Optiver-Ready-Trader-Go
Unverified Market-making strategy on Multi by keanekwa. BotFinder score 18 out of 100.
Implemented the Avellaneda-Stoikov market-making strategy in an automated trading algorithm. Completed as part of the Optiver Ready Trader Go competition.
Source: github
BotFinder analysis pending.
Optiver-Ready-Trader-Go
Optiver-Ready-Trader-Go How the Competition Works This repository documents our submission for the Optiver Ready Trader Go competition. This competition involves creating a algorithmic trading strategy to trade a Future and ETF, both of which are highly correlated. The Future was highly liquid, while the ETF was highly illiquid. We were also provided with some basic template files (refer to the /readytradergo folder) and some market data for backtesting (refer to the /data folder) to interface with the trading system, and we had to follow these competition rules. Models We Tried We tried out a variety of different strategies, which can be split into 2 categories: arbitrage through pairs trading, and market making around the midprice. We first started by experimenting with the arbitrage strategies, where we performed pairs trading on the ETF and Future by buying the underpriced instrument and selling the overpriced instrument. This was implemented in the following strategies: - Arbitrage strategy between the ETF and Future. Refer to arbitrage.py - Arbitrage strategy that took into acc
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