Strategies
Quantitative strategies presented with equity and risk metrics, rule validation, and full trade records.
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Explore Strategies & Portfolios
Select rules based systems or diversified bundles across futures, equities, crypto, and FX, all with transparent backtests, each presented with verifiable metrics and trade records.
Portfolios
Correlation aware bundles targeting steadier performance across assets and market conditions.
Explore portfolios
Quantitative Analysis Workflows
Institutional grade due diligence is embedded. Monte Carlo resampling and walk-forward tests verify edge and mitigate overfitting.
Audit grade backtests
Realistic P&L with trading frictions and embedded bias controls.
Walk forward validation
Walk forward analysis to confirm durable performance.
Monte Carlo simulations
Randomized paths and trade order to pressure-test the edge.
Trade transparency
Full trade history: entries, exits, drawdowns, and timestamps.
Portfolio construction
Multi asset diversification with correlation controls.
Integrated Risk Controls
Position sizing and risk limits integrated across all strategies.
Market Challenge
Markets reward systematic, data driven edge over intuition. Most backtests suffer from look ahead bias, curve fitting, and regime blindness, creating fragile strategies that collapse in live trading. Investors need a disciplined quantitative framework that isolates true signal, withstands market turbulence, and adapts as conditions evolve.
Algorithmic Strategy Research
We start with an economic hypothesis that explains why an edge may exist. We translate that idea into simple, testable rules and apply realistic data treatment and costs. Candidates that meet quality thresholds move to validation.
Define the hypothesis
Document the edge rationale such as trend persistence, mean reversion, breakouts, seasonality, carry, or market structure.
Specify the rules
Write deterministic entries and exits, timing and holding period, order model, and risk rules.
Prepare data and markets
Apply contract rolls and corporate actions, set session hours, filter for liquidity, and include financing, funding, and fees.
Set parameter ranges
Use sensible ranges and guardrails, favoring stability and simplicity over curve fit.
Test across assets
Evaluate in futures, equities, crypto, and FX, across multiple time frames and market regimes.
Promote candidates
Screen on net results, risk and stagnation, trade count, and rule clarity. Only qualified systems advance to the validation queue.
Robustness Validation Engine
Each strategy candidate is examined for stability, realism, and transparency. We use walk forward studies to track performance through time, Monte Carlo resampling to size dispersion and tail risk, sensitivity maps to confirm robust parameter regions, regime checks to test behavior in different market states, strict data and bias controls, and execution assumptions that match live trading.
Walk forward testing
Rules selected on one window are evaluated on the next. Rolling windows track stability and flag performance decay.
Monte Carlo analysis
Resamples price paths and trade order to estimate the range of outcomes and tail losses.
Parameter stability
Small changes in parameters should not change results materially. We map sensitivity to confirm robust zones.
Market state checks
Verifies behavior in trending and ranging markets and across different activity levels.
Integrity controls
No look ahead or survivorship effects. Corporate actions and contract rolls handled correctly. Results include fees, slippage, and financing.
Execution realism
Order models respect liquidity and latency. Size limits, stop logic, and cost assumptions.
Investment Perfomance Audit
Independent review that reconstructs net results, separates skill from luck, and turns findings into actions.
Equity
Investment
Benchmarks
Financial
01
Ingest trade logs and statements; construct net equity including fees, slippage, and financing.
02
Measure peak to trough loss, recovery time, stagnation days, and rolling returns.
03
Call out regime behavior and risk concentrations; note sizing and safeguard adjustments.
Responsible Capital Allocation
A disciplined approach built on clear reporting, consistent rules, and measured guidance.
Transparency
Equity and risk metrics reported net of fees, slippage, and financing, with trade records.
Reliable execution
Deterministic entries and exits that account for real costs, slippage, and latency.
Portfolio guidance
Diversify across assets with correlation review and overlap control.
FAQ
Frequently asked questions
What is RatioStreet?
RatioStreet a powerful strategy generator and research tool. It allows traders to generate strategies automatically for any market and any time frame using machine learning techniques and it does not require programming skills.
You can use SQ to find new and unique algo-trading systems that can give you a competitive advantage (edge) against other traders.
RatioStreet is much more than a “just” strategy generator – its powerful research capabilities allow you to test your own trading ideas, run complex tests, and analysis of systematic trading strategies.
How can I find out that strategies are going to be profitable also in real trading?
This is what the robustness tests are for. RatioStreet includes many tools for robustness testing that allow you to find out how your strategy is vulnerable to different changes. You will get an e-book (as one of the bonuses to FULL license) where the testing is thoroughly explained. Moreover, our support is ready to help you.
Build the process of accounting tickets from different OBTs?
Create an account, choose a plan, and follow the onboarding checklist. You can switch plans any time.
How do I get started?
Create an account, choose a plan, and follow the onboarding checklist. You can switch plans any time.