Erasure Quant is a new decentralized marketplace for stock market data built on Ethereum. It allows anybody to upload signals, build a track record that anyone can verify, and earn money. Read the original Medium post on why we built Erasure.
Upload signals on stocks in the Russell 3000 universe (see example signals)
Prove you believe in your signals by staking them with cryptocurrency
Earn money if your signals get bought by Numerai’s hedge fund
Lose money if your signal quality decreases
Stock market signals are feeds of data that can be used by hedge funds like Numerai to improve their performance. A count of the number of tweets mentioning ticker symbols in the Russell 3000 universe every day could be a signal. By itself, it might not be very predictive but taken together with other signals, it might improve performance a lot. Other examples of signals include: signals produced from quant models such as those created on Quantopian, raw high quality data about stocks such as P/E ratios, executive compensation data, signals based on public filings or earnings calls, etc.
Format your signals as a CSV, with tickers on one column and signals, expressed between 0 and 1, on the other. Your CSV upload must contain at least 100 predictions to be considered a valid submission.
An example CSV is here. This CSV includes the full range of tickers in the Russell 3000 that we want you predicting against.
Unlike websites such as Numerai which provide clean training data to build your model, Erasure Quant provides no data. This is because Erasure Quant is a tool for people who have already built their own models or already have access to data they believe might produce good signals. However, there is a lot of free or low cost data available on the internet and a number of tools such as Quantopian and Alpaca that provide data or make it easy to turn data into signals.
Quantopian has a hosted IDE, with tightly integrated data sources and backtesting engine. Unfortunately, it’s tricky to export orders from that IDE. One strategy:
Publish your algorithm for live trading
Copy the live trading ID in the URL (ie, ...live_algorithms/[your_ID])
Go to their research notebook (Research > Notebooks)
Run this command:
bt = get_live_results(‘[your_ID]’)bt = bt.pyfolio_positions.to_string()print(bt)
Alpaca has a freely available set of scripting tools, including data, with a broker backend to place trades once designed. Alpaca built a tool to export from Alpaca to Erasure.
Signal uploads will be scored daily (see Evaluating Data below). Your submission is valid for 60 days from the time of submission. After that, you will no longer be eligible for payments and will be removed from the leaderboard. You will still receive scores, and as soon as you submit again, you will be eligible for payouts.
To be eligible to receive payouts from Numerai, Erasure Quant users are required to stake the NMR cryptocurrency on their signals. If you don't have NMR, there are exchanges where you can trade ETH for NMR. For example Uniswap.
Without staking, users could create hundreds of accounts in the hopes of getting lucky and Numerai would not be able to determine which signals are worth buying. By staking money, users express confidence in their signals to Numerai which gives Numerai confidence to buy the signals.
By staking NMR you enter into an agreement with Numerai and give Numerai a special right to destroy your entire stake for any reason (known as “griefing”). When you stake, Numerai doesn’t receive your money, it just gets locked up on the Ethereum blockchain. And if Numerai destroys your stake, it gets destroyed on Ethereum forever.
When a user enters an agreement with Numerai by staking, they become eligible to receive payouts from Numerai. Being eligible to receive payouts does not mean you will receive payouts. In fact, Numerai does not fully specify which kinds of signals will earn the most but Numerai does pay as a percentage of the stake size. Numerai will aim to pay out about 200 NMR per week (see current NMR to USD exchange rate). Numerai has several million NMR that it has allocated to Erasure applications and Erasure Quant is our main one. 200 NMR per week is just the beginning.
Numerai earns nothing when a user is griefed. But griefing is an important aspect of Erasure Quant. Without any risk of losing your stake, the stake is meaningless. We don’t specify the criteria for griefing either. We will tend to grief users that appear to be abusing the system in some way or whose signal quality is suspect in some way. Users coming last based on the leaderboard metrics are more likely to be griefed than those doing well.
All agreements are perpetual unless they are terminated by either party. Numerai can terminate agreements immediately in which case your stake is returned immediately. You can terminate the agreement with 40 days notice i.e. your stake is still locked and Numerai can still grief it for 40 days after you request to terminate the agreement. After the 40 days notice, your remaining stake is returned to you. This delay gives Numerai a chance to grief bad signals.
Numerai does not state how they choose people to pay people or how much they pay and it changes all the time. This is because Numerai can’t predict what data they’ll want to buy in the future so they can’t define upfront how much they will pay. Even the highest quality signal can become worthless or become crowded. So submit signals that you think are high quality, and we’ll email you when we start buying your signals.
Numerai looks for consistency where the signal is high quality over a long period. Numerai looks for low correlation with other users on the platform (if you create a signal that’s the same as a signal we’re already buying, we won’t want to buy yours too). Numerai also looks for signals that are not obvious (eg if a signal is just a big factor exposure to value). Quantopian descriptions on the kinds of models they like give some good insights as to what would make a good Erasure Quant signal as well. See https://www.quantopian.com/get-funded#the-constraints and https://www.quantopian.com/risk-model
Even if Numerai never buys your signals or doesn’t pay enough, our vision is to have other hedge funds buy data on Erasure as well. At the moment, very few people understand crypto so it may take time for other buyers to show interest but the reputation you build on Erasure is forever because all your data will be available on Ethereum and IPFS--your track record is not on Numerai’s servers. And your most recent submission is always encrypted and hidden even from Numerai. If you create and maintain a set of signals with incredible quality and performance for a long period, there’s a good chance you’ll catch the attention of all the best hedge funds in the world over the long term.
Your submissions are encrypted by default and even Numerai cannot see them. You automatically privately reveal the submission to Numerai when uploading through the website. In the future, we will let you publicly reveal your past predictions. This will allow you to prove your track record to other parties.
We use the historical sharpe of your daily returns as the primary metric for the leaderboard. Your daily returns are calculated by taking the average returns for the top half of your predictions and dividing it by the average returns for the bottom half of your predictions. You need to have at least 20 scores before you can be considered for the leaderboard. This will typically take around 4 weeks.
High placements on the leaderboard based on this metric does not imply that your signals will be bought or that you won't be griefed and the leaderboard metric may change.
We are using Quandl’s stock adjusted price data to determine stock returns to calculate your signal’s daily correlation. Returns for a given day are from the market close to the next day’s market close. You can submit at any time but you will always be scored against your last submission before the previous close. For example, if your last submission was at 1pm ET on Tuesday, your score at the close of trading on Wednesday will be the return from Tuesday’s close to Wednesday’s close. If you submitted on Tuesday at 1pm and Tuesday at 10pm, we would use your Tuesday 1pm submission to score you for Wednesday as that submission came in before the close but we will use your 10pm Tuesday submission to score you on Thursday (provided you made no additional submissions on Wednesday before market close).
We take the top half of your prediction by its score and consider them "longs". Then we take the bottom half of your predictions by its score and consider them "shorts". If there is an odd number of stocks predicted on, we make the middle stock a long.
For example in the prediction set below, AAPL and GOOG are longs and FB is a short.
To calculate the "long short portfolio return" for each day, we calculate the average returns of the longs and the average returns of the shorts and then the long short portfolio return is (1+average_long_return)/(1+average_short_return)-1.
If the subsequent daily return of each stock is as follows:
Then the long portfolio return is (4% + 2%)/2 = 3% and the short portfolio return is 1%. Then the long short portfolio return is 1.03/1.01 - 1 = 1.98%.