{"repo":"globophobe/django-quant-tick","free":true,"listed":false,"github":"https://github.com/globophobe/django-quant-tick","clone":"git clone https://github.com/globophobe/django-quant-tick.git","description":"📈 Aggregate candlesticks from high frequency tick data from S3 and REST APIs","language":"Python","stars":21,"topics":["bitmex","bybit","coinbase","candlesticks","bitfinex","cryptocurrency","quant","tick-data","financial-data"],"license":"MIT","category":"trading","readme_excerpt":"What? Django Quant Tick aggregates candlesticks from high frequency tick data. Why? Tick data is preferable for analyzing financial markets. Candlesticks aggregated by django-quant-tick are equally informationally dense. Such candles can be useful for analyzing financial markets. As an example, refer to \"Low-Frequency Traders in a High-Frequency World: A Survival Guide\" and \"The Volume Clock: Insights into the High Frequency Paradigm\". Lopez de Prado recommends volume candlesticks, however they are are computationally expensive to generate. Tick data may be downloaded raw, or optionally aggregated. Aggregation can save disk space, and may increase information. There are 2 complementary aggregations. The first is by equal symbol, timestamp, nanoseconds and tick rule. The second is by filtering significant trades, for example at least $1000. By aggregating and filtering raw tick data, volume candlesticks can be computed faster, with little loss in precision. 1. First tick data may be aggregated by equal symbol, timestamp, nanoseconds and tick rule. Aggregating trades in this way can increase information, as they are either orders of size or stop loss cascades. As well, the number of rows can be reduced by 30-50% 2. By filtering aggregated rows, for example only writing a row when an aggregated trade is greater than significant trade filter = 1000 , the number of rows can be reduced more. 3. Clustering trades by trade direction, such that a row is created only if the tick rule c","default_branch":null,"files":null,"tree":[],"storefront":"/r/globophobe","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/globophobe/django-quant-tick/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}