TechDev Newsletter - ETH Backtest - 13235x Last 6 Years
TechDev Newsletter - ETH Backtest - 13235x Last 6 Years
I received several questions as to the applicability of the BTC strategy on other assets. Especially, can the same or similar set of rules work on more volatile assets, and if so, what is the outperformance?
I've carefully inspected the system on the ETH chart for the last 6 years (BTC was also backtested over 6 years, not 5, apparently I can't do simple math.)
These results were significant enough that I wanted to share will all subscribers.
This will be the last general announcement all subs will receive for a few weeks.
Members will of course receive the weekly newsletter issues with market updates and swing trading setups.
Reminder: Today is the last day of TradingAlpha's 25% discount on their yearly Alpha Bundle, which offers the Dots and Trackline tools used in this backtest and most setups I will provide.
If interested, visit the TradingAlpha website to sign up and email manage@tradingalpha.io for the steps to receive the discount.
ETH Strategy Rules
The rules for an asset with more volatility turn out to be nearly identical to BTC's, with some small adjustments on entry criteria to accommodate the volatility.
The rules are...
Backtest Results
Asset: ETH
Duration: Last 6 years
Compounded Gains: 13235x
Market During Same Time: 91x
Win Rate: 61%
28 wins, 17 losses, 1 break-even
Avg Win PNL: 131%
Avg Loss PNL: -8%
On 3D charts, these are the rules I will apply to all assets other than BTC.
The dots and trackline are available only in TradingAlpha's yearly Alpha Bundle if you wish to apply this strategy yourself.
Yes, with a 13235x vs 91x market outperformance, I find these tools are more than worth the investment.
I hope you all have a great week ahead.
Hi TechDev - I just signed up and also have the Alpha Bundle. Are you still using this 3D chart in combo with TradingAlpha dots and which coins are you finding have worked the best with this method YTD? Also - what sensitivity are you using for the trackline? Thank you!
This seems like a bit of overfitting...You tested all you could to get the best results, which is a natural reflex, for sure.
But I am suspicious of the predicting power of that model, especially when looking at all the tweaking going into the short portion. What do you think about it ?
Very interesting btw, thank you.