BLACK SWAN FUNDS
In 15 September 2008, Lehman Brothers declared bankruptcy with its total assets of 639 billion USD. This biggest banktruptcy in human history worsened the crisis and caused to wipe out 10 trillion USD from world economy.
Investors who experienced significant losses, started to seek insurance against next financial crisis. Black Swan funds (BSFs) profited from huge demand by offering very expensive insurance.
SOLUTION: ALBATROSS ALGORITHM
In 2008 Universa BSF returned 115% while 36 South BSF returned 234%.
BSF sector became popular after these returns. May 6, 2010 flash crisis and 2011 crisis enforcened their popularity and aggregate AUM of BSFs reached to 40 billion USD in 3 years (left)
However, bullish trend, started in 2011, unveiled their weaknesses. As a result, investors turned their back to these funds. Their problems are discussed in the following section.
If a balanced portfolio (60/40) purchases BSF protection, allocating 5% to a BSF, its annual return would reduce from 7.56% to 5.52%.
* Eurekahedge Tail Risk Hedging Index is used as a benchmark for BSFs
* Calculation covers 2008-2015 as there is no prior data for BSFs.
* Balanced portfolio is assumed to allocate 60% to S&P 500 and 40% to 10 year T-notes.
BSFs prone to generate negative returns in extended financial crises while investors expect them to generate high returns as insurance. It is because their strategy is to buy put options, constantly even when these options are already overvalued.
The only BSF that existed prior to 2007, Empirica Kurtosis LLC, allegedly returned 58% in 2000 during dot-com crisis. When crisis lasted for more than a year, Empirica generated negative returns in 2 consecutive bearish markets while it was supposed to generate high returns. The fund closed in 2004.
Balanced portfolio (blue) should sacrifice 27% of its annual return to buy an adequate BSF protection (red). That's why, investors allocate only 1%-2% to attenuate adverse effect of BSF insurance. However, it leads to insufficient protection.
Buying protection with Albatross algorithm actually improves annual return by 45% (green). Therefore, it is ideal for investors that seek insurance against crises but don't hedge the risk due to ridicoulously high costs of BSFs.
BSF strategy is solely based on purchasing put options on one or a few underlying contracts (S&P 500, VIX, etc.). As such, they generate negative returns in extended financial crises due to overvalued option premiums.
Albatross algorithm is a multi asset multi strategy algorithm, trading on various contracts. Adverse conditions for any given factor (e.g. high option premiums) don't affect performance, significantly. As such, Albatross algorithm is less likely to generate negative returns in financial crises.
Normal distribution of monthly returns for BSFs Mean: -0.23% Median: -0.72%
Normal distribution of monthly returns for Albatross algorithm Mean: 5.56% Median: 4.90%
"Holy Grail distribution" is characterized by positive mean to justify investment and a co-located positive fat tail to add protection to investment portfolios during tail risk events. It is considered the ideal distribution for tail risk hedging funds.
As seen above, BSFs fail to generate positive returns. On the other hand, Albatross algorithm has a textbook Holy Grail distribution, proving that it is the most effective tail risk hedging mechanism.