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
Cloud
The cloud or cloud computing helps provides data and applications that can be accessed from nearly any location in the world so long as a stable Internet connection exists. Categorized into three cloud services, cloud computing is segmented into Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). In terms of trading, the versatility of the cloud service allows retail traders the ability to test out new trading strategies, backtest pre-existing conc
The cloud or cloud computing helps provides data and applications that can be accessed from nearly any location in the world so long as a stable Internet connection exists. Categorized into three cloud services, cloud computing is segmented into Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). In terms of trading, the versatility of the cloud service allows retail traders the ability to test out new trading strategies, backtest pre-existing conc
Read this Term-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
Cloud
The cloud or cloud computing helps provides data and applications that can be accessed from nearly any location in the world so long as a stable Internet connection exists. Categorized into three cloud services, cloud computing is segmented into Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). In terms of trading, the versatility of the cloud service allows retail traders the ability to test out new trading strategies, backtest pre-existing conc
The cloud or cloud computing helps provides data and applications that can be accessed from nearly any location in the world so long as a stable Internet connection exists. Categorized into three cloud services, cloud computing is segmented into Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). In terms of trading, the versatility of the cloud service allows retail traders the ability to test out new trading strategies, backtest pre-existing conc
Read this Term-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.
