One connected stack for
systematic investment workflows.
MethodTech connects risk modelling, alpha creation, portfolio construction, strategy testing, analytics, and wealth portfolio intelligence into one workflow for modern investment teams.
Scroll to explore
Risk Model
Understand Risk
Alpha Machine
Build Signals
Portfolio Construction
Optimise Portfolios
Strategy Builder
Test Strategies
Wealth Management
Serve Clients
Analytics
Explain Outcomes
Products
How MethodTech Fits Into the Investment Process
Risk Model
Alpha Machine
Portfolio Construction
Strategy Builder
Analytics
Wealth Management
Design, constrain, and test repeatable investment strategies.
Strategy Builder helps teams turn investment rules into systematic strategies. Define a universe, choose signals, set objectives, apply constraints, test one-day outputs, run backtests, and validate whether the strategy behaves as intended across time.
Strategy Builder is where investment logic becomes a repeatable portfolio process.
Teams can build strategies from scratch using MethodTech signals, risk model factors, or user-created alphas. They can also refine fundamental ideas with systematic overlays, using constraints to control unintended exposure and objectives to align the portfolio with the desired outcome.
The workflow supports both quick inspection and deeper validation. One-day results allow teams to check whether the portfolio generated by the rules looks sensible on a specific date. Full backtests then show how those same rules would have behaved across different periods, rebalance cycles, and market environments.
Portfolio Construction is for optimising an existing portfolio or selected list of stocks.
Strategy Builder is for creating a rules-based strategy that can be repeatedly run, tested, and monitored over time.
Portfolio Construction vs Strategy Builder
What It Helps You Do
Define strategy universes, benchmarks, and iterations
Combine signals, factors, constraints, and objectives
Control beta, tracking error, turnover, liquidity, factor exposure, and position size
Run one-day results to inspect whether the output matches the investment intent
Backtest strategy behaviour across historical periods and rebalance frequencies
Validate out-of-sample before moving toward deployment