So we'll log it all-whereas others often only have tickers from exchanges. So if an exchange has great data we'll get it and if they have terrible data we'll get that too because people often do want data from these crappy exchanges. I think the beauty of our data approach is that we have a database that allows raw trade data to coexist with candle data to coexist from ticker data as the primary source data from exchanges and we inform you about what kind of data you're getting and how the numbers that you're asking for are derived from these data points. And then the worst case scenario is you're in exchange that only provides tickers. If an exchange only provides candle data then we will get the candle data and will calculate tickers but we won't use their tickers-we'll calculate them ourselves. So trade data is better than candle data, is better than ticker data, which is the worst and this is what our data set looks like: We have raw trade data and from those raw trades we can construct candles and from those candles we can construct tickers and that's for exchanges that do have raw trade data from. So, because we have the trades, we can compute the candles ourselves. They'll pump up the volume by just adding volume numbers to their candles and when you actually count-when you have gapless historical raw trade data-you can actually like count each individual trade and add it up and get to the volume and see if the math checks out, and often it doesn't. So, what we found in some cases is that exchanges are reporting candle data that is, in fact, inaccurate, right. So there's a lot that goes into this and a lot of our competitors just are ingesting tickers or candles and we normalized the way that we compute candles based on the raw trade. From there, we can create aggregated candles for Ethereum/BTC across all exchanges, and then we would aggregate those and arrive at a price. So, for example, if we have all these trades, we can create the candle for the Ethereum to BTC pair (ETH/BTC) on Coinbase Pro. Then we would move to creating exchange candles based on this pair. We'd start off with all the trades on all the Ethereum pairs-and this is an example of one. So, we would get, for example, every trade on the Ethereum to BTC pair (ETH/BTC) on Coinbase Pro. We start out by gathering every-let's start with a trading pair on an exchange, right, because there's a lot of trading activity on Ethereum that isn't with USD or fiat pair.
So let's say, for example, that you wanted to price Ethereum. So at the bottom kind of underlying everything that we do is gapless historical raw data. So probably a good way to think about data and how we do data is around this idea of a data pyramid. You essentially get tickers whenever they're computed, you don't necessarily get them at a specific time, so if you want to find out what an asset was priced at the end of a given time period you can't do that with tickers. And then you have tickers-which a lot of our competitors are gathering ticker data rather than candles or trades.
As you can see, there's just a lot that's left out-you can actually hide a lot of fake volume in candles. As you can see, this is fairly high fidelity. So, we have essentially the entire trading history of that exchange and from those trades we construct candles and from those candles we construct tickers. So, for the majority of the exchanges that we have data from we have literally every trade on every trading pair on that exchange.
So, our service and most of what we do is based around raw trade data, right. So I think perhaps the way to start this out is by talking about data and data quality. Our investors include Coinbase Ventures, Digital Currency Group, CityBlock Capital, and a bunch of people that we really respect in the space. If you do go to Nomics that entire website was built with our API so anything you see on the website we have available but we also have a lot of data available that is not on our website.
We built the API before we built anything else. We found that most price aggregators and most market data services are failing in a number of ways that I think we've solved for and I wanted to cover that first.Ī little bit about the company: we are an API first product company, so out of everything that we do our API comes first. Hi, so I wanted to cover Nomics and our data and why we're different.
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