Detect And Trade Cycles In Financial Markets – Book Series Overview

Decoding The Hidden Market Rhythm – Online Magazine & Books

WhenToTrade

 

The online magazine presents articles on cycle analysis, detection, forecasting and trading. Extending the knowledge of the book series “Decoding The Hidden Market Rhythem” by Lars von Thienen. The Online Magazine can be found here: http://flip.it/0lVVm

Book – Decoding The Hidden Market Rhythm Part 1: Dynamic Cycles

Decoding The Hidden Market Rhythem
Book Part 1

Abstract / Summary:
A dynamic approach to identify and trade cycles that influence financial markets. This book reveals new algorithms to identify cycles that drive financial markets. Learn about how to properly detect tradable cycles in markets, how to use that information to improve technical indicators and how to forecast using cycles. Watch as we step through many trading examples using these tools.

The book provides solid knowledge on a new cycle analysis approach and ways to use it in the trading world. Included is the methodology behind the implemented tools along with concrete examples of how to put cyclic analysis into trading practice. This approach is different from traditional cycle approaches in that this is the first time that a dynamic approach to cycles has been presented.

WhenToTrade Charting Platform or Wave59 Cycles Plug-In is required to use the tools in a standalone real-time environment.

Click here for Table of Content (pdf)

Amazon:
http://amzn.com/1499283490

 

Book – Decoding The Hidden Market Rhythm Part 2: Metonic Cycles

Decoding The Hidden Market Rhythem
Book Part 2

Abstract / Summary:
The second book of the series introduces correlations between markets and external energy cycles like gravity and geomagnetism. Digital signal processing techniques are used to reverse engineer Gann’s master cycles, resulting in a 100% mechanical cycle-based trading system that has shown a compounded growth rate of 20% per year over the last 30 years when back-tested using the Dow.

Part 2 introduces new non-linear indicators and reviews the significance of a cyclic sentiment predictor for the Dow Jones Industrial Average Index. To that end, using daily data covering the period from 1935 to 2013, ancient cycles are condidered as predictors to forecast daily sentiment for years ahead of time.

The forecast plotted as an indicator is transformed into a mechanical trading rule whose profitability has been evaluated against the Dow buy-and-hold performance of 1990-2013. The results suggest that trading based on recurring sentiment significantly outperforms the Dow in nearly all performance metrics, including net return, profitability, and Sharpe ratio.

Includes TradeStation / EasyLanguage code to rebuild indicators and use the trading system. Generic pseudo code and step-by-step guidelines included.

Click here for Table of Content (pdf)

Amazon:
http://amzn.com/1499562594