What Allocation pre-sets can I choose from?
What is the difference between the allocation pre-sets?
What are the benefits of the different pre-sets?
We have developed two allocation pre-sets customers can choose from.
The default Pre-set is Equal Weight. Equal Weight means that the portfolio gets divided in equal amounts between the trading algorithms. When you select this pre-set, each algorithm will invest 33% of your portfolio. The Equal Weight pre-set leverages the basic statistical properties of the three independently correlated trading algorithms.
The Equal Weight pre-set is simple and many investors at Unhedged may prefer this method and its likely suitable when you have a longer time horizon. As the algorithms are more or less uncorrelated to each-other; one algo can do well for a period and another algo might perform better over the next period. We do not know in advance and therefore regular rebalancing to an equal weight is a good way of ensuring each algorithm contributes to the investment equally, over time.
Our back tests show a total return of approximately +450% over the period 2010-2020, when monthly rebalancing the portfolio to the Equal Weight pre-set. The Sharpe ratio helps investors understand an investment's return compared to its risk. It was above 1.0. The largest drop in the value of the portfolio was -9% (this while individual algo's can drop double). Please note that past performance is not always an indicator of future performance.
A second Allocation Pre-set we offer is Equal Risk. The Equal Risk pre-set suggests a different allocation every month, as it looks for a combination where each algorithm contributes the same amount of risk to the investment portfolio. Following the Equal Risk pre-set every month smooths out the returns.
The Equal Risk pre-set is an algorithm in itself. This type of algorithm is a so-called Hierarchical Risk Parity Algorithm. It takes the output of the three trading algorithms and calculates how much risk each of them contributes to the end result. It will find a way, through complex mathematics, to combine the algorithms so that they contribute the same amount of risk.
In long-term back-testing, the Equal Risk pre-set generated a lower return than Equal Weight, but it was also less volatile. Our back tests show a total return of approximately +350% over the period 2010-2020, when monthly rebalancing the portfolio to the Equal Risk pre-set. The Sharpe ratio helps investors understand an investment's return compared to its risk. It was just below 1.0. The largest drop in the value of the portfolio was -8.5% (this while individual algo's can drop double that). Please note that past performance is not always an indicator of future performance.
Which to choose?
We are not licensed to give you personal advice, that is how we keep investing affordable. In summary, you can note the following when comparing the different pre-sets:
Equal Weight has shown to generate higher returns in our back tests, over a long time horizon (10+ years). However, over a shorter period it can be riskier / more volatile.
Equal Risk has shown to smoothen returns in our back tests. It is less risky and less volatile than Equal Weight.
Equal Weight and Equal Risk are both solid ways of investing in a diversified manner, without studying the markets too much
Note that in all our analysis, we assume that the portfolio is rebalanced every month to the chosen pre-set.
Links to related articles:
Choose Investment Allocation
Change my allocation
Performance of Unhedged
You should always do your own analysis, read the PDS and make a decision that fits your situation. If you cannot make a choice we suggest you consult a Financial Advisor to ascertain your risk profile.
Products issued by Melbourne Securities Corporation (MSC). Please consider the PDS and TMD available on our website before applying. All investments carry risks and you may lose your money. Past performance is not indicative of future performance. The information in this report has been compiled from sources we believe are reliable and we make no warranty in respect of its accuracy.
Updated on: 31 / 12 / 2021