Was the observed Sharpe above a benchmark?
Probabilistic Sharpe Ratio adjusts for sample length, skew and non-excess kurtosis. The zero-benchmark result does not know how many alternatives were tried.
Open research instrumentDeflated Sharpe calculatorContract v1.0.0
Deflated Sharpe ratio calculator (PSR and DSR)
How much of your Sharpe ratio survives after you count the full search?
How this tool works
This is a Probabilistic Sharpe ratio calculator that also reports its Deflated form. How much Sharpe survives the search? A strong backtest is less surprising after a long search. Put the observed Sharpe, return shape and complete selection process on the same surface. The calculator reproduces ALPHAC's per-period PSR and DSR formulas in your browser. Canli Capital, the research house that publishes ALPHAC, runs this calculator free, with no account or key required.
Published preset and source boundary
The current-union preset supplies only trial count and dispersion. The observed Sharpe, sample length, skew and kurtosis are illustrative until you replace them. No output on this page is an ALPHAC performance claim or an admission verdict.
Selection pressure chamber
How many trials did you run?
One result. The whole search behind it.
Book-maturity referenceBelow 0.95
Deflated Sharpe ratio
0.250
The supplied inputs do not clear the full-union book-maturity reference.
Observed1.50
Best by luck1.99
-0.7Annualized Sharpe2.7
- PSR against zero
- 98.09%
- Sampling uncertainty only
- Best-by-luck benchmark
- 1.988
- Annualized for display
- Search haircut
- -0.488
- Observed minus benchmark
- Non-normality term
- 1.0454
- Must remain positive
Read the result
What is a deflated Sharpe ratio?
PSR asks about the sample. DSR asks about the search.
What would the best null trial look like?
The expected maximum rises with the number of effectively independent trials and their cross-trial Sharpe dispersion.
Did the result clear the search-adjusted benchmark?
DSR is PSR evaluated against SR*. It is one diagnostic inside a larger research contract, never proof that a strategy is deployable.
Implemented formula
Phi(((SR - SR*) * sqrt(T - 1)) / sqrt(1 - skew*SR + ((kurtosis - 1)/4)*SR^2))
sqrt(V[SR]) * ((1-gamma)*PPF(1-1/N) + gamma*PPF(1-1/(N*e)))
sr_per_period = sr_annualized / sqrt(periods_per_year). variance_per_period = (sd_annualized / sqrt(periods_per_year))^2.
Current ALPHAC policy
A probability is not a promotion decision.
Under canli.alphac-sleeve-admission-contract.v7, per-sleeve DSR is mandatory to measure and publish, but it is not a universal sleeve gate. Incremental admission is not decided by DSR alone.
The 0.95 reference applies to a full-union portfolio-maturity claim. Clearing it inside this calculator does not clear robustness, execution, stress, capacity, bootstrap-improvement or trial-accounting requirements.
Read the complete policy contextReproduce and inspect
The interface is downstream of the evidence.
Formula contract4f0043376bff896f...Golden vectors and policy boundary
Trial union5b48a944779c63af...Current N and identity-aligned V[SR]
Python implementationac2f18440e21b824...Production arithmetic in ALPHAC
Primary paperBailey and López de PradoJournal of Portfolio Management 40(5), 94-107 (2014)
This contract reproduces ALPHAC's PSR and DSR arithmetic for supplied inputs. It does not validate a strategy, prove profitability, estimate current portfolio performance, or replace the complete admission contract.
A deflated Sharpe asks whether one result survives the search that produced it. The probability of backtest overfitting calculator asks the sharper question of whether the in-sample winner predicts anything out of sample. Run the same arithmetic against your own numbers through the validation API.