[Daily Discussion] - Sunday, April 25, 2021 Bitcoin Markets |
| [Daily Discussion] - Sunday, April 25, 2021 Posted: 24 Apr 2021 09:00 PM PDT Thread topics include, but are not limited to:
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| Streaming Cryptocurrency Orderbooks, Trades and Arbitrage Posted: 25 Apr 2021 06:30 AM PDT Hi I've just released the first draft of a streaming cryptocurrency data website you may be interested in. It collects normalized data from multiple exchanges and produces central, fee-adjusted orderbooks and arbitrage tables for each currency along with analysis (e.g. option pricing, trade size distributions/skews/kurtosis, arbitrage alerts, breakout alerts etc.) You can see the: Home page: https://cryptostats.dev Docs: https://docs.cryptostats.dev Pro Version: https://pro.cryptostats.dev And as an example, you can look at the: BTCUSD perpetual central orderbook: https://www.cryptostats.dev/combined_orderbook/BTCUSD%C2%A0perpetual Huobi BCHUSD asset: http://cryptostats.dev/asset/huobi-dm-swap/BCH-USD BTCUSD spot arbitrage table: https://www.cryptostats.dev/arbitrage The rest are available as links from the home page. The idea is that the web platform will provide all the data and analytics for free in as useful a format as possible, such as combined orderbooks, depth graphs, etc. whilst there will be a subscription-based Pro version which allows WebSocket subscription to subsidize the free version. The web platform uses the entry-tier marginal Taker fees to adjust the central orderbook prices, but the WebSocket version allows for a parameter to be set to adjust the fee level on each exchange - for example, if you have a VIP or market-maker tier fee arrangement. It is a very early draft (as you can tell!) but the goal is to add more of the features that I have been developing, ranging from commodified indicators (SMAs, Vanna Volga Pricing, Heston Pricing etc.) through to potentially new or interesting indicators, like some measures of jump diffusion, breakout detection, order execution / implementation shortfall estimates, and fragmentation measures. Some of these are listed in the documentation along with examples. You can just plug the WebSocket into your existing codebase and then not have to worry about collecting the data or using your compute resource to calculate essential but commodified indicators. There is also always the chance that some of the additional indicators can incrementally improve a strategy or allow an AI model to distinguish slightly better between states. It effectively means you can spend more time on trading strategies and less on monitoring, editing and updating the core data sourcing and analytics. Anyway, I would be very interested in your thoughts, suggestions, and ideas for anything you might find useful, and I will try to accommodate. As I say, it's a very early draft so if you find any bugs – and I am sure there are many – it would be really helpful if you could let me know. Thanks [link] [comments]  |
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