We are academic researchers who study prediction markets. We are writing in favor of allowing NADEX, or a similar entity, to offer a broad range of political and policy event futures, including the three they are currently proposing.

There are four broad reasons for our support:

1. Existing political event futures have proven useful. Political event futures have been offered in small quantities by the onshore Iowa Electronic Markets (IEM), and by offshore exchanges such as Intrade. Prices from these markets have made possible a broad range of academic research.

2. Political event futures facilitate price discovery in other asset markets. One of the findings of this research is that firms and industries are exposed to political and policy risk. Political event futures provide investors with a market-based assessment of outcome probabilities, which reduces investors’ uncertainty when trading other assets. In addition, if allowed to operate onshore, political event futures markets might eventually grow to the point where they might provide useful hedging opportunities for firms. The currently proposed position limits are likely sufficient for most individuals to hedge their personal exposure to election outcomes.

3. The full potential of political event futures cannot be realized in academic-scale markets or offshore. Despite the utility of the IEM and Intrade, both markets are hampered by the current regulatory environment. An onshore exchange that allowed positions of the size NADEX is suggesting could ultimately reach a scale where it could attract liquidity to contracts that currently do not succeed on Intrade. There are many exciting potential applications of such markets, in research and policy making. Offering contracts on questions of great popular interest (such as Presidential elections) is crucial to attracting investors to an exchange. Once there, they face lower costs of participating in other markets, such as those currently offered by NADEX.

4. Concerns about gambling and manipulation are misplaced. Trading securities whose payoffs depend on political outcomes is no more “gaming” than trading securities whose payoffs depend on commodity or equity prices. Clearly, one can trade any security out of gambling motives, so the key question is whether the subject of these contracts is a “game,” or an economically important event. It is hard to argue that elections are not economically important events.

One might be concerned with two forms of manipulation: outcome and price manipulation. Many individuals have already large stakes in election outcomes; for example, a top executive in a public company will have will have a significant exposure via their equity holdings, as well as through any impact of the election on policies such as tax rates. Many individuals also have substantial exposure to election outcomes via their careers. Given the position limits proposed by NADEX, the market is likely to make at most a small contribution towards the number of individuals with meaningful stakes in election outcomes. One might be concerned with trading by those involved in supervising elections, and it might be reasonable for policy to prohibit trading by those individuals.

Turning to price manipulation, there have been a couple episodes that appeared to be attempt by traders to influence perceptions of an election by manipulating prediction market prices. The evidence suggests that effects on prices are relative short-lived, and effects on perceptions are often counter-productive for the manipulator (e.g., through media stories mentioning the manipulation). Onshore election markets will likely be significantly more liquid, making price manipulation even less attractive. A further protection comes from the fact that the outcomes of interest (election winners) will be linked to prediction market prices only through perceptions. Concern about price manipulation might be better devoted to cash-settled futures, where contracts settle based on other financial market prices.

To summarize, we view markets in securities contingent on economically-relevant events as an innovation that generate positive externalities (by aggregating information) as well as benefits to participants. Innovations with positive externalities should be encouraged by policy makers, not limited. If the Commission has questions about any of the statements made or research mentioned in this letter, it should feel free to contact any of the undersigned.

- Over the long run and many predictions, markets outperform most individuals;
- The more participants there are in a market, the more accurate it is (although there are diminishing returns);
- The more participants there are in a market, the fewer individuals are able to outperform its accuracy.

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More.

7:45 into

Steve Blank nailed it.

Paul, don’t talk about “shares”. The right vocabulary is “event derivatives” — or, in other contexts, “event derivative markets” and “prediction markets”.

[...] If I interpret correctly what you suggest, this will be equivalent to a “prediction market on a prediction market”, aka “options on markets”: Guess where the price of a long term market will be at set points in the future, before the expiration of the long-term market. InTrade experimented with such contracts last Fall (the X contracts). I was initially fascinated. However, we soon realized that such markets do not offer much additional information: Current price of the long-term contract and time to expiration are enough to determine the optimal price of the “X” contract.

The solution: Bite the bullet and have a long-term contract, based on a verifiable outcome. If you are interested in having checkpoints along the way, use conditional prediction markets (e.g., see the tax features, conditional of the result of the presidential election). Or think harder of what you are trying to measure and build a contract that has a verifiable outcome early on.

Download this post to see the embedded video —in case your feed reader doesn’t show it to you.

This BetFair video totally misinforms the public about the history of the betting exchange industry. It actually started in the United States of America, with the Iowa Electronic Markets in 1988, the ForeSight Exchange in 1994, and the Hollywood Stock Exchange in 1996.

More-detailed reporting on who has which kinds of positions in oil would make the market more understandable. It would show that so-called financial speculators are trying to predict price movements, but also trying to hedge risk. Likewise, commercial traders that take delivery of oil are hedging risks, while also predicting future prices. As oil expert Daniel Yergin points out, more visibility “will give a better sense of how much is the market responding to supply and demand in physical oil and how much is it responding to the supply and demand of money on the part of investors.”

It doesn’t make sense to shoot either kind of messenger. Markets are collections of information, translated through trading into prices. These prices, unless there is manipulation, are the best estimate of future supply and demand. Such price discovery should not be controversial, though it too often has been.

Here is what they say:

Prediction markets can be viewed as a form of forecast pooling or model averaging, a common forecast technique (Bates and Granger 1969, Hoeting et al 1999 and Stock and Watson 2004). That is, forecasts from different models are combined to produce a single forecast. In prediction markets, each market participant makes a forecast based on his or her own forecasting model, and the market price is some function of each of these individual forecasts.

Since the “prediction” implied by a prediction market is set by the marginal transaction, it depends not at all on the distribution of earlier trades, nor on the valuations of parties priced out of the market at the current price.

For example, consider two event markets: in the first 999 contracts trade at $0.50 and the 1000th and final trade is at $0.75; in the second 999 contracts trade at $0.76 and the 1000th and final trade is at $0.75.  In the typical interpretation of prediction markets, the event is “predicted” to result with a 75 percent probability in both cases.  However, averaging among the different predictions doesn’t get you that result.

(Well, strictly speaking the market price is “some function” of the prices – namely, one in which all trades but the last are weighted zero and the last trade is weighted one. You can call this “averaging,” but that isn’t the most useful explanation of the function.)

I’m not arguing that forecast averaging might not be a good idea in many situations, just that averaging doesn’t seem like a good way to explain what a prediction market is doing.