Forex Forest Lowers Cost of Algorithmic Trading by 70% Using AWS

Hong Kong-based Forex Forest specializes in providing education and skills training for automated trading across various markets, including foreign exchange (forex), indices, gold, silver, and cryptocurrency. It also develops software for automated trading on the Mega Trader 4 (MT4) platform, which is used by millions of traders around the world.

Volumes of automated trading, where algorithmic models identify the most profitable trades, are increasing. In 2018, the market for these trades was worth $10.35 billion, increasing to $13.18 billion by 2021. Within the next three years, it’s expected to hit $23.74 billion, growing at a compound annual growth rate of 10.3 percent. With volumes growing, more people want to learn the required skills, presenting Forex Forest with an opportunity to expand. With this in mind, Forex Forest is planning an initial public offering (IPO) in 2025 to raise additional funds to open operations in multiple countries.

To facilitate expansion, Forex Forest sought to replace its on-premises infrastructure, which supports training and trading on the MT4 platform. Jimmy Kwok, chief technology officer at Forex Forest explains, “Scaling our on-premises IT infrastructure became challenging as our data handling and machine learning requirements continued to grow. We wanted to migrate our IT to the cloud, laying the foundation for easier scaling both before and after our IPO.”

Forex Forest chose to migrate its on-premises infrastructure to Amazon Web Services (AWS). Kwok says, “AWS offered services to develop our capabilities, a global infrastructure to drive expansion, and support to ensure we completed migrations and deployments in line with best practices.”

The IT team at Forex Forest engaged with AWS Professional Services (ProServe) to design its AWS Landing Zones to reflect best practices. The ProServe team followed principles in the AWS Well Architected Framework, fulfilling industry and regional security standards. “With the support of AWS ProServe, we gained confidence that our cloud environment adhered to both regional and global standards, empowering us to drive expansion worldwide,” states Kwok.

The ProServe team helped Forex Forest migrate its virtual private servers (VPSs) for automated trading to Amazon Elastic Compute Cloud (Amazon EC2) Auto Scaling instances. In addition, the team also helped the Forex Forest implement Amazon Aurora, a cloud-native service, for database workloads. Forex Forest also deployed AWS Security Hub to automate AWS security checks and centralize security alerts, and AWS WAF to protect Forex Forest applications from common threats.

By migrating to AWS, Forex Forest gained scalability to support its plans. The company also reduced costs for VPSs by 70 percent, freeing up resources to invest in service development. “We can cost-effectively support separate trading environments for tens of thousands of students to learn AI-based trading,” says Kwok.

Forex Forest also made significant infrastructure management savings by moving to AWS. A global on-premises infrastructure would have required local support at multiple data centers around the world. However, with AWS, Forex Forest can manage a global infrastructure from Hong Kong. Wayne Ng, founder of Forex Forest, says, “We need no more than 5–7 engineers in our central location to administer our IT worldwide with AWS.”

With AWS ProServe, the Forex Forest IT team is developing its data analytics and improving the efficiency of its machine learning (ML) modelling. The business is building a data lake, with Amazon Redshift as its data warehouse and Amazon Athena, a serverless service, to query data. In addition, the company has switched to Amazon SageMaker to build, train, and deploy ML models. Through adopting the fully managed Amazon SageMaker service, Forex Forest can now complete ML models in just a couple of days, a significant improvement from the previous timeline of a couple of weeks.