Dollar Cost Averaging (DCA) at Capitalise.ai Starts Now!!!
Capitalise.ai listens to your suggestions and added Dollar Cost Averaging (DCA) strategies to your trading toolbox.
Now you can invest equal amounts at regular intervals automatically. Check out this tutorial and see how easy it is:
What is Dollar Cost Averaging (DCA)?
Traditionally, Dollar Cost Averaging (DCA) allows investors and day traders to increase their trade sizes on scheduled time intervals. An investor might invest in an asset once a month when they get paid their salary. Others might want to enter a DCA after they receive scheduled payments from an investment property. Other traders might want to increase trade sizes or acquisitions on a regular basis around events or at times they expect prices to be advantageous.
While adding to an investment portfolio or trading position with a DCA strategy, the entry price for the total amount of entry price averages out over at various times instead of one moment in the market. Many investors view this as a less risky option than predicting one ideal entry price or time.
What are the Primary Reasons for Using a DCA Strategy?
Although some investors may have their own reasons, typically traders use DCA strategies for two primary reasons:
Limit the exposure to volatility fluctuations
One primary reason for using DCAs clearly derives from what the name Dollar Cost Averaging implies. By spreading out investments over a series of entry points, instead of fewer entries or even one entry, the average price limits exposure to volatility fluctuations in the market.
Spread out one larger investment into smaller investments
Another primary reason for executing Dollar Cost Averaging would be to spread out one larger investment into smaller investments. A large order might not be fully filled at the same price and all at one time. Beyond what initially fills the remaining amount could be driven to a less attractive more expensive price as the market reacts to that large influx of capital.
How to automate a Dollar Cost Averaging trading strategy with Capitalise.ai?
A simple DCA strategy requires to:
- create an entry strategy using everyday English
The strategy should include the asset & amount, as well as the interval schedule. For example:
- skip the exit strategy
as DCA is about accumulating, rather than exiting after each entry
- set the strategy to run in-loop and define the Hits-Limit
You can leave the Hits-Limit empty if you want the strategy to continue endlessly until you stop it.
Automated DCA strategy examples
Simple DCA bot
Let’s consider an investor, as an example, who commits to acquiring an asset but resists committing to a specific price. They may want to have 5 Bitcoin by the end of five weeks. That investor with a DCA strategy could buy 1 bitcoin a week each week for five weeks instead of one purchase of 5 BTC at $41,000 USD. In order to apply this strategy, they will need to create the following strategy and set a limit of 5 hits:
In this example, that investor might have bought the five bitcoin each at $41,000, $43,000, $39,000, $33,000 and $36,000 USD. That trader would have bought at an average price of $38,400 USD per coin. Then using the DCA strategy would have netted an average savings of $1,600 for each coin or $8,000 total in contrast if they had purchased all five coins at $40,000. In theory, DCA purchases will not always be delivering the best price; but, typically, an average price offers stability and predictability over a price determined by one moment in the market.[br]
A DCA Strategy for a Large Market Investment with Lower Exposure to Volatility and Order Filling Issues
So, for example, a trader wanted to buy $1,000,000 of Tesla stock or Bitcoin.
A $1 million dollar trade may not be fillable at any given time at one rate. Just entering one large trade risks alerting other traders, or being impacted by a momentary peak in the asset price.
That trader might want to set up 100 $10,000 trades that execute every ten minutes. For this purpose, the strategy would be written as follows:
Advanced DCA bots, combined with additional conditions
Adding other conditions to a DCA strategy, assists in limiting risk and increasing profit potential. Certain traders for instance might choose to have their DCA intervals coincide with market events or rely on certain criteria. additionally, Capitalise.ai has the advantage of adding conditions based on any TradingView alert.
For example, a trade that requires to buy 5,000 USD worth of ETH/USDT every 30 days (but only) if the 1 day RSI is under 30. The initial trade wouldn’t first open until both conditions fulfill their requirements after 30 days. Future trades wouldn’t execute for at least another 30 days after when the first entry was executed.[br]
More complex DCAs resemble a simple DCA except more than one condition triggers the trade. The first and subsequent trades will not open unless all requirements meet their criteria. It will delay execution for the first and future entries for the time interval entered. So, in this example each entry might take 30 days or more but never before all requirement meet their criteria.[br]
Go ahead and try it!
Don’t hurry up to go live, you should always test your strategy first in Simulation mode to make sure it works as intended.
Stay tuned for further updates for every kind of trader: day trader or swing trader, small or large, DCA techniques now exist to enhance your automated trading executions with Capitalise.ai
Plan Like A Human. Trade Like A Machine_
With Capitalise.ai you can test and automate any trading scenario, using a simple & intuitive interface – no coding or technical knowledge required.
Simply type in your trading strategy in everyday English and Capitalise.ai will monitor the markets 24/7 for you. Once your conditions are met – your trading orders will be sent automatically to yourtrading account.