very much look forward to this series. although a fan of marks, i rarely listen anymore because of frustrations over his comments on risk :
a. it is critical item #1 and every oaktree employee is responsible
B. you cannot measure risk before or even after the fact\event
so wtf does oaktree actually do!? marks never tell us!
am also interested in hearing if you measure portfolio risk as anything other than some combination of short/med/long term correlation.
finally, the dice throw analogies are a little confusing because it seems you eventually imply that 'exact probabilities' also cannot be known beforehand.
Hey! Thanks for the comment. I really like following people that have been around the industry for a while. And I'd put Marks up there with Buffet in terms of temperament and being able to simplify his thoughts for us normal people. His memos are a little repetitive, but I always find new nuggets of wisdom in his writings.
I think on your point B, there's always a chance that you're wrong (even if very small). You can make a good decision, and for all the right reasons, but have an investment still not work out. So I think he's just saying that the process can be good, even if the outcome is bad. So you shouldn't judge the process on a single outcome. ...now if every investment you make is bad, then it probably is the process lol
Yeah I think correlation is a big driver for allocation decisions. By nature, you'll almost always trail the best investment (which is impossible to know ahead of time), but with the benefit of always performing better than the worst investment. It's a great middle ground for building wealth. But a lot of portfolio decisions are personal and should be customized for your own risk tolerance and timeline.
And thanks for the feedback on the confusion; I think being able to effectively communicate is most import in forums like this. I'll definitely explore trying different examples or different ways to express my ideas.
In terms of not knowing the probabilities, if you're referring to John Galt and I's discussion in the comments, then I'm just saying that the example laid out in the post is theoretical (and will fall apart if you try to apply it in the real world).
On the diversifying dice throws point, i think this makes sense given the expected return for the 1/6 chance of winning is 6x. But if that return is anything below 6x, across many, many throws, wouldn't the expected return fall below 0? Is that right? So it being risk-less across a diversified strategy really depends on that expected return when you hit.
Secondly, on the averaging of cash flows and thereby using the risk-free rate, wouldn't there still be risk involved? I understand that the average of lumpy cash flows produces the constant .166 / year, but isn't there still risk embedded within that .166? After all, there are individual companies behind the .166 of aggregate cash flow, and any number of factors can change the cash flow for a given company in a given period away from the average, right? Since these aren't bonds the .166 isn't contractual, so while it might be the average over a period of time, there is no guarantee that is the return you will get each year. I would think about that like the 6-7% average return on stocks historically. While that's true, you often rarely get that return year over year. Curious to hear your thoughts. Thanks for this post - super interesting!
You're right on both counts, if the dice throw were less than 6x you'd lose money, and if the 0.166 average cash flows are uncertain, then it's not riskless.
I would say that the dice throw paying out 5x still has a known outcome. So, in a sense, it's still risk-less as there's no uncertainty. But as you've alluded, it would be a crappy bet.
And yes, the lumpy cash flow example was just a thought experiment. We 'assume' that we know what the average cash flow is, just not the timing - i.e., known unkown. But the thought experiment quickly unravels once you try to apply it in practice. I've got another post coming that should help bridge the gap between theory and practice (and maybe even answer why annual returns are rarely the average).
Makes sense! Many thanks for the post and response - all quite interesting. Any discussion of risk from this standpoint interests me — I remember getting ‘annoyed’ as an undergrad listening to my professors define risk as pure volatility. Anyways, looking forward to the next post! Thanks Brian
very much look forward to this series. although a fan of marks, i rarely listen anymore because of frustrations over his comments on risk :
a. it is critical item #1 and every oaktree employee is responsible
B. you cannot measure risk before or even after the fact\event
so wtf does oaktree actually do!? marks never tell us!
am also interested in hearing if you measure portfolio risk as anything other than some combination of short/med/long term correlation.
finally, the dice throw analogies are a little confusing because it seems you eventually imply that 'exact probabilities' also cannot be known beforehand.
thx.
Hey! Thanks for the comment. I really like following people that have been around the industry for a while. And I'd put Marks up there with Buffet in terms of temperament and being able to simplify his thoughts for us normal people. His memos are a little repetitive, but I always find new nuggets of wisdom in his writings.
I think on your point B, there's always a chance that you're wrong (even if very small). You can make a good decision, and for all the right reasons, but have an investment still not work out. So I think he's just saying that the process can be good, even if the outcome is bad. So you shouldn't judge the process on a single outcome. ...now if every investment you make is bad, then it probably is the process lol
Yeah I think correlation is a big driver for allocation decisions. By nature, you'll almost always trail the best investment (which is impossible to know ahead of time), but with the benefit of always performing better than the worst investment. It's a great middle ground for building wealth. But a lot of portfolio decisions are personal and should be customized for your own risk tolerance and timeline.
And thanks for the feedback on the confusion; I think being able to effectively communicate is most import in forums like this. I'll definitely explore trying different examples or different ways to express my ideas.
In terms of not knowing the probabilities, if you're referring to John Galt and I's discussion in the comments, then I'm just saying that the example laid out in the post is theoretical (and will fall apart if you try to apply it in the real world).
Thanks again!
On the diversifying dice throws point, i think this makes sense given the expected return for the 1/6 chance of winning is 6x. But if that return is anything below 6x, across many, many throws, wouldn't the expected return fall below 0? Is that right? So it being risk-less across a diversified strategy really depends on that expected return when you hit.
Secondly, on the averaging of cash flows and thereby using the risk-free rate, wouldn't there still be risk involved? I understand that the average of lumpy cash flows produces the constant .166 / year, but isn't there still risk embedded within that .166? After all, there are individual companies behind the .166 of aggregate cash flow, and any number of factors can change the cash flow for a given company in a given period away from the average, right? Since these aren't bonds the .166 isn't contractual, so while it might be the average over a period of time, there is no guarantee that is the return you will get each year. I would think about that like the 6-7% average return on stocks historically. While that's true, you often rarely get that return year over year. Curious to hear your thoughts. Thanks for this post - super interesting!
Hey! Thanks for the comment.
You're right on both counts, if the dice throw were less than 6x you'd lose money, and if the 0.166 average cash flows are uncertain, then it's not riskless.
I would say that the dice throw paying out 5x still has a known outcome. So, in a sense, it's still risk-less as there's no uncertainty. But as you've alluded, it would be a crappy bet.
And yes, the lumpy cash flow example was just a thought experiment. We 'assume' that we know what the average cash flow is, just not the timing - i.e., known unkown. But the thought experiment quickly unravels once you try to apply it in practice. I've got another post coming that should help bridge the gap between theory and practice (and maybe even answer why annual returns are rarely the average).
Thanks again!
Makes sense! Many thanks for the post and response - all quite interesting. Any discussion of risk from this standpoint interests me — I remember getting ‘annoyed’ as an undergrad listening to my professors define risk as pure volatility. Anyways, looking forward to the next post! Thanks Brian