quant-reseach

Unverified Other strategy on Crypto by augmento-ai. BotFinder score 18 out of 100.

Augmento sentiment data quickstart and research

Source: github

Explorer/Crypto/quant-reseach
18
Data index
CryptoMedium risk⚠ Unverified

quant-reseach

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Sharpe
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Profit factor
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Track record
7.4y
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About

quant-reseach

Quant Reseach This repo serves as a quickstart guide for using using Augmento sentiment data, as well as a working repo for analysing the data and developing example strategies. Augmento API docs: http://api-dev.augmento.ai/v0.1/documentation Bitmex API docs: https://www.bitmex.com/api/explorer/ Getting started Prerequisites python 2.7 or later Install requirements pip install -r requirements.txt --user zlib (already included with MacOS) Run tests python -m unittest discover -v Examples Quickstart The quickstart examples are the quickest way to download some data, plot the data, and run a simple strategy. Cache two years of Augmento data from the Augmento ReST API to a local folder python examples/0loadaugmentoexampledata.py Cache a list of sources, coins, bin sizes, and topics from the Augmento ReST API to a local folder python examples/1loadaugmentoexampleinfo.py Cache two years of XBt candle data from the Bitmex ReST API to a local folder (this may take a few minutes) python examples/2loadbitmexexampledata.py Plot some of the cached raw Augmento data against the cached Bitmex XBt

Jupyter NotebookMITOpen-sourcecryptocurrenciescryptocurrencyquantitative-financequantitative-tradingsentiment-analysissentiment-classificationtradingtrading-algorithms
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⚠ No verified equity curve — no track-record source connected.

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Source
augmento-ai
Since 2018 · 1 bots

Open-source maintainer on GitHub.

Trust 0Profile
Score & reliability18/100
Perf data0/35
Community0/25
Evidence8/20
Recency10/10
Verification0/10

Data-completeness & trust index (not a profitability rating)

Source facts
Stars73
Forks39
Open issues1
LanguageJupyter Notebook
LicenseMIT
Last update2020-07-12
Created2019-05-16
Website
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