Something Interesting to Read - page 11

Sergey Golubev  
Advances in Financial Machine Learning

by Marcos López de Prado

Advances in Financial Machine Learning

Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest.

In the book, readers will learn how to:

  • Structure big data in a way that is amenable to ML algorithms
  • Conduct research with ML algorithms on big data
  • Use supercomputing methods and back test their discoveries while avoiding false positives
Sergey Golubev  
Quantitative Technical Analysis: An integrated approach to trading system development and trading management

by Dr Howard B Bandy

Quantitative Technical Analysis: An integrated approach to trading system development and trading management

I have 4 of Howard's books on my bookshelf, 'Quantitative Technical Analysis' being the latest addition.  This book is rich with instruction, and where Howard's does things differently than I do, his concise explanations and logical descriptions always challenge my thinking.  For example, in the book Howard discusses Cross Validation, something I have never attempted, but will now.  And that is just one example, as Howard covers a lot of ground in this book.  Thank you Howard, for once again significantly adding to the body of trading system knowledge.
- Kevin Davey, full time trader, author "Building Winning Algorithmic Trading Systems"
Sergey Golubev  

Big Data and Machine Learning in Quantitative Investment
by Tony Guida

Big Data and Machine Learning in Quantitative Investment

Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance.
Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment.

Sergey Golubev  

Machine Learning for Finance: Data algorithms for the markets and deep learning from the ground up for financial experts and economics
by Jannes Klaas

Machine Learning for Finance

Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself.

Muhammad Syamil Bin Abdullah  

A Complete Guide To Volume Price Analysis

By Anna Coulling



What do Charles Dow, Jesse Livermore, and Richard Ney have in common?

They used volume and price to anticipate where the market was heading next, and so built their vast fortunes. For them, it was the ticker tape, for us it is the trading screen. The results are the same and can be for you too.

I make no bones about the fact I believe I was lucky in starting my own trading journey using volume. To me it just made sense. The logic was inescapable. And for me, the most powerful reason is very simple. Volume is a rare commodity in trading - a leading indicator. The second and only other leading indicator is price. Everything else is lagged.

As traders, investors or speculators, all we are trying to do is to forecast where the market is heading next. Is there any better way than to use the only two leading indicators we have at our disposal, namely volume and price?

In isolation, each tells us very little. After all, volume is just that, no more no less. A price is a price. However, combine these two forces together, and the result is a powerful analytical approach to forecasting market direction with confidence.

What you will discover

This book will teach you all you need to know from first principles. So whether you're a day trader or a longer-term investor in any market, instrument, or timeframe, this book is the perfect platform to set you on the road to success and join those iconic traders of the past. All you need to succeed is a chart with volume and price...simple.

Muhammad Syamil Bin Abdullah  

TRADING SARDINE

BY LINDA RASCHKE



What's inside: Trading Sardines Lessons in the Markets from a Lifelong Trader. Trading Sardines is not just a spirited book on trading, it's a Ph.D in market experience summed up in 315 entertaining pages. The recipe to my secret sauce while you laugh your head off Lessons from 38 years of spirited trading. How to pull yourself up by the bootstraps. One more time even if it kills you. A Ph.D. in-market experience summed up in 315 entertaining pages! Trading Sardines celebrates grit and resilience in the financial markets. It is a hilarious, honest, and poignant account of the evolution of a professional trader over nearly four decades. From the raucous trading floors of the early eighties to the days of giant server racks thirty years later, the reader takes a chronological trip through the markets, trading strategies, and unimaginable events, watching how one woman responds with unblinking honesty. Linda Raschke shares a lifetime of market lessons while highlighting the tension between luck, risk, and passion. Along the way, she shows that perseverance can overcome the most inconceivable challenges, both in life and in trading. Her stories, documented with charts and photos, will keep you captivated and prove that humor may just be the key ingredient for survival. You won’t hear these types of tales anywhere else–this is the REAL world of trading. This book will motivate every trader, no matter the level of proficiency and experience. Linda’s success is testimony that you don’t have to be perfect, you just have to stay in the game!
Muhammad Syamil Bin Abdullah  

The Mental Game of Trading

By Jared Tendler



A step-by-step system for mastering trading psychology.Think about your most costly and recurring trading mistakes. Chances are that they’re related to common errors, such as chasing price, cutting winners short, forcing mediocre trades, and overtrading. You’ve likely tried to fix these errors by improving your technical skills, and yet they persist. That’s because the real source of these mistakes is not technical—they actually stem from greed, fear, anger, or problems with confidence and discipline.If you are like most traders, you probably overlook or misunderstand mental and emotional obstacles. Or worse, you might think you know how to manage them, but you don’t, and end up losing control at the worst possible time. You’re leaving too much money on the table, which will either prevent you from being profitable or realizing your potential.While many trading psychology books offer sound advice, they don’t show you how to do the necessary work. That’s why you haven’t solved the problems hurting your performance. With straight talk and practical solutions, Jared Tendler brings a new voice to trading psychology. In The Mental Game of Trading, he busts myths about emotions, greed, and discipline, and shows you how to look past the obvious to identify the real reasons you’re struggling.This book is different from anything else on the market. You’ll get a step-by-step system for discovering the cause of your problems and eliminating them once and for all. And through real stories of traders from around the world who have successfully used Tendler’s system, you’ll learn how to tackle your problems, improve your day-to-day performance, and increase your profits.Whether you’re an independent or institutional trader, and regardless of whether you trade equities, forex, or cryptocurrencies, you can use this system to improve your decision-making and execution. Finally, you have a way to reach your potential as a trader. Now’s the time to make it happen.
Muhammad Syamil Bin Abdullah  

The Little Book Still Beats The Market by Joel Greenblatt


In 2005, Joel Greenblatt published a book that is already considered one of the classics of finance literature. In The Little Book That Beats the Market―a New York Times bestseller with 300,000 copies in print―Greenblatt explained how investors can outperform the popular market averages by simply and systematically applying a formula that seeks out good businesses when they are available at bargain prices. Now, with a new Introduction and Afterword for 2010, The Little Book That Still Beats the Market updates and expands upon the research findings from the original book. Included are data and analysis covering the recent financial crisis and model performance through the end of 2009.

In a straightforward and accessible style, the book explores the basic principles of successful stock market investing and then reveals the author's time-tested formula that makes buying above-average companies at below-average prices automatic. Though the formula has been extensively tested and is a breakthrough in the academic and professional world, Greenblatt explains it using sixth-grade math, plain language, and humor. He shows how to use his method to beat both the market and professional managers by a wide margin. You'll also learn why success eludes almost all individual and professional investors, and why the formula will continue to work even after everyone "knows" it.

While the formula may be simple, understanding why the formula works is the true key to success for investors. The book will take readers on a step-by-step journey so that they can learn the principles of value investing in a way that will provide them with a long-term strategy that they can understand and stick with through both good and bad periods for the stock market.

As the Wall Street Journal stated about the original edition, "Mr. Greenblatt says his goal was to provide advice that, while sophisticated, could be understood and followed by his five children, ages six to fifteen. They are in luck. His Little Book is one of the best, clearest guides to value investing out there."

Muhammad Syamil Bin Abdullah  

Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals By David R Aronson


As an approach to research, technical analysis has suffered because it is a "discipline" practiced without discipline. In order for technical analysis to deliver useful knowledge that can be applied to trading, it must evolve into a rigorous observational science.

Over the past two decades, numerous articles in respected academic journals have approached technical analysis in a scientifically rigorous and intellectually honest manner, and now, Evidence-Based Technical Analysis looks to continue down this path. Organized into two parts, this valuable resource first establishes the methodological, philosophical, and statistical foundations of evidenced-based technical analysis (EBTA), and then demonstrates this approach—by using twenty-five years of historical data to test 6,400 binary buy/sell rules on the S&P 500.

Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout these pages, expert David Aronson details this new type of technical analysis that—unlike traditional technical analysis—is restricted to objective rules, whose historical profitability can be quantified and scrutinized.

Filled with in-depth insights and practical advice, Evidence-Based Technical Analysis provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining. Experimental results presented in the book will show you that data mining—a process in which many rules are back-tested and the best performing rules are selected—is an effective procedure for discovering useful rules/signals. However, since the historical performance of the rules/signals discovered by data mining are upwardly biased, new statistical tests are required to make reasonable inferences about future profitability. Two such tests, one of which has never been discussed anywhere heretofore, are described and illustrated.

If you want to use technical analysis to navigate today's markets, you must first abandon the subjective, interpretive methods traditionally associated with this discipline, and embrace an approach that is scientifically and statistically valid. Grounded in objective observation and statistical inference, EBTA is the approach to technical analysis you need to succeed in your trading endeavors.

Sergey Golubev  

Stefan Jansen. Hands-On Machine Learning for Algorithmic Trading: Design and implement smart investment strategies to analyze market behavior using the Python ecosystem

ands-On Machine Learning for Algorithmic Trading

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.