Transition from intuition to data-driven investing. SQ Capital uses backtested AI models to identify market patterns, helping you manage risk without needing a finance degree.
Most first-time investors are not short on interest — they are short on time and reliable filters. Here is where the gap usually shows up, and how the analysis is built to close it.
Markets generate more data daily than a person can review manually. SQ Capital's models process global signals continuously, surfacing only the patterns that historically correlated with price movement.
Price swings tend to trigger decisions faster than analysis can support. The system applies the same criteria in calm and volatile conditions, removing same-day sentiment from the calculation.
Without prior market cycles to compare against, new investors often can't tell a normal correction from a structural shift. Every recommendation is anchored to comparable historical periods.
Every recommendation passes through the same four-stage process. No step is skipped, and each stage is designed to be explainable rather than a black box.
Millions of global signals are processed daily, spanning price history, volatility metrics, and macroeconomic indicators.
Models identify historical correlations between current conditions and past market behavior, filtered for statistical relevance.
Outputs are adjusted for present-day volatility, so a pattern from a calmer period is not applied at full weight during turbulence.
Findings are translated into plain-language guidance with a stated probability range, not a guaranteed outcome.
Backtesting window: our models are trained and validated against market data from 2008 to the present, covering multiple full economic cycles including the 2020 and 2022 corrections. Past performance in this window does not guarantee future results.
A compact set of tools, each tied to a specific stage of decision-making — from spotting a trend to keeping a portfolio in line with your risk tolerance.
We don't promise returns; we provide probability. See how our models behaved during two historical market corrections, compared against a baseline index.
During both the 2020 liquidity shock and the 2022 rate-driven correction, our models reduced recommended equity exposure ahead of the steepest drawdown periods, based on backtested signals available at the time.
This is presented as historical model behavior, not a forecast. Every investor's outcome depends on their own entry point, allocation, and risk tolerance.
Straightforward answers to the concerns that come up before someone decides to start.
The model flags when current conditions resemble historical periods of elevated volatility and adjusts its recommendations accordingly. It does not eliminate risk — it aims to size it appropriately for the environment you're investing in.
Data handling follows applicable EU data protection requirements, including data minimization and storage limitation principles. Details on specific safeguards are available on request before you create an account.
No. Recommendations are presented in plain language with a stated probability range, rather than raw technical indicators. The methodology section explains the reasoning behind each output.
Guessing has no traceable basis. Our predictions are derived from patterns validated against market data since 2008, with the underlying correlation and its historical accuracy disclosed alongside each recommendation.
Join 5,000+ users leveraging AI-backed insights for smarter strategic decisions.