TreasuryFutureTrading
Unverified Arbitrage strategy on Multi by jerryxyx. BotFinder score 37 out of 100.
A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change
Source: github
BotFinder analysis pending.
TreasuryFutureTrading
Drift Model Model Inventor: Prof. Raphael Douady Strategy Engineer: Yuxuan(Jerry) Xia Date: 2018/06/10 Note: This program is only a small demo about back-testing system (not the whole strategy). Performance: |Metrics|Value| |---|---| |Risk-free Rate | 0.50%| |Initial |$3,000,000 | |Percentage Invested|30%| |Performance |24.09%| |Gross Profit|13.38%| |Max Recovery |48.04166667| |Volatility |11.9%| |Minimum Draw Down |-6.98%| |Sharpe|1.975501601| Input and Output One can view this as a python implementation about the excel program developed by Prof. Douady. But with much better time-efficiency and robustness. This project is made to replace the old excel back-testing system. And all columns can be found in the excel file "TradesResult 2017Driftnew positionwith spot unfrozen durationRaphael2.xlsm" The system input is a data frame like the following, which we can calculate on the original matlab programs easily. Professor, Tony and Yao used to generate this data. | DateTime | PriceTU | PriceFV | PriceTY | PriceUS | PriceUB | DurationTU | DurationFV | DurationTY | DurationUS | DurationUB
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