Bitcoin market api
Bitcoin Charts API: Bitcoin Market Data API - Blockchain Blockchain Charts & Statistics API The Blockchain Charts & Statistics API provides a simple interface to programmatically interact with the charts and statistics displayed on aicrypto4.de aicrypto4.de Exchange APIs Build bitcoin apps on top of aicrypto4.de Exchange API for free. Websockets Leverage the Websocket API to receive market data and to interact with the trading system in real time. Every message comes in JSON format and trading messages use the FIX standard for naming fields, and message types. View Documentation. Some API calls are available with CORS headers if you add a &cors=true paramter to the GET request. URL: aicrypto4.de No Parameters. Returns a JSON object with the currency codes as keys. "15m" is the 15 minutes delayed market price, "last" is the most recent market price, "symbol" is the currency symbol.
Bitcoin market apiFree Cryptocurrency & Market Data API (Historical & Real-Time Price, Exchange & Trade Data)
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.
For more information, please see our docs. Trades and orders on top cryptocurrency exchanges including historical trade data behind one API. Historical aggregate cryptocurrency market cap since January of Price, crypto market cap , supply, and all-time high data.
Uptime and response time guarantees through Service level agreements SLAs. Rapid customer support turnaround times. Brian Krogsgard: Hello and welcome to Ledger Cast. 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. 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. He's the co-founder of Nomics and nomics. 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. 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. 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. We're gonna eventually open source completely the front end as well as iOS and Android apps. 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.
But we have candlestick data for individual markets for example, like the [inaudible ] 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. 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.
So there's no back doors, there's no hidden in points. We're consuming this exactly like a customer is. 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 So that was something else that y'all were looking to add and now people can use this to build something just like nomics.
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. 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.
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. 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 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 Other exchanges do things like We were looking at an exchange the other day that had a market called 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 ] market and one of those was a stable code. You just didn't know which-. Clay Collins: Because 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 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.
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 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.
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 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 From to , we grew that to about 50, 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 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 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. So I started-. Brian Krogsgard: So you're on the board of Leadpages today and Clay Collins: Exactly, yeah. I'm not going into the office and I mean I'm officially chairman of the board, but that's kind of a nice honorary title.
I asked for it. 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 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 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 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 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. Clay Collins: Yeah, yeah. What pages they visited, what emails they've opened, what webinars they've attended, what You know. 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 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. 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. 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 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. 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.
Clay Collins: Yep. 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? 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. 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.
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. Clay Collins 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-.
You're saying you'll be 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. 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. 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?
Sometimes we get a little insight when we do onsite visits and stuff like that. 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? 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.
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. 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.
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. If there are no trades during an interval like no trade within 24 hours no value will be returned. Prepare your code to handle this cases! The returned JSON is dictionary with elements for each currency.
Each currency has up to three key-value pairs: 24h, 7d and 30d. This will return an array with elements for each market. Returned fields per market are:. Trade data is available as CSV, delayed by approx. It will return the most recent trades. Email index coindesk. If you have a press query about the XBP, please see our Press page or contact press coindesk. Currently, these bitcoin exchanges meet the criteria and are therefore included in the US dollar XBP calculation:.
The decision to apply a simple average, as opposed to a volume-weighted average, for the CoinDesk XBP was made because the bitcoin market currently lacks sufficient depth and regional liquidity.
Since trading volume now favors particular regions, a volume-weighted approach would not act as a proper global indicator, because each international bitcoin exchange is not equally available to all national trading participants. A simple average does not favor a regional exchange with high volume and ensures that the XBP is meaningful for the largest number of market participants.
Also, a simple average approach minimizes the impact of volume irregularities and accidentally excluding an exchange. As overall liquidity improves and the number of global exchange choices increases, the impact of regional variances should diminish and a volume-weighted approach may become more appropriate.