Published on Feb 21, 2020
Enigma is a privacy protocol that enables truly decentralized applications and unlocks the value of blockchains.
Using secure multi-party computation (sMPC or MPC), data queries are computed in a distributed way, without a trusted third party. Data is split between different nodes, and they compute functions together without leaking information to other nodes. Specifically, no single party ever has access to data in its entirety; instead, every party has a meaningless (i.e., seemingly random) piece of it.
Unlike blockchains, computations and data storage are not replicated by every node in the network. Only a small subset perform each computation over different parts of the data. The decreased redundancy in storage and computations enables more demanding computations.
Catalyst is the first application to be built on the Enigma protocol, already active with tens of thousands of users. Catalyst is a revolutionary platform for data-driven cryptoasset investing and research, built for professional crypto traders.
Catalyst is an algorithmic trading library for crypto-assets written in Python. It allows trading strategies to be easily expressed and backtested against historical data (with daily and minute resolution), providing analytics and insights regarding a particular strategy’s performance. Catalyst also supports live-trading of crypto-assets starting with three exchanges (Bitfinex, Bittrex, and Poloniex) with more being added over time. Catalyst empowers users to share and curate data and build profitable, data-driven investment strategies. Please visit enigma.co to learn more about Catalyst.
Catalyst builds on top of the well-established Zipline project. We did our best to minimize structural changes to the general API to maximize compatibility with existing trading algorithms, developer knowledge, and tutorials. Join us on Discord where we have a #catalyst_dev channel for questions around Catalyst, algorithmic trading and technical support.
Ease of use: Catalyst tries to get out of your way so that you can focus on algorithm development. See examples of trading strategies provided.
Support for several of the top crypto-exchanges by trading volume: Bitfinex, Bittrex, and Poloniex.
Secure: You and only you have access to each exchange API keys for your accounts.
Input of historical pricing data of all crypto-assets by exchange, with daily and minute resolution. See Catalyst Market Coverage Overview.
Backtesting and live-trading functionality, with a seamless transition between the two modes.
Output of performance statistics are based on Pandas DataFrames to integrate nicely into the existing PyData eco-system.
Statistic and machine learning libraries like matplotlib, scipy, statsmodels, and sklearn support development, analysis, and visualization of state-of-the-art trading systems.
Addition of Bitcoin price (btc_usdt) as a benchmark for comparing performance across trading algorithms.
