Scalar markets

Scalar markets are like binary markets in that they have two outcome shares—“Long” and “Short”—though the payout between those two shares is not winner-take-all. The payout of one “Long” share and one “Short” share always sums to 1 ETH, but the allocation can be any two fractions from 0.0 to 1.0.

Scalar markets are great for situations where you want to trade on the direction of something or don’t want to expose yourself to winner-take-all risk. Examples would be the price of REP at the end of the week, the weather tomorrow, how many 3 pointers Steph Curry will make this season, or when the government will re-open. For all these examples we could create markets with many possible outcomes (70–72°F, 73–75°F, etc for the weather example), but there are three disadvantages to that approach. First, we lose precision, meaning 71°F and 72°F are the same outcome. Second, we don’t reward traders for being close. If the weather ends up being 70°F, a bet on 73°F is just as bad as a bet on 50°F. And third, the more outcomes there are, the more expensive it is to provide liquidity. As we’ll see, scalar markets fix all these issues—they are precise, reward closeness, and are efficient.

Scalar markets require two more data points to define: a lower bound and upper bound. These bounds are constraints on the ultimate resolution value (i.e. price of REP, °F for weather, number of 3 pointers, dates, etc). And in a scalar market you are trading on where the market will resolve between the pre-defined bounds.

To demonstrate let’s take a cryptoasset like ZRX which has a price in USD around $0.30 right now and design a scalar market that lets us take a position on ZRX/USD 30 days from now. We’ll call our market “ZRX/USD-30d” and set two bounds—$0.0 as the lower bound and $0.60 as the upper bound. Like any other Augur market, our market has both a “Long” outcome share and a “Short” outcome share. But rather than representing a specific outcome, the “Long” and “Short” shares represent directions between the two bounds. The “Long” share pays out more if the 30 day price resolves closer to the upper bound, $0.60, and the “Short” share pays out more if the 30 day price resolves closer to the lower bound, $0.0. If the price is $0.3, exactly halfway between the two bounds, both “Long” and “Short” shares resolve to 0.5 ETH. Specifically, here is the formula for both:

And here is a chart showing the payout of “Long” and “Short” shares at each final price of ZRX/USD (X axis) from $0 to $0.60.

Notice that the same rule of 1 ETH still applies: together one “Long” share and one “Short” share always sum to 1 ETH upon expiration. But as the resolution price moves towards the upper bound, $0.60, the value of the “Long” share increases linearly and the value of the “Short” share decreases linearly. And vice versa as the resolution price approaches the lower bound, $0.0.

Now let’s get into pricing shares in a scalar market. Unlike in a binary market where the price per share implies probability, the price per share in a scalar market translates to a particular strike price in the underlying asset, or whatever is being predicted.

Example 1: Buying Long

Let’s say Trader Bull thinks the price of ZRX/USD will be above $0.30 upon expiration. She examines the order book in the market, and it looks like she can buy 1 “Long” share for 0.5 ETH. Using the same formula from above, we can translate 0.5 ETH into $0.30 because $0.30 is half way between the bounds, $0.0 and $0.60. So Trader Bull buys 1 “Long” share for 0.5 ETH and waits for expiration.

Example 1: Buying Long

At expiration, the price of ZRX/USD has increased 10% to $0.33. That means the market resolves such that Trader Bull’s “Long” share can be redeemed for 0.55 ETH because $0.33 is 55% of the way from $0.0 to $0.60. Trader Bull has made a 10% return on her investment, the same return she would have gotten if she invested in ZRX directly.

Example 2: Buying Short

Trader Bull still thinks the price of ZRX/USD will rise, but she doesn’t think it will increase more than 10% from the initial spot of $0.30. She looks at the order book on Veil, and she notices the community is even more enthusiastic than she is because she can buy “Short” at 0.4 ETH (or “Long” at 0.60 ETH). So the community is pricing the future price of ZRX/USD at $0.36 (60% from $0.0 to $0.60), which is greater than her expectation of $0.33 (10% increase from spot). Even though Trader Bull thinks ZRX/USD will increase by 10%, she decides to buy one “Short” share for 0.4 ETH, which is the equivalent of saying she thinks the price will be less than $0.36.

Example 2: Buying Short

At expiration, the price has again increased 10% to $0.33, and each “Long” share is worth 0.55 ETH and each “Short” share is worth 0.45 ETH. That means Trader Bull has made 0.45 ETH from 0.4 ETH, a 12.5% return. Review the Example 2 graphic to see how this plays out.

Example 3: Leverage

For the final example, we will tighten the bounds on our market to a lower bound of $0.15 and an upper bound of $0.45. We can think of this as adding leverage to the market, because increases in price now have a magnified effect on the value of “Long” and “Short” shares. Review this chart to see what we mean:

In the above chart, if the price of ZRX/USD goes from $0.3 to $0.45, the “Long” share increases in value from 0.5 ETH to 0.75 ETH, but the “2x Long” share increases from 0.5 ETH to 1 ETH. The price movement of the underlying asset, ZRX/USD, is magnified because the bounds are tighter.

Example 3: Leverage

Let’s say Trader Bull is able to buy her “Long” share in the new market (with 2x leverage) at 0.5 ETH or $0.3. And again ZRX/USD increases 10% to $0.33. Then Trader Bull is paid out 0.6 ETH ($0.33 is 60% between the bounds, $0.15 and $0.45), making a 20% return. That’s twice as good as if she bought ZRX/USD directly and held!

Bringing all of this back to Veil, here is a graphic that shows the Veil order form in a scalar market.