I kind of miss the days when I believed in the EMH… Denial of EMH, along with realizing that 100% and 0% are not practical upper and lower bounds for exposure to the market (i.e., there are very cheap ways to short and leverage the market), is making me a lot more anxious (and potentially regretful) about not making the best investment choices. Would be interested in coping tips/strategies from people who have been in this position longer.
I have a general life heuristic that I will only ever try to be in the ballpark of optimal. By analogy, I want to get the Big O right, and not worry about the constants.
A picture I have in my head related to this is the scene at the end of Schindler’s List where he’s lamenting that he could have saved more people by selling his car, or his jacket, or whatever. But he’d saved hundreds. I decided I didn’t want to live thinking that way.
I kind of miss the days when I believed in the EMH… Denial of EMH, along with realizing that 100% and 0% are not practical upper and lower bounds for exposure to the market (i.e., there are very cheap ways to short and leverage the market), is making me a lot more anxious (and potentially regretful) about not making the best investment choices. Would be interested in coping tips/strategies from people who have been in this position longer.
(It seems that in general, fewer constraints means more room for regret. See https://www.wsj.com/articles/bill-gates-coronavirus-vaccine-covid-19-11589207803 for example.)
Can you find a way to bound your error?
I have a general life heuristic that I will only ever try to be in the ballpark of optimal. By analogy, I want to get the Big O right, and not worry about the constants.
A picture I have in my head related to this is the scene at the end of Schindler’s List where he’s lamenting that he could have saved more people by selling his car, or his jacket, or whatever. But he’d saved hundreds. I decided I didn’t want to live thinking that way.
Maybe see also Slack (or Studies on Slack).
Or also consider that if you optimize too hard you might Goodhart.