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qis - performance analytics, backtesting, and factsheet reporting

qis - performance analytics, backtesting, and factsheet reporting

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Installation
Offline quickstart
Factsheet gallery

Part I - Foundations

Notation and conventions
Returns, NAVs, excess returns, fees and leverage
Reporting frequency and annualisation
Incomplete and mixed-frequency data

Part II - Performance measurement

The performance-statistic catalogue
Sharpe ratios: conventions and inference
Drawdowns and time under water
Alpha, beta and benchmark-relative performance
Regime-conditional performance
The convexity premium and smart diversification

Part III - Estimation

Exponentially weighted estimators
Covariance, correlation and principal components
Serial dependence and autocorrelation
Regression and HAC inference
Resampling and the bootstrap
Private-asset unsmoothing

Part IV - Portfolios

Portfolio backtesting
Turnover conventions
Risk-adjusted returns and volatility targeting
Signal diagnostics: information coefficient and information ratio

Part V - Risk

Portfolio risk and Euler contributions
Factor risk models
Tracking error and risk
Portfolio breadth
Factor stress testing
- Factor stress testing
Instrument portfolios and stress reports
- Instrument portfolio valuation and stress reports
Stress testing with options
FX hedging and market data

Part VI - Attribution

Brinson attribution
Model-layer attribution

Reporting guides

Factsheets and reporting
Factsheet reference

Reference

API reference
Bibliography
Software design
Package comparison
API migration history
Documentation standard
Sharpe convention summary
Reporting-frequency reference
Shared plotting arguments

qis.SignalAggType¶

class qis.SignalAggType(*values)[source]¶

Bases: Enum

__init__(*args, **kwds)¶

Attributes

`LAST_VALUE`
`MEAN`

LAST_VALUE = 1¶

MEAN = 2¶

qis.SignalDiagnosticsColumns

qis.SharpeConvention

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qis.SignalAggType
- SignalAggType