CHANGELOG.md

Changelog

0.0.81

Bugfixes for 0.0.78 release

• Fixed circular import errors that broke import quantstats (#499, #501)

• Fixed NameError: name 'dd_get_stats' is not defined in reports.full() (#502)

• Fixed reports.html() to work without specifying output file (opens in browser)

• Fixed profit_ratio() to handle DataFrame inputs properly

• Removed dark mode CSS from HTML report template

• Suppressed pandas FutureWarning for callable resampler.apply()

• Improved HTML report header:

  • Title shows "(Compounded)" only when compounded=True
  • Date range shows "(matched dates)" only when match_dates=True with benchmark
  • Parameters now always show Benchmark, Periods/Year, and RF rate

• Added new metrics to full HTML report:

  • Ulcer Performance Index, Risk-Adjusted Return, Risk-Return Ratio
  • Avg. Return, Avg. Win, Avg. Loss, Win/Loss Ratio, Profit Ratio

• Added terminal output parameters table for reports.full() and reports.basic()

• Added comprehensive test suite (125 tests):

  • Tests for stats, reports, utils, plots, compat, extend_pandas, and Monte Carlo

0.0.78

2026 Modernization Update

• Added comprehensive type hints to stats.py functions:

  • All major public functions now have full type annotations
  • Uses Python 3.10+ union syntax (X | Y instead of Union[X, Y])
  • Added Returns type alias for pd.Series | pd.DataFrame
  • Functions typed include: ghpr(), outliers(), remove_outliers(), best(), worst(), consecutive_wins(), consecutive_losses(), exposure(), win_rate(), avg_return(), avg_win(), avg_loss(), rolling_volatility(), implied_volatility(), autocorr_penalty(), smart_sharpe(), rolling_sharpe(), smart_sortino(), rolling_sortino(), adjusted_sortino(), probabilistic_ratio(), probabilistic_sharpe_ratio(), and more

• Simplified compatibility layers for Python 3.10+/pandas 2.0+/numpy 1.24+:

  • _compat.py: Removed obsolete pandas < 1.0.0 and < 1.4.0 version checks
  • _numpy_compat.py: Removed obsolete numpy < 1.17.0, < 1.21.0, and < 1.22.0 version checks
  • Cleaner, more maintainable codebase for modern dependency versions

0.0.77

• Fixed issue #467 - CVaR calculation returning NaN for DataFrame inputs:

  • The conditional_value_at_risk() function now properly handles DataFrame inputs
  • When filtering DataFrames, NaN values are now correctly removed before calculating the mean
  • CVaR calculations are now consistent between Series and DataFrame inputs
  • This fix ensures accurate risk metrics in HTML reports when using benchmarks

• Confirmed issue #468 is already resolved:

  • The "mode.use_inf_as_null" pandas option error reported in v0.0.64 no longer occurs
  • This issue was resolved in a previous version through updates to pandas compatibility

0.0.76

• Fixed issue #457 - Inconsistent benchmark EOY returns in reports:

  • Benchmark yearly returns now remain consistent regardless of strategy's trading calendar
  • HTML reports preserve original benchmark data for accurate EOY calculations
  • Previously, benchmark returns would change when aligned to different strategies' trading days
  • Added comprehensive tests to verify benchmark consistency across different comparisons

• Improved timezone handling for cross-market comparisons:

  • All resampling operations now normalize timezones to prevent comparison errors
  • Mixed timezone-aware and timezone-naive data can now be compared without errors
  • Data is converted to UTC then made timezone-naive for consistent comparisons
  • Fixes "Cannot compare dtypes datetime64[ns] and datetime64[ns, UTC]" errors

• Fixed FutureWarning for pandas pct_change():

  • Updated all pct_change() calls to use fill_method=None parameter
  • Prevents "fill_method='pad' is deprecated" warnings in pandas 2.x
  • Ensures compatibility with future pandas versions

0.0.75

• Fixed FutureWarning for deprecated pandas frequency aliases:
  • Updated make_index default rebalance parameter from "1M" to "1ME"
  • Ensures compatibility with pandas 2.2.0+ without warnings
  • The _compat module already handles conversion for older pandas versions

0.0.74

• Completed fix for issue #463 - DataFrame handling in qs.reports functions:
  • kelly_criterion: Fixed improper use of 'or' operator with Series values
    • Now properly detects Series vs scalar inputs
    • Handles zero and NaN values correctly for DataFrames
  • recovery_factor: Added proper DataFrame input handling
    • Detects when max_dd is a Series and handles accordingly
    • Prevents "truth value of Series is ambiguous" errors
  • All functions now tested with qs.reports.html() and qs.reports.metrics() with benchmarks
  • Verified working with exact code examples from issue reporters

0.0.73

• Fixed payoff_ratio to handle DataFrame inputs properly (fixes issue #463)
  • When using qs.reports.html with a benchmark, payoff_ratio receives a DataFrame
  • Previously caused "ValueError: truth value of Series is ambiguous"
  • Now properly handles both Series and scalar avg_loss values
  • Returns Series for DataFrame inputs, scalar for Series inputs

0.0.72

• Fixed ValueError "truth value of Series is ambiguous" for DataFrame inputs in multiple stats functions:
  • sortino: Properly handles Series downside deviation from DataFrame inputs
  • outlier_win_ratio: Handles Series positive_mean calculations correctly
  • outlier_loss_ratio: Handles Series negative_mean calculations correctly
  • risk_return_ratio: Handles Series standard deviation properly
  • ulcer_performance_index: Handles Series ulcer index values
  • serenity_index: Handles Series std and denominator calculations
  • gain_to_pain_ratio: Handles Series downside calculations
  • All functions now properly return Series for DataFrame inputs and scalars for Series inputs

0.0.71

• Fixed RuntimeWarnings in tail_ratio function by properly handling edge cases:

  • Handle divide by zero when lower quantile is 0
  • Handle invalid values when quantiles return NaN
  • Handle DataFrame inputs that return Series from quantile operations
  • Return NaN gracefully instead of triggering warnings

• Added comprehensive divide by zero protection across multiple stats functions:

  • gain_to_pain_ratio: Returns NaN when no negative returns (downside = 0)
  • recovery_factor: Returns NaN when no drawdown (max_dd = 0)
  • sortino: Returns NaN when downside deviation is 0
  • calmar: Returns NaN when max drawdown is 0
  • ulcer_performance_index: Returns NaN when ulcer index is 0
  • serenity_index: Returns NaN when std or denominator is 0
  • payoff_ratio: Returns NaN when average loss is 0
  • outlier_win_ratio: Returns NaN when no positive returns
  • outlier_loss_ratio: Returns NaN when no negative returns
  • risk_return_ratio: Returns NaN when standard deviation is 0
  • kelly_criterion: Returns NaN when win/loss ratio is 0 or NaN
  • greeks: Returns NaN for beta when benchmark variance is 0
  • rolling_greeks: Handles zero benchmark std gracefully
  • All functions now return NaN instead of triggering RuntimeWarnings

0.0.70

• Fixed chart naming inconsistency: renamed "Daily Active Returns" to "Daily Active Returns (Cumulative Sum)" and "Daily Returns" to "Daily Returns (Cumulative Sum)" to accurately reflect that charts show cumulative values (fixes issue #454)
• Fixed CAGR calculation bug where years were incorrectly calculated using calendar days instead of trading periods, causing drastically reduced CAGR values (fixes issue #458)
• Fixed inconsistent EOY returns for benchmarks by preserving original benchmark data for aggregation while aligning to strategy index for other calculations (fixes issue #457)

0.0.69

• Added periods parameter to calmar() function to support custom annualization periods (fixes issue #455)
• Updated reports.py to pass periods parameter to Calmar ratio calculation for consistency with other metrics

0.0.68

• Fixed ValueError when comparing Series with scalar in _get_baseline_value() function (fixes issue #448)
• Properly handle both DataFrame and Series inputs in drawdown calculations

0.0.67

• Added support for NumPy 2.0.0+ (fixes issue #445)

0.0.66

• Fixed bug with calculating drawdowns when first return is < 0

0.0.65

• Misc bug fixes

0.0.64

MAJOR RELEASE - Comprehensive Compatibility and Performance Improvements

🔧 Major Fixes:

• Fixed pandas resampling compatibility issues (UnsupportedFunctionCall errors)
• Added yfinance proxy configuration compatibility layer for all versions
• Implemented comprehensive pandas compatibility layer with frequency alias mapping (M→ME, Q→QE, A→YE)
• Fixed all pandas FutureWarnings related to chained assignment operations
• Added numpy compatibility layer for deprecated functions (np.product → np.prod)
• Replaced broad exception handling with specific exception types throughout codebase

📈 Performance Improvements:

• Implemented LRU caching for _prepare_returns function (10-100x faster for repeated operations)
• Optimized autocorrelation calculations with vectorized numpy operations
• Improved rolling Sortino calculation performance and memory usage
• Optimized multi_shift memory usage with incremental concatenation
• Eliminated redundant dropna operations with intelligent caching
• Replaced inefficient iterrows usage with vectorized operations

🛡️ Reliability Improvements:

• Added comprehensive input validation to public functions
• Implemented safe_resample compatibility function for all pandas versions
• Created robust error handling with custom exception classes
• Added safe_yfinance_download function handling proxy configuration changes
• Fixed matplotlib/seaborn compatibility issues and deprecation warnings

🎨 Visualization Fixes:

• Updated seaborn compatibility (sns.set() → sns.set_theme())
• Fixed legend handling in plotting functions
• Improved chart rendering with better error handling
• Fixed monthly heatmap display issues

📊 Technical Improvements:

• Created comprehensive compatibility layer in _compat.py module
• Implemented frequency alias mapping for pandas version compatibility
• Added version detection and handling for pandas/numpy changes
• Enhanced data preparation pipeline with caching and validation

🚀 Overall Impact:

• 10-100x performance improvement for large datasets
• 5-10x memory usage reduction
• Eliminated all pandas/numpy compatibility warnings
• Future-proofed against dependency updates
• Maintained full backward compatibility

This release addresses 23+ community-reported issues and PRs, making QuantStats significantly faster, more reliable, and compatible with modern pandas/numpy versions.

0.0.63

• Misc pd/np compatibility stuff

0.0.62

• Changed serenity_index and recovery_factor to use simple sum instead of compounded sum
• Reports passing the compounded param to all supporting methods
• Fixed a bug related to monthly_heatmap display

0.0.61

• Fixed positional arguments passed to cagr()

0.0.60

• Multi-strategy reports! You can now pass a dataframe with a column for each strategy to get a unified, single report for all
• Support request proxy with yfinance
• Added custom periods to CAGR
• Correct drawdown days calculation when last day is a drawdown
• Write report in correct file path
• IPython 7+ compatibility
• Pandas 2.0 compatibility
• Fix for benchmark name when supplied by the user
• Handles tz-native and tz-aware comparisson issue
• Adding benchmark name to html report
• Update README ticker to META :)
• Many pull requests merged

0.0.59

• Fixed EOY compounded return calculation

0.0.58

• Run fillna(0) on plot's beta (issue #193)

0.0.57

• Fixed sigma calculation in stats.probabilistic_ratio()

0.0.56

• Added option to explicitly provide the benchmark title via benchmark_title=...

0.0.55

• Fix for benchmark name in html report when supplied by the user

0.0.54

• Fixed dependency name in requirements.txt

0.0.53

• Added information ratio to reports

0.0.52

• Added Treynor ratio

0.0.51

• Added max consecutive wins/losses to full report
• Added “correlation to benchmark” to report
• Cleanup inf/nan from reports
• Added benchmark name to stats column and html report
• Added probabilistic sharpe/sortino ratios
• Fix relative dates calculations

0.0.50

• Fixed a bug when reporting the max drawdown

0.0.49

• Fixed an issue with saving the HTML report as a file

0.0.48

• Fixed RF display bug

0.0.47

• Fixed average DD display bug

0.0.46

• Misc bug fixes and speedups

0.0.45

• Fixed stats.rolling_sharpe() parameter mismatch

0.0.44

• Match dates logic on utils.make_index()

0.0.43

• Fixed stats.rolling_sortino() calculations
• Added match_dates flag to reports to make strategy and benchmark comparible by syncing their dates and frequency
• Added prepare_returns flag to utils._prepare_benchmark()
• Misc code cleanup and speedups

0.0.42

• Usability improvements

0.0.41

• Typos fixed

0.0.40

• Added rebalance option to utils.make_index()
• Added option to add log_scale=True/False` to plots.snapshot()``

0.0.39

• Fixed plots.rolling_volatility() benchmark display (bug introduced in 0.0.37)

0.0.38

• Added stats.smart_sharpe() and stats.smart_sortino()

0.0.37

• added stats.rolling_sharpe(), stats.rolling_sortino(), stats.and rolling_volatility()
• Added stats.distribution()
• Added Omega ratio
• BREAKING CHANGE: Eenamed trading_year_days param to periods_per_year
• Misc code cleanup and speedups

0.0.36

• Added as_pct params to reports.metrics() for when you need display data as DataFrame

0.0.35

• Passing correct rolling windows in rolling_beta()
• Added Serenity Index
• Passing trading_year_days to method metrics
• Fixed "day is out of range for month" error

0.0.34

• Fixed bug in stats.consecutive_wins() and stats.consecutive_losses()
• Fixed seaborn's depreated distplot warning
• Improved annualization by passing trading_year_days

0.0.33

• Added option to pass the number of days per year in reports, so you can now use trading_year_days=365 if you're trading crypto, or any other number for intl. markets.

0.0.32

• Fixed bug in plot_histogram() (issues 94+95)

0.0.31

• Enable period setting for adjusted sortino
• Added utils.make_index() for easy "etf" creation

0.0.30

• Fixed PIP installer

0.0.29

• Minor code refactoring

0.0.28

• gain_to_pain renamed to gain_to_pain_ratio
• Minor code refactoring

0.0.27

• Added Sortino/√2 and Gain/Pain ratio to report
• Merged PRs to fix some bugs

0.0.26

• Misc bug fixes and code improvements

0.0.25

• Fixed conditional_value_at_risk()
• Fixed %matplotlib inline issue notebooks

0.0.24

• Added mtd/qtd/ytd methods for panda (usage: df.mtd())
• Fixed Pandas deprecation warning
• Fixed Matplotlib deprecation warning
• Try setting %matplotlib inline automatic in notebooks

0.0.23

• Fixed profit Factor formula

0.0.22

• Misc bug fixes

0.0.21

• Fixed chart EOY chart's xticks when charting data with 10+ years
• Fixed issue where daily return >= 100%
• Fixed Snapshot plot
• Removed duplicaated code
• Added conda installer
• Misc code refactoring and optimizations

0.0.20

• Misc bugfixes

0.0.19

• Cleaning up data before calculations (replaces inf/-inf/-0 with 0)
• Removed usage of pandas.compound() for future pandas version compatibility
• Auto conversion of price-to-returns and returns-to-data as needed

0.0.18

• Fixed issue when last date in data is in the past (issue #4)
• Fixed issue when data has less than 5 drawdown periods (issue #4)

0.0.17

• Fixed CAGR calculation for more accuracy
• Handles drawdowns better in live trading mode when currently in drawdown

0.0.16

• Handles no drawdowns better

0.0.15

• Better report formatting
• Code cleanup

0.0.14

• Fixed calculation for rolling sharpe and rolling sortino charts
• Nicer CSS when printing html reports

0.0.13

• Fixed non-compounded plots in reports when using compounded=False

0.0.12

• Option to add compounded=True/False to reports (default is True)

0.0.11

• Minor bug fixes

0.0.10

• Updated to install and use yfinance instead of fix_yahoo_finance

0.0.09

• Added support for 3 modes (cumulative, compounded, fixed amount) in plots.earnings() and utils.make_portfolio()
• Added two DataFrame utilities: df.curr_month() and df.date(date)
• Misc bug fixes and code refactoring

0.0.08

• Better calculations for cagr, var, cvar, avg win/loss and payoff_ratio
• Removed unused param from to_plotly()
• Added risk free param to log_returns() + renamed it to to_log_returns()
• Misc bug fixes and code improvements

0.0.07

• Plots returns figure if show is set to False

0.0.06

• Minor bug fix

0.0.05

• Added plots.to_plotly() method
• Added Ulcer Index to metrics report
• Better returns/price detection
• Bug fixes and code refactoring

0.0.04

• Added pct_rank() method to stats
• Added multi_shift() method to utils

0.0.03

• Better VaR/cVaR calculation
• Fixed calculation of to_drawdown_series()
• Changed VaR/cVaR default confidence to 95%
• Improved Sortino formula
• Fixed conversion of returns to prices (to_prices())

0.0.02

• Initial release

0.0.01

• Pre-release placeholder