4 years of a 15x-leveraged daily BTC signal — Sharpe 2.2, MDD -13%. Here's the stuff that actually kept leverage from killing me.

Long-time lurker. Posting because I keep seeing "15x leverage" treated like an inherent death sentence here, and I think that framing misses the actual issue. The problem isn't leverage — it's running leverage over a signal that can't handle it. I built a daily long/short/flat model on BTC perp about 4 years ago. Backtest window is Aug 2021 → present (\~1,500 trading days). Base signal Sharpe \~2.2. I run it at 15x. Full 15x results from the backtest: * Total return: \~+374% * CAGR: \~45% * Sharpe: 2.26 (leverage-invariant, same as 1x) * MDD: -13.3% * Worst single day: -4.7% * Best single day: +7.7% * Days with |return| > 10%: 0 BTC buy-and-hold over the same window was +96% with -76% MDD. So the leveraged signal returned \~4x BTC hold, at roughly 1/6th the max drawdown. I know how this looks. If I saw these numbers without context I'd call BS too. So here's what I actually did, and more importantly what I tested to convince myself it wasn't fit-to-backtest noise. **What I did that I think actually mattered:** 1. **Picked the leverage from the MDD distribution, not from net Sharpe.** I looked at rolling 90-day MDD percentiles at 1x, then picked a leverage level where 99th-percentile drawdown stayed inside my pain threshold. 15x was where that line landed. I did NOT pick "leverage that maximizes final equity" — that way lies gambling. 2. **±20% parameter perturbation on everything.** ±5% sensitivity tests pass almost any overfit strategy. Anything that dies at ±20% is either underspecified or fit. I killed 3 candidate signal versions with this test alone. 3. **Funding as actual historical payments, not theoretical cost of carry.** Single biggest thing people underestimate for crypto perps. An early version of my strategy looked amazing until I subtracted real 8h funding — it was partly just being short overheated perps during the 2021 blowoff. 4. **Short train / long test walk-forward.** Standard 12/3 splits let signals accumulate too much regime memory. I used 6/1 rolling. If the model needs >6 months of memory in a market that shifts regime every 3–6 months, it's fitting noise. 5. **Signal-level ablation, not outcome-level ablation.** I tested what happens if each individual input to the signal is replaced with random noise. If the Sharpe drops by <10% when an input is randomized, that input doesn't matter and I remove it. Forces the signal to only keep inputs that are actually doing work. **What I deliberately did NOT do (despite common advice here):** * No Monte Carlo bootstrap on trade returns. Daily directional on a single asset has enormous serial correlation. Bootstrapping trade returns destroys that structure and gives you confidence intervals that are almost meaningless. People quote this test constantly and it's mostly theater at this scale. * No rebalance-frequency optimization via grid search. Cadence came from signal half-life analysis (\~5 days). Grid-searching it would have "found" weekly on the backtest window and I'd have no defense for it being stable forward. * No ensembling. One signal, one sizing rule. If I can't defend each input, I can't hide it inside an ensemble. **The leverage-specific things that actually scared me:** * Funding cost compounds violently at 15x. On days where funding is 0.1% per 8h against me, that's \~4.5% annual drag at 1x — at 15x it becomes a 67%/yr drag. You can't carry a leveraged position through extended funding regimes * without the strategy being short-biased to harvest it. * Execution and slippage at 15x size. Live execution is maker (limit) at \~2bps per side, but backtest models 4bps conservatively so I'm not flattering the numbers. Slippage at 5bps per side is probably optimistic at scale. Size * assumptions that are fine at 1x can be completely wrong at 15x if the strategy ends up concentrated on one coin. Single-asset avoids this but it's worth naming. * Exchange risk. A 15x position that would survive the backtest MDD of -13% would NOT survive a 30-minute exchange outage during a fast move. This is not a backtestable risk. It's the single biggest thing I can't defend against, and I accept it as a cost of running this at all. **Stuff I still don't trust about the result:** * Live sample is short compared to the backtest. I have a real holdout running but nothing close to a 4-year live record. * The window I backtested includes two bull runs and one bear. Not enough distinct regimes to claim the signal is truly general. * Single-asset strategies on BTC specifically benefit from BTC's narrative dominance in crypto. If alt-correlation patterns shift, the signal could weaken in ways the backtest can't show me. **Questions I'd actually appreciate discussion on:** 1. For those running leveraged directional on single assets live — how do you size against non-backtestable risks (exchange outage, fast tail moves)? "Reduce leverage" is an answer but not a satisfying one. 2. Anyone doing signal-level noise ablation routinely? I keep thinking it should be more standard than it is. Maybe I'm missing a reason people don't do it. 3. For crypto perps specifically — what's your personal bar on live sample size before you'd call a 4-year backtest "real"? I'm using 12 months live. Curious if that's reasonable or naive. Not selling anything. Posting because I've gotten a lot from this sub and wanted to contribute something real. Happy to go deep on any single piece in comments.