Prediction Markets

♪ [music] ♪ – [Tyler] Today, we look
at a new type of market. A market which has been designed
to make predictions. In previous talks we discussed
how prices are signals that convey information. Information about where goods
have high value and where they have low value,
which goods have high value and which have low value
and so forth. Prices also can convey information
about world events, even predictions of the future. So, the orange juice futures price
for instance, implicitly contains a prediction
about the weather in Florida. It’s not that these markets
were designed for this purpose, rather it’s that speculators,
if they are to profit from movements in the price
of orange juice futures, have to make some predictions
about the weather in Florida. They have to know something
about the weather in Florida. So the price
of the orange juice futures, comes in part to reflect
the information that speculators hold about future weather
patterns in Florida. Indeed, economists and others
often have looked informally to market prices
to help make predictions. To help predict Florida weather,
they look to the price of orange juice
in the futures market. To help predict
Middle Eastern politics, they look to the price
of oil and oil futures. To help predict the consequences
of global climate change, they look to the price
of flood insurance in coastal regions. Now, in each of these cases,
the implicit prediction is just a by-product of the market
and indeed many other things are going on in these markets
which also influence the prices. The prices in these markets
are noisy predictors. They’re rather imperfect predictors
because they weren’t designed to only predict. What would happen if we design
the market explicitly to make predictions? Then the predictions we got
out of the market might be even more robust
and even more accurate. Let’s take a look at some markets
which have been designed to make predictions. Prediction markets
are speculative markets which have been designed
so that the prices can be interpreted as probabilities
and used to make predictions. One of the most famous of these
is the Iowa Electronic Markets. I encourage you to go
to the web and check them out. Traders on the Iowa Electronic
Markets buy and sell shares of political candidates,
and the prices of the shares can be used to predict
the outcomes of elections. Let me give you an example. Here’s the case
of the Iowa Electronic Markets from the 2008 election
between Barack Obama and John McCain. In these markets,
one Obama share pays you a dollar if Obama wins and pays you
nothing otherwise. One McCain share pays you a dollar
if you hold the share and McCain wins,
and pays zero if he loses. Now, suppose you think Obama
has an 80% chance of winning that election, how much
would you be willing to pay for an Obama share? Well, if an Obama share
pays a dollar if Obama wins and he has an 80% chance
of winning, then that share is worth 80 cents. You would be willing to pay
up to 80 cents for such an Obama share. Suppose you enter this market
and you find that these Obama shares
are selling for 65 cents, well, that’s a buying opportunity. Something which you think
is worth 80 cents is selling for 65, so then,
you should buy Obama shares. In buying the shares, you would
be pushing up their price. In this way, your predictions,
your information, your opinions about which candidate
is likely to win become incorporated
into the price of an Obama share. By the way, suppose you thought
Obama had an 80% chance of winning but his shares
were selling for 90 cents, well then, you would want
to sell Obama shares. Even if you’re an Obama supporter,
to make more money you would sell the Obama shares
and buy the McCain shares. Again, in this way, prices come
to reflect the information. There are lots of traders
in these markets. People who are
very politically astute, who understand
the electoral college and who understand
how elections work and how well or how badly
a campaign is going. When these individuals
buy and sell shares, their information comes
to be reflected in the market prices. Here are the actual prices
on August 8th, 2008. Obama shares were selling
for 63 cents per share and McCain shares
were selling for 37 cents. The market was predicting
a high likelihood of an Obama win and in fact, that did, of course,
turn out to be the case. In over 20 years of testing
these markets, in presidential elections,
congressional elections, and state elections,
these market prices from the Iowa Electronic Markets
have turned out to be better predictors
of the outcomes than have political polls. That makes a lot of sense.
Think about it. With real money on the line,
people have an incentive to think carefully
when they’re investing and they have an incentive
to collect and process and interpret all
of the information from available all over the world. The resulting market prices
reflect a lot of deep-seated information
and indeed interpretation in a way which political polls
simply cannot. Similar prediction markets
have been creating all kinds of things. Some are pretty trivial things,
such as which actor or actress is going to win the next Oscar,
but also, firms have begun experimenting with prediction
markets to help from forecast variables,
like their future sales or which is the better decision,
or what will happen in some particular market
or some particular economy. Firms have been using
prediction markets to try to help themselves
make better decisions. Let’s give an example. At the Hollywood Stock Exchange,
traders buy and sell shares and options in movies,
music, and Oscar contenders. Some 800,000 traders
do this for fun. They’re using make-believe
“Hollywood dollars” but they still care enough
about the outcome to make the prices in these markets
pretty reliable predictors of future film profits. Now, although the traders
are doing this for fun, the website is owned
and run for profit. The information,
the implicit predictions in these prices,
that’s valuable to studios who want to try and understand
what’s going to work in their next film
and what’s not going to work. Here is an example. Some of us may believe
that sex sells, but is that actually the case? Well, on the Hollywood
Stock Exchange, we can be much more precise
using market prices. Here is some of the trading
for the movie “Fifty Shades Of Grey”
and you can see the price made a whole bunch of leaps
up and then leaps downward. That’s reflecting changing
revenue estimates for the movie. A leap up came
when Charlie Hunnam was cast to play the title role in the movie
and then the price did go up. Later on, Charlie dropped out
and the price dropped right back down again. The prices in these markets
are important information for the studios. They tell the studios how much
are these actors really worth. If we hire this actor,
how much will revenue for the movie go up? Are people excited
about a particular actress in a particular role,
what about the director? By using the information
and the prices from the Hollywood Stock Exchange,
studios are able to better cast their movies and they
can make better decisions. No prediction process
has perfect accuracy, but the prices from the Hollywood
Stock Exchange turn out to be pretty useful,
especially when compared to other methods. Along here, we have predicted
opening revenues as shown by the prices on the Hollywood
Stock Exchange, and then here we have
actual revenues. If the predicted revenues
always equal the actual, well then, everything
would be along the red line. When the actual revenues
turn out to be more than predicted,
we’re above the red line. So the original movie,
“Kings Of Comedy”, was a smash hit because it did
much better than predicted. The movie, “The Adventures
of Pluto Nash” with Eddie Murphy, well that was a disaster. It did much worse than predicted. On average however,
the predicted revenues are pretty good indications of what the actual revenues
would be. And again, that’s why the studios
look at these market prices because they are relatively
accurate predictions, more accurate
than other available measures. Alright, let’s conclude. Market prices reflect information
and they convey information. Prices in futures markets,
can signal all kinds of things such as war in the Middle East,
cold weather in Florida, or who will win the next election. Prediction markets
are new types of markets which have been created
to help businesses, governments, and scientists
predict future events. Market prices are good ways of aggregating dispersed
information and summarizing that information
in a single key figure, the price. Thanks. – [Narrator] If you want
to test yourself, click Practice Questions, or if you’re ready
to move on, just click Next Video. ♪ [music] ♪

7 Replies to “Prediction Markets”

  1. In your Iowa Electronics Market example, does purchasing Obama stock (with an 80% chance of winning) at $.60 cause his prediction percentage to change? if so increase or decrease and why? That was the part i could not grasp. Great vid!

  2. Hello everyone!

    Delphy is a social prediction market platform built on Ethereum. Bo Wang founded Delphy, who is also the co-founder of FACTOM.

    As the Delphy mobile app is nearing its product launch, Delphy would like to connect and grow its community. With this, they launched their Post-ICO Bounty program in which they will distribute 10,000 (DPY) Delphy Tokens for several bounties.

    Current DPY token price is $2.50. Please go to this link and check out the bounty details program:

  3. This market equilibrium solution assumes economical rationality, which was disproven by Kahneman. Some prediction markets use proper ruling scores for better ensuring calibration

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