A better question.
A deeper understanding.

EdgeVeris is a research and validation workspace for systematic trading strategies. It brings strategy code, historical data, backtesting, optimization, out-of-sample validation, robustness testing, Monte Carlo simulations, prop evaluations, options context, portfolio analysis and PDF reporting into one connected workflow.

Instead of treating an attractive equity curve as the final answer, EdgeVeris helps you investigate how the result was created, what risks may be hidden inside it and whether the strategy holds up beyond the data used to develop it.

EdgeVeris is designed for systematic traders, strategy developers, quantitative researchers and prop traders who want to evaluate rule-based trading ideas through a structured research process.

It is suitable for experienced Python users as well as traders who use an AI assistant to turn clearly defined trading rules into compatible code. EdgeVeris is not a signal service, copy-trading platform or discretionary charting terminal.

An attractive backtest is only the beginning. Overfitting, trading costs, parameter selection and changing market conditions can all undermine a strategy that initially appears promising.

EdgeVeris helps you build a repeatable research process: develop an idea, test it, compare alternatives, validate it on unseen data, challenge its robustness and document the final result. Prop simulations, options context, Monte Carlo analysis and portfolio tools allow you to examine the strategy from several different risk perspectives before relying on it.

A regular backtest shows what happened under one set of rules and assumptions. EdgeVeris helps you investigate why it happened and how dependent the result is on those assumptions.

You can compare parameter candidates, separate development data from unseen validation data, examine performance across market conditions, test sensitivity to trading costs and determine whether returns depend on a narrow parameter range, a small number of trades or a favourable historical period.

No. EdgeVeris does not sell trading signals or automatically generate a profitable strategy.

It provides the research environment and analytical tools needed to test, compare, validate and refine strategies that you define. An external AI assistant can help translate your trading idea into compatible Python code, but you remain responsible for reviewing the strategy logic and deciding how the results should be used.

Your trading idea comes first — you do not have to write every line yourself.

Describe your entry rules, exits, filters and risk management to an AI assistant such as ChatGPT, Claude or Grok, and ask it to create Python code that follows EdgeVeris’s strategy requirements. The AI Instructions button gives you a ready-to-copy specification for your chosen assistant.

Paste the resulting code into EdgeVeris, review it carefully and confirm that it matches your intended rules before starting the analysis. AI-generated code can contain mistakes and should not be treated as automatically valid.

Start with a trading idea, clearly defined entry and exit rules and a compatible Python strategy.

Choose your instrument, timeframe and date range, provide supported historical data and configure your position sizing and trading-cost assumptions. Paste or upload your code, review it in the editor, create the strategy and run your first analysis.

No live brokerage connection is required to analyse historical data.

Yes. You can bring your own Python strategy together with compatible CSV or Parquet price history, select the relevant instrument and date range and keep the entire research process inside one workspace.

You can also use the supported Databento connection with your own credentials and compatible source data. Available historical coverage, resolutions and instruments depend on the selected provider, dataset and subscription tier.

EdgeVeris supports compatible imported price history and selected CME futures workflows, including historical price and volume data.

You can also work with imported option quotes, instrument definitions and option statistics. When matching underlying-market data is available, EdgeVeris calculates implied volatility and Greeks including delta, gamma, theta, vega, vanna and rho, and connects them to strategy performance.

Historical coverage, instrument availability and provider licensing depend on the selected data source.

EdgeVeris separates strategy development from evaluation on unseen data.

You can optimize and compare parameters on a development period, examine candidates on separate validation data, freeze the selected configuration and optionally evaluate it on a final holdout that was not used during development.

Parameter stability analysis, robustness tests, Monte Carlo simulations and distribution-based diagnostics help reveal whether performance depends on a narrow parameter choice, a small number of trades or unusually favourable market conditions.

These tools can reduce the risk of overfitting, but they cannot eliminate it completely.

A frozen candidate is the strategy configuration selected after the development and validation process.

Freezing records the chosen strategy and its relevant analysis settings before the optional final holdout is opened. This creates a clearer separation between selecting a strategy and evaluating it on data that did not influence that selection.

The final holdout should be treated as a one-time final check rather than another opportunity to adjust parameters. Repeatedly modifying a strategy after seeing its holdout results would gradually turn the holdout into additional development data.

Before running an analysis, you can configure the supported position-sizing and trading-cost assumptions relevant to the strategy, including commissions, spread and slippage.

These assumptions should reflect the instrument, broker, venue, order type and intended trading frequency as realistically as possible. Even a small change in execution costs can materially affect a short-term or low-margin strategy.

EdgeVeris also allows you to examine how sensitive the result is to changes in those assumptions rather than relying on one idealized cost scenario.

Every backtest remains a historical simulation rather than a record of live execution.

Its realism depends on the quality of the source data, the strategy code, position sizing and assumptions about commissions, spread, slippage, liquidity and intrabar execution. Missing data, future-data leakage, unrealistic fills or incorrect contract handling can all distort the result.

EdgeVeris provides tools for testing assumptions and identifying potential weaknesses, but you should still review the code, data and execution logic before interpreting the results.

Yes. Select a saved candidate and a supported prop program, then simulate strategy paths against its profit target and loss limits.

You can compare estimated pass rates, completion times, failed attempts and associated costs. Funded-account and payout analyses extend the evaluation beyond passing the initial challenge and help you explore what may happen under the selected funded and payout rules.

The results are estimates based on historical performance and the chosen simulation inputs. They do not guarantee that a real challenge will be passed.

Yes. Portfolio Trader combines saved strategy candidates on a shared timeline.

You can compare each strategy with the combined portfolio, examine overlapping losses and drawdowns and determine whether the strategies provide meaningful diversification or simply behave similarly during difficult periods.

Portfolio-level robustness, Monte Carlo and prop evaluations allow you to analyse the combined result rather than evaluating every strategy in isolation.

No. EdgeVeris is currently focused on historical research, backtesting, validation and reporting.

It does not place orders, manage brokerage accounts or automatically trade capital. EdgeVeris is a research platform, not a broker, investment adviser or trade-execution service.

No brokerage connection is required to use the analytical features.

Your hosted strategy code, imported data and saved workspace are processed in your account workspace on EdgeVeris infrastructure. When running the local application, they are processed on your computer.

EdgeVeris does not automatically publish your strategy or send it to ChatGPT, Claude, Grok or another AI provider. The AI Instructions button only prepares text that you may choose to copy into an external AI service.

Sharing your strategy code or other information with an external service is a separate decision and is governed by that service’s privacy policy and terms.

Available features, usage limits and data access depend on your subscription tier. The Pricing page provides a direct comparison of the available plans.

Elite brings together the full research workflow, including backtesting, optimization, validation, robustness, frozen candidates, prop simulations, options analytics, Monte Carlo, portfolio analysis and PDF reporting. It also includes COT, macro, CPI and NFP analysis, seasonality, Exit Efficiency, the code library and reusable input sets.

Third-party data charges are not automatically included unless explicitly stated. When using your own data-provider account, such as Databento, the provider’s pricing and licensing conditions continue to apply.

Yes. The 24-hour paid trial costs $7.99 USD and gives you full Elite access for 24 hours after payment is confirmed.

You can work with your own strategies, data and analyses and explore the complete workflow before choosing a longer subscription.

The trial is a one-time purchase and does not renew automatically. It does not automatically convert into a subscription when the 24-hour period ends.

Your trial access ends after 24 hours unless you separately choose a subscription.

The trial does not initiate an automatic recurring payment. Your own strategy code and source data remain your files, while continued access to subscription features and new analyses requires an active plan.

No. EdgeVeris helps you perform more structured and rigorous historical research, but no backtest, robustness test or simulation can guarantee future trading performance.

Market conditions change, execution may differ from historical assumptions and previously observed relationships can weaken or disappear. All results should be treated as research evidence rather than a promise of future returns.

EdgeVeris is designed to help you ask better questions before putting confidence in a strategy — not to remove uncertainty from trading.