Trading Price Action Reversals : Al Brooks
detailed guide to profiting from trend reversals using the technical analysis of price action
The key to being a successful trader is finding a system that works and
sticking with it. Author Al Brooks has done just that. By simplifying
his trading system and trading only 5-minute price charts he's found a
way to capture profits regardless of market direction or economic
climate. His first book, Reading Price Charts Bar by Bar, offered an
informative examination of his system, but it didn't allow him to get
into the real nuts and bolts of the approach. Now, with this new series
of books, Brooks takes you step by step through the entire process.
By breaking down his trading system into its simplest pieces:
institutional piggybacking or trend trading, trading ranges, and
transitions or reversals (the focus of this book), this three book
series offers access to Brooks' successful methodology. Trading Price
Action Reversals reveals the various types of reversals found in today's
markets and then takes the time to discuss the specific characteristics
of these reversals, so that you can use them in your everyday trading
endeavors. While price action analysis works on all time frames, there
are different techniques that you can use in trading intraday, daily,
weekly and monthly charts. This, among many other issues, is also
addressed throughout these pages.
Other books in the series include Trading Price Action Trends and Trading Price Action Trading Ranges
If you're looking to make the most of your time in today's markets the
trading insights found in Trading Price Action Reversals will help you
achieve this goal.
Forum on trading, automated trading systems and testing trading strategies
Something Interesting in Financial Video September 2013
newdigital, 2013.09.28 10:43
Interview With Al Brooks, Price Action Day Trader
Brooks has authored a number of books on trading. Interested traders may find it worthwhile to check out his page on Amazon.
newdigital, 2013.09.28 10:38
To be clear, Brooks' approach to price action trading is much more thorough; this strategy is just one tool in his arsenal.
newdigital, 2013.08.27 12:35
The Signal and the Noise: Why So Many Predictions Fail — but Some Don't by Nate Silver
My description: in my opinion, some of the best books regarding algorithmic trading are not books wrote for this intention. This one is for me a great example and read, there are lots of new ideas that can be used in quantitative finance area. I like too much the "prediction paradox" described below, since when we talk about future no one has monopoly on truth.Amazon description: "Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future."
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
Numerical Analysis for Statisticians (Statistics and Computing)by Kenneth Lange
Every advance in computer architecture and software tempts statisticians to tackle numerically harder problems. To do so intelligently requires a good working knowledge of numerical analysis. This book equips students to craft their own software and to understand the advantages and disadvantages of different numerical methods. Issues of numerical stability, accurate approximation, computational complexity, and mathematical modeling share the limelight in a broad yet rigorous overview of those parts of numerical analysis most relevant to statisticians. In this second edition, the material on optimization has been completely rewritten. There is now an entire chapter on the MM algorithm in addition to more comprehensive treatments of constrained optimization, penalty and barrier methods, and model selection via the lasso. There is also new material on the Cholesky decomposition, Gram-Schmidt orthogonalization, the QR decomposition, the singular value decomposition, and reproducing kernel Hilbert spaces. The discussions of the bootstrap, permutation testing, independent Monte Carlo, and hidden Markov chains are updated, and a new chapter on advanced MCMC topics introduces students to Markov random fields, reversible jump MCMC, and convergence analysis in Gibbs sampling. Numerical Analysis for Statisticians can serve as a graduate text for a course surveying computational statistics. With a careful selection of topics and appropriate supplementation, it can be used at the undergraduate level. It contains enough material for a graduate course on optimization theory. Because many chapters are nearly self-contained, professional statisticians will also find the book useful as a reference. Kenneth Lange is the Rosenfeld Professor of Computational Genetics in the Departments of Biomathematics and Human Genetics and the Chair of the Department of Human Genetics, all in the UCLA School of Medicine. His research interests include human genetics, population modeling, biomedical imaging, computational statistics, high-dimensional optimization, and applied stochastic processes. Springer previously published his books Mathematical and Statistical Methods for Genetic Analysis, 2nd ed., Applied Probability, and Optimization. He has written over 200 research papers and produced with his UCLA colleague Eric Sobel the computer program Mendel, widely used in statistical genetics.
Sergey Golubev, 2014.06.10 19:47
Off Topic with Irene Aldridge
Alpha Pages: You took great issue with Michael Lewis’ claim that the market is “rigged.” Why?
Irene Aldridge: On the Michael Lewis topic, I
suppose I am most disappointed in the pay-for-play quality of the book.
Even the fastest best-selling writers can tell you that they are only
capable of writing 15 pages per day, at best. To write a 300-page book,
[is] a five-month process, at a bare minimum.
Incidentally, at the time Mr. Lewis’s book was released, the trading
venue around which much of the book revolves, has been in existence for,
wait for it, exactly five months! In other words, Mr. Lewis began to
write the novel about his great protagonists and its creation prior to
the launch of this trading venue at the center of this book—I really
don’t see how he could have covered this in depth. [It appears to be an]
elaborate marketing campaign for this trading venue. In other words,
the book is marketing masquerading as a fair markets discourse. For a
writer like Lewis, stooping so low is a complete disgrace. Markets have
moved a long way toward fairness since then, so most of his criticism is
AP: Is high frequency trading taking the heat for problems caused market structure or regulations?
IA: From what we are seeing, this HFT pre-hedging
that boils down to front-running [may have] unfortunately become common
practice following the Volcker and Dodd-Frank rules. There still exists a
FINRA rule that encourages brokers to avoid front-running, but FINRA is
a self-regulatory organization, and the consequences of not following
its rules [may not be so harsh]. While most of ABLE Alpha clients have
the permission to access the markets directly and, as a result, avoid
front-running, many smaller entities are not so lucky and end up losing
money. I do not believe that this is what the regulators had in mind
when they designed the laws, but these are the unintended consequences.
AP: There is an ongoing argument over whether HFT is a net liquidity maker or taker as opposed to traditional market makers?
IA: I was just presenting at the Princeton Quant
Trading conference, where a fellow speaker, [from a] prominent broker
discussed how they are forced to spend money to build systems that
monitor the number of zeroes human brokers put at the end of their
orders simply because brokers so often come to work hung over and unable
to focus. Well, needless to say, hangovers do not happen to computers.
Overall, the computers are considerably cheaper, more reliable and less
demanding than human brokers, so there is absolutely no doubt in my
mind that the computerized trading technology, known as HFT, will
replace most of the presently-human trading operation at brokers in
continuing the digital revolution observed elsewhere in the society.
AP: Will the size of HFT be self-correcting? Will algorithms exploit inefficiencies until they’re gone?
One of our products is the HFT Index, science, not hear-say, based
[on a] real-time estimate of aggressive HFT participation in electronic
markets of customer choice. According to our estimates, activity level
of aggressive HFTs by volume averages 15% to 20% in most markets,
although intraday it may spike up 100%, or drop to 0%.
Something Interesting to Read June 2014
Muhammad Syamil Bin Abdullah, 2014.06.04 15:01
High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems By Irene Aldridge
Financial markets are undergoing rapid innovation due to the
continuing proliferation of computer power and algorithms. These
developments have created a new investment discipline called
high-frequency trading. Despite the demand for information on this
topic, little has been published to help investors understand and
implement high-frequency trading systems—until now.
industry expert Irene Aldridge, High-Frequency Trading offers the first
applied "how to do it" manual to building high-frequency
systems.Covering sufficient depths of material to thoroughly pinpoint
issues at hand, High-Frequency Trading leaves mathematical complexities
to their original publications, referenced throughout the book.
Page by page, this accessible guide:
Discusses the history and business environment of high-frequency trading systems
Reviews the statistical and econometric foundations of the common types of high-frequency strategies
Examines the details of modeling high-frequency trading strategies
Describes the steps required to build a quality high-frequency trading system
Addresses the issues of running, monitoring, and benchmarking high-frequency trading systems
the way, this reliable resource skillfully high-lights numerous
quantitative trading strategies—from market microstructure and event
arbitrage to deviations arbitrage—and puts the creation and management
of portfolios based on high-frequency strategies in perspective.
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.