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A Python powered CLI that calculates most important descriptive statistics for given assets

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Stock Statistics

This Python CLI calculates various descriptive statistics and risk measures for the given asset symbols. See refer to example output below.

The tool leverages the yfinance library to obtain stock data.

Features

  • Annual mean return (in %)
  • Annual volatility (in %)
  • Annual semi volatility (in %)
  • Minimum return (in %) and its date
  • Maximum return (in %) and its date
  • Minimum trading range and its date
  • Maximum trading range and its date
  • Kurtosis
  • Skewness
  • Value-at-Risk at different quantiles (0.001, 0.01, 0.05)
  • Conditional Value-at-Risk at different quantiles (0.001, 0.01, 0.05)
  • Maximum drawdown (daily)

Parameters

  • symbols: List of strings. Stock symbols for which statistics should be calculated. Could be one or more.
  • start: String in YYYY-MM-DD format. Start date of the period for which statistics should to be calculated (optional)
  • end: String in YYYY-MM-DD format. End date of the period for which statistics should to be calculated (optional)
  • picture: Boolean. Whether or not to plot the maximum drawdown (optional, default is False)
  • markdown: Boolean. Whether or not to output the statistics in markdown format (optional, default is True)

Utilize -h flag to get more infos on usage.

Example

Show statistics for AAPL, GOOG and TSLA stock, use longest available data, .txt output is ready-to-use for embedding in Markdown files:

> init.py -s AAPL GOOG TSLA -d True 

Output

.png and .html files are saved in output/ subfolder:

Example 1 - Output (.png and .html available)

AAPL GOOG TSLA
Period 1980-12-12 - 2023-02-01 2004-08-19 - 2023-01-31 2010-06-29 - 2023-02-01
Annual mean return (in %) 17.27 20.01 37.67
Annual volatility (in %) 45.54 30.59 57.22
Annual semi volatility (in %) 35.42 22.04 41.49
Minimum return (in %) -73.12 -12.34 -23.65
Date of minimum return 2000-09-29 2008-09-29 2020-09-08
Maximum return (in %) 28.69 18.23 21.83
Date of maximum return 1997-08-06 2008-04-18 2013-05-09
INTRADAY TRADING RANGES
Minimum trading range (in %) 0.0 0.38 0.85
Date of Min. trading range 1981-08-10 2016-08-12 2021-10-14
Maximum trading range (in %) 32.94 15.01 39.26
Date of Max. trading range 1998-01-06 2006-02-28 2010-06-29
Kurtosis 46.77 8.19 5.02
Skewness -1.74 0.39 -0.04
Maximum drawdown (daily, in %) -80.58 -64.17 -72.97
RISK OF LOSS (daily, in %)
VaR(95.0) -4.2 -2.86 -5.26
VaR(99.0) -7.32 -5.25 -9.44
VaR(99.9) -15.54 -9.21 -18.63
EXPECTED SHORTFALL (daily, in %)
Conditional VaR(95.0) -6.44 -4.45 -8.31
Conditional VaR(99.0) -10.85 -7.1 -13.81
Conditional VaR(99.9) -26.19 -10.84 -21.13

The maximum drawdown ("from peak to trough") is calculated based on daily log returns with a 252 days trailing window.

Feedback & Contributions

I'd love to hear from you! 🙏

If you have any feedback, ideas for improving the project or have found a bug , please just open an issue :)

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A Python powered CLI that calculates most important descriptive statistics for given assets

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