47 lines
3.2 KiB
Markdown
47 lines
3.2 KiB
Markdown
## What this is
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This is a set of libraries and a command line interface that fetches probabilities/forecasts from prediction markets and forecasting platforms. These forecasts are then hosted on airtable, and used to power a search engine for probabilities.
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For now, a demo can be found [here](https://metaforecast.org/) (try searching "Trump", "China" or "Semiconductors"), and the database can be perused [here](https://airtable.com/shrUotmcMmmTdIjmX). I also have a json endpoint [here](https://metaforecast.org/data/metaforecasts.json) and a csv endpoint [here](https://metaforecast.org/data/metaforecasts.csv).
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I also created a search engine using Elicit's IDE, which uses GPT-3 to deliver vastly superior semantic search (as opposed to fuzzy word matching). If you have access to the Elicit IDE, you can use the action "Search Metaforecast database".
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## How to run
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### 1. Download this repository
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``git clone https://github.com/QURIresearch/metaforecasts``
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### 2. Enter your own cookies
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Private session cookies are necessary to query CSET-foretell, Good Judgment Open and Hypermind. You can get these cookies by creating an account in said platforms and then making and inspecting a request (e.g., by making a prediction, or browsing questions). After doing this, you should create a `src/privatekeys.json`, in the same format as `src/privatekeys_example.json`
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### 3. Actually run
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From the top level directory, enter: `npm run start`
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## What are "stars" and how are they computed
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Star ratings—e.g. ★★★☆☆—are an indicator of the quality of an aggregate forecast for a question. These ratings currently try to reflect my own best judgment based on my experience forecasting on these platforms. Thus, stars have a strong subjective component which could be formalized and refined in the future.
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Currently, stars are computed using a simple rule dependent on both the platform and the number of forecasts:
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- CSET-foretell: ★★☆☆☆, but ★☆☆☆☆ if a question has less than 100 forecasts
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- Elicit: ★☆☆☆☆
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- Good Judgment (various superforecaster dashboards): ★★★★☆
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- Good Judgment Open: ★★★☆☆, ★★☆☆☆ if a question has less than 100 forecasts
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- Hypermind: ★★★☆☆
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- Metaculus: ★★★★☆ if a question has more than 300 forecasts, ★★★☆☆ if it has more than 100, ★★☆☆☆ otherwise.
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- Omen: ★☆☆☆☆
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- Polymarket: ★★☆☆☆
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- PredictIt: ★★☆☆☆
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## Various notes
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- Right now, I'm fetching only a couple of common properties, such as the title, url, platform, whether a question is binary (yes/no), its percentage, and the number of forecasts. However, the code contains more fields commented out, such as trade volume, liquidity, etc.
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- A note as to quality: Tentatively, Good Judgment >> Good Judgment Open ~ Metaculus > CSET > PredictIt ~> Polymarket >> Elicit > Omen.
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- I'm not really sure where Hypermind falls in that spectrum.
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- Prediction markets rarely go above 95% or below 5%.
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- For elicit and metaculus, this library currently filters questions with <10 predictions.
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- Omen *does* have very few active predictions at the moment; this is not a mistake.
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