Shares - Rotational Portfolio

Rotational Trading (RT) is a medium term technique that takes advantage of a well-documented market anomaly whereby rapid long term price increases are often followed by a continued move in the same direction.

RT is a relatively new approach for HomeTrader.

Here’s what a typical rotational trade looks like.

Please note all results are theoretical backtests, made on real historic stock market data.

Winning Trade	Winning Trade
Break Even Trade	Losing Trade

Of course RT trading is not just as simple as buying any share that trends upwards! If you do that, you will of course lose money!

Our RT systems use an extensive array of filters that narrow the tradeable universe of shares down to those that are most likely to exhibit this momentum behaviour, and combine this with sensible risk management and exit criteria.

Example Rotational Trades

Before looking at these results, you should read about the risks of trading.

Download Rotational Trade Database

Properties of Rotational Systems

Please note all results are theoretical backtests, made on real historic stock market data.

This is an equity curve of the Gyro trading system that we published to our members.

The assumptions used in collating this data are:

• Starting capital of $100,000
• Trade size of $20,000
• Brokerage of 0.2%
• All trades taken as per Gyro system rules

Rotational trading and the Gyro System

This strategy offers a systematic way of constructing and regularly rebalancing a portfolio with a view of outperforming the market on a 12 month rolling basis.

It is a strategy that aims for Relative Performance. For example, if the market falls 20% in a year the model will likely produce a negative result, but with the aim of losing less than the market.

This was once the exclusive domain of Hedge Funds but we have developed this system to be viable for Retail and Sophisticated Investors. This strategy is suitable for patient investors who wish to maintain an active investment strategy.

The strategy works under the assumption that returns of ASX equities persist. This is to say that high past returns are more likely than not to be followed by high returns in the future, in other words, it is a Momentum strategy.

The performances of Momentum strategies do, in some sense, challenge aspects of the Efficient Market Hypothesis.

Understanding as to why this strategy produces superior results is not uniformed. An academic theory relates to the inefficient diffusion of information on the ASX. By targeting stocks that have displayed persistent positive growth, investors can benefit from the buying pressure created, after they entered, by other investors buying “too late”; the later investors did not efficiently act on new information.

Disclaimer

Past performance is not a guarantee or a reliable indication of future results. Trading involves the risk of loss and may not be suitable for you. All information contained in our website, documentation, software and training materials is general in nature and should not in any way be considered as personal advice. The decision to invest or trade and the method selected is a personal decision and involves an inherent level of risk, and you must undertake your own investigations and obtain your own advice regarding the suitability of our products for your circumstances.

Please ensure you obtain and read any current offer documentation, including the Financial Services Guide, prior to acquiring the products mentioned herein, so you are fully informed regarding the key risks and costs associated with these products.

It is also important to understand the inherent limitations of backtesting. Backtesting does not involve actual trading or investing, nor actual investment performances being achieved. Backtesting is a simulation of what an investor might have achieved in the past (based on a series of theoretical assumptions) using a particular investment methodology. As with any simulation, the theoretical results will be dependent upon the assumptions made in the backtest, including but not limited to the timing of the execution of trades and transaction costs.

Backtesting is only helpful as broadly a “modelling” tool of what may have occurred had a particular strategy been adopted, subject to the assumptions made by the person who has written the backtesting software. In fact, there may be sharp differences between simulated performance results and actual results subsequently achieved by any particular trading programme because of the inherent limitation of being able to model every possible variable into the programme (such as market sentiment). By way of example, if a person sought to analyse the performance of an investment strategy for internet initial public offerings on world markets by backtesting data from the so-called “dotcom boom” years in the mid to late 1990s, the strategy would have been seen to outperform the market. Applying the same backtested investment strategy between 2000 and 2002 would have resulted in significant losses.

Under absolutely no circumstances should backtested data be used as a predictive or forecasting tool as to what may happen in the future using any particular investment methodology. Past performance is not a reliable indicator of future returns.