Crypto machine learning model
A. Christian Silva
3/1/2024
Machine learning model (MLMS)
Strategy
Strategy uses pattern recognition and machine learning to identify trend and mean-reversion periods.
Strategy is long/short and it can have holding period of few hours. It can trade perpetuals or spot.
Capacity depends on implantation (DEX or CEX) but less than $10M per token.
IMPORTANT! Strategy is under active development: performance as well as other stats will change.
Performance (simulation)
- Trading Ethereum (ETH).
- Long/Short.
- TC = 5 bps per trade.
- Interest rates are taken to be zero: cash positions do not accrue interest.
- Volatility level comparable to spot ETH by design.
- Performance of a long buy-and-hold Bitcoin (BTC) position is also shown for comparison.
| Statistics (2016-2024) | ||
| MLMS | BTC | |
|---|---|---|
| Annualized return(%) | 163.90 | 77.5 |
| Annualized volatility(%) | 68.10 | 70.4 |
| Annual Sharpe (Rf=0) | 2.41 | 1.1 |
| Max drawdown(%) | 52.00 | 83.0 |
| Day VaR 99% (%) | -10.00 | -15.2 |
| Day corr w/BTC(%) | 6.00 | NA |
| MLMS | |||||||||||||
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Year | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020 | 26.9% | 31.5% | 26.6% | 0.9% | 1.1% | 0.0% | 32.2% | 47.1% | 30.6% | −10.6% | 34.8% | 9.6% | 632.7% |
| 2021 | 22.5% | 36.0% | 6.0% | 2.7% | 14.6% | 30.8% | −1.4% | −2.9% | 1.1% | −2.1% | 30.7% | −12.6% | 194.5% |
| 2022 | −19.1% | −21.8% | 1.6% | 19.2% | 10.8% | 30.6% | 23.7% | 26.6% | 3.1% | −0.1% | 26.0% | −6.2% | 111.0% |
| 2023 | 10.5% | 16.9% | −12.5% | 4.7% | 3.3% | 15.1% | 2.9% | −6.2% | −6.7% | −0.7% | 7.3% | 2.0% | 37.8% |
| Simulated returns that include transaction costs but do not include management fees and/or performance fees. The simulation also does not include interast rate on cash reserves. | |||||||||||||
Disclaimers
It is important to note that simulations are not real returns and therefore can only serve as an approximate view of the risk/return profile of a given strategy. Finally, it is fundamental to stress that past performance is not indicative of future results, and any historical returns presented should not be taken as a guarantee of future performance. Investors should carefully consider their financial objectives, risk tolerance, and investment horizon before investing.