Customer Stories / Financial Services / Hong Kong

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

Forex Forest gains significant savings on server costs to power automated trades by adopting Amazon EC2 Auto Scaling, while driving expansion through global compliance.


reduction in server costs


Meets global regulations to drive expansion


engineers to manage global IT infrastructure

Low latency

Ensures fast trading for students


Forex Forest provides training in automated trading and develops software for executing trades through algorithmic models. To drive growth, the company wanted to migrate from its on-premises infrastructure to a scalable cloud platform that could support global expansion.

Forex Forest moved to Amazon Web Services (AWS) with the support of AWS Professional Services, migrating virtual private servers (VPSs) for automated trading to Amazon EC2 Auto Scaling instances. As a result, the business lowered server costs by 70 percent and reduced the time to develop machine-learning models from weeks to days with Amazon SageMaker.

Hand with pen drawing financial chart. trading and investing concept

Opportunity | Meeting the Growing Demand for Automated Trading Skills

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.”


We are training thousands of people in Hong Kong in trading using MT4, but that could be tens of thousands more globally in a few years’ time with AWS.”

Wayne Ng
Founder at Forex Forest

Solution | Scaling Cost Effectively While Accelerating ML Modelling with AWS

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.

Outcome | Achieving Scalability, Global Expansion, and IPO Readiness

By migrating to AWS, the company has overcome the challenges of cost-effectively scaling its legacy on-premises infrastructure, empowering the business to meet the growing market for its services.

Moving forward, Forex Forest aims to offer automated trading education globally, leveraging its AWS Global Infrastructure to meet compliance regulations in various regions. “We are currently training thousands of individuals in Hong Kong in trading using MT4, but we anticipate expanding that number to tens of thousands globally in the coming years with AWS,” says Ng.

In addition, students are gaining a greater user experience, completing trades 24/7 with low latency using their VPSs running on AWS. In the past, performance with the on-premises servers could vary during periods of volatile trading. “Our AWS environments scale automatically as trading volumes change, giving users a consistently high quality of service,” says Kwok.

By migrating its systems to AWS, Forex Forest is now better prepared for its upcoming IPO. Kwok, with his experience in IPOs, recognizes the significance of corporate governance and regulatory compliance to instill confidence in investors. “We can move towards a more successful IPO using the business agility, control, and security we gain from using AWS,” states Kwok.

About Forex Forest

Forex Forest teaches mass market trading across a range of markets using automated trading programs. The company also develops enterprise-level artificial intelligence software that people interested in automated trading can use. Founded in 2017, the company has taught more than 15,000 students.

AWS Services Used

AWS Professional Services

The AWS Professional Services organization is a global team of experts that can help you realize your desired business outcomes when using the AWS Cloud.

Amazon Elastic Compute Cloud (Amazon EC2) Auto Scaling

Amazon EC2 Auto Scaling helps you maintain application availability and lets you automatically add or remove EC2 instances using scaling policies that you define.

AWS Security Hub

Use AWS Security Hub to automate security best practice checks, aggregate security alerts into a single place and format, and understand your overall security posture across all of your AWS accounts.

Amazon SageMaker

Amazon SageMaker helps you prepare, build, train, and deploy high-quality machine learning models quickly by bringing together a broad set of capabilities purpose-built
for machine learning.

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