Backtesting Arena

What happened historically after the Bitcoin cycle looked like this? Conditional forward-return distribution for a named preset cycle state — over N DISTINCT historical episodes matching that state (matched_episodes), returns median/IQR/positive-share forward returns (30/90/180/365d) with per-horizon n, small-n warnings, point-in-time integrity and an `evidence` block that names which field its sample-size gate checked (gate_applies_to), against which threshold, over which data window. A distribution with its sample size. Not obtainable from web search or public market-data APIs — requires poi…

What do the classic indicators read right now? Current RSI(14), MACD(12/26/9), Bollinger(20,2), ATR(14) and OBV for a pair — each with a PERCENTILE RANK against that indicator's own history on that pair, plus the observation count — the rank turns a raw reading into a placement. ATR comes as a percentage of price so it is comparable across time, and OBV as a 30-bar slope normalised by that window's volume (raw cumulative OBV would mostly rank how long the series has existed). Where the reading sits in an extreme AND a study on this platform has tested that exact state, the payload carries the …

What is the options market pricing in? Latest Deribit volatility snapshot for BTC or ETH. Returns DVOL (30d vol index), constant-maturity ATM implied vol (30/60/90/180d via options chain), 30d realized vol, and `vol_risk_premium_30d`, which is the TRAILING spread: ATM implied vol (30d, from the options chain — not DVOL) minus the realised volatility of the PAST 30 days. It answers "are options priced expensively right now?". Set include_implied=true to additionally get the FORWARD premium in an `implied` block: DVOL(t) minus the realised volatility of the FOLLOWING 30 days, which answers the d…

Is my universe backtest finished? Polls an async job by job_id (created via arena_run_universe_backtest). Returns status (pending/running/completed/failed), progress_pct, pairs_completed, and once completed: the full result (summary + per-pair results). [Free tier]

Which price levels matter above and below spot? Reproducible Bitcoin structural levels on BOTH sides of spot, in TWO distinct provenance classes. (1) resistance/support: swing-pivot clusters — where past pivot highs+lows cluster into price zones (touch-count, band, last-touch date, signed distance), resistance above spot, support below, nearest-first. (2) indicator_levels.above / .below: named indicator STANDS as marks — 200-day & 200-week simple moving averages, short-term-holder cost basis, Pi-Cycle legs — each carrying its source, formula and as_of date. The two classes are kept separate on…

What does the platform know about this subject? Fetch a versioned, explainable Knowledge Object by type + subject (e.g. type='market_regime', subject='GLOBAL'). Returns the current published envelope: payload, explanation (factors + weights + confidence), provenance (inputs + params), ontology binding, compute version. ONE tool covers ALL knowledge types. Set include_graph=true to also walk the knowledge graph: resolved outbound edges (what this object is derived_from / references) + inbound edges (what derives from / references it), each with api_path + seo_slug so you can follow them. [Free …

What is the macro backdrop doing? Daily Macro Regime snapshot from 18 components in 6 tiers (Liquidity 30%, Financial Conditions 20%, Risk Appetite 15%, Crypto Liquidity 10%, Business Cycle 15%, Inflation/Real Rates 10%). FRED-sourced. Returns composite_score (0-100), regime_label (risk_off/neutral/risk_on_leaning/risk_on), cycle_phase_label (contraction/early_expansion/mid_expansion/late_expansion), matrix_quadrant (sweet_spot/late_cycle_warning/crisis/recovery), tier_scores (6 sub-scores), components (flat key/value of all 18), plus stale_components_detail dating each stale input (last_good_…

What happened at the last Deribit expiry? Max pain and how spot settled against it: max_pain_strike, spot_at_expiry, %-diff, put_call_ratio, notional. Plus up to 10 upcoming expiries, each with current live max-pain level, days_to_expiry, open_interest_contracts and open_notional_usd. Field semantics: days_to_expiry is floored at 0 and cannot separate "expires later today" from "already settled" — settles_at (full ISO timestamp) and hours_to_settlement (SIGNED; negative = settled but not yet finalized) carry that distinction. settlement_time_utc names the settlement time where evidenced agains…

Does max pain actually pull price to the strike? Settled Deribit BTC options expiries with the max-pain level we compute per expiry, for measuring the convergence question: does spot drift toward the max-pain level as expiry approaches? Each row: expiry_date, max_pain_strike, spot_at_expiry, %-diff, P/C ratio, notional, expiry-type flags. The mandatory base_rates block answers the convergence question PER expiry class (n, median |diff|, shares within 1%/2%, max, sample_adequate at n>=30) — the pooled median mixes tiny daily expiries with large quarterlies, which is what the per-class split sep…

How has this on-chain metric moved over time? Returns the full TIME SERIES of one on-chain metric from the Bitcoin Research Kit — date/value pairs in ascending order, with history back to 2009 for most series. Use it for trend and percentile work; for the single current reading call arena_get_onchain_latest, and to discover valid series_ids call arena_list_onchain_series. Values are as-reported: on-chain metrics can be revised retroactively, so this is not a point-in-time vintage. Range capped by tier — the response carries a `range` block (requested_days, granted_days, clamped, clamp_reason, …

What does this on-chain metric read right now? Returns the most recent value of ONE on-chain series from the Bitcoin Research Kit as { series_id, metric_name, date, value }. Cheapest way to answer "what is X right now" (MVRV, SOPR, realized price, hash rate, …). Discover valid series_ids with arena_list_onchain_series; for the history behind the number use arena_get_onchain_history. A single reading has no context — pair it with the series percentile before calling any level high or low. [Free tier]

How hot is the Bitcoin market today? Daily 0-100 heat score for the Bitcoin market, aggregated from 8 components (BTC-Cycle, F&G, Altcoin-Season, Bullmarket-Ampel, Funding-Rate, Hash-Ribbons, Mayer-Multiple, MVRV-Z). Returns score, band label, color, 7d/30d delta, verdict, components breakdown, plus score_percentile ranking today’s score against its own history (e.g. 42 = 44th percentile — how hot/cold vs history, not just the raw number). score_semantics says which value you hold: the daily snapshot frozen once a day by the cron, or — before that cron has run for today — a live preliminary th…

Is this backtest result real, or a lucky cell? Assess one backtest result against its neighborhood instead of trusting a single "+X% CAGR" cell. Given a (strategy, interval, pair) and YOUR result (user_cagr, optional user_sharpe), returns: the cross-asset distribution of the SAME strategy+interval across every pair the backtest factory ran it on (median, IQR, positive-share, your percentile), a plateau/spike/fragile/mixed verdict, and — where Sharpe coverage allows — a Deflated Sharpe threshold whose N is COUNTED (the number of neighbor assets IS the testing family), not guessed. Honest small-…

Should I take this entry? Answers it for one (strategy, pair, interval) in ONE call instead of seven. Aligns what each entry filter historically did to this strategy (arena_get_strategy_filter_effect) with where that filter stands TODAY (bull-market gauge, altcoin-season signal, volatility phase, 200-week trend for BTC): `filters[].blocks_this_entry` says which filter would sit this entry out, with the measured worst-loss / return deltas next to it. Adds the current signal state (anticipated is always false — before candle close there is no signal), an `edge_vs_benchmark` block gated by the ME…

Current BTC, ETH and SOL spot price — what is Bitcoin (or ETH/SOL) worth right now? Live USDT-quoted last price plus 24h change %, high and low from Binance. Use this to anchor the connector’s own analytics (cycle, historical-analog, gem scores) with the current market price instead of switching to web search mid-analysis. [Free tier]

Aggregate stablecoin supply (crypto-liquidity proxy) — is the liquidity impulse turning or accelerating? macro_regime only gives the 30d delta; this exposes the trend: current supply, 30d/90d change (USD + %) plus a daily time series (`days`, default 365; `resolution` states points and spacing) so direction and speed are visible, not just a single delta. Read `impulse` for what the supply change is doing — four states (accelerating / decelerating / reversal / flat). The neighbouring `acceleration_usd` is the signed difference last-30d minus prior-30d and gets LARGE exactly when the trend rever…

What did recent buyers pay on average — and how far is spot from that? Latest BTC short-term-holder cost basis (realized price of coins younger than ~155 days, BRK brk_sth_realized_price), derived STH-MVRV (spot ÷ STH cost basis), an in_loss flag, plus ±1σ/±2σ bands: basis × exp(±k·σ), σ of ln(price ÷ basis) over a 730-day ROLLING window (sigma_method/sigma_window_days travel in the payload; similar construction to public STH band charts, own convention — not a rebuild). band_zone names the state (above/below basis, beyond ±2σ); sth_mvrv_percentile is the rolling 730d rank. Measured band cover…

What would each entry filter have changed for this strategy? Per-(strategy, asset, interval) filter-effect analysis. Returns baseline-stats (no filters) + each observed filter-variant's stats with cagr_delta / drawdown_delta / win_rate_delta vs the time-overlap-matched baseline + best_by_cagr pick (null with best_by_cagr_reason when every variant is low_data or none beats the baseline — no pick below the data gate) + not_applicable_filters list (e.g. altcoin_season excluded on BTC-pair). Baseline and each variant carry their aggregation `window` (from/to + avg_run_years) — CAGR is time-normali…

Which strategy and interval combinations actually performed? Aggregated backtest performance per (strategy × interval) cell. If `strategy` AND `interval` provided, returns detail with per-asset breakdown + param variants. Otherwise returns the matrix. Free tier is limited to the same strategies that are free in the backtester itself (rsi_sma, golden_cross, rsi_ob_os, bnh_fixed, dca_reference, dca_reference_v2); the response then carries `plan_capped: true` plus `plan_cap_note`, so a short matrix is never mistaken for a thin database. Detail mode on a Pro-only strategy returns 403 rather than a…

How did this exact strategy, asset and interval perform? Aggregated backtest performance for ONE specific (strategy, asset, interval) combination. Returns run_count, avg_cagr, avg_win_rate, avg_drawdown, effective_years, vs_buy_hold comparison (beats_buy_hold, cagr_delta) and an `evidence` block declaring the gate machine-readably (gate_applies_to: stats.run_count, threshold 5 runs, benchmark value, aggregation data window). For multi-strategy overview use arena_get_strategy_insights. Use this to answer 'How does strategy X perform on asset Y?'. [Free tier]

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…

Which pairs are in this universe? Returns one pair universe in full: its id, label, selection rule and the complete list of pairs it currently contains. Use it to see what you are about to test BEFORE handing a universe_id to arena_run_universe_backtest, or to resolve a universe into explicit pairs. For the list of available universes call arena_list_universes. Without as_of the universe reflects the CURRENT membership (CoinGecko market-cap rank) — a backtest over it carries survivorship bias for the earlier years; the `pit` block in the payload says so. With as_of (YYYY-MM-DD, >= 2026-07-14) …

How volatile has Bitcoin been? Daily Bitcoin volatility time series: realized volatility (30d & 90d, √365-annualized — calendar days, the same basis as DVOL — close-to-close) and ATR% (Wilder EMA-14, captures intraday range + gaps), on the same scale. Ranks come in two flavours answering different questions: `rvRank`/`atrPctAnnRank` expand from the start of history and are look-ahead-free, but they include BTC's structural volatility decline; `rvRankRolling`/`atrPctAnnRankRolling` rank against a trailing 2-year window, which removes that trend from the comparison. History reaches back to 2009 …

Do these two backtest figures actually differ? Check before ranking them. Pass the two values as `a` and `b` (same metric, same basis) plus `axes` — which arbitrary choices went into them — and the tool returns whether their gap clears the MEASURED noise floor of those choices, along with the floor itself, the dominant axis, and the probe + date it was measured on. `axes` accepts: grid_phase (how a multi-day candle grid is aligned to the Unix epoch; exists only on 2d/3d), parameter_choice (neighbouring parameter settings — by far the largest axis), window_edges (shifting the start date), pair_…

Which backtests have I run? Lists the backtest runs belonging to the authenticated user — newest first, with id, strategy, pair, interval, date range and headline metrics per run. Use it to find a run_id, then call arena_get_backtest for its detail or arena_get_backtest_trades for the individual trades. Only your OWN runs; for the public cross-user leaderboard use arena_get_winners. Paginated via limit + offset. [API Pro tier]

What knowledge objects exist here? Discover what Knowledge Objects exist: lists all published types + their subjects (with min_tier, api_path, seo_slug, latest as_of). Use this BEFORE arena_get_knowledge to learn valid type/subject pairs instead of guessing. New types appear automatically. [Free tier]

Which on-chain series are available? Lists all 71 available Bitcoin Research Kit (BRK) on-chain series across the groups pilot, sentiment, mining, supply, cointime, activity, liquidity (e.g. MVRV, NUPL, SOPR, Realized-Price, Mayer, Puell, STH/LTH SOPR, Hash-Ribbons). Returns id + label + group. Use the id with arena_get_onchain_latest / _history. [Free tier]

Which strategies can I backtest here? Lists all backtest strategies (key, label, plan, supported asset classes, primary indicators). Filterable by asset class and plan. Use this before calling arena_run_backtest to discover valid strategy names. Entries deprecated for an asset class stay listed (historical results depend on them) and carry deprecated_for + deprecation {since, reason} — do NOT call arena_run_backtest or validate_strategy for those combinations, they return 400. [Free tier]

Which asset universes can I test against? Lists all crypto asset universes (BTC, top-10 crypto, top-50 crypto, etc.) — the underlying pair-sets used by custom-report and universe-backtest endpoints. [Free tier]

How would this strategy have performed? Run ONE strategy on ONE pair over a date range and get the full result: CAGR, total return, max drawdown, win-rate, trade count, Buy & Hold comparison, net-of-fees figures, and a run_id for later retrieval. Synchronous, typically 3–10s. Use this when the user wants a concrete result for a specific setup. For several strategies side by side use arena_compare_strategies; for many pairs at once use arena_run_universe_backtest; to judge whether an EXISTING result is trustworthy rather than produce a new one, use validate_strategy or arena_get_robustness_fiel…

Would a grid bot have made money here? Simulate a GRID BOT (buy-low / sell-high ladder inside a fixed price range) on historical candles. Returns final value, return %, CAGR, trade count, fees paid and a Buy & Hold comparison — plus `zerlegung` (spot runs): `decomposition` splits the result into ladder P&L from completed buy→sell cycles, allocation P&L of the starting coins, open grid buys and fees (identity_check_usd must be ~0); `benchmarks` anchors buy-and-hold, the never-touched starting split (static_allocation, with coin_share_start) and an arithmetic 50/50 at the entry price — grid_vs_s…

Does this strategy hold up across a whole universe? Runs it against every pair in the universe. Pair cap depends on your API tier: Pro 50, Power 250 — Power covers crypto-top-250 in ONE job, and a single job keeps the ranking on one pair set (merging results across different pair sets measures pair selection, not strategy quality). THIS CALL IS ASYNCHRONOUS AND RETURNS NOTHING BUT A job_id: the result is NOT in this response. You MUST poll arena_get_job_status until status is 'completed'; estimated_seconds in the create-response says how long to budget. Provide either universe_id (call arena_l…

Am I connected, and what can this key do? Returns auth status (key kind: oauth connector or bearer API key, tier), server version, current UTC time, and the rate-limit state (hour/day used, remaining, reset) WITHOUT consuming extra quota beyond this call itself. Call this first when other tools fail: it separates auth problems (reconnect), tier problems (upgrade) and rate limits (wait) from real outages. [Free tier]

Does this strategy survive an honest test? Backtest a trading strategy honestly — look-ahead-aware validation with Deflated-Sharpe-Ratio / multiple-testing correction (Bailey & López de Prado). Returns an EVIDENCE verdict (insufficient_evidence | anecdote | failed_oos | passed_oos) plus metrics, flags and caveats — NOT a buy/sell recommendation. Call this before acting on a strategy or signal list. Accepts a named catalog strategy (type=rules), a timestamped BUY/SELL signal list (signal_list), or a timestamped trade list (trade_list). Checks: realistic next-bar fills (look-ahead/optimism), net…