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Kevin J. Davey - Building Winning Algorithmic Trading Systems, A Trader_s Journey From Data Mining to Monte Carlo Simulation to Live Trading

Building Winning Algorithmic Trading Systems, A Trader’s Journey From Data Mining to Monte Carlo Simulation to Live Trading

$23.02

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In Building Algorithmic Trading Systems: A Trader’s Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading.

Author’s Introduction:

Regardless of the type of trader you are, or your experience level with trading, I think you’ll find something in this book that resonates for you. For beginner traders, I hope this book is an eye‐opener for you. I can’t, and I won’t, fi ll your head with thoughts of trading profi ts raining down from the sky. Anyone who tells you trading is easy is flat‐out lying to you. Sure, you can make lots of money trading, but you also need to be prepared for a lot of losing, a lot of drawdowns, and a lot of risk. Whenever someone tells me trading is a piece of cake, I always suspect that they are half‐baked.

My story, as painful as it is at times, is a realistic journey for many retail traders. Of course, as I tell all beginners, read what I have written, but then read books by other traders, too. Keep an open mind to everything. After a lot of reading, you’ll be able to make solid judgment calls on what is correct, what is BS, and what you like and don’t like. The amount of misinformation about trading is staggering, so all beginners must be wary.

For intermediate or slightly experienced but struggling traders, maybe your failures up until this point aren’t a result of psychology or confidence. Many trading books nowadays put a lot of emphasis on the mental aspect, but all the mental preparation in the world won’t help you if you are developing strategies incorrectly. If you’ve ever lost money after you started trading a strategy right after optimizing it, then you probably realize you were doing something wrong. The process detailed in this book should be right up your alley, since it will steer you in the right direction.

For expert traders, most of what I present here you’ll have already seen before in some fashion. Certainly, there are many great trading books that discuss many of the issues and problems that I address here. But there is always something new to learn, a different approach to try, and a different way to think. You probably fi nd many items in this book that are different from your current method, and you’ll likely benefit from incorporating these new ideas in your trading. I have organized Building Winning Algorithmic Trading Systems into seven parts. In all seven sections of the book, you’ll see me use certain terms interchangeably:

  • Strategy or trading system —the approach used to trade. This can be rigid rules, general guidelines and principles, or flat‐out random guessing. The net result is your strategy or trading system.
  • Mechanical or rule‐based trading or algorithmic trading —a style of trading in which all the rules are defined 100 percent. There is no discretion involved, no decisions to be made by the trader.
  • Hybrid or mixed trading system —a style of trading that includes aspects of algorithmic trading, along with discretionary trading. An example would be a mechanical system that gives entry and exit signals, but gives the trader the option to accept or reject the signal.

Contents:

  • A TRADER’S JOURNEY
  • YOUR TRADING SYSTEM
  • DEVELOPING A STRATEGY
  • CREATING A SYSTEM
  • CONSIDERATIONS BEFORE GOING LIVE
  • MONITORING A LIVE STRATEGY
  • CAUTIONARY TALES
Building Winning Algorithmic Trading Systems, A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading By Kevin J. Davey pdf
Author(s)

Kevin J. Davey

Format

PDF

Pages

281

Publication Year

2014

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