Interesting post, would love to hear your opinion about my suggested alternative to EMH, I don’t see anything in your post that contradicts it. But i’m having a very hard time accepting the idea that you can’t beat the market using public data and infinite amount of computing power.
Your formulation is nifty, and intuitively makes sense to me. I am feeling too wiped right now to think about it carefully, but my off-the-cuff response is that it has something to do with the fact that ‘informational edge’ is a much broader category than information about the actual underlying assets.
For example, a complicated day-trading algorithm is on some level a reflection of the fact that the market is missing some information. But that information looks more like ‘there is a complex relationship between assets under XYZ specific conditions’ than ‘the EBTDA figure in Walmart’s quarterly report’. I guess this is what most anomalies represent: they are more like meta-information than information.
In which case, if you had a superintelligence with near-infinite compute, I think your intuition that it could indeed beat the market is right. I don’t know much about quants, but I imagine this is pretty much what they are trying to do, with the difference being that they have bounded resources.
Indeed, Jalex Stark is a quant and says: “I spend most of my days working on specific (proprietary) instances of the general problem “design and enact decision procedures that identify market inefficiencies as well as possible, measured in terms of maximizing the ratio (expected value in dollars of trading against the inefficiency) / (amount of human time required to find the inefficiency and execute the trades).”
Interesting post, would love to hear your opinion about my suggested alternative to EMH, I don’t see anything in your post that contradicts it. But i’m having a very hard time accepting the idea that you can’t beat the market using public data and infinite amount of computing power.
Your formulation is nifty, and intuitively makes sense to me. I am feeling too wiped right now to think about it carefully, but my off-the-cuff response is that it has something to do with the fact that ‘informational edge’ is a much broader category than information about the actual underlying assets.
For example, a complicated day-trading algorithm is on some level a reflection of the fact that the market is missing some information. But that information looks more like ‘there is a complex relationship between assets under XYZ specific conditions’ than ‘the EBTDA figure in Walmart’s quarterly report’. I guess this is what most anomalies represent: they are more like meta-information than information.
In which case, if you had a superintelligence with near-infinite compute, I think your intuition that it could indeed beat the market is right. I don’t know much about quants, but I imagine this is pretty much what they are trying to do, with the difference being that they have bounded resources.
Indeed, Jalex Stark is a quant and says: “I spend most of my days working on specific (proprietary) instances of the general problem “design and enact decision procedures that identify market inefficiencies as well as possible, measured in terms of maximizing the ratio (expected value in dollars of trading against the inefficiency) / (amount of human time required to find the inefficiency and execute the trades).”