In investments, does more risk really equal more return, in the long haul?

Answer by Laurent Bernut:

This morning Palermo time, Andrew Swanscott from Better System Trader podcast interviewed me. The above question came up.

The answer is Yes and it is No, the real question is when. Best analogy is driving, will driving faster get You to destination: Yes when on the highway but No when in downtown.
I define my identity as a professional short-seller. As such, I have a different relationship with risk than most people. There is an interesting paradox in short-selling:
  1. If You are wrong, your position balloons and hurts immediately
  2. If You are right, it helps less and less
So, the whole game is of short selling is about position sizing and risk management:
How can positions be sized so that they would contribute but not hurt ?
This is probably one of the tallest order in fund management.

Between Charybdis and Scylla: Open Vs closed risk dichotomy

People perceive risk as either static, as in constant or completely random.

The perilous trip of the ship of Ulysses between Scylla and Charybdis.

The perilous trip of the ship of Ulysses between Scylla and Charybdis.

Well, it is somewhere in between and it depends on how You trade risk in the first place.

It reflects back on the concept of open versus closed risk. Open risk is the tropism of mean reversion strategy. Everything hums fine until the big iceberg. Closed risk means risk is capped.
Your view of the world will shape your risk profile. If You run an open risk model then because of its inherent unpredictability You are condemned to run it at low risk ad perpetuitam.
If You run a closed risk, then You can accelerate and decelerate within the bounds of your risk tolerance.

Accelerator and brakes

This is one of the most profound discoveries I made in 2015. there are two types of people when it comes to sizing a bet: those who take risks and sometimes get hurt along the way and the risk adverse crowd who will consistently take minimal risk.
I think this relates to the essence of the question: Can I build a system that preserves capital when strategy does not work but takes risk when it  does.
I think I can answer this one with good wisdom. Please read this post:
The thought behind the math was this: is there a middle ground between pedestrians and F-1 racers ? I think I found the formula. Please read the above post. We have used it and it does wonders, beyond what i theoretically expected in fact:
  1. When good times roll over, risk per trade is extremely responsive: brings risk to minimum right away.
  2. Concentration decreases: smaller risk per trade means smaller positions, means lower concentration , more positions, diversification
  3. But because surface does not change dramatically, position sizes are fairly reasonable. They do not swing from 0.15% to 15%
When the sh*** hits the fan, everything goes into Guantanamo, but it can still trade and thereby reboot itself.
  1. The skew of the convexity means that every marginal cgains translates into buying power restoration
  2. That posSizer is the best sleeping pill i know
Conclusion
I am sorry if i came across as boasting this position sizing algorithm. The point was that nothing is static. The answer You are looking for is in your position sizing algorithm.
Subscribe to my website to get free material, resources. Subscribers have free resources, files, code. Moreover, your feedback keeps me going on Quora
In the end, ask yourself this question every time You think about sizing a position: can I live with earning a little less than I could or lose a lot more than I should ?

In investments, does more risk really equal more return, in the long haul?

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