**Toward Info Accounting In Competitive Forecasting** – PPT file – by Robin Hanson – 2008-10-15

An interesting set of slides —-though it’-s **about the technicalities of value assessment**, and not about the big picture.

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**Toward Info Accounting In Competitive Forecasting** – PPT file – by Robin Hanson – 2008-10-15

An interesting set of slides —-though it’-s **about the technicalities of value assessment**, and not about the big picture.

**Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events** by aggregating disparate pieces of information that the traders bring when they agree on prices. These event derivative traders feed on the primary indicators —-i.e., the primary sources of information. (Garbage in, garbage out…- Intelligence in, intelligence out…-) Hence, prediction markets are meta forecasting tools.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism.

**A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event**, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative can be interpreted as the objective probability of the future outcome (i.e., its most statistically accurate forecast). **A 60% probability means that, in a series of events each with a 60% probability, then 60 times out of 100, the favored outcome will occur- and 40 times out of 100, the unfavored outcome will occur.**

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, **a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.**

[The title above is **a joke** based on Bo Cowgill’s latest comment. To get his joke, you will have to read all the comments there, till the final one (at the time of writing).]

Bo challenges me to publicize a Wikipedia link about the concept of information value. So, here is it:

Value of information (VoI) is undoubtedly one of the most useful notions in decision analysis. […]

Standard Definition

Consider a general decision situation having n decisions (d1, d2, d3, …-, dn) and m uncertainties (u1, u2, u3, …-, um). Rationality assumption in standard individual decision-making philosophy states that what is made or known are not forgotten, i.e., decision-maker has perfect recall. This assumption translates into the existence of a linear ordering of these decisions and uncertainties such that-

– di is made prior to making dj if and only if di comes before dj in the ordering

– di is made prior to knowing uj if and only if di comes before uj in the ordering

– di is made after knowing uj if and only if di comes after uj in the orderingConsider the case where the decision-maker is enabled to know the outcome of some additional uncertainties earlier in his/her decision situation, i.e., some ui are moved to appear earlier in the ordering. In such case, VoC is quantified as the highest price in which the decision-maker is willing to pay for all those moves. […]

*Voila*.