Introduction to Volatility, Part 1

What is Volatility?

Disclaimer

Thales protocol utilizes the Parimutuel Market structure to create shared pools of collateral that pay out to the holders of winning positional tokens. Terms such as “long” or “short” can be replaced by “up” and “down” in line with the mechanics of Parimutuel Markets. The term “option” is essentially interchangeable with “positional token” in this context. Throughout this series I will use both sets of terms.

Options and Volatility

Cryptocurrency markets are famous for extreme price movement with huge jumps and sometimes even bigger drops taking place regularly. This rate of change in the price of an asset is known as volatility and it’s a key metric used for pricing many financial derivatives products. The larger and/or more frequent these changes in price, the higher the volatility. Where traditional stock traders need to factor in volatility so they can know how much an asset is expected to move and then use that calculation to figure out realistic price targets, this isn’t as important for an asset class like cryptocurrency with no shortage of dynamism. Crypto traders could always find the volatility for a token, but in a way it didn’t really matter. Most cryptos have the potential to make huge moves at any point in time, so traders just dial up as much leverage as possible, cross their fingers and wait for the inevitable 10% candle. But now that Layer 2 solutions have made on-chain transactions cost-effective again, a market for crypto-derivatives is finally developing. This means crypto traders can deploy options to improve capital efficiency, execute complex strategies and hedge positions in ways that weren’t easily done before, but to do this effectively they need to understand how these products are priced. The rise of options reflects crypto’s growing maturity, and like traditional financial instruments they can be hard to understand and use correctly without some knowledge of what’s going on under the hood.

What is an Option?

[If you already have a good grasp on options, skip this part]

So what is an option, especially as it applies to crypto markets? An option is an agreement between two parties (a user and smart contract for example) where one party can (but doesn’t have to) buy an asset at a certain price and time. When an option reaches its deadline (or expiry date) it is said to be mature and can now be exercised. To exercise an option is basically to cash out, but only if it makes sense to do so.

Here’s a simple example: let’s say ETH is at $2000. You think ETH will go up, but instead of just buying and holding, you’re going to try an option. You find a long option for $2200 and it costs $0.25 for each chance to profit $1.00. This means you can buy 100 of these $2200 long options for $25. The $25 you spent for the option is called the “premium”, and if you are correct and ETH rises from $2000 to above $2200 at the expiry date, you can sell your option for $100, a profit of $75. But if ETH doesn’t rise above $2200, your option is worthless and you lose the $25 you spent on the premium. This is because your option represents the ability to buy ETH for only $2000 from the seller of the option at expiry when it’s actually worth $2200. You can then immediately sell that ETH for instant profit (but in reality all this happens behind the scenes and you just get the profit when you exercise the option).

This also works in the opposite direction: If you buy a short option for ETH at $1800 when it’s at $2000 and it ends up at $1900 on expiry, your option is worthless. Your short option gave you the chance to sell ETH to the other party for $1800, but since the price is $1900 you wouldn’t want to take that deal anymore and instead you’d just eat the cost of the premium. That’s the basics of options.

[Jump to here to skip options basics]

Why should I care about how an option is priced?

So you might be asking yourself, how did the market in the first example arrive at the price of $0.25 for every 1 dollar, and how can I take advantage of this? The truth is that pricing, and volatility in general, is not perfect a measure and sometimes you can find what you consider to be a cheap option. A big part of options trading is understanding and evaluating the price of a particular option. And you can begin to do this by having an understanding of volatility and how it factors into a option’s price.

You can look to the AMM (Automatic Market Maker) used by Thales for trading positional tokens for an example in practice:

Here you can see a market for ETH at $2,800. The current price is just under $3,100. I’ve selected “short” because I think ETH will fall from its current price to below $2,800 at expiry. The AMM has priced this position at 0.29 sUSD for every 1 sUSD in potential profit. That means for a chance at 100 sUSD, I will need to pay 29%, or about 29 sUSD, for this position. If I’m correct, I will be able to exercise this position for 100 sUSD and realize just over 70 sUSD in profit. The AMM thinks this the correct price for these odds.

Since an option is just a guess that an asset will reach a certain price at a specific moment, it makes sense that a measure of an assets ability move (volatility) would be a huge factor in the price. You’d expect to charge more for the opportunity to profit from a 10% move if the underlying asset regularly jumps 15% or more.

If you can understand why an option is priced the way it is and find a discrepancy between that educated guess and your own, you can theoretically capitalize on a misprice. The problem is that the mathematical tools used to measure volatility can be difficult to understand, especially at a practical level. The reason many don’t trade options is because the learning curve is too steep; It’s too hard to make smart decisions about potential price movement when you don’t know how or why something is priced the way it is. This series will attempt to explain volatility in an intuitive way so you can improve your ability to identify a good price and make better trades.

Volatility is, mathematically speaking, the standard deviation of an asset over a set timeframe. In simple terms, If you were to take the price of Ethereum at 12:00 UTC each day for a year and plot those prices out on a line graph, the annual standard deviation would be a measure of how spread out these prices are on the graph. Finding the standard deviation is the key to understanding volatility and of course the process is a bit complex. There are several concepts and steps involved along the way but they are not beyond comprehension once each component is taken apart. I’ll cover Standard Deviation in the next article, but before that we need to quickly discuss an underlying concept: Randomness.

Randomness in Price Movement

It seems obvious, but there is something to unpack when you consider exactly what randomness means in the context of these calculations. The processes used to predict asset fluctuations can’t be perfect and they aren’t expected to be. This approach, referred to in statistics as “Stochastic”, is used to quantify the results of a situation that can’t be accurately predicted. Unlike a deterministic model that can find an accurate result with 100% certainty, Stochastic models are not expected to produce perfectly precise outputs. This type of model also assumes that will be no direct correlation between what has happened and what will happen, but that’s not necessarily how assets trade. Think of atoms or molecules colliding; there’s no point in looking for patterns or repeatable behavior. If you assume heavily traded assets will follow this behavior and the price is constantly being jostled around with erratic jumps or drops that are totally unrelated to each other, you end up ignoring the impact each move has on the next. Price movement is tied to human (or human programmed) actions and trading doesn’t happen in a vacuum.

This is a trade-off that has to be made when using mathematical calculations. You can’t factor social or psychological impacts into a formula, but you can still use these formulas to determine how the price movements are generally distributed. We are looking at data points (that the formulas consider random) in relation to the group and not considering the impact these data points have on each other. It’s important to understand this distinction as this is one of the blind spots you can leverage when analyzing prices and looking for opportunities. You can compare the results of these imperfect calculations against your idea of what volatility will be and maybe spot a favorable opportunity.

Summary

So, now you understand what an option is and have a general idea of what volatility is. We covered how volatility is the main factor when pricing an option, and we thought about how the calculations used to measure volatility approach randomness.

In the following articles I will dive deeper into the mechanics involved in options pricing and try to break down the math so you can see inside the black box. Then we’ll move on to the real world with examples of how this knowledge can be applied to improve your trading. There’s no doubt that these concepts are complicated and sometimes a bit overwhelming but they can be broken down and understood, and this knowledge can used to develop intuition and confidence when navigating options markets.

Read Part 2 of the series here.

[This article is meant to be used as an educational resource and is not intended to serve as financial advice.]