At Kaiju Capital Management, we view risk a little differently
Rather than utilise cross-asset distribution and traditional beta neutrality to insulate against disadvantageous broad market movements, we employ Stratified Risk Distribution™: Position-level AI-supported early warning systems, AI-directed exit mechanisms optimised for capital preservation, and real-time inverse trade predation tools, all layered across diverse portfolio constructs and multiple market sectors. The result is that no matter what the markets or their component sectors do, there is no single outcome (or collection of disparate outcomes) that can substantially affect our capital base.
An example can be seen in our core strategy performance between February 19th, 2020, and March 23rd, 2020. During this period, the S&P 500 lost 35% of its value, while Kaiju returned 30% realised P&L on aveage allocated capital (4.3% on AUM) using an earlier, less-evolved version of our signature BEX Bilateral Equity Corridor Strategy™ (“BEX™”, for short) — which is a directionally neutral strategy. In other words, we achieved this outcome without betting in any way on a broad market collapse.
real-time probabilistic model
AI Risk Containment (ARC™)
The ARC™ system monitors each discrete position and checks the real-time probabilistic model outcome against the original projected outcome track, which was created by the candidate selection system at inception. When a position underperforms the original forecast, it is flagged and moved through a series of risk containment chambers where further analysis is conducted and mitigation mechanisms applied.
During chamber analysis, a separate AI-directed predatory trade mechanism performs inverse analysis to determine whether a tertiary opportunity exists (that is, whether whatever force which is disadvantageous to the primary position is beneficial to an inverted outlook if executed in the present). This all happens beyond the discrete candidate level as well, across risk-segmented portfolio tranches, sector tranches, and asset tranches (collectively, the strata, or layers, within Stratified Risk Distribution). Added to this are the risk containment mechanisms applied at the outset — modelled, constructed, and applied by the AI candidate selection system — which insulate the portfolio from catastrophic gap risk, should it occur without warning.
The approaches outlined above effectively minimise loss, preserve capital, and execute on opportunities contrary to the original outlook (without lag), all in real time.