Chapter 1: Understanding Algorithmic Trading

Automated trading algorithms serve as a series of commands that enable computers to execute trades without human intervention. For example, an instruction like “purchase Bitcoin when the MACD indicator exceeds 0” can be programmed as part of a crypto trading algorithm.

I have been creating crypto trading bots for some time; however, I recently ventured into the realm of Crypto Algorithmic Trading Platforms. You might wonder what this entails beyond achieving SEO targets. Here’s the breakdown:

Typically, this refers to a web application that empowers users to customize their trading algorithms using predefined templates or rule sets that accept various parameters. In developer jargon, a parameter is an input necessary for a code block to produce an output based on that input.

In essence, an algorithmic trading platform is a pre-coded set of instructions, designed to allow users to adjust the application’s behavior according to their input.

As an illustration of this, consider our previous example: “buy Bitcoin when MACD indicator is higher than 0.” By substituting the hardcoded values with placeholders, we arrive at a more adaptable trading algorithm:

Buy [COIN] when [INDICATOR] indicator is [EXPRESSION].

Section 1.1: The Binance Volatility Trading Bot

I prefer to Open Source my projects, which is how one of my most recognized bots, the Binance Volatility Trading (BVT) Bot, came into existence. If you’re interested, you can find the source code here.

The BVT bot is an Open Source trading algorithm designed for users to tailor it to their trading preferences. By default, it identifies and purchases volatile coins before they experience price surges. For example, it can be set to buy any coin on Binance that has risen at least 5% in the last three minutes.

The BVT bot quickly gained traction on Reddit, racking up over 2.5k upvotes.

Additionally, it has garnered 3.1k Stars on GitHub.

Reportedly, the bot has yielded returns, contingent on the user’s configuration. However, a notable challenge is that users typically need some coding knowledge, such as familiarity with Git, Python installations, and IDE usage.

The bot quickly cultivated a community, with users contributing to its Open Source codebase. After several months of enhancements, my fellow contributors and I decided to transform this project into a full-fledged SaaS solution.

Chapter 2: Launching AESIR

The name we chose for our new algorithmic cryptocurrency trading platform is AESIR [ey-sir, ey-zir]. This platform is designed to automate most trading strategies and is built on the foundation of the BVT bot, but with significantly more power.

We began developing AESIR over a year ago, and it is now in the final stages of development, soon to enter internal testing.

A common issue with existing algorithmic trading platforms is their complexity and lack of customization options for experienced traders. Our primary goal was to strike a balance by introducing unique trading signals that users can create effortlessly.

AESIR will offer several customizable configurations, including:

• Volatility Trading
• Dollar-Cost Averaging (DCA)
• Technical Analysis Trading
• Social / Copy Trading

Here’s a preview of our current configuration options—subject to change as we progress.

One feature I’m particularly enthusiastic about is the ability to combine signals into complex expressions. For instance, you can set up a DCA configuration that states:

“Buy [Bitcoin] [once a week] if [MACD Indicator] is [>0] and [RSI Indicator is 30] and [Bitcoin has spiked] [at least 3%] in the last [5 minutes].”

Of course, you can adjust the granularity according to your preferences.