Two of those “advantages” aren’t as much “advantages” as the market telling you that it thinks it knows better than you. The fact that you have lower trading costs and lower slippage (actually the same thing) is because the market doesn’t respect you.
Re: information acquisition cost. Sure, you might have one small piece of information that BigTradingFirm doesn’t have, but they have plenty of information you don’t have. The relative value of the information is what matters.
I did a similar calculation not just for the base rate of completing his term, but of being the next nominee and the next US President a while back
There’s already some discussion here
I think it would be perhaps helpful to link to a few people advocating averaging log-odds rather than averaging probabilities, eg:
When pooling forecasts, use the geometric mean of the odds
My current best guess on how to aggregate forecasts
Personally, I see this question as being an empirical question. Which method works best?
In the cases I care about, both averaging log odds and taking a median far outperform taking a mean. (Fwiw Metaculus agrees that it’s a very safe bet too)
In contrast, there are no conditions under which average log odds is the correct thing to, because violating additivity of disjoint events is never the correct thing to do (see previous paragraph).
Your example about additivity of disjoint events is somewhat contrived. Averaging log-odds respects the probability for a given event summing to 1, but if you add some additional structure it might not make sense, I agree.
Averaging log-odds is exactly a Bayesian update, so presumably you’d accept there are some conditions under which average log odds is the correct thing to do...
I figured that’s the first thing someone would think of upon hearing “7x” which is why I mentioned “This was done using a variety of strategies across a large number of individual names” in the OP.
Right, I wasn’t disagreeing with you, just explaining why 7x isn’t strong evidence in my own words.
Can you please give some examples of such people? I wonder if there are any updates or lessons there for me.
Yes, but I don’t think there’s a huge amount of value in doing that. If you spend any time following stock touts on twitter / stock picking forums etc you will see these people quickly.
To be clear, I have no interest in dissuading you from trading. You’ve smashed it—you have confidence in your edge—go wild. I’m more cautioning people from following you thinking this is easy. Financial markets are extremely competitive and hard. It’s easy to mistake luck for skill and I don’t want other people losing money they can’t afford. I generally find posts like this are net-negative EV.
But why would you need ~1k trades to verify that I was not doing particularly high variance strategies?
I wouldn’t with something like that. However, assuming 250 trades each done on 5% of your capital, you’d need to be returning >15% on every single trade to return 7x. My experience say that’s unlikely, but ymmv. If that is the case then yes, you have serious edge and please take my money. (Especially if those are after tax returns!).
I don’t supposed you’d actually want to do this? (I also have some privacy concerns on my end, but maybe could be persuaded if the “value added” in doing this seems really high.)
I’m not sure what the value would be for me doing it? I’m not sure adding my word saying “I think this guy is legit because I saw a track record” would bring much value to either of us. I guess if I worked for a fund which might have interest in hiring people then I guess I might. But at the times when I have been in those roles, if someone turns up and makes implausible claims about returns, I politely show them the door.
I’d guess 20-50% above market returns is a realistic expectation if market conditions stay similar to today’s, and I hope I can still outperform if market conditions go more “out of sample” but I currently have no basis to say by how much.
I wish you the best of luck. I have never achieved anything close to those levels of returns, but would sorely love to do so.
Without even checking, I can think of a bunch of assets which 7x’ed since Jan 2020. (BTC/general crypto, TSLA, GME/AMC etc). So yes, I agree this depends on the portfolio you ran.
Personally, I have seen enough people claiming to outperform, but then fail to do so out of sample. (I mean, out of sample for me, not for them) for me to doubt any claim on the internet without a trading record.
Either way, I think it’s very hard to convince me with just ~1.5 years of evidence that you have edge. I think if you showed me ~1k trades with some sensible risk parameters at all times, then I could be convinced. (Or if in another year and a half you have $300mm because you’ve managed to 7x your small HF AUM, I will be convinced).
Everyone else has already pointed out that you misunderstood what EMH states, so I wont bother adding to their chorus. (Except to say I agree with them).
I will also disagree with:
at most one-in-five people [...] It should therefore probably update us nontrivially away from the possibility that the post author just got lucky.
1 in 5 isn’t especially strong evidence. How many of the other 5 people would you expect to be publishing on the internet saying “You should trade stocks”.
I don’t really know how you incentivise people (seriously) in the non-real money prediction markets.
Non-money prediction markets have lots of difficulties to them:
How do you size your bet? (Ie knowing a probability vs “higher” or “lower” than market estimate
Difficult to arbitrage (ie share information between markets)
How do you show your conviction (this is 50% and I’m certain it’s a coin flip vs this is 50% because I don’t understand the question)
I don’t know enough about the etiquette here, but I am having to fight the urge to post a bunch of memes along the lines of “It’s not the bull market, I really am a genius”.
I would strongly advise anyone who’s considering following this to consider doing this with considerably less than their whole portfolio and with much lower expectations than 7x’ing your money.
tl;dr—I don’t believe the Metaculus prediction is materially better than the community median.
Another example is Metaculus Prediction, an ML algorithm that calibrates and weights each forecaster’s prediction after training on forecaster-level predictions and track records. From 2015 to 2021, it outperformed the median forecast in the Metaculus community by 24% on binary questions and by 9% on continuous questions.
This is at best a misleading way of describing the performance of the Metaculus prediction vs the community (median) prediction.
We can slice the data in any number of ways, and I can’t find any way to suggest the Metaculus prediction outperformed the median prediction by 24%.
Looking at (for all time):
None of these are close to 24%. I also think that given the Metaculus algorithm only came into existence in June 2017, we should really only look at performance more recently. For example, the same table looking at everything from July 2018 onwards looks like:
Now the community median outperforms every time!
For continuous questions the Metaculus forecast has more consistently outperformed out-of-sample, but still smaller differences than what you’ve claimed:
I would also note that %age difference here is almost certainly the wrong metric for measuring the difference between Brier scores.
This is a chart of PredictIt volumes for markets I can find data for. I assign the volume to either the last day it was open (if that data is available) otherwise the close date on the market definition.This tells a similar story to Betfair on “2016 vs 2020” and also illustrates the point I was trying to make about this being a tricky question—almost a large fraction of the volumes are coming during a few key events.
The prediction market after the event was ~ a betting market on “Will the election results be upheld?” rather than “Who will win the election on election night?”. We were comparing those markets to similar markets earlier (“who will win” markets) rather than “Will election results be overturned?”
I think this is going to be a difficult question to give a concrete answer to. (For many reasons: data isn’t public, growth is very lumpy)Probably the best approximation I can think of would be betting volumes in equivalent events over time.US Presidential elections matched volumes on Betfair (in £): * 2008: ~15mm (Source)* 2012: ~40mm (Source)* 2016: ~200mm (Source)* 2020: ~1700mm (~600mm pre-event which is possibly more relevant)
That’s a ~40x over 12 years, or ~35%/year.We’ll get another data point after the French Election this year and I guess it would be interesting to look at some other comparable events. (UK General Elections).Another place we could look at is volumes on PredictIt, although that’s really just a proxy for number of markets. You could also look at volumes on Polymarket or one of the other crypto exchanges.
alexrjl collected a decent number of explanations here.I think it’s worth considering the wider story: similar drops were observed in the Netherlands and Portugal.
Isn’t “prevalence of infections … [rising] … in the week to July 24” completely consistent with the cases peaking on the 16th? Given people are infected for ~10 days, and cases were higher in the week to 24th than the equivalent period 10 days earlier.Calculating the 10-day rolling average of cases* in the UK (from here) I think that the prevalence should have increased by ~10%. The prevalence increasing by 15% obviously suggests there was some affect of fewer people being tested but also cases are definitely declining. (Usually attributed to schools doing less testing rather than ‘freedom day’)* cases calculated using a rolling 7-day average re-centered on each day to remove weekly seasonality
One of my favourite papers The Rate of Return on Everything suggests that property might have Sharpe ratios > 0.5 with 100+ years of history, although I generally think that the volatility is somewhat underestimated there. (It also has a lot of data on the Sharpe ratios for long bonds + equities across a wide range of DM for long histories)
Your second example (to me) demonstrates the issue with your first. If over a 5y window you can be convinced that US equities have a Sharpe >1, you can be convinced over a 5y window that BTC has a Sharpe > 1.5.
[The Sharpe of the best performing stock is always going to be phenomenally high, does that refute this—I say no, on the grounds that we’re interested in ex-ante Sharpe. If the strategy “always buy the best performing stock” had a Sharpe ratio of >> 0.5 then I would be interested, but I don’t believe that is what we see.]
To be clear, I don’t believe that Sharpe (in general) tops out at 0.5. I think there are plenty of strategies which have Sharpes >> 0.5. I just don’t think they are especially relevant in this context. (Usually because they are capacity constrained, although there are other reasons).
To be honest, if you don’t find 0.5 convincing—that’s fine. You should have even less faith in the value of prediction markets. Nothing wrong with that—it’s the whole point of my post. I just wanted to give people a little hope (or at least the hope I have).
Generally, running the Olympics comes with a lot of local economic activity to make the event happen and various actors benefit from being able to plan ahead.
I agree with this, I just don’t think hotel rooms are a particularly good example since supply is fixed there is little hotel operators can do with knowledge of the probability of the event. (They can “change” prices, but prices are effectively driven my a market equilibrium (which is going to effectively be a prediction market on the Olympics going ahead))
Having access to an accurate probability about whether the Olympics will tell local hotels about how important it is to have a lot of beds available
Aside from changing pricing on the rooms (which is already an implicit prediction market on the Olympics) I’m not really sure what the hotels are supposed to do. Individual hotels can’t exactly increase supply overnight. (Unlikely your example with Airbnb)