Something Interesting to Read - page 13

Muhammad Syamil Bin Abdullah  

The Art Of Conrarian Trading : How to Profit from Crowd Behavior in the Financial Markets By  Carl Futia


Why is it so hard to beat the market? How can you avoid getting caught in bubbles and crashes? You will find the answers in Carl Futia’s new book, The Art of Contrarian Trading. This book will teach you Futia’s novel method of contrarian trading from the ground up.

In 16 chapters filled with facts and many historical examples Futia explains the principles and practice of contrarian trading. Discover the Edge which separates winning speculators from the losers. Find out how to apply the No Free Lunch principle to identify profitable trading methods.  Learn about the wisdom and the follies of investment crowds – and how crowds are formed by information cascades that drive stock prices too high or too low relative to fair value. Discover the power of your Media Diary - and how to use it to spot these information cascades, measure the strength of the crowd’s beliefs, and decide when the crowd’s view is about to be proven wrong.

You will watch Futia apply these principles of contrarian trading to navigate safely and profitably through the last 26 tumultuous years of roller coaster swings in the U.S. stock market – a time during which Futia kept his own media diary and developed his Grand Strategy of Contrarian Trading.  See how this Grand Strategy worked during the Great Bull Market of 1982-2000. Watch the Contrarian Rebalancing technique in practice during the dot.com crash of 2000-2002. Find out when the Aggressive Contrarian Trader bought and sold during the bull market of 2002-2007. Read about the causes of the Panic of 2008 and ups and downs of contrarian trading during that dangerous time.

Futia shows you how the market turning points during the 1982-2008 period were foreshadowed by magazine covers and newspaper headlines that astonishingly and consistently encouraged investors to do the wrong thing at the wrong time. By monitoring crowd beliefs revealed by news media headlines – and with the guidance provided by the many historical examples Futia provides – a trader or investor will be well-equipped to anticipate and profit from market turning points.

Muhammad Syamil Bin Abdullah  

Contrarian Investment Strategies: The Psychological Edge By David Dreman


In this major revision of his investment classic, one of the premier investment managers introduces vitally important new findings in psychology that show why most investment strategies are fatally flawed and his contrarian strategies are the best way to beat the market.

The need to switch to a new approach for investing has never been more urgent. The Crash of 2007 revealed in dramatic fashion that there are glaring flaws in the theory that underlies all of the prevailing investment strategies—efficient market theory. This theory, and all of the most popular investing strategies, fail to account for major, systematic errors in human judgment that the powerful new research in psychology David Dreman introduces has revealed, such as emotional over-reactions and a host of mental shortcuts in judgment that lead to wild over and under-valuations of stocks, bonds, and commodities and to bubbles and crashes. It also leads to horribly flawed assessments of risk.

Dreman shows exactly how the new psychological findings definitively refute those strategies and reveals how his alternative contrarian strategies do a powerful job of accounting for them. He shows readers how by being aware of these new findings, they can become saavy psychological investors, crash-proofing their portfolios and earning market beating long-term returns. He also introduces a new theory of risk and substantially updates his core contrarian strategies with a number of highly effective methods for facing the most pressing challenges in the coming years, such as greatly increased volatility and the prospect of inflation. This is every investor’s essential guide to optimal investing.


Sergey Golubev  

Deep Learning and Scientific Computing with R torch (Chapman & Hall/CRC The R Series)
by Sigrid Keydana

Deep Learning and Scientific Computing with R torch

torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++.
Though still "young" as a project, R torch already has a vibrant community of users and developers. Experience shows that torch users come from a broad range of different backgrounds. This book aims to be useful to (almost) everyone.

Bogdan Ion Puscasu  


Algorithmic Trading: Winning Strategies and Their Rationale

By   Ernie Chan 

"Algorithmic Trading: Winning Strategies and Their Rationale" by Ernie Chan is an excellent book on algorithmic trading. The author provides a detailed and practical guide to designing and implementing profitable trading strategies using various programming languages. The book covers a wide range of topics related to algorithmic trading, including backtesting, risk management, and portfolio optimization. The author also provides several real-world examples of trading strategies and how to implement them. What sets this book apart is the author's emphasis on understanding the rationale behind trading strategies, rather than just providing code to implement them. This approach makes the book useful for both beginner and experienced traders. Overall, I highly recommend this book to anyone interested in algorithmic trading.

YOU can buy it on Amazon
Sergey Golubev  

Trade the Patterns: The Revolutionary Way of Trading the CCI
by Ken Woodie Wood

Trade the Patterns: The Revolutionary Way of Trading the CCI

More than 30 years ago Ken Wood, also known as, Woodie, discovered a revolutionary way of trading on the CCI, a little-known moving average index. Woodie noticed that patterns forming on the CCI reveal how the market is moving. The CCI is a leading indicator, and Woodie figured out how it could help him get into a trade ahead of standard trend lines.
Reason: