Build professional multi-strategy portfolios

Combine your strategies with ours into a single portfolio. Test allocation mixes, analyze combined performance, and verify diversification benefits.

How it works

Adjust weights

Adjust capital distribution across strategies using percentage sliders. Test tactical overweights, equal allocations, or custom blends to optimize portfolio construction.

Monitor equity

Observe portfolio-level performance as allocations change. The equity curve updates in real-time using daily constant-mix rebalancing methodology.

Review metrics

Analyze Sharpe Ratio, Maximum Drawdown, MAR Ratio, and correlation matrix. All statistics calculated net-of-fees with IBKR-realistic execution assumptions.

Download strategies

Once allocation meets your risk parameters, invest in strategies with automatic bundle discounts: 20% off 4+ strategies, 30% off 6+ strategies.

Professional portfolio simulation tool

Notes and Disclosures
  • IMPORTANT: The projections or other information generated by SetupAlpha Portfolio Architect regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results and are not guarantees of future results. Results may vary with each use and over time.
  • The results do not constitute investment advice or recommendation, are provided solely for informational purposes, and are not an offer to buy or sell any securities. All use is subject to terms of service and disclaimer.
  • Model Limitations: Hypothetical returns do not reflect the impact that material economic and market factors might have had on the advisor's decision-making if the advisor were actually managing client money.
  • Market Impact: The simulation assumes that trades could have been executed at the historical prices used, which may not be possible during periods of high volatility or low liquidity.

1. COMPREHENSIVE DATA & SIMULATION METHODOLOGY 3.1. Net-of-Fees Performance Calculation: To provide a more realistic estimation of potential performance, the underlying strategy data used in this simulation is calculated Net of Estimated Fees. This methodology differs from standard "gross" backtests and specifically accounts for:

  • Commissions: Transaction costs are modeled based on the Interactive Brokers (IBKR) "Pro" tiered commission structure for US Equities and ETFs (e.g., typically $0.0035 per share with minimums).
  • Slippage & Market Impact: A proprietary slippage model is applied to every theoretical trade. This model deducts a penalty from the entry price and adds a penalty to the exit price to simulate the "Bid-Ask Spread" and the cost of crossing the spread.
  • Limit Order Buffers: For strategies utilizing limit orders, an execution buffer is applied to ensure that the simulation only credits a "fill" if price penetrated the limit level by a statistically significant margin, reducing "phantom fills."
  • Exclusions: The simulation does NOT account for: capital gains taxes (short-term or long-term), platform data feed fees, exchange subscription fees, margin interest (unless explicitly shorting with leverage), or external advisory management fees.

1.2. Rebalancing Protocol (The "Synthetic Portfolio" Approach): The Portfolio Architect utilizes Rebalancing engine.

  • Mechanism: At the close of every trading session, the simulation mathematically calculates the total Net Asset Value (NAV) of the portfolio and redistributes capital to match the user-defined percentage allocations exactly.
  • Implications: This creates a "Synthetic Constant-Mix" portfolio. In a real-world live account, rebalancing daily would incur significant turnover and transaction costs. Most investors rebalance monthly or quarterly. Therefore, this simulation may overstate the "smoothness" of the equity curve compared to a live portfolio that allows allocations to drift. It assumes perfect friction-less reallocation of capital between strategies.
  • In-Market Status: The engine does not track whether Strategy A is "in cash" or "in a trade" on Day X. It simply allocates Y% of the total capital to Strategy A's equity curve. This captures the performance exposure but not the precise cash management of a unified brokerage account.

1.3. Capital Injections & Cash Flow Logic:

  • Initial Balance: The simulation normalizes all strategy data to start at the user-defined Initial Balance (e.g., $100,000) at the common start date.
  • Recurring Contributions: If the user enables "Cash Inflow" (Monthly, Quarterly, Semi-Annual, or Annual), the model simulates an external cash injection.Timing Assumption: Cash is assumed to be deposited on the first trading day of the period.Allocation: New cash is immediately deployed across all strategies according to target weights. The model does not simulate "dollar-cost averaging" lag; it assumes 100% deployment efficiency.

2. RISK & PERFORMANCE METRIC DEFINITIONS (QUANTITATIVE GLOSSARY) The following metrics are calculated using daily resolution data and annualized where appropriate:

  • Compound Annual Growth Rate (CAGR): The geometric mean annual growth rate. Formula: (Ending Value / Beginning Value)^(1 / Years) - 1. This represents the steady-state growth rate required to reach the final balance.
  • Sharpe Ratio (Risk-Adjusted Return): A standard industry metric calculated as Annualized Excess Return / Annualized Volatility. For specific clarity: This simulation assumes a Risk-Free Rate (Rf) of 0%. Therefore, it is a measure of pure return per unit of total risk. A Sharpe Ratio > 1.0 is generally considered "Good," and > 2.0 is considered "Excellent."
  • Sortino Ratio (Downside Efficiency): A variation of the Sharpe Ratio that differentiates "bad" volatility (losses) from "good" volatility (profits). It uses Downside Deviation determines the denominator. This metric is often more relevant for systematic strategies, as it does not penalize upside parabolic moves.
  • Maximum Drawdown (MaxDD): The deepest "peak-to-valley" percentage decline in the portfolio's equity. This measures the worst historical pain point. A 20% MaxDD means that at some point, the portfolio lost 20% of its value from a previous high before recovering.
  • Calmar Ratio: A measure of return relative to drawdown risk. Calculated as Annualized Return / Absolute Max Drawdown. A high Calmar Ratio indicates that the strategy's return is high relative to the risk of loss it has historically incurred.
  • Correlation Matrix (Pearson Coefficient): A statistical measure ranging from -1.0 to +1.0.1.0: Strategies move in perfect lockstep (No diversification).0.0: Strategies are uncorrelated (Maximum random diversification).-1.0: Strategies are inversely correlated (Perfect hedging).Usage: Use this matrix to ensure you are not simply stacking multiple strategies that all buy/sell the same risk factors at the same time.
  • Stress Period Analysis: This module filters the dataset to specific date ranges corresponding to historical market crises (e.g., the 2008 GFC, 2020 COVID Crash, 2022 Inflation Bear Market). This allows you to inspect "Tail Risk"—how the portfolio behaves during 3-sigma or 6-sigma market events.

3. USER-GENERATED CONTENT & UPLOADS 5.1. User Uploads: The "Upload Strategy" feature allows users to valid .CSV files containing their own proprietary data. 5.2. No Validation: SetupAlpha does not audit, verify, or validate the accuracy, integrity, or ownership of user-uploaded files. 5.3. Liability Release: By using the upload feature, you agree that SetupAlpha is not liable for any errors, corruptions, or misleading simulation results derived from user-uploaded data. You warrant that you have the right to use any data you upload.

4. TECHNOLOGY & PLATFORM LIMITATIONS 6.1. Browser-Based Calculation: All simulations are performed client-side within your web browser. Performance may vary based on your device's processing power. Extremely large datasets or complex combinations of 10+ strategies may cause browser latency. 6.2. Visualizations:

  • Logarithmic Scale: Charts may default to Logarithmic scale to visualize percentage growth over long periods. This can visually minimize recent volatility. Users can toggle to Linear scale for an absolute price view.
  • Interpolation: Charts with limited data points may use linear interpolation to connect dates, which may smooth out intra-day or intra-month volatility in the visual representation.

"I have run it live since 2024 and it is still in my portfolio. It also changed how I test the systems I build myself."

Systematic Traders Quant Traders & Writer
A RealTest backtest open on a laptop next to trading books
TradeQuantiX

I've been using a strategy from SetupAlpha and I'm really impressed with its elegance and stability. The unique approach gives me a fresh perspective and ideas I can apply to other strategies I'm developing. I'm currently working on integrating it into my suite of trading strategies.

TradeQuantiX Multi-Country Systematic Trader
Roman Blackwood

Buying a SetupAlpha strategy didn't save me money, it saved me research time. I estimate it replaced 70–90 hours of development, debugging, and validation. Even if I never trade the strategy exactly as delivered, the research process was worth the investment.

Roman Blackwood Founder of AI In Trading
Daniel

I traded discretionary for over a decade and kept putting off going systematic because I did not know where to start. Having a finished, tested system to take apart was what finally got me moving.

Daniel Crypto Trader

The research workflow behind every strategy

A strategy that fails one stage does not continue.

See how each test is run

SetupAlpha backtesting pipeline, seven stages Seven stages 01 Academic research 02 Signal testing 03 In-sample strategy build 04 Out-of-sample validation 05 Walk-forward analysis 06 Monte Carlo stress testing 07 Paper and live trading Dropped, and never listed

What each stage tests

Published research

The starting point is a paper from SSRN, arXiv or Science Direct. The raw signal is tested on its own, for whether it predicts future returns, before any rules exist.

Rules, data and costs

Rules are written in RealTest and tested on Norgate data that includes delisted companies. Interactive Brokers commissions and slippage are subtracted from every result.

Out-of-sample and live

What survives out-of-sample, walk-forward and Monte Carlo is traded in a live account at small size. The date it went live is shown on the strategy page.

Randomised equity paths from the Monte Carlo heatmap test of one RealTest strategy

One equity curve is not a test.

Strategies are tested beyond a single equity curve, across market regimes, trading costs, parameter variations and randomized trade sequences.

Every strategy includes the RealTest script and the rules.

The .rts file holds the complete strategy source. It imports into RealTest, runs the backtest straight away, and every rule in it can be read and edited.

The same logic is written out in plain text, without RealTest syntax, for reading through the strategy before running it or rebuilding it on another platform.

Both files are yours to keep. Parameters, position sizing and the universe can be changed, and the code can be used as the starting point for research of your own.

Research workflow, the seven stage process behind every SetupAlpha strategy
The RealTest .rts script and the plain text strategy rules you get with every strategy

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