789342710

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Hands-On Machine Learning for Algorithmic Trading by Stefan Jansen Pdf

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 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 learnImplement machine learning techniques to solve investment and trading problemsLeverage market, fundamental, and alternative data to research alpha factorsDesign and fine-tune supervised, unsupervised, and reinforcement learning modelsOptimize portfolio risk and performance using pandas, NumPy, and scikit-learnIntegrate machine learning models into a live trading strategy on QuantopianEvaluate strategies using reliable backtesting methodologies for time seriesDesign and evaluate deep neural networks using Keras, PyTorch, and TensorFlowWork with reinforcement learning for trading strategies in the OpenAI GymWho 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.

Python for Algorithmic Trading

Yves Hilpisch
Python for Algorithmic Trading Book PDF

Author : Yves Hilpisch
Publisher : O'Reilly Media
Page : 380 pages
File Size : 42,5 Mb
Release : 2020-11-12
Category : Computers
ISBN : 9781492053323

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Python for Algorithmic Trading by Yves Hilpisch Pdf

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

An Introduction to Algorithmic Finance, Algorithmic Trading and Blockchain

Satya Chakravarty,Palash Sarkar
An Introduction to Algorithmic Finance Algorithmic Trading and Blockchain Book PDF

Author : Satya Chakravarty,Palash Sarkar
Publisher : Emerald Group Publishing
Page : 208 pages
File Size : 43,9 Mb
Release : 2020-08-20
Category : Business & Economics
ISBN : 9781789738933

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An Introduction to Algorithmic Finance, Algorithmic Trading and Blockchain by Satya Chakravarty,Palash Sarkar Pdf

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.

Quantitative Trading

Ernest P. Chan
Quantitative Trading Book PDF

Author : Ernest P. Chan
Publisher : Unknown
Page : 181 pages
File Size : 50,9 Mb
Release : 2009
Category : Investment analysis
ISBN : 1119203376

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Quantitative Trading by Ernest P. Chan Pdf

"While institutional traders continue to implement quantitative (or algorithmic) trading, many independent traders have wondered if they can still challenge powerful industry professionals at their own game? The answer is "yes," and in Quantitative Trading, Dr. Ernest Chan, a respected independent trader and consultant, will show you how. Whether you're an independent "retail" trader looking to start your own quantitative trading business or an individual who aspires to work as a quantitative trader at a major financial institution, this practical guide contains the information you need to succeed"--Resource description page.

High-Frequency Trading

Irene Aldridge
High Frequency Trading Book PDF

Author : Irene Aldridge
Publisher : John Wiley & Sons
Page : 326 pages
File Size : 48,6 Mb
Release : 2013-04-22
Category : Business & Economics
ISBN : 9781118343500

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High-Frequency Trading by Irene Aldridge Pdf

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.

Electronic and Algorithmic Trading Technology

Kendall Kim
Electronic and Algorithmic Trading Technology Book PDF

Author : Kendall Kim
Publisher : Academic Press
Page : 224 pages
File Size : 54,8 Mb
Release : 2010-07-27
Category : Business & Economics
ISBN : 0080548865

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Electronic and Algorithmic Trading Technology by Kendall Kim Pdf

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

Algorithmic Trading 2021: The Best Guide to Developing Winning Trading Strategies Using Financial Machine Learning

Collane LV
Algorithmic Trading 2021 The Best Guide to Developing Winning Trading Strategies Using Financial Machine Learning Book PDF

Author : Collane LV
Publisher : Unknown
Page : 124 pages
File Size : 54,6 Mb
Release : 2021-11-07
Category : Business & Economics
ISBN : 1803342579

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Algorithmic Trading 2021: The Best Guide to Developing Winning Trading Strategies Using Financial Machine Learning by Collane LV Pdf

For decades, stock trading was locked behind the door of wealth and exclusivity. When that door opened with the introduction of online trading platforms and discount brokers, a flood of new investors and traders entered the market exchange. In many ways, the introduction of discount brokers and online trading platforms was a breath of fresh air. It opened up the market and boosted our global economy. It also gave everyone with a bit of cash and an internet connection the opportunity to grow their wealth. However, when you're just starting out in trading and investment, the world of financial investments can be quite overwhelming, especially if you're starting without much guidance, which is the case with discount brokers. After all, as a newbie, how do you know what to invest in, how to invest, and when to invest? Well, when embarking on any new venture, the first thing most of us tend to do is jump into some research. In the time before Google, research often meant pouring over large texts and getting yourself dusty in the library. We're glad to say that those days are long gone. With increasingly sophisticated technological advancements, trading no longer needs to be a daunting task. These days, there are paper trading accounts and online webinars, all of which are aimed at helping beginners land on their feet. When you've traversed the financial markets for a bit, you'll be exposed to a plethora of trading techniques, methods, and strategies that you can use when interacting with financial markets. These methods and strategies come in all shapes and sizes and are suited toward every level of expertise there is. If you're a bit more tech-savvy and are looking to jump into trading and investment, algorithmic trading might be the perfect way to navigate the financial market. If you're reading this book, chances are pretty high that you've heard about algorithmic trading and are interested in exploring it as a possible avenue of trade and investment. But, as with all things concerning finance, you know that you should be doing your research before jumping in. That's where we come in. This book is aimed at discussing the basics of algorithmic trading and helping you use algo trading as a means of managing your investment portfolio. We're here to answer questions like whether algo trading is better than manual trading and if algo trading even works. In short, this book is a crash course on algorithmic trading and covers things like the basics of algo trading, its uses, risks and benefits, and how to get started

Algorithmic Short Selling with Python

Laurent Bernut,Michael Covel
Algorithmic Short Selling with Python Book PDF

Author : Laurent Bernut,Michael Covel
Publisher : Packt Publishing Ltd
Page : 377 pages
File Size : 42,8 Mb
Release : 2021-09-30
Category : Business & Economics
ISBN : 9781801810395

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Algorithmic Short Selling with Python by Laurent Bernut,Michael Covel Pdf

Leverage Python source code to revolutionize your short selling strategy and to consistently make profits in bull, bear, and sideways markets Key Features Understand techniques such as trend following, mean reversion, position sizing, and risk management in a short-selling context Implement Python source code to explore and develop your own investment strategy Test your trading strategies to limit risk and increase profits Book Description If you are in the long/short business, learning how to sell short is not a choice. Short selling is the key to raising assets under management. This book will help you demystify and hone the short selling craft, providing Python source code to construct a robust long/short portfolio. It discusses fundamental and advanced trading concepts from the perspective of a veteran short seller. This book will take you on a journey from an idea (“buy bullish stocks, sell bearish ones”) to becoming part of the elite club of long/short hedge fund algorithmic traders. You'll explore key concepts such as trading psychology, trading edge, regime definition, signal processing, position sizing, risk management, and asset allocation, one obstacle at a time. Along the way, you'll will discover simple methods to consistently generate investment ideas, and consider variables that impact returns, volatility, and overall attractiveness of returns. By the end of this book, you'll not only become familiar with some of the most sophisticated concepts in capital markets, but also have Python source code to construct a long/short product that investors are bound to find attractive. What you will learn Develop the mindset required to win the infinite, complex, random game called the stock market Demystify short selling in order to generate alpa in bull, bear, and sideways markets Generate ideas consistently on both sides of the portfolio Implement Python source code to engineer a statistically robust trading edge Develop superior risk management habits Build a long/short product that investors will find appealing Who this book is for This is a book by a practitioner for practitioners. It is designed to benefit a wide range of people, including long/short market participants, quantitative participants, proprietary traders, commodity trading advisors, retail investors (pro retailers, students, and retail quants), and long-only investors. At least 2 years of active trading experience, intermediate-level experience of the Python programming language, and basic mathematical literacy (basic statistics and algebra) are expected.