H-028: Um modelo diário estima a chance de um movimento maior que o normal melhor que a frequência base
Passou Tipo: previsão · Status: aprovada
Esta hipótese passou no teste pré-registrado. Isso é motivo para confirmação independente e trading simulado, não para operar com dinheiro real.
Um modelo diário consegue prever grandes movimentos cripto? A ideia atingiu a meta definida antes do teste. Merece uma verificação independente. Não é promessa de lucro.
Resultado
pooled Brier skill +0.0383 (p = 0.000, need p < 0.025); skill above zero on 13/13 coins
| Ativo | Dias | Brier skill | p-valor | q (FDR) | Acertos |
|---|---|---|---|---|---|
| BTC | 1760 | +0.0172 | 0.001 | 0.001 | 56.3% |
| ETH | 1760 | +0.0282 | 0.001 | 0.001 | 56.4% |
| SOL | 1760 | +0.0246 | 0.001 | 0.001 | 57.3% |
| BNB | 1760 | +0.0300 | 0.001 | 0.001 | 58.1% |
| XRP | 1760 | +0.0406 | 0.001 | 0.001 | 57.5% |
| ADA | 1760 | +0.0439 | 0.001 | 0.001 | 57.6% |
| LTC | 1760 | +0.0152 | 0.001 | 0.001 | 56.4% |
| LINK | 1760 | +0.0372 | 0.001 | 0.001 | 57.8% |
| DOGE | 1760 | +0.0542 | 0.001 | 0.001 | 57.4% |
| XLM | 1760 | +0.0564 | 0.001 | 0.001 | 59.0% |
| TRX | 1760 | +0.0364 | 0.001 | 0.001 | 59.5% |
| EVER | 1306 | +0.0715 | 0.001 | 0.001 | 58.7% |
| GRAM | 946 | +0.0600 | 0.001 | 0.001 | 57.7% |
| ∑ | 21612 | +0.0383 | 0.001 | — | 57.7% |
Calibração: previsão contra o que aconteceu
| Previsão | Previsão ⌀ | Aconteceu | Dias |
|---|---|---|---|
| 10%–20% | 18.6% | 44.4% | 9 |
| 20%–30% | 27.1% | 33.3% | 615 |
| 30%–40% | 36.1% | 38.1% | 4426 |
| 40%–50% | 45.1% | 43.8% | 8013 |
| 50%–60% | 54.4% | 51.8% | 5819 |
| 60%–70% | 64.0% | 62.2% | 2079 |
| 70%–80% | 73.9% | 73.9% | 547 |
| 80%–90% | 83.6% | 83.8% | 99 |
| 90%–100% | 92.8% | 80.0% | 5 |
Por que poderia funcionar
Same model and inputs as H-027, different question: the probability that the next day's absolute log move is larger than the coin's median absolute daily move over the past 365 days (measured up to D, so the base rate is near one half). Price direction is close to unpredictable, but the size of moves clusters in calm and nervous stretches, so this is where a model can show real skill; it would help size positions and avoid big losses, not make money by itself. One logistic regression shared by all 13 coins. Inputs at the close of day D: log returns over 1, 3, 7 and 30 days, distance from the 50- and 200-day averages, 7- and 30-day volatility, Bitcoin's 1- and 7-day returns, and, lagged one day for publication delay, BTC funding (7-day mean), Fear & Greed, 30-day USDT+USDC supply growth and 7-day BTC net exchange flow. Every input is a rolling 365-day z-score of its own past (min. 180 days, clipped at ±5), so coins with very different volatility share one model. The model is refitted on the first day of every month on decisions whose outcome was already known (up to two days before), L2 = 1. Costs: 0.1 % per side on Binance, 0.4 % per side on Gate.io coins (0.2 % fee + 0.2 % slippage). Passes on the same pooled Brier-skill test from 2022 on; the circular shift is conservative here, because rotated forecasts still overlap long volatility regimes. Shares alpha with H-027 (0.05 / 2).
Histórico de veredictos
- 2026-10-28: Passou (este motor, dados até 2026-10-26)
Especificação pré-registrada
kind: forecast
target: risk
model:
type: pooled_logit
features:
- r1
- r3
- r7
- r30
- d50
- d200
- v7
- v30
- btc_r1
- btc_r7
- funding
- fear_greed
- stable30
- flow7
zscore_window: 365
zscore_min_periods: 180
clip: 5
l2: 1.0
refit: monthly
external_lag: 1
ffill_limit: 3
universe:
- BTCUSDT
- ETHUSDT
- SOLUSDT
- BNBUSDT
- XRPUSDT
- ADAUSDT
- LTCUSDT
- LINKUSDT
- DOGEUSDT
- XLMUSDT
- TRXUSDT
- EVERUSDT
- GRAMUSDT
costs:
default: 0.001
EVERUSDT: 0.004
GRAMUSDT: 0.004
periods:
- name: oos
start: '2022-01-01'
significance:
method: circular_shift
n: 2000
alpha: 0.025
criterion:
metric: brier_skill
pooled: true