Backtesting Arena

Get Regime-Aware Strategy Performance

arena_get_strategy_performance_by_regime

Read-only

In which macro regime has this strategy worked? Historical backtest performance for ONE (strategy, asset, interval) combination SPLIT BY macro market regime (sweet_spot / late_cycle_warning / crisis / recovery — classified at each trade's entry date), PLUS the CURRENT live regime so you can align the buckets yourself. You get the per-regime numbers to weigh directly (per-bucket verdicts live in the per-cell tools, where the pool is stable). Each regime bucket returns trades, trades_per_config (trade counts pool ALL parameter-variant configs — see config_count), win_rate, avg_pnl_pct (per-trade return, not annualized), reward_risk_ratio (per-trade mean/stddev, NOT annualized Sharpe), share_of_time_pct (calendar-day-weighted — each regime observation counts the days until the next one, so the mixed weekly/daily cadence of the regime history does not skew the share) and a rating. The benchmark block anchors the payload with the combination's buy-and-hold CAGR (identical to arena_get_strategy_performance vs_buy_hold — without that anchor, regime avg_pnl_pct is a trajectory, not an excess). For a decision-grade view compose with arena_get_strategy_filter_effect and arena_is_distinguishable. [Free tier]

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "strategy": "<strategy>",
      "asset": "<asset>"
    },
    "name": "arena_get_strategy_performance_by_regime"
  }
}

Input Schema

Name	Required	Description
`asset`	Yes	Crypto pair / symbol (e.g. BTCUSDT, ETHUSDT). Case-insensitive.
`interval`	No	Default '1w'. Candle interval: '1d' daily, '2d'/'3d' multi-day, '1w' weekly, '1M' monthly. Multi-day candles (2d/3d) are anchored to the Unix epoch, so one of n possible alignments is used. Measured on our own corpus, the choice of alignment alone moves CAGR by 6.66 pp on average (max 12.30). Treat differences below that as not distinguishable — 1d/2d/3d behaved as one block in our tests, not a ranking.
`strategy`	Yes	Strategy key (e.g. rsi_sma, golden_cross). See arena_get_strategies.
`asset_type`	No	Optional asset class filter to disambiguate identical pair-names.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 29, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```

Changed3 schema fields changedAug 25, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

removedInput schema / properties / context

Removed value: -{
-  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
-  "type": "string"
-}

changedInput schema / required

Previous value: -[
-  "strategy",
-  "asset",
-  "context"
-]New value: +[
+  "strategy",
+  "asset"
+]

Changed1 schema field changedJul 31, 2026

changedInput schema / properties / interval / description

Previous value: -"Default '1w'."New value: +"Default '1w'. Candle interval: '1d' daily, '2d'/'3d' multi-day, '1w' weekly, '1M' monthly. Multi-day candles (2d/3d) are anchored to the Unix epoch, so one of n possible alignments is used. Measured on our own corpus, the choice of alignment alone moves CAGR by 6.66 pp on average (max 12.30). Treat differences below that as not distinguishable — 1d/2d/3d behaved as one block in our tests, not a ranking."

Changed1 schema field changedJul 31, 2026

changedInput schema / properties / interval / enum

Previous value: -[
-  "1d",
-  "1w",
-  "1M"
-]New value: +[
+  "1d",
+  "2d",
+  "3d",
+  "1w",
+  "1M"
+]

Changed1 schema field changedJul 24, 2026

changedInput schema / properties / asset_type / enum

Previous value: -[
-  "crypto"
-]New value: +[
+  "crypto",
+  "tokenized_equity",
+  "tokenized_etf",
+  "commodities"
+]

Changed2 schema fields changedJul 14, 2026

changedInput schema / properties / asset / description

Previous value: -"Pair / symbol (e.g. BTCUSDT, AAPL.US). Case-insensitive."New value: +"Crypto pair / symbol (e.g. BTCUSDT, ETHUSDT). Case-insensitive."

changedInput schema / properties / asset_type / enum

Previous value: -[
-  "crypto",
-  "stock",
-  "etf",
-  "commodities",
-  "forex"
-]New value: +[
+  "crypto"
+]

First observedJul 13, 2026

TDQS

A4.4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With only readOnlyHint in annotations, the description carries the behavioral load and does so richly: it explains that trade counts pool ALL parameter-variant configs (pointing to config_count), that avg_pnl_pct is per-trade not annualized, that reward_risk_ratio is mean/stddev rather than a Sharpe, and that share_of_time_pct is calendar-day-weighted to avoid skew from mixed weekly/daily cadence. It also warns that without the benchmark anchor, regime avg_pnl_pct is a trajectory rather than an excess.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the governing question and the scope, then metrics, then benchmark, then composition. Each sentence earns its place, though the nested parentheticals make it dense and slow to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must explain the payload and it does: it enumerates every per-regime field (trades, trades_per_config, win_rate, avg_pnl_pct, reward_risk_ratio, share_of_time_pct, rating) plus the benchmark block and the current live regime. Nothing an agent needs to interpret the result is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the interval enum docs are already extensive (alignment caveat, 6.66 pp CAGR drift), so the schema does the heavy lifting. The description only names the strategy/asset/interval triple and adds no syntax or format guidance beyond it — baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific question ('In which macro regime has this strategy worked?') and states the exact unit of analysis: ONE (strategy, asset, interval) combination, split by the four named macro regimes. It also distinguishes itself from the near-name sibling arena_get_strategy_performance by noting the benchmark block is identical to that tool's vs_buy_hold.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes composition: 'For a decision-grade view compose with arena_get_strategy_filter_effect and arena_is_distinguishable,' and explains that per-bucket verdicts live in per-cell tools where the pool is stable. It gives clear context but does not state an explicit 'do not use this when…' exclusion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Backtesting Arena tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.