Discussing the article: "Forex arbitrage trading: A simple synthetic market maker bot to get started"

 

Check out the new article: Forex arbitrage trading: A simple synthetic market maker bot to get started.

Today we will take a look at my first arbitrage robot — a liquidity provider (if you can call it that) for synthetic assets. Currently, this bot is successfully operating as a module in a large machine learning system, but I pulled up an old Forex arbitrage robot from the cloud, so let's take a look at it and think about what we can do with it today.

The revolution in my thinking happened in 2017, when, after a series of painful losses, I began to study how big players actually trade. I meant not those who talk about their "million-dollar earnings" on YouTube, but real institutions – banks, hedge funds, and proprietary trading firms.

And here's what I found: they do not use fancy indicator strategies. They apply mathematical principles, risk management, arbitrage, market making and other approaches based on a fundamental understanding of market mechanisms. That is when I made my decision: I had to trade like a big player, or not trade at all.

I spent the next three years studying institutional trading methods. I immersed myself in the world of intermarket correlations, statistical arbitrage and algorithmic trading. I experimented with Python and MQL, creating prototype systems that mimicked the approaches of large market participants, but were adapted for retail traders with their capital and technology limitations.

In January 2020, on the eve of one of the most turbulent periods in the history of financial markets, Tris_Optimized was born — my answer to the question: "How can a retail trader apply institutional strategies?"

This EA does not attempt to predict market movements, does not rely on technical analysis indicators, and does not require "intuition". Instead, it mathematically calculates potential imbalances between three related currency pairs and places a grid of orders ready to catch these imbalances when they arise.

Over five years of continuous operation in real market conditions, Tris_Optimized has proven its viability. It has survived the pandemic, inflation spikes, interest rate changes, and geopolitical crises — and continues to generate consistent profits (in those rare times when I actually trade, rather than sitting up all night poring over code ideas and the actual codes). This is not a miracle system promising exorbitant returns, but a reliable working tool based on the fundamental principles of institutional trading.


Author: Yevgeniy Koshtenko

 

Interesting approach. Started as is without optimisation. It keeps the balance, there is an increase in small steps.

If you want, you can move the closing of the grid to the end of the day, before the formation of swap. At present, the grid is closed at the start of trading. Or not to use daily closing at all.

There is definitely room for development and application in complex solutions.

Go on!