At the end of the day the market is a sandbox and you can develop your view of it as you please. Volatility is seen as a common proxy for risk. But it’s not static.. and arguably we as a collective market can’t avoid understating risk of extreme outliers in order for everything to run somewhat properly the other 99% of the time. So the distribution curve has fat tails.. this is commonly known.
Kevin gave you a pretty solid answer of financial orthodoxy. You pretty much restated your question.. just apply what he said. To make greater returns you can either operate a better strategy or sit on more risk. With SPY vols we already suffered a very statistically unlikely DD of 50%+ in recent years.
If you want to hold that vol 1.5x’d you’re going to get paid more. But how confident are you that if vol is 1.5x, the worst tail event is going to perfectly follow that ratio? If your thesis is wrong you’re going to start edging up to some real insolvency risk. Which is fine but at least be clear on what risks you’re holding.
There’s a few much more low-hanging fruits to harvest before you go the route of brute force leverage. Lower yielding assists have been found to have consistently higher risk-adj returns over equities.. perhaps due in part to leverage aversion as we just discussed and also since more of your liquidity will still be there when you might need it most.. i.e. a lot less volatility drag to realize.
Also holding less correlated assets simultaneously and rebalancing them smooths global portfolio vol without dampening returns to the same magnitude. A lot of these foundational concepts have been very well discussed over recent decades under Modern Portfolio Theory. If you understand the implications of the above, some ways to squeeze more yield out of your investments will be obvious.
It’s the next wall after optimization via a backbone of broad statistics that’s got me stuck at the moment. I feel like there’s got to be the next step of iterative refinement from this point just like there is from 100% long equities to MPT.. but I still don’t know quite where to look.
Kevin gave you a pretty solid answer of financial orthodoxy. You pretty much restated your question.. just apply what he said. To make greater returns you can either operate a better strategy or sit on more risk. With SPY vols we already suffered a very statistically unlikely DD of 50%+ in recent years.
If you want to hold that vol 1.5x’d you’re going to get paid more. But how confident are you that if vol is 1.5x, the worst tail event is going to perfectly follow that ratio? If your thesis is wrong you’re going to start edging up to some real insolvency risk. Which is fine but at least be clear on what risks you’re holding.
There’s a few much more low-hanging fruits to harvest before you go the route of brute force leverage. Lower yielding assists have been found to have consistently higher risk-adj returns over equities.. perhaps due in part to leverage aversion as we just discussed and also since more of your liquidity will still be there when you might need it most.. i.e. a lot less volatility drag to realize.
Also holding less correlated assets simultaneously and rebalancing them smooths global portfolio vol without dampening returns to the same magnitude. A lot of these foundational concepts have been very well discussed over recent decades under Modern Portfolio Theory. If you understand the implications of the above, some ways to squeeze more yield out of your investments will be obvious.
It’s the next wall after optimization via a backbone of broad statistics that’s got me stuck at the moment. I feel like there’s got to be the next step of iterative refinement from this point just like there is from 100% long equities to MPT.. but I still don’t know quite where to look.
