Coverage for src / jsharpe / __init__.py: 100%

1"""JSharpe: Sharpe Ratio Analysis and Statistical Testing. 

2 

3This package provides comprehensive tools for Sharpe ratio analysis, 

4including statistical significance testing, multiple testing corrections, 

5and portfolio optimization utilities. 

6 

7Key features: 

8 - Sharpe ratio variance estimation under non-Gaussian returns 

9 - Minimum track record length computation 

10 - Probabilistic Sharpe Ratio (PSR) calculation 

11 - False Discovery Rate (FDR) control for multiple strategy testing 

12 - Family-Wise Error Rate (FWER) corrections (Bonferroni, Šidák, Holm) 

13 - Minimum variance portfolio optimization 

14 

15Example: 

16 >>> import numpy as np 

17 >>> from jsharpe.sharpe import sharpe_ratio_variance, probabilistic_sharpe_ratio 

18 >>> # Compute variance of a Sharpe ratio estimate 

19 >>> var = sharpe_ratio_variance(SR=0.5, T=24) 

20 >>> # Compute the Probabilistic Sharpe Ratio 

21 >>> psr = probabilistic_sharpe_ratio(SR=0.5, SR0=0, T=24) 

22""" 

23 

24from .sharpe import ( 

25 FDR_critical_value, 

26 adjusted_p_values_bonferroni, 

27 adjusted_p_values_holm, 

28 adjusted_p_values_sidak, 

29 autocorrelation, 

30 control_for_FDR, 

31 critical_sharpe_ratio, 

32 effective_rank, 

33 expected_maximum_sharpe_ratio, 

34 generate_autocorrelated_non_gaussian_data, 

35 generate_non_gaussian_data, 

36 get_random_correlation_matrix, 

37 make_expectation_gh, 

38 minimum_track_record_length, 

39 minimum_variance_weights_for_correlated_assets, 

40 oFDR, 

41 pFDR, 

42 ppoints, 

43 probabilistic_sharpe_ratio, 

44 robust_covariance_inverse, 

45 sharpe_ratio_power, 

46 sharpe_ratio_variance, 

47 variance_of_the_maximum_of_k_Sharpe_ratios, 

48) 

49 

50__all__ = [ 

51 "FDR_critical_value", 

52 "adjusted_p_values_bonferroni", 

53 "adjusted_p_values_holm", 

54 "adjusted_p_values_sidak", 

55 "autocorrelation", 

56 "control_for_FDR", 

57 "critical_sharpe_ratio", 

58 "effective_rank", 

59 "expected_maximum_sharpe_ratio", 

60 "generate_autocorrelated_non_gaussian_data", 

61 "generate_non_gaussian_data", 

62 "get_random_correlation_matrix", 

63 "make_expectation_gh", 

64 "minimum_track_record_length", 

65 "minimum_variance_weights_for_correlated_assets", 

66 "oFDR", 

67 "pFDR", 

68 "ppoints", 

69 "probabilistic_sharpe_ratio", 

70 "robust_covariance_inverse", 

71 "sharpe_ratio_power", 

72 "sharpe_ratio_variance", 

73 "variance_of_the_maximum_of_k_Sharpe_ratios", 

74]