Very Interesting, though I still wonder if intelligence agencies can out perform betting markets (at least on questions with enough interest to be able to generate a liquid price).
That assumes that intelligence agencies are not utilizing betting markets.
In fact there was a big push in 2010 to build a betting market type system for analysis across the Intelligence Community. It is not used 100% of the time but has some measure of success where applied.
When I was in the IC I actually built a hypothesis estimation tool based on the Delphi method and a Bayesian updater to give probabilities for future events, crowdsourcing the votes from the community. Worked ok in our limited run, but needed a lot more work to implement really well.
There was an article in NPR a while back about the Good Judgment Project (which was run by Dr. Tetlock - mentioned in the article). In some cases, betting/prediction markets (& other similar tools) were beating intelligence analysts - http://www.npr.org/sections/parallels/2014/04/02/297839429/-...
I participated in GJP for a couple seasons. Honestly, I didn't do that well.
But I was approaching it very differently than I would if it was my job. Since the system that was set up gave high rewards to unpopular predictions, I just gambled on the few most unpopular that had at least some shot at reversing. It wasn't the smartest approach, but it was the most fun. If I was doing it for real, obviously I'd go a different way.
The people who did best, at least from what I saw, tended to ride waves of popularity on the more active questions, buying low and selling high.
What I did was like betting on a few biotech startups, what the best scorers did was like riding waves of the market leading stocks.
In the end, I'm not that sure it had much to do with actual prediction of events. Then again, neither did my approach. I guess I'm not sold on the version of prediction markets they were using.
Kinda depends on which platform you were on (GJP used several). Some were prediction markets while some were opinion pools, both of which are scored/rewarded differently.
Our company (Cultivate Labs) recently acquired Inkling Markets (a very early YC company that built prediction market software) and have been building a new version of the PM platform, which will hopefully address some of the risk/reward quirks.
The big difference they have is that they are playing a more strategic role than the tactical short term play in most market activities - in that their predictions will drive government action which will be a major factor in any outcomes. Makes more sense to test against successful opportunism than prediction
Could there be an element of self-fulfilling prophecy explaining why intelligence analysts, on whose advice governments decide their actions, have a better success rate at prediction than others who do not so closely influence government decision making?
Apparently, given that governments are cracking down on prediction markets. The conspiracy-theorist side of me could interpret it as intelligence agencies beating them quite directly.
wow I read the original post and now this. Though I disagree with (this post's) author on some points, he is correct that the the regulation is mostly reasonable.
If it was up to me, I would remove items 5,6. They strike me as an unreasonable burden on both homeowner and airbnb respectively.
I see no reason why an in law unit should be regulated differently within the 75 day period of allowed hosting.
I'd thought previous poster was providing the P/E for the specific HCV drug used in the HuffPo piece. Which is what was being implied should be kept lower then 100x in this thread.
Perhaps, but I would take that metric to be ridiculous, because the company cares about it across it's entire portfolio, in this case 21 products it's currently selling (https://en.wikipedia.org/wiki/Gilead_Sciences), looks like they do some very early stage/general research, products like Tamiflu they evidently had to license to get to market (reduced profit for them), products which have expired or soon to expire patents, and all their failures, past and future.
At least one of which is implied in the Wikipedia article, also see their current pipeline, some of those are going to fail, and at the end their 22 failures to date. 1 in Phase III trials ($$$, efficacy, the most expensive), 5 in Phase II (fairly expensive, I think), 5 in Phase I (certainly not "cheap").
It sure looks like they're doing the right thing with their science and medicine, their founder was motivated by having contracted deng fever, which is untreatable (besides of course supportive measure). Clearly the right thing to do is to beat them up the few times they hit it out of the ballpark with a "100x" success, that'll teach them and the other drug companies!
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this is really nothing other than very straight forward "Insurance". In the long run, the optimists almost always win. Keeping money sitting idle and constantly rolling short dated put options is not a particularly sophisticated trading strategy.
I don't think there is any correlation between exciting/boring and profitable. Index funds ar one of the more profitable strategies (as they don't involve paying some guy a ton of money to play lotto for you). They are certainly boring. Taleb argues that people Investing are really bad at estimating the value of catastrophic failure (or blowout success) and invests accordingly. He is playing the other side of Y combinators strategy, very much in agreement with Fred Wilson, Y combinator etc, just the other side of the spectrum.
Er, well, sharpe ratio and all that. The existence of a risk free investment that pays better than the risk free rate would be quite the discovery (certainly not boring!).
Sure, but the trader from the article is just a single person with millions.
How many other traders out there look forward to bubble bursting events like this? Commodity disasters? Oil disasters and shortages? The whole "dumb money" (retail trades, casual investments, passive investment funds) vs "smart money" (day traders, hedge funds, insider traders, HFT) would lead me to believe that it's beneficial to exploit the excessive pumping up and bursting of financial bubbles, as it only siphons up 'dumb money'.
Some of our users find it useful, for example, to know how much of a trade a particular counter-party can absorb. While it doesn't establish the efficacy of the manager (or even come close), we find it interesting in terms of individual entity trading power. Readers' mileage will certainly vary. Based on your feedback, we'll try to be more clear about those points in future reports.
I'm even less convinced about the usefulness knowing "how much of a trade a particular counter-party can absorb". And somehow deriving this information from the current book size (as opposed to available capital) also seems somewhat dubious.
Moreover, absent the AUM (or leverage) and asset mix, this number won't tell you much about the actual size of the book.
Though this is an interesting thought experiment, the author misses one key point: Advertising has historically only been about 1% of GDP and there is nothing to suggest that it will grow. To suggest that Advertising can support increasingly large parts of the economy is a bit unrealistic.
Something like this could be extremely valuable inside an organization. A lot of very valuable knowledge is locked up by employees with no incentive to reveal it.
People have been singing this song for quite some time now, the question is still: can they do it?
I'm yet to see this mythical Uber Logistics play, and their ancillary products, RUSH, EATS, CARGO etc all seem poorly thought through and bolted on, not deeply integrated into their car driver base.
I should also note that this is probably partially a regulatory problem. I'm not sure NYC (and other cities) will allow livery cars to simultaeously be delivery cars. Of course Uber has demonstrated an ability to bend the law to their will, so we will see.
