Canli Validation: is your backtest real?
Validates trading backtests for AI assistants: deflated Sharpe ratio, probability of backtest overfitting (CSCV), minimum track record and backtest length…
What it can do
- Get Key: Issue a free validation key for this session. Rarely needed: the first validation issues one itself unless CANLI_KEY or local mode is set, and the read tools need none. Quotas: 1000 validatio
- Validate Deflated Sharpe: Deflated Sharpe ratio: the probability (0 to 1) that the selected strategy's Sharpe beats the best that luck gives across the variants tried, with the probabilistic Sharpe an
- Validate Overfitting: Probability of backtest overfitting (0 to 1) by CSCV: how often the in-sample best variant falls below the out-of-sample median. Needs every variant's returns (periods by variant
What data it sees
Do you need an account
No: the server works without sign-in
Validates trading backtests for AI assistants: deflated Sharpe ratio, probability of backtest overfitting (CSCV), minimum track record and backtest length, haircut Sharpe ratio, luck-equivalent trials and more. Each tool is checked against its source paper and states what its result does not establish; hosted results come with a signed receipt anyone can recompute. Free, no API key needed.
How to connect
How to connect Canli Validation: is your backtest real? to Claude
The server address to paste into Claude settings:
https://canli-validation--arhancanli8.run.tools
- Open Claude (claude.ai or the desktop app).
- Go to Settings → Connectors.
- Click Add custom connector.
- Paste the server address copied below into Remote MCP server URL and click Add.
- In a chat, click + → Connectors and switch the new connector on.
Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.
Authorization
After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.
How to connect Canli Validation: is your backtest real? to ChatGPT
The server address to paste into ChatGPT settings:
https://canli-validation--arhancanli8.run.tools
- Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
- Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
- Open Settings → Connectors and click Create.
- Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
- Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
- In a new chat open + → Apps/Connectors and enable the connector.
OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.
Authorization
On first use ChatGPT opens the service's sign-in window. Sign in and approve access.
How to connect Canli Validation: is your backtest real? to Cursor
The server address to paste into Cursor settings:
https://canli-validation--arhancanli8.run.tools
Fastest: click Open in Cursor below and confirm the prompt.
Manually:
- In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
- Paste the JSON copied below into
~/.cursor/mcp.json(per project:.cursor/mcp.jsonin the repo root). - Save the file. The server appears in the MCP list; authorize it there if asked.
Authorization
If the service needs sign-in, an authorize button appears next to the server in the MCP list.
Server tool list (15)
Raw names from tools/list. Only developers need these.
| get_key | Issue a free validation key for this session. Rarely needed: the first validation issues one itself unless CANLI_KEY or local mode is set, and the read tools need none. Quotas: 1000 validations per key per UTC day, 5 keys per client per UTC day, 1048576 bytes per validation request, 1024 bytes per key revocation request, 20000 observations per series, 200 variants per matrix. |
| validate_deflated_sharpe | Deflated Sharpe ratio: the probability (0 to 1) that the selected strategy's Sharpe beats the best that luck gives across the variants tried, with the probabilistic Sharpe and that luck benchmark. Send the seven statistics or a return series. With every variant's returns use validate_overfitting; luck as a trial count, validate_luck_trials; a multiple-testing haircut, validate_haircut_sharpe. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| validate_overfitting | Probability of backtest overfitting (0 to 1) by CSCV: how often the in-sample best variant falls below the out-of-sample median. Needs every variant's returns (periods by variants); with summary statistics only, use validate_deflated_sharpe. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| validate_reality_check | Data-snooping tests on every variant a search tried: Hansen's SPA p-value that the best beat the benchmark only by luck, White's Reality Check, and the variants Romano-Wolf StepM finds better. Send all variants tried, not only the winners. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| validate_paper_evidence | Whether a paper or simulated performance record meets canli.paper-evidence.v0, with a JSON pointer per failure. Checks structure and required disclosures, not whether the returns are good. This verdict is about the series exactly as submitted. The service never saw the data source, its costs, survivorship, or any lookahead in how the series was built. |
| validate_breadth | Book Sharpe ceiling from adding sleeves of this quality and correlation, the Sharpe at a sleeve count, and the sleeves a target needs. For portfolio construction; it validates no single strategy. This verdict is about the series exactly as submitted. The service never saw the data source, its costs, survivorship, or any lookahead in how the series was built. |
| validate_track_record | Minimum track record length (observations and years) for an observed Sharpe to beat a benchmark at a confidence level; with observations, the record's probabilistic Sharpe so far. For live or paper records; to size a backtest for its trials, use validate_backtest_length. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| validate_backtest_length | Minimum backtest length (years) before the best of N independent trials is not expected to reach a target Sharpe by luck; with backtest_years, the most trials those years allow. For planning a search; once it has a result, use validate_deflated_sharpe. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| validate_haircut_sharpe | Haircut Sharpe for multiple testing (Harvey and Liu 2015): the Sharpe a single test would have needed, by Bonferroni and independent tests, and with the other tests' Sharpes, Holm and BHY. For the probability the Sharpe is real, use validate_deflated_sharpe. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| validate_luck_trials | How many skill-less strategies a search would need for its best to reach this Sharpe by luck (Monte Carlo), and with a trial count, the chance it did. States luck as the best of N random tries; for the probability the Sharpe is real, use validate_deflated_sharpe. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| audit_backtest | One-call audit of a strategy's returns: deflated Sharpe, minimum track record and, with every variant's returns, the probability of backtest overfitting, each the matching validator's result with its own receipt. Point returns_file at the backtest's CSV or JSON instead of pasting long series. Prefer it to calling the validators one by one; one validation per check. A deflated Sharpe or overfitting probability above or below any threshold is not admission to anything and is not a forecast. |
| get_receipt | Fetch a stored verdict by receipt id to re-read it. No key; verify_receipt checks it is genuine. The receipt is content-hashed, reproducible from the open-source core it names, and signed with Ed25519 by a key published at https://canlicapital.com/.well-known/canli-receipt-keys.json. |
| verify_receipt | Verify a receipt offline: its Ed25519 signature against the bundled canlicapital.com key, its output hash and its id. Send an id to fetch it first, or the receipt itself. The receipt is content-hashed, reproducible from the open-source core it names, and signed with Ed25519 by a key published at https://canlicapital.com/.well-known/canli-receipt-keys.json. |
| service_status | Whether the validation API is up, with its quotas; check after a timeout before resubmitting. No key. This verdict is about the series exactly as submitted. The service never saw the data source, its costs, survivorship, or any lookahead in how the series was built. |
| company_financial_history | SEC-reported financial history for one company in the canlicapital.com reference, by cik or ticker: without a concept, the histories available; with one, observations newest first with accession, form, filed date and unit, plus the source's SHA-256. For point-in-time values use canli-fundamentals-mcp. Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns. |