The seasonal sector rotation strategy is built upon the precept that certain areas of the market place exhibit patterns over time which coincide with the calendar, and the US election cycle.
There are many ways to 'follow the trend' and one which we have built here is a combination of following cyclical trends which have held up for almost 50 years both on an annual basis and within the 4-year US election cycle. We have tested a wide range of different instruments, covering a diverse pool of sectors and industries, and our seasonal sector rotation strategy is the zenith of this.
Starting balance of $100,000 USD
This Seasonal Sector Rotational Strategy works by cross referencing a list of of differing ETF's which cover the entire width and breadth of the market with our indicator matrix which we have developed.
This matrix is made up of multiple elements to determine which position should be held for the forth coming month. This ranking system take into consideration multiple facets including:
Month of Year
Year within US Election cycle
Fama-French 3-Factor Model
Relative Strength Index
Exponential Moving Average Cross Over
There are a few other key indicators we use, which is part of our intellectual property, and which we will not disclose. Each indicator produces a number which is then added up to give either a positive or negative score (positive meaning go long, and negative meaning go short). The instrument with the highest or lowest value is then selected for the following months trade.
The position sizing is 100% weighted at all times, being totally re-balanced at the end of each month, meaning unless cash has been selected as the investment of choice, all funds will be deployed all of the time.
The portfolio of possible ETF's we currently use are:
Over time, we believe this list will grow to include other ETF's which we feel would work well against our matrix. We aim to close out a position at the end of the trading day on the last trading day of the month, and look to enter our new position at the beginning of the first trading day of the month. With this strategy and all associated testing, there was no market timing model applied to try and get the most out of each trade. This is something which may be layered into the process in the future.