TakeProfit Debuts Web-Based Algo Testing Platform as Market Set to Double by 2030

Tuesday, 10/03/2026 | 14:22 GMT by Jared Kirui
  • The growth projection are based on forecasts from Fortune Business Insights, Grand View Research, Mordor Intelligence, and IMARC Group
  • It comes amid a strong demand for automated trading technologies.
Source: Shutterstock
Source: Shutterstock

Global algorithmic trading is projected to grow from about $21 billion in 2024 to nearly $43 billion by 2030, according to estimates from Fortune Business Insights, Grand View Research, Mordor Intelligence, and IMARC Group.

Amid this projections, cloud-based trading and research platform TakeProfit is eying this expanding market with the launch of a cloud-based strategy backtesting module available to all users.

Algorithmic trading is when a computer follows a set of predefined rules to place trades automatically in the market. It uses code to decide when to buy or sell based on factors like price, time, or volume, instead of a human clicking manually.

New Cloud-Based Tool

The space has been scaling beyond institutions into a fast‑growing, multi‑billion‑dollar market. Retail traders now expect browser‑based backtesting, scripting, and marketplace tools that once sat only inside banks and quant funds. This shift forces brokers, platforms, and vendors to rethink their infrastructure, product design, and how they deliver so‑called institutional‑grade workflows over the cloud.

TakeProfit said the new module allows traders to design, test, and evaluate algorithmic strategies directly from a web browser.

Market data shows retail investors are becoming one of the fastest-growing segments in algorithmic trading. TakeProfit’s Digital Growth Strategist, Pavel Medvedev, said the trend reflects traders seeking systematic tools built for more accessible, web-based workflows.

"The growth in the retail segment points to traders who want systematic approaches but are working with platforms designed for institutional workflows or built around proprietary scripting environments," said Medvedev. "This gap is where cloud -native infrastructure and modular trading environments are finding traction."

Read more: cTrader Brings Cloud Based Algo Trading and Risk Controls to Swiss CFD Traders

TakeProfit's latest feature is integrated into the platform’s Workspaces and supports Indie, TakeProfit’s Python-based scripting language for custom indicators. The update extends access to systematic testing tools without requiring any local installation.

Retail Adoption Rising

Besides TakeProfit, several other firms are active in browser‑ or cloud‑based algo tooling for retail and quant users. They include QuantConnect/LEAN, AlgoBulls, Algogene, and NautilusTrader, all of which offer strategy development and backtesting environments that push institutional‑style workflows into more accessible, often web‑delivered stacks.

On the institutional side, quant firms report that legacy market data and front‑office stacks already struggle with higher volumes, longer trading hours and more venues, leaving many without robust backup data or capacity for 2030‑level loads.

On the retail side, platforms such as TakeProfit are pushing cloud‑native backtesting and scripting into the browser, giving self‑directed traders easier access to systematic tools that once sat only inside banks and large quant shops.

Amid last year’s push to upgrade trading platforms, CFD Swiss for instance added cTrader on desktop, web, and mobile. The broker linked the move to improving user experience while meeting FSRA and global AML/CFT rules.

Global algorithmic trading is projected to grow from about $21 billion in 2024 to nearly $43 billion by 2030, according to estimates from Fortune Business Insights, Grand View Research, Mordor Intelligence, and IMARC Group.

Amid this projections, cloud-based trading and research platform TakeProfit is eying this expanding market with the launch of a cloud-based strategy backtesting module available to all users.

Algorithmic trading is when a computer follows a set of predefined rules to place trades automatically in the market. It uses code to decide when to buy or sell based on factors like price, time, or volume, instead of a human clicking manually.

New Cloud-Based Tool

The space has been scaling beyond institutions into a fast‑growing, multi‑billion‑dollar market. Retail traders now expect browser‑based backtesting, scripting, and marketplace tools that once sat only inside banks and quant funds. This shift forces brokers, platforms, and vendors to rethink their infrastructure, product design, and how they deliver so‑called institutional‑grade workflows over the cloud.

TakeProfit said the new module allows traders to design, test, and evaluate algorithmic strategies directly from a web browser.

Market data shows retail investors are becoming one of the fastest-growing segments in algorithmic trading. TakeProfit’s Digital Growth Strategist, Pavel Medvedev, said the trend reflects traders seeking systematic tools built for more accessible, web-based workflows.

"The growth in the retail segment points to traders who want systematic approaches but are working with platforms designed for institutional workflows or built around proprietary scripting environments," said Medvedev. "This gap is where cloud -native infrastructure and modular trading environments are finding traction."

Read more: cTrader Brings Cloud Based Algo Trading and Risk Controls to Swiss CFD Traders

TakeProfit's latest feature is integrated into the platform’s Workspaces and supports Indie, TakeProfit’s Python-based scripting language for custom indicators. The update extends access to systematic testing tools without requiring any local installation.

Retail Adoption Rising

Besides TakeProfit, several other firms are active in browser‑ or cloud‑based algo tooling for retail and quant users. They include QuantConnect/LEAN, AlgoBulls, Algogene, and NautilusTrader, all of which offer strategy development and backtesting environments that push institutional‑style workflows into more accessible, often web‑delivered stacks.

On the institutional side, quant firms report that legacy market data and front‑office stacks already struggle with higher volumes, longer trading hours and more venues, leaving many without robust backup data or capacity for 2030‑level loads.

On the retail side, platforms such as TakeProfit are pushing cloud‑native backtesting and scripting into the browser, giving self‑directed traders easier access to systematic tools that once sat only inside banks and large quant shops.

Amid last year’s push to upgrade trading platforms, CFD Swiss for instance added cTrader on desktop, web, and mobile. The broker linked the move to improving user experience while meeting FSRA and global AML/CFT rules.

About the Author: Jared Kirui
Jared Kirui
  • 2668 Articles
  • 53 Followers
About the Author: Jared Kirui
Jared is an experienced financial journalist passionate about all things forex and CFDs.
  • 2668 Articles
  • 53 Followers

More from the Author

Retail FX

!"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|} !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}