Description
The book 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, leading to a 100% mechanical cycle-primarily based trading system that has shown a compounded growth rate of 20% per year over the past 30 years when back-tested the use of the Dow.
The book introduces new non-linear indicators and reviews the importance of a cyclic sentiment predictor for the Dow Jones Industrial Average Index. To that end, the use of day-to-day data covering the period from 1935 to 2013, ancient cycles are thought to be as predictors to forecast day-to-day sentiment for years ahead of time.
Forecasts plotted as predictive indicators are transformed into a mechanical trading rule whose profitability has been evaluated against the Dow buy-and-hold performance of 1990-2013. The consequences suggest that trading in line with 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 trading system. Generic pseudo code and step by step guidelines included.