Currently, prediction markets have trouble pricing extreme probabilities. Roughly speaking, getting more confident than about 95% is very difficult, and distortion appears even by 90% on relevant time frames. Nonetheless, many markets of public interest trade in this regime -- nuclear war and other catastrophes being a prime example.
I'm attempting to create a template for derivative markets, trading bots, and subsidy structures that will improve on this. The project is in progress already. The full plan is not yet written up, but hopefully the current work is enough that one can see where it's going: https://manifold.markets/browse?topic=extreme-probabilities-project
Roughly speaking, the template is this: create tranches of related or unrelated high-confidence markets, and a derivative on how many resolve in the expected direction. Traders can bet on the group, mildly reducing information costs and trading friction and improving their potential return. Bots can arb against the underlying. And traders with specific knowledge can touch up the low-probability events mostly by betting on the individual low-prob events to happen. For example, betting Yes on "10" here lets you play the house (in conjunction with the bots) against folks who want good odds on weird stuff: https://manifold.markets/EvanDaniel/long-shot-bets-how-many-of-these-10
The project is to continue along that path. It will include a mix of further writeups of the plan, creating and subsidizing markets to support it, and bounties for trading bots and feature additions to Manifold.
What are this project's goals and how will you achieve them?
Minimally successful: better quantify the effects that cause this. Be able to say things like "the market believes these markets are mispriced" in a useful way. Improve our understanding of extreme-probability pricing behavior, interest rate effects, and so on. This goal is well underway; it already looks like we have minimal data to support it, but it has not been analyzed in detail or written up.
Moderate success: rich enough data to chart a path forward. Currently I can guess where some stumbling blocks are; chart them in detail. Produce a set of feature requests that Manifold or another prediction market could implement to improve the situation, with enough data and analysis for the case to be convincing.
Extreme success: those feature requests get implemented. They do in fact work as desired. There exists a template for market structure and subsidy structure required to produce a significant improvement in market accuracy at extreme probabilities, at least on markets with enough interest and public value. Manifold charts new territory, solving a problem that has plagued prediction markets for decades.
How will this funding be used?
A mix of labor and cash costs. Labor is split between my time and bounties. Bounties will be to pay for software development work, including arb bots and hopefully also feature additions to the Manifold code base. My time will include market creation, analysis, and blog post writing. Non-bounty cash costs will include market creation and subsidization.
This project does not neatly fit in any defined category for the Manifold Community Fund. There are several other promising submissions so far. The fund is small, at only $30k, and capturing even 10% of it seems optimistic.
I'm pricing this on the assumption that investors are unlikely to make a profit off it. I don't see a way to make investors a profit off only the community fund grants, while also paying anything resembling fair prices for either my time or the software development work I plan to post bounties on.
A guess at a budget (not a commitment in any way):
Market creation, subsidies, and standing limit orders: $200
Bounties for bots and features: $1500+
Bot investment / capitalization: $200+
My labor: $1000+
The "extreme success" version of this certainly requires more budget for labor hours priced at a fair wage. The minimum valuation reflects this. If things are looking promising I plan to sell my equity and/or fund the above budget out of pocket; I'm in a position to afford that, and the minimum funding level is adequate to ensure that the above budget or equivalent is available.
Who is on your team and what's your track record on similar projects?
Just me. Hopefully also bounty respondents.
I don't have meaningful experience on a project like this. However, my professional background includes technical writing, math, programming, and other engineering work. I've been participating in prediction markets for over 20 years.
What are the most likely causes and outcomes if this project fails? (premortem)
Possibly the problem is just too hard and my plan is in fact not adequate to solve it or even make meaningful headway.
This will not work without interest and support from the broader community. If I (or the community) cannot identify interesting markets, and generate liquidity on them, we won't get accurate pricing info to inform the project.
If things aren't seeing public interest and support, I'll probably give up on it somewhere midway to the "moderate success" state.
I don't have the time to do the software work myself; my software dev skills are quite rusty and merely adjacent to what's needed. If I don't attract any interest and/or don't have enough funding to pay for development bounties the project will likely fizzle somewhere between minimal and moderate success.
What other funding are you or your project getting?
None. I'm supplying some out of pocket cash so far, and will supply a bit more even if this gets no funding.