Data statis (sesuai desain)— Dihitung atas hasil backtest tetap — bukan real-time.

Deflated Sharpe Ratio — multiple testing correction

Crypto bisa jadi investasi aman + passive income — kalau kamu pakai platform legitimate (Bappebti-registered exchange) + strategi 9-tahun validated, bukan "bot Telegram 1% per hari". Realistic return: 10-35% annual + 4-7% DeFi yield untuk modal nganggur.

UPDATE (Meta Optimizer findings — 2026-05-12, v2 koreksi): Setelah exhaustive grid-search 210 kombinasi, ditemukan trade-off:

75R/25H = absolute return tertinggi (ROI 2.5× vs baseline 30/70) — pilih kalau prioritas compounding
30R/70H baseline = Sharpe lebih tinggi (1.29 vs 1.16) — pilih kalau prioritas risk-adjusted + tidur nyenyak
DD: 75R/25H punya max drawdown lebih dalam (~62% vs 37%) — bear market lebih brutal

Tidak ada "winner" tunggal — sesuaikan dengan toleransi risk kamu. Lihat detail Meta Optimizer →

ℹ️ Sharpe Basis di Halaman Ini: Sharpe 1.45 = full-sample pre-fee. Net-fee 9y = 1.29 (Master Dashboard). After DSR correction 210 trials = effective lower. Cross-file Sharpe akan beda karena basis beda. Untuk overview semua bases, lihat Master Dashboard footnote.

Bailey-Lopez de Prado 2014. Adjust Sharpe ratio untuk fact bahwa kita sudah test strategi/variant. Pure chance dengan N trials, expected MAX Sharpe = .
Real edge harus EXCEED nilai ini. DSR = probability strategi punya true SR > 0. DSR >= 0.95 = significant (p < 0.05).

Results table

Sharpe vs Expected Max Sharpe

Referensi Ilmiah:

Primary: Bailey, D., & López de Prado, M. (2014). "The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting, and Non-Normality." Journal of Portfolio Management, 40(5), 94-107. DOI: 10.3905/jpm.2014.40.5.094
Bailey, D., Borwein, J., López de Prado, M., & Zhu, Q. (2014). "Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance." Notices of the AMS, 61(5), 458-471.
Pardo, R. (1992). The Evaluation and Optimization of Trading Strategies. Wiley.

Past performance does not guarantee future results. Crypto is high-risk; size positions accordingly. Industry sources (Glassnode, CryptoQuant) flagged sebagai methodology praktisi, bukan peer-reviewed.

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Deflated Sharpe Ratio — multiple testing correction

UPDATE (Meta Optimizer findings — 2026-05-12, v2 koreksi): Setelah exhaustive grid-search 210 kombinasi, ditemukan trade-off:

75R/25H = absolute return tertinggi (ROI 2.5× vs baseline 30/70) — pilih kalau prioritas compounding
30R/70H baseline = Sharpe lebih tinggi (1.29 vs 1.16) — pilih kalau prioritas risk-adjusted + tidur nyenyak
DD: 75R/25H punya max drawdown lebih dalam (~62% vs 37%) — bear market lebih brutal

Tidak ada "winner" tunggal — sesuaikan dengan toleransi risk kamu. Lihat detail Meta Optimizer →

Sharpe vs Expected Max Sharpe

Referensi Ilmiah:

Primary: Bailey, D., & López de Prado, M. (2014). "The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting, and Non-Normality." Journal of Portfolio Management, 40(5), 94-107. DOI: 10.3905/jpm.2014.40.5.094
Bailey, D., Borwein, J., López de Prado, M., & Zhu, Q. (2014). "Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance." Notices of the AMS, 61(5), 458-471.
Pardo, R. (1992). The Evaluation and Optimization of Trading Strategies. Wiley.

Deflated Sharpe Ratio — multiple testing correction

Results table

Sharpe vs Expected Max Sharpe

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Deflated Sharpe Ratio — multiple testing correction

Results table

Sharpe vs Expected Max Sharpe

Mau Lebih?

Masuk dulu buat buka tool ini