What is a success fee?
What is a high water mark?
How do you calculate the success fee?
How much is the success fee?
What benchmarks do you compare your performance to?

A Matter of Principle

Studies show that in 2019, 71% of large-cap US actively managed equity funds underperformed the S&P 500, according to the S&P Dow Jones Indices' SPIVA (S&P Indices Versus Active) Scorecard. Over the past five years, almost 81% of large-cap, active US equity funds underperformed their benchmarks - S&PGlobal
Overperforming is hard. But we have confidence in our algorithms to outperform their benchmarks and are introducing a success fee. Success fees (or performance fees) are quite common in investing when you talk big money. It is not common for everyday investors. We believe this is unfair, and want to show how things can be done differently.

'Performance hurdle' & 'High Water Mark'

The success fee is charged only on days when the return of an algorithm exceeds the 'Performance hurdle' AND hits the 'high water mark'.

The 'performance hurdle' is a growth that would have occurred if the algorithm would have shown the same growth as the benchmark. Merely riding the market is not a skill.

The use of a 'high water mark' means that any previous loss of the algorithm should be recovered before any success fees can be charged. The algorithm should have actually increased in value before we charge a success fee. We need to hit a new all-time high. We won't be rewarded for losing less than the market.

The Calculation

The success fee = 20% * (return of the algorithm - return of the benchmark) on days when the performance hurdle and a new high water mark are reached.

In our backtests, a success fee was charged in 18-45% of the days. In these days, our algorithms exceeded the performance hurdle & hit a new high watermark.

The success fee is reasonably estimated to range from 0% - 1.61% per year

Some examples

Investment grows, but not by enough
The value of an algorithm increases with 1 %
The value of the benchmark increases with 1.2 %
Although the investment increases in value, the algorithm doesn't outperform the benchmark
Performance hurdle not achieved. Success fee = 0

Investment dips
The value of an algorithm decreases with 1 %
The value of the benchmark decreases with 1.2 %
Although the investment decreases less in value compared to the benchmark, the algorithm doesn't hit a new all time high
No new high water mark achieved. Success fee = 0

Investment grows, but is still recovering losses
The value of an algorithm increases with 0.9 %, the day after it had dipped 1 %.
The value of the benchmark increases with 0.8 %
Although the investment increases in value, and outperforms the benchmark, it doesn't hit a new all time high
No new high water mark achieved. Success fee = 0

Investment grows more than the benchmark AND reaches a new all time high!
The value of an algorithm increases with 2 %, reaching a new all time high
The value of the benchmark increases with 1.9 %
YES! The investment increases in value, outperforms the benchmark, AND reaches a new all time high
Success fee = 20% * (2% - 1.9%) = 0.02% of the investment

Benchmarks

Each algorithm has a different strategy and trades in different asset classes. This also means that the benchmark we use for each algorithm varies. Please see an overview of the algorithm and their benchmarks below
Industrial activity: SPDR S&P 500 Trust ETF (SPY.ARC)
Sector Rotation: iShares Core Growth Allocation ETF (AOR.ARC)
Momentum: SPDR S&P 500 Trust ETF (SPY.ARC)

Note that the success fee is not charged for any value you hold in cash.

Links to related articles:
Fees to Invest with Unhedged
Impact of Buy/Sell spread
Tax
Performance of Unhedged

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.
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