Crypto-ML uses advanced machine learning to deliver swing trading signals for cryptocurrency. Thanks to the volatility of crypto, this approach has proven exceptionally profitable, as you can see on the trade history page.
The swing trading approach was developed for two reasons:
- The machine-learning models identified it as the most profitable approach
- Trading no more than once per day (and generally just once or twice per month) reduces the burden and stress on users
But what do you between trades? Or what if you just want to make some quick cash?
As we announced recently, the Crypto-ML team is currently testing a “day trading” platform that will allow users to make intraday trades.
Machine-Learning Based Day Trading for Cryptocurrency
Here’s some actual testing in progress on the Crypto-ML Day Trading platform.
And yes, if you don’t have an ultrawide monitor yet, you owe it to yourself to order right now–hopefully funded by your profits from Crypto-ML.
There are two primary ways in which day trading will differ from the primary swing trading platform:
The frequency of trades will be as high as possible, ideally opening and closing several trades per day. The primary Crypto-ML algorithms, on the other hand, do not have consideration for frequency.
The algorithms and models will seek to maximize the average return of trades. The primary Crypto-ML algorithms instead seek to maximize the long-term profit.
What are the benefits of Crypto-ML day trading?
While the existing Crypto-ML platform is effective at maximizing your profits from Crypto trading, we can look at a couple of scenarios for day trading.
The algorithms are currently delivering an average return of 4% per trade.
- If you were to use $1,000 as your trade amount, and you are ideally able to capture two trades, your would average approximately $80 in profit per day. That is $2,480 per month.
- What if you instead day traded with a $10,000 account? That would deliver you $24,800 per month.
This opens very exciting possibilities.
Of course, traders need to consider fees (0.3% currently on GDAX/Coinbase Pro) and taxes.
What are the challenges of machine-learning based day trading?
The biggest challenge our team has faced is in finding the right balance between frequency and profit.
High frequency is ideal from an activity perspective, but not necessarily form a profit perspective. In fact, in the day-trading timeframes, trade frequency is inversely related to profit.
Additionally, we need to ensure users of the platform can open and close trades with minimal slippage on price. While trading bots and APIs are available, it’s important for us to have a solution that humans can use and control.
When will Crypto-ML day trading be available for members?
The team is targeting to deliver day trading to its members as part of their existing membership by the end of June. However, governance and quality assurance are of the utmost importance. Please expect to see continued updates as we progress.
Do you have questions or comments? Please let us know below.
Are you interested in signing up for Crypto-ML? Please see more info and sign up on the homepage: Crypto-ML.com