Research index

Every analysis / research page published on aitradeanalytics.tech (57 live pages, each checked for HTTP 200 at build time). Newest first within each category. Verdicts are taken from each page; * = derived from the page's out-of-sample table.

Latest

Option buyer, ATM weekly, REAL costs, trail 50% after 2R. All 8 lose on train (Oct-24..Dec-25); 5 of 8 slightly positive in 2026, none significant (BH q>=0.67). Regime analysis: 8 ex-ante labels (VIX, DMA trend, efficiency ratio, prior-day range, NR7, gap, expiry, FII long %), 32 OOS regime/meta-switch tests, 0 survive BH. Lead: breakouts after an NR7 day (+23 to +28 pts/trade in 2026, reversed in 2024).

· Rules & simulators · /rl-trading/research/popular-strategies/

Old studies charged 3 pts slippage/side; real Upstox ATM bid-ask median 0.25 pt -> realistic cost ~2.0 pts/trade (Rs133/lot) not ~7; fixing it adds ~+4.9 pts/trade. Buyer-style exits, with-trend, first-hour, strike choice change results by <1 pt. Re-run (train Oct-24..Dec-25, test 2026, pre-declared, BH over 6): no candidate profitable OOS (best +0.9 pts, p=0.41). ORB with-gap has a real spot edge (+6 to +8 pts/trade 2022-26) but the long option keeps only 25-50% of it.

· Rules & simulators · /rl-trading/research/buyer-method-audit/

callwall/scripts build_panel.py charts.py cwlib.py evaluate.py events.py fetch_today.py publish_callwall.py section.py select_rule.py stats.py trades.py back

· Uncategorized · /rl-trading/research/intraday-recoveries/callwall/scripts/

callwall/results data_gaps.csv events.csv events.log excursions.csv fixed_rule.json hit_stats.csv rule_breakdowns.csv rule_trades.csv rule_vs_bench.csv rule_worst_days.csv stats.log today_events.csv t

· Uncategorized · /rl-trading/research/intraday-recoveries/callwall/results/

Live dashboards 3

Live read-only Nifty bias dashboard: fusion factor A–I scores, ATM chain, 1m chart with VWAP and S/R, news and research rule cards; refreshes every 30s.

· Live dashboards · /live/

Live multi-agent dashboard for Nifty 50 & Sensex: charts, EMA, liquidity sweeps, global cues, options PCR, risk, journal and Q&A.

· Live dashboards · /insight/

Live Upstox tick-feed viewer (raw payloads + up to 30 depth levels) for the Nifty index and ATM options.

· Live dashboards · /ml/ticks

Rules & simulators 8

Option buyer, ATM weekly, REAL costs, trail 50% after 2R. All 8 lose on train (Oct-24..Dec-25); 5 of 8 slightly positive in 2026, none significant (BH q>=0.67). Regime analysis: 8 ex-ante labels (VIX, DMA trend, efficiency ratio, prior-day range, NR7, gap, expiry, FII long %), 32 OOS regime/meta-switch tests, 0 survive BH. Lead: breakouts after an NR7 day (+23 to +28 pts/trade in 2026, reversed in 2024).

· Rules & simulators · /rl-trading/research/popular-strategies/

Old studies charged 3 pts slippage/side; real Upstox ATM bid-ask median 0.25 pt -> realistic cost ~2.0 pts/trade (Rs133/lot) not ~7; fixing it adds ~+4.9 pts/trade. Buyer-style exits, with-trend, first-hour, strike choice change results by <1 pt. Re-run (train Oct-24..Dec-25, test 2026, pre-declared, BH over 6): no candidate profitable OOS (best +0.9 pts, p=0.41). ORB with-gap has a real spot edge (+6 to +8 pts/trade 2022-26) but the long option keeps only 25-50% of it.

· Rules & simulators · /rl-trading/research/buyer-method-audit/

1-min spot/futures/options/VIX/BN 2022–26-Oct-2026. ≥200-pt recovery days: 26% of days in 2024–25, 8/16 in Oct-2026 (p=0.007) — a volatility regime (13/16 big-range days), not a new bottom-catching pattern. Put writing/call cover/basis/BN-lead/heavy-put-strike did NOT separate recoveries. Price rule (low within 30 min of open, bounce ≤5 min, VIX≥14.46) hit 28.8% vs 14.5% base OOS 2026 (p=0.003, BH q=0.024); ATM-CE trades after costs ≈ breakeven only with a spot-based runner exit (+2 pts/trade, p=0.39). Today 26-Oct case study included.

· Rules & simulators · /rl-trading/research/intraday-recoveries/

Fusion bias flipped a median 76 min after 80+ pt moves began (or never); of 14 leading signals tested out-of-sample 2025-26, 3 passed (Bank Nifty divergence and fast-market as either-way warnings, day high/low rejection modestly directional) and are live on /live/; none profitable alone for an option buyer.

· Rules & simulators · /rl-trading/research/early-warning/

Hub of descriptive "if this happens early in the session, how often does that follow?" rules on Nifty 1m data with Wilson CIs; in-sample, no costs, not an edge by itself.

· Rules & simulators · /rl-trading/rules/

9.2M hypotheses searched, 972 frozen rules tested once out-of-sample: 276 PASS / 105 WATCH / 591 FAIL; level/structure facts replicate, direction does not.

· Rules & simulators · /rl-trading/rules/ml-discovered/

38 trigger days (2022 – Oct 2026) with a >150-pt first-30-min move: 55% held ±150 at the close, 21% never re-crossed, 79% closed beyond the open in the same direction.

· Rules & simulators · /rl-trading/rules/opening-30m-move/

When Nifty moves >150 pts in the first 30 min (34 of 987 days), it held beyond 150 at the close only 50% of the time (up 8/16, down 9/18).

· Rules & simulators · /rl-trading/setups/nifty-first30-150/

Strategy backtests (setups) 14

Buying ATM CE/PE/straddle at 15:25 and selling at the next 09:15/09:16 loses every day after costs (CE −14.7, PE −5.4, straddle −20.1 pts/trade, 2024-08 to 2026-09); day-direction and last30 filters do not fix it; 0 of 1,440 variants pass both halves + random test — FAIL.

· Strategy backtests (setups) · /rl-trading/research/overnight-carry/

All 1,167 sessions 2022–2026: last-30-min direction has ~zero link to next-day gap/first hour (ρ −0.01); late sell-offs gap up more (73% vs 60%) but the bounce is gone by 09:20; 12 of 960 ATM option-buy variants positive after costs, none beat random — FAIL.

· Strategy backtests (setups) · /rl-trading/research/last30-carryover/

Hub for intraday rule backtests (ORB, gap fill/go, stop-hunt, power hour, regimes) with walk-forward OOS after costs; all OOS net-negative except one regime filter the page flags as not a tradable edge.

· Strategy backtests (setups) · /rl-trading/setups/

Buying ATM CE at day-low / PE at day-high retests lost money in all 8 variants; slow, decelerating approaches do predict holds (PASS as a predictor) but the option buys still lose.

· Strategy backtests (setups) · /rl-trading/setups/day-hilo-retest/

Same ATM S/R entries traded as a CE/PE buyer (SL10 scale-out): 476 OOS trades, 47.3% win rate, −715 option pts (≈ −₹51,400), PF 0.74.

· Strategy backtests (setups) · /rl-trading/setups/atm-daily-sr-optbuyer/

Option-buyer fills for the last available week (22–29 Sep 2026): 7 trades, net −11.78 option pts (−₹766).

· Strategy backtests (setups) · /rl-trading/setups/atm-daily-sr-optbuyer/last-week/

Prior-session ATM CE/PE prices mapped to spot support/resistance, bounce/reject entries with scale-out exits: 275 OOS trades, −2,830 net index pts, PF 0.34.

· Strategy backtests (setups) · /rl-trading/setups/atm-daily-sr/

The ATM daily S/R rules on real option charts for the last complete option week (22–29 Sep 2026): 7 trades with CE/PE markers.

· Strategy backtests (setups) · /rl-trading/setups/atm-daily-sr/last-week/

Same confluence entry with SL20 / 40%@1R / 30%@2R scale-out exits: 30 OOS trades, −364.8 net pts, PF 0.21 (t −3.29).

· Strategy backtests (setups) · /rl-trading/setups/confluence-v1-scaleout/

Trap + AMD fake-break + ATM option premium support (all required): 20 OOS trades, 25% win rate, −83.8 net pts, PF 0.69.

· Strategy backtests (setups) · /rl-trading/setups/confluence-v1/

AMD, retailer trap, breakout+retest, expiry ITM and hero-zero setups: all five are net-negative out-of-sample after costs (PF 0.18–0.59).

· Strategy backtests (setups) · /rl-trading/setups/price-action-v2/

Options detail for Price Action v2 (expiry ITM / hero-zero on 1m full-chain option data, adapted walk-forward folds).

· Strategy backtests (setups) · /rl-trading/setups/price-action-v2/summary_options.html

Spot-index detail for the Price Action v2 setups (Nifty 1m, yearly walk-forward folds, hard SL, trail-to-cost, min 1:2 R:R).

· Strategy backtests (setups) · /rl-trading/setups/price-action-v2/summary_spot.html

Overnight/swing and weekly option-premium setups with walk-forward OOS after costs; no result is statistically significant (best OOS p≈0.12, overnight) and the options sample is short.

· Strategy backtests (setups) · /rl-trading/setups/swing-options.html

Option pricing & mispricing 3

SVI smile fits the Nifty weekly chain best (1.00 pt RMSE; Bates, SABR, Heston behind); none of 11 smile/IV/OI/parity clues gave a buy-side edge after costs in the 2026 test.

· Option pricing & mispricing · /rl-trading/setups/option-pricing-outliers/

Do multi-day build-ups of option mispricing predict Nifty? Direction FAIL; next-day range PASS as a predictor but FAIL as a buy; breakout WATCH — mostly FAIL for an option buyer.

· Option pricing & mispricing · /rl-trading/setups/mismatch-accumulation/

Every-minute option prices vs SVI fair value: only 4,055 tradable mismatches (median 1.6 pts), clustered on expiry days and the first 30 min; buying "cheap" ones lost money after costs.

· Option pricing & mispricing · /rl-trading/setups/option-pricing-outliers/top-mismatches/

News & events 4

Component-level breakdown of 9 sessions (Upstox 1-min + NSE delivery/participant OI): rallies on 13/15/16-Oct were FII index-futures short covering (OI down, FII shorts −3k/−13k/−5k) with clients selling; 14/19/22/23-Oct sell days saw FIIs re-short; falls led by HDFCBANK/ICICIBANK/RELIANCE/BHARTIARTL on mostly below-normal delivery; Jio-IPO days hit mid/small caps far harder than Nifty. Descriptive, n=9.

· News & events · /rl-trading/research/flow-forensics-2026-10/

Bank results surprise vs next open (293 events, 2012–2026): the bank's own stock reacts (ρ 0.23) but the Bank Nifty gap does not (ρ 0.04); net-beat Saturday weekends median BN gap +0.26% (n=10, WATCH).

· News & events · /rl-trading/setups/bank-earnings-reaction/

Over 15 years, high-impact news days averaged a 1.47% absolute Nifty move vs 0.69% on quiet days, but direction correlation is weak (ρ −0.04): news tags track volatility, not direction.

· News & events · /rl-trading/setups/india-news-nifty-corr/

Day-by-day India/markets news calendar, Oct 2011 – Oct 2026 (5,485 days, 134 high-impact), with CSV/JSONL downloads keyed by IST date.

· News & events · /rl-trading/setups/india-daily-news/

Macro / factor models 1

How Nifty responds to sectors, oil, the Dow, rupee and rates (2012–2026): +0.29% open gap per 1% overnight Dow (R² 0.23); the Hang Seng open is the top feature; oil barely matters.

· Macro / factor models · /rl-trading/research/factor-regression/

RL / ML 9

First PPO reinforcement-learning run on Nifty (80k steps, CPU): −6.40% total return over 554 trades (42.8% win rate), vs buy-and-hold −11.69%. Research only.

· RL / ML · /rl-trading/

Plain-English explainer of the v2 RL trader: an agent looks at Nifty hourly, chooses flat/long/short plus its own stop and target, and learns by trial and error.

· RL / ML · /rl-trading/explainer.html

Google TimesFM 3.0 5-minute-ahead forecast of Nifty spot and ATM CE/PE, with a rolling backtest vs a persistence baseline.

· RL / ML · /ml/research/timesfm

Infers latent regimes / hidden participants from option-chain structure with walk-forward validation; run or load the latest report.

· RL / ML · /ml/research/strategic

PPO walk-forward on Nifty 5m (long/flat/short), scored on out-of-sample PnL vs buy-and-hold and MA baselines.

· RL / ML · /ml/research/rl

Smart Money Concepts detector on Nifty: order blocks, FVGs, BOS/CHoCH and liquidity pools, with forward returns after the first touch.

· RL / ML · /ml/research/smc

Google TabFM zero-shot tabular model vs HistGBM for direction and 1h-return prediction on walk-forward folds.

· RL / ML · /ml/research/tabfm

Trader-log analysis 3

Logged trades matched to real 1m Nifty/Sensex option bars: strike+premium match 29% (Nifty) / 35% (Sensex); logged win rate 78% vs 28.3% simulated on matched contracts.

· Trader-log analysis · /rl-trading/setups/trader-fill-match/

Rebuild at exact entry times (225 takes; holdout Jul–Sep 2026): no narrow take-filter survives the holdout with time-symmetric controls (holdout AUC 0.49–0.51).

· Trader-log analysis · /rl-trading/setups/trader-filter-mine-timed/

IF/THEN filters mined from the trade log, takes vs skipped similar setups (3,001 rows): logged takes +3.40 pts vs skipped +1.40; GB AUC 0.58 (modest). Superseded by the timed rebuild.

· Trader-log analysis · /rl-trading/setups/trader-filter-mine/

Platform apps & data tools 4

Entry point to ML training, live data fetching, the dataset browser and latent-regime research.

· Platform apps & data tools · /ml/

Run the ML pipeline: Qlib Alpha158 features + Greeks, LightGBM / MLP / LSTM training, backtest metrics and equity curves.

· Platform apps & data tools · /ml/dashboard

Browse, filter and export structured datasets: index bars, options chains and processed features.

· Platform apps & data tools · /ml/data-repo

Ask research questions answered by agents over PDFs, stock data, VectorPro backtests, news and web search.

· Platform apps & data tools · /

Uncategorized 8

callwall/scripts build_panel.py charts.py cwlib.py evaluate.py events.py fetch_today.py publish_callwall.py section.py select_rule.py stats.py trades.py back

· Uncategorized · /rl-trading/research/intraday-recoveries/callwall/scripts/

callwall/results data_gaps.csv events.csv events.log excursions.csv fixed_rule.json hit_stats.csv rule_breakdowns.csv rule_trades.csv rule_vs_bench.csv rule_worst_days.csv stats.log today_events.csv t

· Uncategorized · /rl-trading/research/intraday-recoveries/callwall/results/

Who bought / who sold — scripts ← back to report components.py (3 KB) fetch.py (2 KB) intraday.py (3 KB) options.py (3 KB) participants.py (1 KB) section.py (6 KB) up.py (1 KB)

· Uncategorized · /rl-trading/research/flow-forensics-2026-10/whoflow/scripts/

Who bought / who sold — results ← back to report components_2026-10-13_0915.csv (2 KB) components_2026-10-13_1428.csv (2 KB) components_2026-10-23_1336.csv (2 KB) components_report.txt (5 KB) fut_minu

· Uncategorized · /rl-trading/research/flow-forensics-2026-10/whoflow/results/

Buying at the lows — scripts ← back to report backup_s3_lows.py (1 KB) build_minute.py (2 KB) charts_lows.py (4 KB) fetch_fut.py (2 KB) fetch_fut2.py (2 KB) fetch_opts.py (2 KB) find_lows.py (1 KB) ma

· Uncategorized · /rl-trading/research/flow-forensics-2026-10/lows/scripts/

Buying at the lows — results ← back to report lows_list.csv (1 KB) lows_minute_windows.csv (165 KB) lows_stock_bounce.csv (73 KB) lows_summary.csv (44 KB) news_ignored_move_mismatch.csv (1 KB) p2_benc

· Uncategorized · /rl-trading/research/flow-forensics-2026-10/lows/results/

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