Event study: what would directional BTC trading after the 9 biggest Trump posts of 2025 have yielded? Entry 5 min after the post, trailing stop 1-3%, max hold 6h. Simulation on real Binance 1m data. Result: +19.5% total P&L (9 trades, 89% win rate with a 1.5% trail). But with an important selection-bias disclaimer.

How Trump posts on Twitter and Truth Social move BTC and the S&P 500 — from seconds to weeks afterwards. Synthesis of 5+ academic studies and concrete event data from 2024–2025.

10 algorithmic BTC strategies from academic papers, institutional studies and open-source projects - with verified performance data, evidence quality and concrete Botty recommendations.

The third structural edge of the dead-end initiative (after funding-carry live + VRP harvest infra-gated): every week go long the relative winners (top tercile) and short the losers (bottom tercile), dollar-neutral across 20 HL coins. Market-neutral (BTC beta ~0) - we do NOT forecast direction, we bet on relative strength (the momentum anomaly). Tamed with inverse-vol + vol-targeting + crash filter (sit out bear-market rebounds). It PASSED the cross-universe gate that killed donchian (generalizes across disjoint coin sets), PBO 0.27 solid, walk-forward time-stable; Deflated Sharpe 0.71->0.93 with crash filter (just under 0.95 = real but borderline). Backtest ~+42%/yr filtered, honest expectation ~15-25%/yr market-neutral. Runs as a monitor in the bot, armed after wallet top-up. With principle visualizations.

Does the funding-carry idea (collect a structural premium directionlessly) also work with options? Yes: the direct analog is the VRP harvest - selling vol + delta-hedging collects the variance risk premium (implied vol sits systematically above realized, like an insurance premium). Measured on 5y of DVOL+BTC data across four scouts (without a single options trade): the premium is real & large (Sharpe 0.89, but tail -74), unhedged it collapses (0.26), delta-hedging rescues it (Sharpe 1.5-1.9, tail -4%), and it survives the intraday gap stress test at 4h hedging (Sharpe 1.4, tail -5.5%, robust). The first structural edge after funding to pass the realism gate - but infra-gated (no Deribit trading client, HL without native options). A build decision, not a research kill. The article explains options from the ground up in plain language, with principle visualizations.

Scalping sounds tempting (many small wins add up), but it splits into two variants with two different causes of death. TAKER scalping (taking with market orders) dies at the fee floor - measured in `liquidation_mr_scout`: 56% hit rate, yet net -7 to -10bps in 0/7 years. MAKER market-making (providing liquidity, earning spread + rebate) is the only structurally conceivable way out - but it dies at the ADVERSE-SELECTION floor: measured in the new `spread_capture_scout.py` (BTC/ETH/SOL, 6+ years) it is deeply negative everywhere at the HL base maker fee, positive in 0/7 years, and even with a rebate only crosses zero marginally and unstably. Graveyard. The structurally clean 'scalping cousin' we DO have is the delta-neutral [[funding_carry_botty]] (live on Wallet 3).

Botty's own investigation of delta-neutral funding carry (long spot + short perp, directionless): the first approach to cleanly pass the cross-asset gate. In plain language with examples — plus the two lessons that only emerged while building: (1) a live funding snapshot ≠ realized return (HYPE wins persistently, ZEC's 40% was a spike), (2) delta-neutral for the majors is inherently cross-venue on HL because HL spot is illiquid for BTC/ETH. Theory [[funding_rate_arbitrage]], context [[frische_ansaetze_2026]].

Diagnosis + therapy for Botty's core problem: for months we have been mining time-series prediction of a single, highly efficient asset (BTC direction) - the mathematically hardest quant problem there is, which is why [[walk_forward]] & [[pbo]] correctly shoot down almost every edge as overfit ([[divergences]], donchian curve-fit). The way out is not to 'search harder' but to switch the AXIS. Four concrete bets, testable in the backtest infra: funding carry, cross-sectional relative value, vol-targeting overlay, options/positioning signals. In plain language with examples.

A survey of every sizing family (Fixed Fractional, Risk Units, Kelly, Vol Targeting, Throttles, Pyramiding, Scaling-Out) with academic evidence, the Turtle rules in detail, and the sizing practice of our 20 analyzed traders. Key findings: Vol Targeting adds little on the return side (verified) but provides tail protection; Pyramiding raises the EV of trend following but costs Sharpe; the workable range for us is 1/4-1/2 Kelly ~ 1.75-3.5x exposure.

The positive counterpart to [[what_doesnt_work]], but drawn from Botty's OWN data: a consolidated ranking of what has demonstrably and reliably worked across 22+ megasweeps, 45 ML experiments, the Indicator Lab, and shuffle tests. The bar: walk-forward across multiple windows, a shuffle test, or PBO — no in-sample winners. Core picture: reliable performance comes almost exclusively from the RISK side (vol forecasting IC +0.74…+0.84, BOCPD, VRP, vol targeting) plus structural discipline (regime gates as the edge carriers, timeframes 30m–1d, adaptive exits). On the directional side there is exactly ONE narrow, validated candidate: the Donchian@4h family (gated, ATR trailing + partial TP, PBO 0.164). ema@1d was downgraded on 06/11 after a failed reproduction sweep (PBO 0.77); outside_inside_day@4h does have a genuine signal edge but failed as a strategy in the validation sweep (edge ~+0.3%/year — significant but too small) (the only significant raw signal in the Indicator Lab). Plus: the validation methodology itself is the most important 'edge' — it has repeatedly exposed convincing fakes before money was riding on them.

A consolidated Botty learning synthesis from the simultaneous deep analysis of 5 YouTube quant traders/educators (audio transcripts + frame analysis, with coverage varying due to throttling). Common thread: three independent experts (Kevin Davey, Algovibes, QuantPy) confirm exactly Botty's validation architecture (walk-forward + Monte Carlo + PBO + EV CI). The strongest NEW building blocks: Davey's incubation gate (which Botty lacks entirely), Unbiased's funding carry on perps (a market-neutral return driver that Botty's 3 directional strategies do not cover), volatility-targeting sizing, and TheStopHunter's live-ops hardening checklist.

Evaluation of all 22 archived megasweeps by their PBO values. Only 4 sweeps are trustworthy (PBO < 0.20); the meta-pattern: the robust edge lies in the trend/regime gate, not the entry. ATTENTION UPDATE (2026-06-08): the clean counter-check sweep MS_20260606_162121 (min_trades=30, training 2024+2025, held-out crash) has LARGELY DEBUNKED the archetype-optimism thesis (aggregate PBO 0.77): A (sfp) and B (bb_extreme) are 'one-window wonders', regime_switch collapses in the cross-window test. Single-window sweeps feigned robustness. See the update chapter.

Botty currently determines the regime with Wilder's ADX(14)+DMI (trend vs. range). This article places that in the full landscape: first the clean separation of the two different "regimes" (structural = trend/range vs. volatility = calm/turbulent), then the alternative detectors (Hurst, variance-ratio test, Efficiency Ratio/KAMA, Choppiness Index, regression R^2, return autocorrelation), the probabilistic models (HMM, Markov switching, k-means/GMM, changepoint via BOCPD/PELT/CUSUM, GARCH for vol) and external context signals (funding, term structure, DXY, implied vol/DVOL). Core insight from Botty's OWN walk-forward experiments: the volatility regime is predictable (BOCPD promoted, HMM IC +0.39, vol forecast IC +0.83), the directional regime practically not (vol_regime_transitions DEAD, clustering inconclusive). "Predicting" realistically means: vol regime + changepoint probability - not the next trend direction. UPDATE 2026-06-10: the research became code - the answer to "how to use it?" is FILTER, not switch (regime_switch empirically refuted: -392 bps). New: regime_ensemble_filter, a real 2-of-3 majority vote over ADX+ER+Choppiness, plus the ready-to-run mega-sweep bake-off (regime_gate_bakeoff_v1) that compares ADX vs. ER vs. CHOP vs. ensemble on identical trades.

A consolidated, evidence-based list of the things that, per the quant research of Thomas Skinner (Delta Trend Trading), do not work - and the mechanistic reason behind each. Drawn from 11 long-form videos + 22 shorts, many backed by programmatic backtests over thousands of trades. Matches Botty's own live_readiness pipeline and ml philosophy 1:1. Goal: a yardstick to sort out your own ideas early, before capital flows.

Classic trader folklore says: when price makes a new high but RSI/volume do not follow, the market will soon reverse. We tested all 8 divergence variants (regular/hidden x bull/bear x RSI/volume) four times walk-forward over 6+ years of BTC data - with small pivots, large pivots + rolling volume, 6 timeframes (5m to 1D) x 4 confirmation delays x literature-calibrated horizons, and finally Wilder's structure-triggered failure-swing variant (RSI structure break instead of bar delay). Total tests: 2200 cells. Result: not a single pattern has statistically robust predictive power, whether the confirmation is time- or structure-triggered. Divergences are dead as a standalone entry filter on BTC.

A backtest shows ONE path of history - Monte Carlo shows the cloud of all plausible alternatives and thereby separates substance from luck. This article explains the method from its Manhattan-Project origin through the mathematics (1/sqrt(N) convergence, GBM, Ito) to the three trading families: simulating price paths (GBM, calibrated on real BTC data), resampling trade sequences (reshuffle vs bootstrap -> drawdown distribution & risk of ruin) and permutation tests against overfitting. With three original charts, the i.i.d. stumbling block (block bootstrap as the solution) and an honest inventory of what Botty already does (bootstrap CIs, permutation tests, walk-forward) and where the gap is (no trade-sequence MC and no risk-of-ruin sizing on the live strategies).