When to go Long on Bitcoin | Algo Trading and Signals — Part 9

Photo by Haneen Krimly on Unsplash

This time, this trading-signal combination shows a high winning rate and consistently makes a profit in the backtesting phase regardless of initial portfolio cash value and size. There is no obvious weakness of this trading-signal combination so far at this point.

The key point in its entry conditions is that it looks into the inconsistent in the price fluctuation. In contrast, the exit conditions are full of simple rules pertaining to all sorts of price information.

I particularly like this trading-signal combination since I created it in the first place and the notion of this trading signal can also be applied to other things with similar traits. Let’s take a look!!!

Assumptions:

  1. Timeframe: January 1st, 2017 to November 15th, 2020
  2. Trade Frequency: Daily
  3. Executed Price: Close Price
  4. Position: Long
  5. Initial Portfolio Cash Value: $100,000
  6. Size: 1 unit of Bitcoin per trade
  7. Commission: 0.1 %
  8. Limitation on Exposure: None
  9. Leverage: None
  10. Close all holdings when exiting conditions triggered

Results:

- Original Combination

2017–2020

Final Portfolio Value: 110937.13
Sharpe Ratio: 0.9032126699725065
Total Compound Return: 0.10379343472133654
Average Return: 7.445727024486122e-05
Annualized Return: 0.018940367685400812
Max Drawdown: 1.2323244265070228
SQN score: 3.0682769583669036
Trades: 21

2018–2020

Final Portfolio Value: 105986.36
Sharpe Ratio: 0.6428094188041596
Total Compound Return: 0.05814020194959217
Average Return: 5.5424406052995396e-05
Annualized Return: 0.014064943868200404
Max Drawdown: 1.2924581644693076
SQN score: 2.6988849447660974
Trades: 14

- Optimized Combination

2017–2020

Final Portfolio Value: 118099.42
Sharpe Ratio: 1.726168263196913
Total Compound Return: 0.16635661813233288
Average Return: 0.00011933760267742675
Annualized Return: 0.030529838071359613
Max Drawdown: 2.4532059565346884
SQN score: 2.8783523054221223
Trades: 30

2018–2020

Final Portfolio Value: 110467.67
Sharpe Ratio: 2.341890027563965
Total Compound Return: 0.09955266906942231
Average Return: 9.490244906522623e-05
Annualized Return: 0.02420368417500894
Max Drawdown: 2.6394618483226218
SQN score: 1.988596884644627
Trades: 20

Scenario II:

  1. Initial Portfolio Cash Value: $1,000,000
  2. Size: 80 units of Bitcoin per trade
  3. ceteris paribus

- Original Combination

2017–2020

Final Portfolio Value: 1876139.43
Sharpe Ratio: 1.1644071293645764
Total Compound Return: 0.6292161707562391
Average Return: 0.0004513745844736292
Annualized Return: 0.12046793290131125
Max Drawdown: 6.9300026697937875
SQN score: 3.0730617470090142
Trades: 21

2018–2020

Final Portfolio Value: 1374967.21
Sharpe Ratio: 1.2729205773076295
Total Compound Return: 0.3184298818852803
Average Return: 0.0003035556548000766
Annualized Return: 0.07949789933487132
Max Drawdown: 9.38571441188009
SQN score: 2.86251848192939
Trades: 14

- Optimized Combination

2017–2020

Final Portfolio Value: 2447953.52
Sharpe Ratio: 1.6425548113990802
Total Compound Return: 0.8952523794286605
Average Return: 0.0006422183496618799
Annualized Return: 0.17567097141212842
Max Drawdown: 12.847744907763692
SQN score: 2.878352305422123
Trades: 30

2018–2020

Final Portfolio Value: 1829645.36
Sharpe Ratio: 1.9374529875342008
Total Compound Return: 0.6041221557874884
Average Return: 0.00057590291304813
Annualized Return: 0.15618701412231542
Max Drawdown: 20.379083528147962
SQN score: 1.9689608039586244
Trades: 20

Never Stop Learning!

Graduate Student | CFRM program-UW | Writer on Quantitative Investing, Coinmonks || contact me:https://www.linkedin.com/in/jui-lin-jamie-keng-3883b6131/