Hi, so I wanted to cover Nomics and our data and why we're different. 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.
A little bit about the company: we are an API first product company, so out of everything that we do our API comes first. We built the API before we built anything else. 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.
Our investors include Coinbase Ventures, Digital Currency Group, CityBlock Capital, and a bunch of people that we really respect in the space.
So I think perhaps the way to start this out is by talking about data and data quality. So, our service and most of what we do is based around raw trade data, right. 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, we have essentially the entire trading history of that exchange and from those trades we construct candles and from those candles we construct tickers.
Here we have on this chart, trades. As you can see, this is fairly high fidelity. This is Binance BTC/USD market. Here we have candles for BTC/USD. As you can see, there's just a lot that's left out—you can actually hide a lot of fake volume in candles. And then you have tickers—which a lot of our competitors are gathering ticker data rather than candles or trades. And ticker data is pretty bad... 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. There's just a lot of problems...
So probably a good way to think about data and how we do data is around this idea of a data pyramid. So at the bottom kind of underlying everything that we do is gapless historical raw data. So let's say, for example, that you wanted to price Ethereum. 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, we would get, for example, every trade on the Ethereum to BTC pair (ETH/BTC) on Coinbase Pro. We'd start off with all the trades on all the Ethereum pairs—and this is an example of one. Then we would move to creating exchange candles based on this pair. 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. 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 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.
So, what we found in some cases is that exchanges are reporting candle data that is, in fact, inaccurate, right. 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, because we have the trades, we can compute the candles 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. 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. And then the worst case scenario is you're in exchange that only provides tickers.
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.
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. So we'll log it all—whereas others often only have tickers from exchanges. In other words, they're ingesting tickers and then constructing candles from those tickers and that's something that I think is pretty important to talk about. A lot of our competitors, what they're doing is they're ingesting tickers like ticker feed data in real time and they're constructing candles from that.
So let's say you want to construct a 1-minute candle and then you've got 24-hour tickers coming in so a ticker is basically like a 24-hour candle that you get whenever you get it—whenever it's computed—it isn't computed on specific time intervals that you can rely on. So let's say you're ingesting data from an exchange that only provides ticker data (that's all that they do) and you want to construct a 1-minute candle. Well, let's say that only one ticker comes in during this one minute—that means that the open/close high and low for this candle is all the same price. Similarly, let's say you want to create a 1-hour candle and you've got the steady stream of tickers coming in. You know whenever they send them to you, well, you can't use. So, let's just go all the way down. So let's say you do luck out, you hit the lottery and you do get a ticker that gives you a data point at the exact time of this candle opening and let's say you get some additional points that you are going to believe are the high and low. The low at least they're the highest and lowest prices of the ticker points that you have—which are not a lot—during this period and let's say the last ticker you get before the close of this candle is at 2:50 257. Well, you have to just taken this price that you got at 2:57, just assume that it's close (if you are constructing tickers from candles), which is generally a bad idea. This isn't how we do things.
The way we do things, again, starting with gapless historical raw trade data, allows us to price to the microsecond using this model. So, anyway, there's a lot I can talk about here.
I think it's probably worth discussing a little bit our transparency ratings. So you might recall that Bitwise put out a report where they identified 10 exchanges that they say have actual volume and in order to do this analysis they looked at Bitcoin to USD (BTC/USD) and Bitcoin to Tether (BTC/USDT) markets and they looked at 80 exchanges. They did not look at exchanges that did not have Bitcoin to USD in Bitcoin to other markets and we were looking at this data and we found something interesting... We found that of the 10 exchanges that were deemed to be trusted by Bitwise, that 8 out of these 10 exchanges provided historical gapless raw trade data. And why would that be, right? I think the reason this would be the case is that just like the IRS if you provide a lot of data and you're doing something wrong you're likely to be caught. So we have found that providing historical gapless raw trade data is correlated with being a good exchange. And then of the exchanges that Bitwise identified as being suspect, that they explicitly called out as being suspect, all but two of those did not provide historical gapless raw trade data.
We care quite a bit about how we approach data. I can tell you a little bit about our data services. Basically, we can create customized endpoints for you. Often, there's analysis that people want that requires them to download a whole lot of data and then analyze that data and often—because we have all the data in our database—we can just give you an API endpoint that just outputs the number that you're looking for that just sort of does the analysis for you. So, that's one of the things that we do.
Let's start off with the first one. I'm not going to go through all these slides but we do custom asset pricing so what we found is that a lot of hedge funds and funds that calculate nav for investors, that they want to calculate prices according to a specified methodology. So they might say, "We want to calculate prices based on only these ten exchanges and even just in and only based on Fiat pairs on these ten exchanges," and so they specify and they want to "calculate end-of-day prices based on the end of the day" in their time zone. Let's say they're in California... Then they would calculate these based on end of day prices in the Pacific time zone...
Another thing that we do is we provide low latency data. So if you need super low latency order book snapshots and trading data, that's something we can do. We can get order book snapshots down to 100 milliseconds.
Another thing that we do—and this is more for exchanges—but we can power white label market data API. So if you're an exchange and you do have a data API, we can run that for you.
And, finally, we can stand up market data websites for you. So let's say you have an investor portal and you want to give your investors like, you know, real-time access to what's happening with the price of a whole bunch of different cryptocurrencies and you want to give them real-time access to maybe an index or prices on the exchanges that you guys
or gals are trading on, then we can do that for you.
Yeah so anyway, I kind of went through all [these slides] anyway...
On behalf of all of us, thank you.
Our Cryptocurrency and Bitcoin API is a lightning fast REST API that aspires to be the data backbone for developers and professional cryptoinvestors. Our product roadmap revolves around a “Triple A” feature set: we're building our core product to archive, aggregate, and analyze both on- & off-blockchain cryptoasset data relevant to investors and traders. For more information, please see our docs.
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Brian Krogsgard: Hello and welcome to Ledger Cast. My name is Brian Krogsgard and today we have Clay Collins on the show from Nomics. Nomics.com is his website. This is an all encompassing API project where he's really looking to be the data layer for crypto and for maintaining the history of the price of any crypto asset previously and going forward. He believes that there will be thousands and thousands of these assets that need to be tracked and they're looking to create a hardened layer of data to maintain that price history and integrity. We talk all about this project. Clay is a seasoned entrepreneur and this is his latest project. He was part of Leadpages. I think you'll really enjoy it. This episode is brought to you by Delta. Go to ledgerstatus. com/delta to check it out. They have some really great stuff going on right now because they just released live order books and depth charts. It's all in the latest version of Delta. This is one of the most requested features they've had. So I'm really excited to be able to share with my listeners that that's now available because I know a lot of technical traders want to be able to check out the order books, get an idea of depth on the price a while they're looking at their portfolio. They've got that and so much more. Thanks to Delta for being a Ledger Status partner. Now, here's the show.
Brian Krogsgard: Hello and welcome to the Ledger Cast. My name is Brian Krogsgard and today we have Clay Collins on the show from Nomics. He's the co-founder of Nomics and nomics.com the website for that. Clay and I've been talking a good bit over the past several weeks, ever since I pinged him on Twitter looking for information about their API. Hey Clay, welcome to the show.
Clay Collins: Hey Brian. It's great to be here. Thanks for having me. I'm stoked.
Brian Krogsgard: Yeah. So I was a stalking what y'all were building for a bit, between listening to your podcast and then just kind of checking out your blog posts and your newsletter and all that kind of stuff. And then I was actually looking to potentially use your API and we're gonna dig into this about what Nomics is, why you're building what you're building. And you responded to me in like record time and it required y'all to potentially build a new feature and you're like, "Yeah. We'll have that like tomorrow." So you piqued my interest for sure purely based on an incredible response time to trying to help someone use the product that you're building. And I'd like you to fill in for everyone else, like what the heck is Nomics at a thousand foot view?
Clay Collins: Yeah. So, great question. There's two components of Nomics. The front end, which is at nomics.com is it's a coin market cap competitor. We're gonna eventually open source completely the front end as well as iOS and Android apps. So we really wanna open source that and it's powered on the back end by the Nomics API, which is an aggregator API. And not only do we have ticker data, but we have multiple candlestick links on the back end for aggregate market, so all Bitcoin markets, all Ethereum markets, et cetera. And ... But we have candlestick data for individual markets for example, like the [inaudible 00:03:49] market on Poloniex for example. So we've got aggregate candlestick data and we have data for individual markets on individual exchanges, and we have every single trade on all of those markets, on all of those exchanges going back to the inception of those markets.
Clay Collins: So if I can beat my chest a little bit here, I really do think after reviewing all the APIs in this space, hands down I believe we have the best market data API in this space. It's fast, it's free and you can sign up and get an API really quickly and be in business. And something that I think is worth noting is that everything you see on nomics.com is powered by the free version of our API and we're using the free version of our API. So there's no back doors, there's no hidden in points. We're consuming this exactly like a customer is. In fact, we went in and we signed up and we've got an API key and we just use that API key in our app. So we're a big believer in dog fooding and being a customer of our own products. And that was one of the rules that we put in place from day one, is that we couldn't do anything with our app that our customers couldn't do with the free version of our product.
Brian Krogsgard: Nice. So at a baseline you are providing data specifically around coin data at a high level and then very specific data in terms of pricing on a daily basis, and I think an hourly basis at a core. I think what I actually asked you all about in that thing was whether y'all could do ... provide either like four, six hour data. So that was something else that y'all were looking to add and now people can use this to build something just like nomics.com or they can use it within a trading strategy if they want to do automated trading or pretty much anything else. Right?
Clay Collins: Yep.
Brian Krogsgard: So-
Clay Collins: Yeah-
Brian Krogsgard: This is essentially just a massive data feed, but instead of me going and saying, "Hey, I want this data from a Poloniex.", as your example that you used earlier. Your dealing with all the hassles of getting data off an exchange, so that I don't have to integrate with every single exchange in the world and instead I integrate with Nomics and I'm good to go.
Clay Collins: Yeah. So I think you summarized that correctly. I think kind of accompany that were similar to is a company called ... You know what actually, I won't get too much into that. Yeah. So basically, one of the ... The problem that we're solving for is a problem that kind of came up a lot in conversations when we were talking to hedge funds and family offices and institutional investors, which was, they'd hire a pretty fancy developer to do data science work, to find edge and opportunities in the data sets. And their developer that they'd hired for that purpose would end up spending much of their time rather than finding opportunities in the data set, just maintaining those data sets. So if you spend much time at all ingesting data from these exchanges, you'll find that ticker symbols change from exchange to exchange, and then the exchanges themselves will change a ticker symbols. They'll change their data schemas without telling you, their data feeds will turn off and then they'll come back on again, there's lots of downtime.
Clay Collins: And so if you're just ingesting data from one of these exchanges and you're okay with dealing with just a bunch of friction, then I think it's probably okay. The second you want to ingest data from multiple exchanges, things get a lot trickier. And when we started in this business, we just ... we started off by integrating with five exchanges and we had 80% of the volume. Now in order to get 50% of the volume, you need to integrate with like 20 exchanges and-
Brian Krogsgard: Meaning like global trade volume for whatever currencies that you're tracking.
Clay Collins: Exactly, exactly. So you're having to integrate with more and more of these exchanges to get an accurate picture of what's happening-
Brian Krogsgard: So the long tail ... The long tail of a global trading is getting larger basically.
Clay Collins: Yep, exactly. So there's lots of just real oddities when integrating with these exchanges. For example, some exchanges when their APIs go down because of the way they're cashing works, they just persist the last candle. So they'll give ... they'll just keep on giving you the same candle over and over and over again and so it looks like the same things happening, and that's really stupid. Other exchanges do things like ... We were looking at an exchange the other day that had a market called USD ... it was called USDT USD and people were integrating with that and they didn't know is that tethered to USD or is that USD to true USD. Like what the hell is going on here? There's just a lot of bizarre stuff happening in this space. So we wanted to create a super professional lightening fast API and that's what we're solving-
Brian Krogsgard: Out of of curiosity on that exact pair, were they basically seeking to provide a trading pair between to different stable coins in order to smooth the market on their own platform?
Clay Collins: So one of those was the [inaudible 00:09:25] market and one of those was a stable code. You just didn't know which-
Brian Krogsgard: Oh, okay.
Clay Collins: Because ... Yeah. USDT USD could either be USD to true USD or tether to [inaudible 00:09:34] USD.
Brian Krogsgard: Yeah. Yeah. The blend of stable coins is super interesting to me, like the way ... And trying to find out like what's gonna be supported, how do we measure stuff like that. I even saw one the other day where ... and I'm sure y'all will start tracking these types of things too. So they are creating kinda index funds on the go and one of their funds is actually a stable coin blend. So if you buy their stable coin blend, I guess their whole point is like you're buying the average of all the stable coins so that it will be stabilized to stable coin mix to be even closer to a dollar.
Clay Collins: Oh, my God.
Brian Krogsgard: There's just a lot of effort going into people trying to call a dollar a dollar in crypto, which I ... And I think it's perhaps just a bit of a signal for how difficult data is in not only this space, but pretty much any space. And I'm fascinated by this play because there's so much opportunity I think as the ecosystem grows and I never had heard what you said earlier about just how much trading is going on on the long tail. Because when you think about like, "Hey, where are people trading crypto?" You hear the same stuff, right? You hear that they're on Binance and that they're on Coinbase and to a lesser degree, Bittrex and Poloniex, and then you've got some Asian exchanges that are doing a lot of trading, but you don't actually know if it's real for some of them. Like I think WEX recently is like super weird and Tether was trading for like 2.50 a piece or something, like crazy stuff is going on.
Clay Collins: [inaudible 00:11:20].
Brian Krogsgard: And keeping track of all of it is really difficult. I come from a development background. You come from a web background. I actually knew who you were in your prior company, which is Leadpages by the way, for anyone listening from the web space. So how did you transition from building a big company ... of what became a big company with Leadpages to saying, "Hey, we're gonna get involved in cryptocurrency and go after this data play."?
Clay Collins: Yeah. So that's a great question. So to speak to my previous history or what I was doing before this, my first software company was a company called Leadpages that was started in January of 2013. From 2013 to 2017, we grew that to about 50,000 paying customers. We raised 38 million in venture capital, hired hundreds of people, had a really good go there. Something I realized about myself is that I think I cap out at around 100 people in terms of company size and my ability to manage at scale. At some point you're managing people and then you're managing people who manage people and then you're managing the people who manage people who manage people. And I really liked that spot of like between 80 people to 100 people. So perhaps I can scale beyond that with my second software company, but at some point I just kinda went to the board and said, "Hey. I think we should hire a CEO and I can stay on the board." In fact, I wanted to stay on the board and so I started thinking about ... Yeah. So I started-
Brian Krogsgard: So you're on the board of Leadpages today and ... but you're not involved in the day to day management of the company.
Clay Collins: Exactly, yeah. I'm not going into the office and ... Yeah. I mean I'm officially chairman of the board, but that's kind of a nice honorary title. I asked for it.
Brian Krogsgard: Yeah.
Clay Collins: They were nice enough to me. So one of the things that I saw in the marketing tech space, which was really fascinating, was just how a data got ... became more and more distributed over time. So when you first started using marketing tech in the space, someone would use something like Infusionsoft or HubSpot or Salesforce and everything would be in one place. But then as the space exploded about every single year, the number of martech companies doubled. So folks found themselves sort of originating a place where everything was in their CRM or everything was in their email service provider, to a space where they had to open ... an email open rate and click data and like a MailChimp. And then they had information about who attended what webinars in a place like Zoom or GoToWebinar. And then they had ... They had payment data in something like Stripe and they had information about what webpages people are visiting in a place like Google Analytics.
Clay Collins: And over time, the data just got more and more distributed and it became harder to know what was actually happening in terms of the 360 view of the customer and what they were doing across all these different SAS products that you were using to run your business. And as that happened, there became a real desire to integrate all these different systems and that became a real challenge. And at that time, I got really interested in data platforms and customer data platforms where ... which ... essentially these data hubs.
Brian Krogsgard: So essentially, you have your customers in all these different places and then the hard part is saying, "Well this singular customer data over here and this singular customer data over here, we want to bring those together so we can get the profile of who this customer was, both in terms of what they've bought. But also how they've interacted with our website or app. And then also like how they treat our emails and stuff." Like so they-
Clay Collins: Yeah, yeah. What pages they visited, what emails they've opened, what webinars they've attended, what ... You know.
Brian Krogsgard: Maybe even like whether they follow us on Twitter or something like that.
Clay Collins: All that stuff and tracking their behavior before you even have an email address or some sort of identifier. So while they're anonymous users onto ... they're a customer and then they quit and then they rejoined. So all this sort of post-purchase information and stitching together a unified customer timeline of everything they did across this timeline. And I saw the same thing happening in the crypto space, again with lots of consolidation in data. At first there was just a handful of exchanges that had most of the volume and then over time, that data being more and more distributed. And hearing from developers that every time they add a new integration to the system, it made the system exponentially more complex because they had to deal with these different systems going up and down in the interaction between systems and maintaining the integrations and all that.
Clay Collins: So we are not a blockchain company. We're not issuing a token. This is an API business. This is a really kind of "boring business", but I think that's kind of in my DNA. I'm a product person and I'm in this for the long haul. And it's kind of these companies that other people find boring, I find immensely interesting. Companies like SendGrid that handle SMTP email, companies like AWS. Almost these online utility companies that charge on a metered basis, that's kind of my sweet spot and where I derive the most amount of interest. And I think the opportunity for us is that these are often things that most people just aren't interested in because they find them to boring.
Brian Krogsgard: Yeah. And there's a lot of ... What do you ... You probably know the term for this, but like where degradation and data over time. So I like to use the example of metal just 'cause it's one I remember of being listed on Bittrex and then listed on Binance later and then de-listed on Bittrex, but it's still on Binance. And this is only over the course of whatever the last year that it's existed. We have no idea how this data might happen for an open source ... or open data, open trading data for hundreds or thousands of crypto assets over the course of 10 or 20 or 50 years, and maintaining a source of truth for an asset like that becomes very difficult.
Brian Krogsgard: So I've seen people ... I say metal because that's the example I know where it has this history of Bittrex and it was way higher than it ever showed on Binance and I've seen people show a chart of metal on Binance and they're like, "Wow. This thing is so destroyed, like it's so far off the top." And every time I see someone post that, I'm like, " Yeah, let me show you this other graph." And it's like the historical context of metal where it was another five times higher because it was ICO and listed in the height of the crypto boom. But people are essentially lacking information to then make a decision because they don't have all of that aggregated. So one of the things that y'all do, because you're pulling it from Bittrex and Binance, you're piling that into your global average over time and you're essentially providing data security for this asset and every other. For as long as you exist, you have that central source of truth if someone can use for making decisions. Right?
Clay Collins: Yep. Yep. Absolutely. And you know, one question we get from folks who don't spend a lot of time looking at data is, "Doesn't QuidMarket cap have this data? Don't other sites like maybe Live Coin Watch have this data?" And they don't. They don't have candlestick data. For the most part, those services are just ingesting live tickers as the data comes in. They don't have historical trade data. They don't have the kind of data that a real trader would want to observe if they're going to create a bot for example.
Brian Krogsgard: Yeah. They may have ... I've actually poked around several of the APIs that are out there. CoinMarketCap in particular, if you're building something really baseline where you're okay being somewhat right limited and you're gonna go cash all that, you can get stuff like 24 hour volume on a coin or you can get like current price or the percentage of the supply that's out, stuff like that. But getting detailed data of everything that's happened over the past or lifetime of the coin, like several years sometimes, it gets a lot more challenging with anything. And then also just the quirks between all the dIfferent exchanges and everything that they support, and that seems to be kind of where y'all are attacking this. So I'm super interested in this, but what I am ... What is hard to figure out is where the heck are you gonna make money and why are you doing this 'cause the ... Everything you do on nomics.com is actually pretty advanced for someone that at least wants to view and use a data. I'm not necessarily trading based on what you have there. So where do you start to make money? Who do ... What kind of people do you charge if I can build something like nomics.com for free?
Clay Collins: Yeah. So we have paying customers. We ... They're tradition ... They're mostly ...
Clay Collins: ... customers. They're mostly institutional traders, quantitative hedge funds. Folks like that. What they're paying for is the raw trade data. When you want every individual trade, then you have to pay us or if you want some custom integrations or if you want SLAs and high level support or you want us to do some custom development work for you-
Brian Krogsgard: The SLA is the service level agreement. You're saying you'll be up 99.9% of the time.
Clay Collins: Yup.
Brian Krogsgard: Or three nines, whatever your promise is.
Clay Collins: Yeah. Yeah. I mean we're somewhat limited by the APIs themselves, but our API is always up. We don't persist the last candle if their API is down even though they're doing it. We'll just mark it as a zero and then we'll backfill it.
Brian Krogsgard: Do y'all do data repair?
Clay Collins: Yeah.
Brian Krogsgard: Okay.
Clay Collins: Yeah. Yeah. If you're just consuming the live data feeds, they don't repair their data. We go back in and we get after the fact. Those are the folks that pay us. What that allows you to do is it allows you to create your own candles. If you decide you want 38 second candles, you can do it because you have the raw trades. You can construct everything. Something that some folks want are like volume candles. They don't want candles based on like every hour or every four hours. They want million dollar candles. They want for the last million dollars in trading volume, what's the open/close, the high and the low. Actually they're doing a lot of the stuff that they won't even tell us.
Clay Collins: I'm a product person, so when someone buys our product, I'll go in and ask them, "What are you doing with this data?" They don't want to tell us "Just send it off to us and we'll do our proprietary thing." That's their strategy, so we're not going to ask them. Sometimes we get a little insight when we do onsite visits and stuff like that. Those are the folks that pay us. It's $500 a month for that plan. Pretty cheap in the scheme of things given the size of folk's data budgets. We'll probably move to a metered plan in the future.
Brian Krogsgard: Okay. What would a metered plan look like? Would that be from there and higher or lower the bar?
Clay Collins: It would be like it's just sort of pay as you go. Ala carte. If you want to make a lot more calls, then you'll pay for those additional exposure to data.
Brian Krogsgard: How do you bring exchanges on to participate to this? I don't think you have like 100% exchange coverage, but y'all have, I can't remember what the number was, maybe a dozen or a couple dozen exchanges right now?
Clay Collins: Yeah. We've got about a dozen. The reason why we only have a dozen right now versus having a lot more is for kicking things off, we only wanted to work with exchanges that give us raw trade data. That allows us to calculate our own candles versus us believing their candles. We've just found fraud. I can talk about that for a second. I'm not going to name an exchange, but the kind of fraud that we see most frequently occurring is when trades happen like far above the spot price. Right? You've got the bid ask spread. You've got the spot price, which would be a market order. It would be the bid jump way across the ask and purchase something like way over here.
Clay Collins: So if you see those charts it's like jumping across the gap. So they'll be really paying some absurd amount for bitcoin, or whatever the crypto asset is, but buying a tiny amount of it at some insane price, and we're like there's no way an order book should let this happen. So that's what we see most frequently.
Brian Krogsgard: I've seen that specifically when people list a coin. They do that weird stuff and you see the massive first bar for some unknown reason. Then two other scenarios I've seen, one was when Binance had the Syscoin hack and shenanigans that they did recently, someone stole 11 Syscoin for 96 BTC each. I don't know if they skipped through the entire order book, like if it was just thin so that they spiked it to that level or what. But then the other scenario that I've heard that's fascinating to me is sometimes you can do that through exchange APIs because a lot of times the way you show an order book in a RESTful API is actually it shows every single one and then you can pluck the individual order.
Brian Krogsgard: So it allows you to essentially skip the order book, whereas typically a limit order's going to choose the lowest one or a market order is going to pull from the bottom or whatever. But I've heard there's some exchanges where they have funkiness in their API that would also allow something like that.
Clay Collins: Yeah, so maybe it isn't fraud. I mean, sometimes-
Brian Krogsgard: Well it might be a bad API integration.
Clay Collins: Yeah. If you have really thin markets and you put in a market order then it could just be that it blew past all the sell orders and jumped to some super high price. But I can see what you're talking about with the APIs. You can pluck a specific order, although I don't know why someone would do that. That would just make no sense. So it could just be a crappy programmer somewhere. But I don't know why a crappy programmer at a hedge fund is buying Syscoin for several bitcoin each. I just can't see any-
Brian Krogsgard: Yeah, I think in that example it was something related to the hack that they had and it was just a hot mess.
Brian Krogsgard: I am curious. Y'all have a ton of data between the pricing data, candle data, exchange rates ... I'm just looking through some of your documentation right now. Since you came from a marketing background, how did you even know like here's the data that we need to put into this API? How do you know what to provide and how to build it?
Clay Collins: Yeah, so I'm a product person first and foremost. So we get it by talking with customers. But we're also traders ourselves. So we know it from that perspective and we create stuff that we want to dog food ourselves. It's really about talking to customers a lot, doing stuff like we did with you on Twitter where you asked for a feature and like okay, we're going to build it. Or when we're talking to customers sometimes they'll say "Hey, we want this, but in order for this to really work for us we need you to add this additional thing."
Clay Collins: So it's just about talking with the customers all the time and I'm on the phone multiple times per week with institutional traders, developers and trying to learn everything I can about making a solid product. I think kind of the DNA you have to have to make this kind of product is very different from the average product in this space. There's a lot of hackathon developers. There's a lot of kind of young dudes in their 20s spitting stuff up over the weekend. And to create a data product and a data platform I think it requires a certain level of discipline.
Clay Collins: So to kind of put this into perspective, we have a 100% unit test coverage on the front-end and the backend. So every single line of code has a unit test that covers that code.
Brian Krogsgard: Which means, for non-programmers, that means that what he says is going to happen has been tested via a whole nother slate of programming tools to verify that that's what happens, because he said it was going to happen. I don't know if that described that well.
Clay Collins: Yeah, we have just as much code testing the app, as the app itself. Which means that myself as a non-developer, my CTO or someone else on the team will often send me a version of the app and I'll log into GitHub and deploy to production without anyone manually testing it. So it's just a certain level of rigor. It's not something that most people have the stomach for because it's slower at first, but it pays off in spades down the road.
Brian Krogsgard: Let's take a break, say thank you to our partner for this episode, Delta. Go ledgerstatus.com/delta to check it out right now. This is the best way to track your portfolio in crypto, bar none, guaranteed. Go to ledgerstatus.com/delta. And you know they've got some great new features. The last two releases have just been chock full of stuff. Live order books and depth charts, number one on the request list for people that I've talked to who said that they like Delta but they want more. That's the biggest thing they've wanted. You've got that now.
Brian Krogsgard: I think they support like a dozen exchanges so that you can see the actual order book, the depth charts, recent trades, all that stuff, right there in the app. It's really great. They've just released portfolio analytics as well and I've thought this was really cool because I can go back and it'll actually tell me, if I'm a pro user it tells me even more, but it tells me stuff like what exchange are my coins on or what wallet is it in and it gives me these really nice graphs with all of that information, with a lot of analytical data. It also even tells me what's a good trade or a bad trade. So if I sold something and it's gone down since then it'll tell me hey that was a good sell because it's gone down since then.
Brian Krogsgard: It gives you some insights on your past decision making to let you know if you've done a good thing or a bad thing with that trade. Just give you a little more information about your trading and so that you can learn more to be a better trader.
Brian Krogsgard: Delta's really awesome. They're always working on cool stuff. Go to ledgerstatus.com/delta and thanks so much to Delta for being a Ledger Status partner. Somebody may be listening to this and they might just say okay, so you want to provide data for hedge funds or for traders or people that want to build something like nomics.com or they want to build an app or whatever it is, is this overkill? You have to be dreaming up more that this will be, in terms of the entire market, beyond a whole bunch of weird crypto assets that most should die. Other than Bitcoin, Ethereum, and some large caps, do we really need this data? What else do you imagine in terms of being able to fit into your ecosystem? You have a grand vision of the future it seems.
Clay Collins: Yeah, totally, totally. There's a couple of functions that we want to serve. One is want to be like the internet archive of the new financial system. So archiving all of these dead coins, all of these markets that have expired, we want to tell the story and the history of what was happening when all of this started to come onto the scene. I think a second thing is that ... Perhaps this is overkill for what we have right now, but what we're intending to build is the data backbone for the new financial world, for the open financial system.
Clay Collins: And we take that very seriously. Also, the think right now there's not a lot of data. Perhaps there is. We've indexed billions of trades. But that trend that we saw where we indexed five exchanges that had 80% of the volume and now you need to have 20 exchanges to even have 50% of the volume, I see that trend continuing, especially with the explosion of decentralized exchanges. And multiple versions of local bitcoins that are reporting their data. Then OTC desks. And then add to that security token exchanges.
Clay Collins: So imagine someday every single local coffee shop, pizza shop, anyone who wants to fundraise in this way, every single building in your city has a token and that token is perhaps traded on some kind of local exchange, there's just going to be an explosion of exchanges. And then add to that order book data. So data for orders that haven't been filled or have been canceled or maybe the order's been placed and that order converts to an actual trade and then add to that blockchain data and you have a huge undertaking in terms of-
Brian Krogsgard: And that's all underlying physical product. Right? That's the asset itself. That doesn't even get into a future where there's derivative products or futures or options. There's a whole nother set of trades and orders and everything. So y'all want to support all of that someday right?
Clay Collins: Oh, no, and we are. And we have specs to handle that right now. So if you're from a blockchain project, if you're from an exchange, if you're from an OTC desk and you want to integrate your data with us, let us know. We have specs for you to write to. If you can stand up three endpoints, pretty simple endpoints, we can give you a heck of a lot of exposure. So yeah, we're doing all of that and then add to that different indexes. So index fund indexes or various crypto versions of the S&P 500 which we're indexing and then we're going to be ranking and indexing performance of bots on different bot engines. So each of those bots are going to have their own rankings. There's quite a future.
Brian Krogsgard: This seems like an exponential explosion of data that's going to be on your ecosystem. How are you looking to be able to scale that? Like is this built on just a regular old database? I mean what's this look like?
Clay Collins: So kind of the latest is using Kafka and Cassandra and that's what we're building on. We're not using Microsoft Access.
Brian Krogsgard: Yeah, definitely not.
Clay Collins: Kind of these large nonrelationable wide column store databases that can handle trillions upon trillions of data points. That's how you got to do it.
Brian Krogsgard: And then ... I don't want to get too much in the weeds. I want to start asking about the output side, but I assume that for someone consuming this y'all have a REST API is the way they're doing that or is it GraphQL or something?
Clay Collins: Yeah, we just haven't had enough interest in GraphQL but yeah it's a RESTful API. There's no rate limiting. So we cache the hell out of our endpoints. So you can hit us as hard as you want. We don't care. Go nuts. A lot of people charge quite a bit for these sort of uncapped non rate limited APIs, but yeah we won't rate limit. That's another thing that no one else will do that we do is we don't rate limit.
Brian Krogsgard: And you're just assuming either that it's worth eating the cost for now or the cost is somewhat nominal for now. Do you expect your pay customers will be able to absorb that function for the long haul?
Clay Collins: So a couple things, one, we're really good at caching. Second, we just want to win in the short term. So we want people to feel comfortable using us and third, I'm funding this myself. In the long term, the way we're modeled the big cost is not that we're not rate limiting it here, it's engineers.
Brian Krogsgard: Right. We probably could have led with this but I think people have probably gotten the picture by now, but this is a centralized business with a open API and there's no token. There's none of that stuff. You're not a crypto project. Unless someday maybe you tokenize nomics.com as a security. But this is a normal old business, not like a blockchain project itself. It's not token based or anything like that.
Clay Collins: Right. Yeah, so we're using centralized databases. We're a centralized company. I'm a big believer in that not everything needs to be decentralized or run on a blockchain and I actually think that what we're doing is kind of a horrible candidate for the blockchain. It's a terrible blockchain use case.
Brian Krogsgard: Especially if you need information back quickly and reliably.
Clay Collins: Yeah. You want millisecond response times on APIs. Yeah, you probably don't want to use a blockchain. So yeah, at some point maybe we'll tokenize equity of the company and let people buy a piece of what we're doing. But for now this is kind of ... We want to be really good at the boring basics. And that's what we're focused on.
Brian Krogsgard: In addition to all of this you're doing a podcast called Flippening. I just listened to a three part series that y'all put out about security tokens and probably tripled my knowledge of not only ... I kind of had an idea of what security tokens potential was, but more about who are the players within the security token landscape and what do they envision and how do they differ from each other. So people might hear of Polymath because it has a token, but people should also be aware of something like Harbor and they provide a different type of service than what poly does. Bruce Fenton was on your show, who's a big Ravencoin guy.
Brian Krogsgard: And they're going to have stuff on top of a platform on Ravencoin, but he created a security token for his company on Counterparty through bitcoin. There's already all these tools for security tokens, so you just did this huge deep dive, why are you spending ... I thought about how much time Clay must have spent making this podcast, because each episode's got half a dozen guests, edited down into the questions. How much time are you spending on this stuff and why? What's your basis for doing such an in depth series like that?
Clay Collins: All in, that was at least 150 hours. I'm embarrassed how much time that series took. Yeah, so that was just one of these stupid ideas where I was like I want to do an audio documentary. I had heard a really good audio documentary about cryptocurrencies and there was a part of me as a product person that respects the craftsmanship that said to myself I want to create something that is like planet money level content for the cryptocurrency space about security tokens.
Clay Collins: And kind of the genesis of that was I interviewed one company. I interviewed Polymath about security tokens and I got just this fraction of a picture of what was happening and then I realized there's exchanges, and there are issuers, and there were just so many regulatory bodies and there was so many different components to this. Because there's already a pretty mature financial system that deals with securities already, so I couldn't do just one interview. So I started booking all these interviews and then I realized that it was too late. Once I interviewed the people now I had a commitment to publish them, but it didn't make sense to publish all these interviews by themselves because they really didn't stand on their own. I needed to weave a narrative through it and then I need to write a narrative, which means I need-
Brian Krogsgard: So you backed your way into this whole documentary.
Clay Collins: Oh, god. And then I had to storyboard out the whole thing. It was really a pain.
Clay Collins: -storyboard out the whole thing. It was really a pain in the ass, but the interesting thing is, after I finished that, I figured out what my workflow was for creating these, and I've realized ... I kind of figured out how I could do one in a third of the time next time, so I'm probably going to be doing another stupid one here in the future.
Brian Krogsgard: So, is the purpose behind these that you just want to share what you're learning and traditional podcast stuff? Or is this marketing for Nomics?
Clay Collins: It's marketing for Nomics.
Brian Krogsgard: Yeah, okay.
Clay Collins: Yeah, it's marketing for Nomics. It's really the only podcast for institutional crypto-investors. There's no podcast that has more listenership and more coverage from the institutional crowd than Flippening. That's exactly who our target audience is. Everyone who's paid for the API so far has [inaudible 00:42:55] the podcast.
Brian Krogsgard: Okay.
Clay Collins: Because I don't have a big content marketing team, we can't churn out a bunch of thought pieces or tutorials. There's just me. If I can do one thing that's going to attract the kind of audience that I want to get, what can I do? It was create this podcast because I started evaluating how much time does CoinDesk spend to put on Consensus or Consensus Invest? And it's millions of dollars. I've thrown big events before.
Brian Krogsgard: And they make millions of dollars too.
Clay Collins: Yeah, and they make millions of dollars too. But having come from the event business, I bet they're just doing better than break even. That's my prediction. I could be completely wrong, but I bet they're just doing better, even with how it's monetized. I bet you they're just doing a little bit better than break even. In New York, in Times Square, that's my prediction.
Brian Krogsgard: Yeah, I've run small events, and it's enormous energy and very little money is what it ends up as most of the time.
Clay Collins: Right. Yeah, so I was doing the stats on my podcast, and every single episode was getting about 50,000 downloads. I was like, "There was 12,000 people at Consensus Invest," so I bet I'm getting just as much coverage with that podcast from this very niche institutional investor crowd. The ROI for me really made sense. Even though it's a pain in the ass that I love to do, I'm probably going to still continue doing it.
Brian Krogsgard: Who do you consider an institutional investor in the space? Is that hedge funds, or is that like a family office, somebody with $1 million to spend on crypto? What's an institutional investor to you?
Clay Collins: Yeah, so I define institutional as someone who raises money from other parties to invest it on their behalf.
Brian Krogsgard: Okay.
Clay Collins: Usually they've filed as a sort of a Reg D fund or they're usually regulated in some way, so they're not just playing with their own money. A family office is technically not an institutional investor, but some of these family offices have billions under management, so it's kind of like they walk like a duck, they talk like a duck, and they have that level of rigor to what they do. They've got an entire staff and stuff. Yeah, institutional investors are-
Brian Krogsgard: What are some of the big lessons that you've learned, based on the people you've talked to, in terms of what's most concerning to an institutional investor? And let's level that up, the higher-end ones. For instance, I know custody is an issue for real institutional investors, whereas, for a lot of people with a little less on the line, they can kind of manage custody in-house. But if you're a regulated entity, custody becomes significantly more important. What kind of lessons for those types of people do you think you've been able to come up with?
Clay Collins: Yeah, so custody is definitely the big one. The next one is just deep markets, being able to make a block trade, if you want to buy $30 million worth of Bitcoin without just burning through the order books and moving the market. That's where good OTC desks come in. You place a phone call, you arrange the price ahead of time, and then you do the trade. OTC desks and clearinghouses are probably the next point of concern.
Clay Collins: And then it's just good projects. I mean, it's hard for a lot of these folks to find coins other than Bitcoin and Ethereum that have enough liquidity and market depth for them to feel comfortable and just history. [inaudible 00:46:53]
Brian Krogsgard: Do you think people that come from traditional markets are having a hard time grasping the mix of speculation versus fundamental value in projects? Because I think one of the things I'm seeing is a lot of stuff is way down to where, if this was a traditional market where the market is fairly efficient and understanding what pricing is and what works, they'd look like deals, right?
Clay Collins: Yeah.
Brian Krogsgard: Yet if you look at a lot of coins now, they could be done 80% and still be overvalued because of the significant cooling-off period. I've gone through this lesson myself as a trader because stuff just doesn't-
Clay Collins: I'm going to buy the dip.
Brian Krogsgard: Yeah, well, stuff just doesn't go down 80% quite like that in traditional markets. Do you think it's a learning curve for people trying to learn how to invest in crypto versus investing in the real world, if you will?
Clay Collins: Yeah. That's a good question. I think everyone's focused on the fact that these things are tokens and kind of forgetting about the real world analogy. A lot of these hedge funds really aren't doing forex trades, but in a lot of ways, that's what Bitcoin coin is. It's a forex thing. There's no underlying value. You're placing a bet on the network and the utility value of the coin, so it's really hard to evaluate what it is because it's not like a security where there's this underlying asset, and then you can try and figure out what that underlying asset is worth.
Clay Collins: And then with things like Filecoin and crypto commodities, that just looks a lot like VC. You're buying something based on the future value of that. But the hard thing there with crypto commodities like Filecoin is it doesn't matter how much utility value exists. There's a lot of hard drive space in the world, so just because it's tokenized doesn't mean that all the sudden this thing is worth more.
Clay Collins: I think folks in general need to not focus as much on the fact that it's a token and the whole thing is some new asset class. I don't think of this as a new asset class. I think what's happening is tokenized versions of the analogous thing that exists in the real world, and there's so many different versions of that. There's tokenized securities that represent equity in a company. There's this new financial system. There's true cryptocurrencies like Bitcoin. There's Ethereum, which is this ... who knows what the hell Ethereum is? I couldn't even tell you.
Brian Krogsgard: I was about to ask, how would you give an analogy for a protocol or a network with a value? Because in the web or whatever, open-source software, historically we don't really assign monetary value directly to the platform, a protocol, an API, whatever. But that's what we're doing in crypto.
Clay Collins: Yeah.
Brian Krogsgard: That one, I agree with you completely, even though I've always said this is a whole new asset class. I agree with you that, at the base layer, it's a business represented by a token or whatever else, except for this protocol side of things. It's weird for me, and I guess maybe that's why the market's inefficient and why we're seeing these drastic swings is because we're trying to figure out what is something like the 0x protocol worth?
Clay Collins: Yeah.
Brian Krogsgard: Or what is EOS or Ethereum worth? And we have this ability to put a monetary value on them.
Clay Collins: Yeah, yeah. I mean, I think a lot of times a monetary value is just that the greater fool is going to come on and buy it for more, and that is the [inaudible 00:50:44] of the token.
Brian Krogsgard: Yeah.
Clay Collins: Yeah, I think-
Brian Krogsgard: Musical chairs is not a game I want to play, but I agree, it does seem like we're all playing it. We're just hoping that some other sucker is going to be the one left without a chair.
Clay Collins: Yeah. I go to Vegas every once in a while. Why don't you know what you're doing? I think there's something real about Bitcoin. I think there's something real about Ethereum. I think something that is not discussed enough with regards to Ethereum is the fact that there's these compound or kind of second-order network effects that occur. Everyone talks about the network effects of Bitcoin. It's like Visa: the more people that accept Visa, the more valuable Visa is. Same with phones. Owning a phone makes owning a phone more valuable to everyone, every time one is purchased. Or Facebook. I think people generally get network effects.
Clay Collins: There's another effect at play: the Lindy effect, which is just the value of something that doesn't break increases with every unit of time that it continues to not break. We develop more trust in the system. That's the Lindy effect.
Clay Collins: But I think second order network effects occur with platforms like Ethereum, where Ether itself has network effects, but then built on top of Ethereum are these additional tokens that themselves have network effects. I really think there's something to that. There's just so much developer activity on top of Ethereum. The transaction volume is there. The combined long-tail of the network effects of the tokens built on Ethereum is just truly outstanding, where none of them individually on their own maybe have world-changing network effects just yet. But the cumulative power makes Ethereum extremely defensible.
Clay Collins: I'm not a philosopher or an economist, and I don't spend all my time writing up Medium posts about this, but there's something really, really powerful about what's happening with Ethereum. I don't know if necessarily all that accrues to the token or how this all plays out, but I think there's something special happening.
Brian Krogsgard: So, network effects, to me, make sense. I come from open-source software, so I understand the power of "Hey, other people use this, so I'm going to use this." Someone could say, "Oh, well, this other thing's better, newer, fancier," whatever, and you're like, "I don't care. Other people use this. I'm going to use this. I can find developers who build on this," etc. It's a known thing. I get it, and I understand it, and it makes sense.
Brian Krogsgard: Your point is that Ethereum is benefiting from some of these same things, and just because something else comes along, and they're like, "We scale 20% better" or some other benefit that we have, someone is going to have to truly compete with Ethereum on that front in your opinion.
Brian Krogsgard: Yeah.
Brian Krogsgard: Right.
Brian Krogsgard: The parallel could be let's say 0x. I apologize for shilling. I don't know any ZRX right now. But let's say 0x becomes the way to create a decentralized exchange, just because their protocol's that good. Now all decentralized exchanges are essentially using 0x, which is built on Ethereum. Or CryptoKitties, like gaming becomes very popular through CryptoKitties or some other thing. Because of that, it's reinforcing the underlying network, so they're self-strengthening. The more stuff that gets built on Ethereum, the more likely Ethereum creates that stronghold, even if, like everybody believes, it's garbage. It doesn't necessarily matter, as long as that's what people keep building on, and the developer ecosystem builds around.
Clay Collins: Exactly. Or I hear this all the time, people talk about WordPress. "Have you seen this other super amazing CMS? It's got this markdown. It's so much faster. WordPress is crap." Nobody cares. Nobody cares.
Brian Krogsgard: Nobody cares because you can go to any ... and I come from this space, so Clay's feeding me here. But you can go to any ad agency, any interactive agency in the world pretty much, and you say, "My website's on WordPress," and they'll just say, "Okay, well, we can build on that." Because it's a PHP and MySQL application. It's straightforward, and people have experience building on it, so it doesn't matter how good your fancy content management system is because everyone in the world has a knowledge and an understanding of WordPress, and they can build on WordPress.
Clay Collins: Right.
Brian Krogsgard: We're seeing the same thing happen with some of these protocols. The first mover advantage is fascinating. What I'll be really, truly ... the most fascinating thing will be, to me, not if Ethereum dominates because that should be expected. It will be who can actually challenge them. Can someone else like Netscape Ethereum and become Chrome or whatever else? That would really make this stuff interesting to me.
Clay Collins: Yeah. I think what's difficult about that is the switching costs. There's just such a pain of disconnect. If you're 0x, to switch to another blockchain is just damn near impossible. I don't want to speak for those guys, but switching to a new blockchain once you've done everything on top of Ethereum or a given platform is just quite an undertaking. You have to reissue tokens and get all your users to not succumb to apathy. It is just a big pain in the ass really.
Brian Krogsgard: Yeah. I know a lot of these projects, to try to essentially hedge that risk, are trying to build their own stuff, like a layer above, so a little agnostic of the underlying platform, so that, if someone integrates with their API, they can change their underlying stuff, but whoever's integrating with them can still [crosstalk 00:57:32].
Clay Collins: Like an abstraction layer.
Brian Krogsgard: Yeah, that abstraction layer to try to protect from that because it's still possible that Ethereum just blows up one day. It's totally possible. This is a new ecosystem. You seem excited to track it all. I wanted to have you on just to talk about what you're building with Nomics.
Clay Collins: Yeah, cool.
Brian Krogsgard: I love the fact that it's just centralized, and you're doing data. I think that's really cool. I think the fact that you're offering so much in a free API, my listeners that are interested in building stuff like that, check it out. I've checked it out, plan on using it for some work that I have going on. It's really cool.
Brian Krogsgard: The Flippening Podcast has me hooked, so you all go cross-subscribe. Make sure you subscribe to both, not just Flippening, not just LedgerCast. Subscribe to both. And, Clay, I look forward to just keeping an open channel and learning more about what you're working on and what you're thinking about. I think you bring a lot to the space, and I'm thankful for you coming on and spreading across a lot of topics today. But I enjoyed it. Thanks for doing that.
Clay Collins: Awesome. Me too. Just a shout-out, if you run an exchange or an OTC desk ...
Brian Krogsgard: Yeah, yeah.
Clay Collins: We really want to do a deep integration with you, so that's one topic.
Brian Krogsgard: Yeah, I'll second that. I mean, the way that you've talked to me about how people can do relatively small changes to their own APIs, just providing endpoints for specific types of access for you. One of the things that makes sense for me is that, if an exchange doesn't want to support every little app and everybody that wants to come and ping their systems and deal with them and all that and all the support that can come along with that, you're essentially telling the exchange, "Hey, we'll do that. We'll manage that component for you, if you just help us grab this data a little easier."
Clay Collins: Yeah, so we're actually working with an exchange right now on a white label version of their API that everyone is going to think comes from them, so they're just providing us with three endpoints. On top of that, we're giving all their customers candlestick data and all-time-high data and all kinds of different market feeds and stuff. That's something-
Brian Krogsgard: So, their API is actually going to come directly from you?
Clay Collins: Yeah. Their users won't know it, but yeah, we're powering all of that.
Brian Krogsgard: Yeah.
Clay Collins: They just expose a few simple endpoints, and their customers get multiple dozens of endpoints that they can use to analyze data on their exchange, which is a good marketing channel for them.
Brian Krogsgard: That's really cool. Well, I look forward to seeing what all this looks like when you've got hundreds more exchanges and derivatives, products, and securities and all this stuff on there, and talk to you about what your data management journey is looking like at that time. I'm sure it'll be something.
Brian Krogsgard: Clay, thanks for coming on, and we will catch everybody next time.
The Nomics team is very responsive, the API is well documented. It’s a no-brainer. Nomics is what most people should be leveraging if they're trying to build out an informative front end with price data. I implemented so many features in just a couple of hours. It was a really incredible experience to be able to get so much done so quickly. Right now we're supporting, pounds, euros, yen, won and rubles. It’s amazing to get all that fiat in there.
Our team was searching for a powerful, fast and consistent solution for accessing historical cryptocurrency trade data. After speaking with the team at Nomics, we decided to go with their RESTful API. The solution, built using Golang, fit all the requirements for our product. Since integrating with the Nomics API, we have been up and running and have had no issues with receiving and extracting the data. You can always expect that the fields returned from the API will be in a consistent format. Data consistency has only been one large benefit of the Nomics API. We have also enjoyed blazing fast responses, and top notch customer support. Building out in-house tools to clean and aggregate exchange data is a laboursome and timely task. Using the Nomics API has completely eliminated this overhead!
Tyler van der Hoeven
I've tried many aggregate crypto APIs over the past few years but since working with the Nomics API my search has finally stopped. Nomics has it all. Lightning speed, pinpoint accuracy, a massive library of tokens and exchanges, consistent updates and a solid business model. They leave so very little left to be desired. It's common knowledge in this space that good enough is often all you'll be able to get. Nomics however is daily raising that bar for all crypto projects, that excellent and flawless can and should be a thing. Their deep knowledge and interest into the industry shines through everything they do. They aren't just here for the fad, they're here to change the landscape for the better and make this place their home. It's amazing, and I'm a fan.
After we launched Bletchley Indexes, we used CoinCap, CoinMarketCap, and CryptoCompare. But we noticed erratic pricing, ticker changes without warning, and API downtime that kept us searching for a better solution. In order to meet the needs of our own customers, we needed reliable and high-quality cryptocurrency pricing as well as feed stability. Fortunately, we found Nomics. Getting started with the Nomics API was a breeze and, despite limited coding knowledge, I was able to pull and reshape everything in under an hour. Between the easy to follow documentation, the unique endpoints Nomics provides, and the responsive communication we receive via their Telegram groups, we would absolutely recommend Nomics to anyone looking for a hassle-free and reliable cryptocurrency API.
Start With Our Free Plan
Nomics.com uses the exact same free API that our customers use. We don't use special/hidden endpoints or have backdoor access to additional functionality. Also, you're not competing with us if you're building an alternative to our pricing website or CoinMarketCap etc.
In fact, we want you to build everything we've created (& much more) with our free API.
Note: We do offer paid plans for institutional investors who need access to certain kinds of data, a free plan suits most developers and individual traders. If you have questions, feel free to contact us here.
Frequently Asked Questions
|Exchange||First Trade||First 1D Candle||First Orderbook Snapshot|
When we say that our API provides gapless raw trade market data, it means that we have all of the trades that occurred on a given currency pair market on a given exchange, going back to the inception of that market … with no gaps in trading data (i.e. no trades are missed or unaccounted).
This is important because when no trades are missing, you have accurate volume information for a given time interval. Having gapless raw trade data also means that quantitative traders and algorithmic investors have higher fidelity data points and can more thoroughly train machine learning models by having every trade available (giving them confidence that they have accurate historical representation). It also means that if you want to look back at a particular time in history and consider what was occurring on a particular cryptocurrency exchange market -- you'll be able to know exactly what was going on on a particular day and that data hasn't been removed, aggregated, or interpolated.
As far as we know, Nomics is the only product that provides gapless (and historical) normalized raw trade/tick data. If you know of others, please let us know.
We are often asked what can be built with the free vs. paid API plans. The paid plan is great for folks who need high-fidelity, normalized, primary-source and gapless raw trade/tick data and order book data. The paid plan is also great for folks who want low-latency real-time information for live trading environments.
The paid version of our (crypto market data) API is for you if . . .
- If you're doing deep analysis that requires as many data points as possible (i.e. tick data vs. candlestick/OHLC data
- You want to create your own new aggregate pricing methodology (i.e. if you don’t like our pricing methodology)
- You want to create/calculate your own OHLC candles (one of our paid customers, for example, creates their own volume candles and prefers them over time bars)
- You need low-granularity data for training your machine learning models
- You need to backtest your trading algorithms
- You don’t trust interpolated data and require 100% primary source data from exchanges
- You need SLAs, uptime guarantees, contracts in place, etc.
The free version is for you if . . .
Simply put, the free version is for you if you don’t need the paid version. If you're building a cryptocurrency dashboard, are OK with summary-level and aggregated data points, and high-granularity historical data, then the free version is for you. Additionally, the free version is great for folks building CoinMarketCap (or Nomics.com) competitors, pricing websites and apps, and high-latency tooling for portfolio or price management.
Nomics.com is actually built 100% with the free version of our API. So if you see us doing something on our front page (or on a page for individual currencies), then you can do it with the free product. We have no issue with your creating a website that’s competitive to us (especially if you’re using our API).
Note: One of our favorite things about Nomics.com is that it runs entirely on the same documented API endpoints our customers use. We don't use backdoors or "off the record" calls to access data. Again, if you see us doing something, you can do it also.
The basic skill set needed to interact with our API is essentially the same skill set needed to interact with any RESTful API. That is, you need familiarity with making HTTP requests, working with JSON and CSV data, etc. For example, if you’re building a simple site that reports the price of BTC/Bitcoin (or a simple script that prints the Ethereum price on your terminal), then you’ll need to make an HTTP GET request, parse the JSON, and you’re done.
The skillset beyond these basic requirements really depends entirely on what you're building. In fact, it’s likely that the bar for whatever you're building is higher than the bar for interacting with our API.
Perhaps the most important skill needed to use our API is understanding of financial data, how markets work, the difference between tick data and OHLC data, how to think about order books and bid/ask spreads, what a base and quote currency is, etc. Indeed, getting the data is easy but understanding how to apply and use the data is much more likely to be the limiting factor.
When we say that we offer normalized data, it means that we’ve created one consistent format for accessing market data across multiple exchanges (and data sources), even though almost every single crypto exchange has different API response formats. Almost every single exchange, cryptocurrency index, bot platform, security token issuance platform, etc. structures and represents data differently; this creates a lot of a lot of unnecessary engineering and data cleanup/sanitization work.
For example, the following may change drastically from exchange to exchange:
- The ticker symbols used to represent cryptoassets (i.e. BAT represent “Basic Attention Token” on one exchange and “BATCoin” on another)
- How dates and time zones are represented (some exchanges report times in UTC, while others report in the local time zone)
- The precision of numbers and dates (numbers may be stored as strings, floating point values, etc. and timestamps might have between millisecond and minute-level granularity)
- Methods for paging through historical data
- Rate limits
- How closed markets are handled
The Nomics API not only aggregates data from several sources, but it also ensures that API response formats and data schemas are consistent across the board. Using a universal common format means that developers and financial analysts only have to code against a dataset once.
Here’s what one of our customers said about how our normalized database has benefited them:
“There’s lots of inconsistency across these APIs. A lot of exchange candles come in at zero value if there's no trading activity. Other exchanges just won't include candles. Others will repeat the last candle if their API is down or there’s no trading activity on that market. That’s why we love that that Nomics API is normalized. It’s good to know that there's a consistent way to expect the data. Being able to go through kind of a single provider that normalizes these and then sends out an expected response is great.
Also, there’s a lot of intersection between market symbols. BAT is Basic Attention Token on some exchanges, but BAT is also BATCoin on others. We are looking at arbitrage spreads and it didn’t make sense. Turns out it was an entirely different token. Consistent symbol lookup across every endpoint is very important to us in a real-time trading environment.”
--Daniel from Travas Research
- Trades are updated as quickly as an exchange will allow. This can vary between a few seconds and a few minutes per exchange market.
- The refresh rate of exchange candles is down to one minute for all candle sizes (except 1m candles which refresh every 10 seconds).
- Aggregated candles are updated 6 times per candle duration
- 1-day candles are updated every 4 hours
- 4-hour candles are updated every 40 seconds
- 1-hour candles are updated every 10 minutes (60min/6 = 10min)
- 30, 5, and 1-minute candles are similarly calculated
- Historical order-book snapshots are captured every 5 minutes (however, for enterprise customers, we can provide snapshots at 100-millisecond intervals).
Trade/Tick Ingestion Latency
We ingest trades as continuously and as quickly as we can making the maximum data requests possible. The latency of our data depends on the rate limits of the exchange APIs that we're working with and the number of markets on their exchange. In the best case, you’ll be able to fetch your data immediately with less than a second of latency.
However, if an exchange we’re ingesting data from has lots of markets and a low rate limit, there may be a small delay around ingesting the data. For example, if an exchange with 100 markets has a rate limit of 100 requests every minute, we can only make a market request every 0.6 seconds and check each market once per minute.
Exchange Candle Computation Latency
Exchange candle computation latency is dependent on the exchange, market and candle size. In candle computation, markets are constantly scanned and candles updated as soon as new trades execute. Our exchange candles are usually extremely fresh, or at least as fresh as the trades, factoring in a little latency for our computation.
Aggregated candles provide volume-weighted summary pricing info for a given cryptoasset (e.g. ETH).
If you need very fresh up-to-the-minute data, we recommend using smaller candle sizes.
If the API endpoint only returns current values, then it's either using trades or one-minute candles to get you a current price. Examples of that include market prices, exchange market prices, and prices. If you set the interval type to one minute, then the candle endpoints will also be one minute meaning the data is updated every 10 seconds.
Interval and History Endpoints
Interval and history endpoints change the candle size used based on the requested time span. For example, if you ask for market cap history for the last six hours, one-hour candles (which update every 10 minutes) are used. If you ask for the past month’s market cap history, one-day candles (updated every four hours) are used.
A technique used by Nomics is the layering of endpoints. For example, we fetch a currency interval to check the previous 24 hours, giving us opening and closing prices, and a volume for that period. Then we fetch the current prices, which are updated more frequently, the currency interval response, and all the close prices and replace them with the data from the prices interval.
That means we take the currency interval for the past 24 hours, using one-hour candles, that are updated every 10 minutes but enhance the close price using the current prices, which are updated every 10 seconds. So every 10 minutes we re-fetch the currency interval, and every ten seconds update the prices. The same logic applies to exchange market interval and exchange market prices.