{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "55822295", "metadata": {}, "source": [ "![Finance Toolkit](https://github.com/JerBouma/FinanceToolkit/assets/46355364/198d47bd-e1b3-492d-acc4-5d9f02d1d009)\n", "\n", "**The FinanceToolkit** is an open-source toolkit in which all relevant financial ratios (100+), indicators and performance measurements are written down in the most simplistic way allowing for complete transparency of the calculation method. This allows you to not have to rely on metrics from other providers and, given a financial statement, allow for efficient manual calculations. This leads to one uniform method of calculation being applied that is available and understood by everyone." ] }, { "cell_type": "markdown", "id": "2937a8f2", "metadata": {}, "source": [ "# Installation\n", "To install the FinanceToolkit it simply requires the following:\n", "\n", "```\n", "pip install financetoolkit -U\n", "```\n", "\n", "From within Python use:\n", "\n", "```python\n", "from financetoolkit import Toolkit\n", "```\n", " \n", "To be able to get started, you need to obtain an API Key from FinancialModelingPrep. This is used to gain access to 30+ years of financial statement both annually and quarterly. Note that the Free plan is limited to 250 requests each day, 5 years of data and only features companies listed on US exchanges.\n", "\n", "___ \n", "\n", "
Obtain an API Key from FinancialModelingPrep here.
\n", "___\n", "\n", "Through the link you are able to subscribe for the free plan and also premium plans at a **15% discount**. This is an affiliate link and thus supports the project at the same time. I have chosen FinancialModelingPrep as a source as I find it to be the most transparent, reliable and at an affordable price. When you notice that data is inaccurate or have any other issue related to the data, note that I simply provide the means to access this data and I am not responsible for the accuracy of the data itself. For this, use their contact form or provide the data yourself. \n", "\n", "The current Notebook is revolved around the Ratios class. If you are interested in the other modules, you can find the related Notebooks below. **Please view the documentation here to find all the available functionality.**\n", "\n", "\n", "\n", "
\n", " Toolkit\n", " Discovery\n", " Ratios\n", " Models\n", " Options\n", " Technicals\n", " Risk\n", " Performance\n", " Economics\n", " Fixed income\n", " Portfolio\n", "
" ] }, { "cell_type": "code", "execution_count": null, "id": "11269a00", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "\n", "from financetoolkit import Toolkit\n", "\n", "API_KEY = \"FINANCIAL_MODELING_PREP_API_KEY\"" ] }, { "attachments": {}, "cell_type": "markdown", "id": "a3f7fc24", "metadata": {}, "source": [ "**Initializing only is required once.** This is the case for any function so once you have obtained a balance sheet statement, it will be stored accordingly which means that requests to FinancialModelingPrep, the source used in these examples, are kept to a minimum. Note that in this example annual data is used but by adding `quarterly=True` to the Toolkit initialization, quarterly data can also be collected. Note that this requires a Premium subscription from FMP." ] }, { "cell_type": "code", "execution_count": 2, "id": "b3507cb1", "metadata": {}, "outputs": [], "source": [ "# Initialize the Toolkit with company tickers\n", "companies = Toolkit(\n", " [\"AAPL\", \"AMZN\", \"META\", \"WMT\"], api_key=API_KEY, start_date=\"2005-01-01\"\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "af12299f", "metadata": {}, "source": [ "After initialization of `Toolkit`, you can get access to the Ratios module which includes over 50 different ratios. This can be done by calling the `ratios` property. Please view the documentation here to find all the available ratios. \n", "\n", "Within this ratios module, the distinction is made between `collect_` and `get_`. The former obtains a collection of ratios (e.g. all solvency ratios) whereas the latter obtains a specific ratio. You will note that it will collect data first, this is done only once so that the ratios can be calculated efficiently. For example, let's start with getting all ratios." ] }, { "cell_type": "code", "execution_count": 3, "id": "3c79b76d", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining financial statements: 100%|██████████| 3/3 [00:04<00:00, 1.42s/it]\n", "Obtaining historical data: 100%|██████████| 5/5 [00:00<00:00, 9.57it/s]\n" ] }, { "data": { "text/html": [ "
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2005200620072008200920102011201220132014...2016201720182019202020212022202320242025
AAPLDays of Inventory OutstandingNaN5.78757.09187.3146.85016.95095.1753.25544.37396.2997...6.22479.04049.81959.09448.79039.11819.40979.610911.814NaN
Days of Sales OutstandingNaN20.286221.962922.807624.598524.821118.341219.005825.661730.5127...27.592626.772328.213832.345425.958121.151725.205727.469929.3645NaN
Operating CycleNaN26.073729.054830.121631.448531.77223.516222.261330.035636.8123...33.817435.812638.033441.439934.748430.269834.615437.080841.1785NaN
Days of Accounts Payable OutstandingNaN68.771896.246589.735979.024481.30675.477374.38974.5485.4527...101.1074105.4983111.5912115.202195.288983.168397.0504108.0033114.1501NaN
Cash Conversion CycleNaN-42.6981-67.1917-59.6143-47.5758-49.534-51.9611-52.1277-44.5044-48.6403...-67.29-69.6856-73.5578-73.7623-60.5405-52.8985-62.435-70.9225-72.9716NaN
.....................................................................
WMTEV-to-EBIT13.29312.320411.896112.392410.935910.393910.121211.119711.712712.7697...11.208115.717519.239330.638721.579520.457821.979825.015933.266531.1534
EV-to-EBITDA10.43789.70388.9189.51638.40827.87697.9838.32348.7869.4542...7.948810.630510.432912.483615.315313.769812.264915.574320.347720.844
EV-to-Operating-Cash-Flow15.059312.894111.479613.237410.72949.334711.204211.903712.463314.5295...9.681811.023611.400814.679619.135712.863718.563916.941522.135524.206
Tangible Asset Value38593000000.041074000000.047814000000.048729000000.052216000000.056829000000.054892000000.055514000000.061760000000.063320000000.0...66916000000.063498000000.062580000000.048453000000.050479000000.058548000000.062877000000.055817000000.062458000000.068900000000.0
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" ], "text/plain": [ " 2005 2006 \\\n", "AAPL Days of Inventory Outstanding NaN 5.7875 \n", " Days of Sales Outstanding NaN 20.2862 \n", " Operating Cycle NaN 26.0737 \n", " Days of Accounts Payable Outstanding NaN 68.7718 \n", " Cash Conversion Cycle NaN -42.6981 \n", "... ... ... \n", "WMT EV-to-EBIT 13.293 12.3204 \n", " EV-to-EBITDA 10.4378 9.7038 \n", " EV-to-Operating-Cash-Flow 15.0593 12.8941 \n", " Tangible Asset Value 38593000000.0 41074000000.0 \n", " Net Current Asset Value -4328000000.0 -5000000000.0 \n", "\n", " 2007 2008 \\\n", "AAPL Days of Inventory Outstanding 7.0918 7.314 \n", " Days of Sales Outstanding 21.9629 22.8076 \n", " Operating Cycle 29.0548 30.1216 \n", " Days of Accounts Payable Outstanding 96.2465 89.7359 \n", " Cash Conversion Cycle -67.1917 -59.6143 \n", "... ... ... \n", "WMT EV-to-EBIT 11.8961 12.3924 \n", " EV-to-EBITDA 8.918 9.5163 \n", " EV-to-Operating-Cash-Flow 11.4796 13.2374 \n", " Tangible Asset Value 47814000000.0 48729000000.0 \n", " Net Current Asset Value -5166000000.0 -10458000000.0 \n", "\n", " 2009 2010 \\\n", "AAPL Days of Inventory Outstanding 6.8501 6.9509 \n", " Days of Sales Outstanding 24.5985 24.8211 \n", " Operating Cycle 31.4485 31.772 \n", " Days of Accounts Payable Outstanding 79.0244 81.306 \n", " Cash Conversion Cycle -47.5758 -49.534 \n", "... ... ... \n", "WMT EV-to-EBIT 10.9359 10.3939 \n", " EV-to-EBITDA 8.4082 7.8769 \n", " EV-to-Operating-Cash-Flow 10.7294 9.3347 \n", " Tangible Asset Value 52216000000.0 56829000000.0 \n", " Net Current Asset Value -6441000000.0 -7511000000.0 \n", "\n", " 2011 2012 \\\n", "AAPL Days of Inventory Outstanding 5.175 3.2554 \n", " Days of Sales Outstanding 18.3412 19.0058 \n", " Operating Cycle 23.5162 22.2613 \n", " Days of Accounts Payable Outstanding 75.4773 74.389 \n", " Cash Conversion Cycle -51.9611 -52.1277 \n", "... ... ... \n", "WMT EV-to-EBIT 10.1212 11.1197 \n", " EV-to-EBITDA 7.983 8.3234 \n", " EV-to-Operating-Cash-Flow 11.2042 11.9037 \n", " Tangible Asset Value 54892000000.0 55514000000.0 \n", " Net Current Asset Value -6591000000.0 -7325000000.0 \n", "\n", " 2013 2014 ... \\\n", "AAPL Days of Inventory Outstanding 4.3739 6.2997 ... \n", " Days of Sales Outstanding 25.6617 30.5127 ... \n", " Operating Cycle 30.0356 36.8123 ... \n", " Days of Accounts Payable Outstanding 74.54 85.4527 ... \n", " Cash Conversion Cycle -44.5044 -48.6403 ... \n", "... ... ... ... \n", "WMT EV-to-EBIT 11.7127 12.7697 ... \n", " EV-to-EBITDA 8.786 9.4542 ... \n", " EV-to-Operating-Cash-Flow 12.4633 14.5295 ... \n", " Tangible Asset Value 61760000000.0 63320000000.0 ... \n", " Net Current Asset Value -11878000000.0 -8160000000.0 ... \n", "\n", " 2016 2017 \\\n", "AAPL Days of Inventory Outstanding 6.2247 9.0404 \n", " Days of Sales Outstanding 27.5926 26.7723 \n", " Operating Cycle 33.8174 35.8126 \n", " Days of Accounts Payable Outstanding 101.1074 105.4983 \n", " Cash Conversion Cycle -67.29 -69.6856 \n", "... ... ... \n", "WMT EV-to-EBIT 11.2081 15.7175 \n", " EV-to-EBITDA 7.9488 10.6305 \n", " EV-to-Operating-Cash-Flow 9.6818 11.0236 \n", " Tangible Asset Value 66916000000.0 63498000000.0 \n", " Net Current Asset Value -4380000000.0 -9239000000.0 \n", "\n", " 2018 2019 \\\n", "AAPL Days of Inventory Outstanding 9.8195 9.0944 \n", " Days of Sales Outstanding 28.2138 32.3454 \n", " Operating Cycle 38.0334 41.4399 \n", " Days of Accounts Payable Outstanding 111.5912 115.2021 \n", " Cash Conversion Cycle -73.5578 -73.7623 \n", "... ... ... \n", "WMT EV-to-EBIT 19.2393 30.6387 \n", " EV-to-EBITDA 10.4329 12.4836 \n", " EV-to-Operating-Cash-Flow 11.4008 14.6796 \n", " Tangible Asset Value 62580000000.0 48453000000.0 \n", " Net Current Asset Value -18857000000.0 -15580000000.0 \n", "\n", " 2020 2021 \\\n", "AAPL Days of Inventory Outstanding 8.7903 9.1181 \n", " Days of Sales Outstanding 25.9581 21.1517 \n", " Operating Cycle 34.7484 30.2698 \n", " Days of Accounts Payable Outstanding 95.2889 83.1683 \n", " Cash Conversion Cycle -60.5405 -52.8985 \n", "... ... ... \n", "WMT EV-to-EBIT 21.5795 20.4578 \n", " EV-to-EBITDA 15.3153 13.7698 \n", " EV-to-Operating-Cash-Flow 19.1357 12.8637 \n", " Tangible Asset Value 50479000000.0 58548000000.0 \n", " Net Current Asset Value -15984000000.0 -2578000000.0 \n", "\n", " 2022 2023 \\\n", "AAPL Days of Inventory Outstanding 9.4097 9.6109 \n", " Days of Sales Outstanding 25.2057 27.4699 \n", " Operating Cycle 34.6154 37.0808 \n", " Days of Accounts Payable Outstanding 97.0504 108.0033 \n", " Cash Conversion Cycle -62.435 -70.9225 \n", "... ... ... \n", "WMT EV-to-EBIT 21.9798 25.0159 \n", " EV-to-EBITDA 12.2649 15.5743 \n", " EV-to-Operating-Cash-Flow 18.5639 16.9415 \n", " Tangible Asset Value 62877000000.0 55817000000.0 \n", " Net Current Asset Value -6309000000.0 -16543000000.0 \n", "\n", " 2024 2025 \n", "AAPL Days of Inventory Outstanding 11.814 NaN \n", " Days of Sales Outstanding 29.3645 NaN \n", " Operating Cycle 41.1785 NaN \n", " Days of Accounts Payable Outstanding 114.1501 NaN \n", " Cash Conversion Cycle -72.9716 NaN \n", "... ... ... \n", "WMT EV-to-EBIT 33.2665 31.1534 \n", " EV-to-EBITDA 20.3477 20.844 \n", " EV-to-Operating-Cash-Flow 22.1355 24.206 \n", " Tangible Asset Value 62458000000.0 68900000000.0 \n", " Net Current Asset Value -15538000000.0 -17126000000.0 \n", "\n", "[268 rows x 21 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_all_ratios()" ] }, { "cell_type": "markdown", "id": "3fcf7e9a", "metadata": {}, "source": [ "Given that you might not be interested in all of them, it is possible to also call each and every single one seperately." ] }, { "cell_type": "code", "execution_count": 4, "id": "8b9fa8b4", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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date2005200620072008200920102011201220132014...2016201720182019202020212022202320242025
AAPL0.26550.29420.30190.29890.31750.24420.24220.25160.26150.2613...0.25560.24560.18340.15940.14430.1330.1620.14720.2409NaN
AMZN0.2220.4960.27880.27410.21790.23510.31160.78680.3701-1.5045...0.37540.20230.10620.170.11830.12560.54190.18960.1352NaN
METANaNNaN-0.0222-0.00.09840.39880.410.89270.45530.4012...0.18380.22630.12810.2550.12160.16740.1950.17560.1175NaN
WMT0.3470.33090.33560.3420.34190.32350.3220.32560.31010.3287...0.30310.30270.30420.37360.24430.33350.25440.33640.25530.2338
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" ], "text/plain": [ "date 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 \\\n", "AAPL 0.2655 0.2942 0.3019 0.2989 0.3175 0.2442 0.2422 0.2516 0.2615 0.2613 \n", "AMZN 0.222 0.496 0.2788 0.2741 0.2179 0.2351 0.3116 0.7868 0.3701 -1.5045 \n", "META NaN NaN -0.0222 -0.0 0.0984 0.3988 0.41 0.8927 0.4553 0.4012 \n", "WMT 0.347 0.3309 0.3356 0.342 0.3419 0.3235 0.322 0.3256 0.3101 0.3287 \n", "\n", "date ... 2016 2017 2018 2019 2020 2021 2022 2023 2024 \\\n", "AAPL ... 0.2556 0.2456 0.1834 0.1594 0.1443 0.133 0.162 0.1472 0.2409 \n", "AMZN ... 0.3754 0.2023 0.1062 0.17 0.1183 0.1256 0.5419 0.1896 0.1352 \n", "META ... 0.1838 0.2263 0.1281 0.255 0.1216 0.1674 0.195 0.1756 0.1175 \n", "WMT ... 0.3031 0.3027 0.3042 0.3736 0.2443 0.3335 0.2544 0.3364 0.2553 \n", "\n", "date 2025 \n", "AAPL NaN \n", "AMZN NaN \n", "META NaN \n", "WMT 0.2338 \n", "\n", "[4 rows x 21 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.get_effective_tax_rate()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "3508a5ee", "metadata": {}, "source": [ "Some of these ratios also include optional fields depending on whether there is room for different methods of calculation. E.g. whether you'd like to have the diluted average shares included in the calculation." ] }, { "cell_type": "code", "execution_count": 5, "id": "70fb0e5d", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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date2005200620072008200920102011201220132014...2016201720182019202020212022202320242025
AAPLDebt-to-Assets RatioNaNNaNNaNNaNNaNNaNNaNNaNinf0.8584...0.22070.13940.01560.01980.18260.0302-0.0342-0.0642-0.0720.0
Debt-to-Equity RatioNaNNaNNaNNaNNaNNaNNaNNaNinf1.3044...0.2590.27170.23810.11750.56730.15630.2082-0.23730.04830.0
Debt Service Coverage RatioNaN-0.19210.2480.16250.8474-0.13050.36170.1864-0.217-0.2627...-0.1402-0.1990.0051-0.01130.04020.3804-0.10660.0141-0.1120.0
Equity MultiplierNaN2.50060.0523-0.0376-0.0713-0.0044-0.0031-0.02510.05560.178...0.0930.0750.15620.15980.1930.23620.17720.0106-0.03630.0
Free Cash Flow YieldNaN-0.44250.20183.2557-0.5740.18320.43060.03610.0312-0.135...-0.2786-0.29960.4089-0.4707-0.265-0.01880.6901-0.3781-0.13980.0
Net-Debt to EBITDA RatioNaN0.2458-0.171-0.1137-0.75940.375-0.5247-0.3341-1.26366.3326...0.80150.4138-0.1884-0.2850.4073-0.2244-0.0133-0.1042-0.11380.0
Cash Flow Coverage RatioNaNNaNNaNNaNNaNNaNNaNNaN-1.0-0.4653...-0.3976-0.27040.2183-0.05060.02740.1550.2098-0.03250.11350.0
CAPEX Coverage RatioNaN-0.65340.64180.44260.04650.0468-0.42560.07410.09320.0291...-0.30890.02680.15880.13680.6694-0.14970.2154-0.11580.2410.0
Dividend CAPEX Coverage RatioNaN-0.65340.64180.44260.04650.0468-0.4256-0.1507-0.36110.0437...-0.269-0.02520.1405-0.01610.33780.07950.1742-0.11020.12620.0
AMZNDebt-to-Assets RatioNaN-0.2773-0.2772-0.6608-0.74440.87360.64221.10.09690.776...-0.16670.5833-0.29430.3768-0.06380.05370.0939-0.1516-0.18450.0
Debt-to-Equity RatioNaN-0.513-0.6132-0.8051-0.78380.94990.95291.5630.13711.1872...-0.25510.7349-0.44390.3381-0.1128-0.06820.1396-0.2998-0.31870.0
Debt Service Coverage RatioNaN-0.32480.14840.0057-0.1359-0.1155-0.573-0.3851-0.0899-0.8056...0.5068-0.2861.5614-0.08810.0942-0.0348-0.54951.83630.71050.0
Equity MultiplierNaN51.3253-0.4402-0.426-0.2704-0.03590.12050.20290.11790.1399...-0.08260.0075-0.0971-0.1097-0.043-0.089-0.0297-0.0836-0.170.0
Free Cash Flow YieldNaN0.09190.04041.0388-0.2048-0.3752-0.147-0.86522.08330.2252...0.2512-0.56821.07020.0042-0.3291-1.54721.2644-2.0457-0.30580.0
Net-Debt to EBITDA RatioNaN-0.5167-4.16950.47490.0984-0.24990.2472-0.2427-0.4204-0.5171...0.641-4.3791-0.955113.86650.17620.54350.1749-0.5429-0.40980.0
Cash Flow Coverage RatioNaN0.12260.8631.77693.5585-0.5828-0.4941-0.6043-0.0318-0.4816...0.3314-0.57180.9143-0.34250.2847-0.4916-0.16160.87710.41320.0
CAPEX Coverage RatioNaN-0.09550.9299-0.18750.7324-0.5956-0.3963-0.48760.4394-0.1204...-0.0136-0.30310.4895-0.0017-0.2795-0.5389-0.03191.193-0.13340.0
Dividend CAPEX Coverage RatioNaN-0.09550.9299-0.18750.7324-0.5956-0.3963-0.48760.4394-0.1204...-0.0136-0.30310.4895-0.0017-0.2795-0.5389-0.03191.193-0.13340.0
METADebt-to-Assets RatioNaN-0.09550.9299-0.18750.7324-1.0179-0.32430.4593-0.8295-0.782...-1.0inf4.666714.1765-0.13570.24960.71290.13270.09560.0
Debt-to-Equity RatioNaN-0.09550.9299-0.18750.7324-1.0248-0.36840.4501-0.8463-0.789...-1.0inf4.916.322-0.18790.33860.90370.14940.10490.0
Debt Service Coverage RatioNaN-0.09550.9299-0.18750.7324-1.3005-0.2637-0.73823.98460.3758...0.33660.2431-0.3392-0.55120.36860.0144-0.51580.36580.41170.0
Equity MultiplierNaN-0.09550.9299-0.18750.7324-1.3005-0.5024-0.0251-0.0583-0.0707...-0.00860.01220.02520.08570.02430.00680.09230.06110.01110.0
Free Cash Flow YieldNaN-0.09550.9299-0.1875-infNaNNaN-1.03.75-0.1627...0.6878-0.03180.209-0.1062-0.1630.3630.4262-0.1834-0.24320.0
Net-Debt to EBITDA RatioNaN-0.09550.9299-0.1875-inf-1.0-0.6416-0.941230.6229-0.123...0.0274-0.4282-0.0551-0.0958-0.4054-0.715-7.3427-1.2524-1.76220.0
Cash Flow Coverage RatioNaN-0.09550.9299-0.1875-inf-1.00.5505-0.70111.96361.6405...inf-1.0-0.8259-0.93990.0340.1433-0.54350.0062-0.02530.0
CAPEX Coverage RatioNaN-0.09550.9299-0.1875-0.0783-0.49280.073-0.48931.3749-0.0386...0.05240.0028-0.41510.1430.06610.2119-0.48310.6241-0.06010.0
Dividend CAPEX Coverage RatioNaN-0.09550.9299-0.1875-0.0783-0.49280.073-0.48931.3749-0.0386...0.05240.0028-0.41510.1430.06610.2119-0.48310.6241-0.17270.0
WMTDebt-to-Assets RatioNaN0.0848-0.08170.0614-0.0545-0.06120.13730.0015-0.03510.0379...0.017-0.0786-0.0160.16410.1576-0.1822-0.06550.0350.0029-0.0514
Debt-to-Equity RatioNaN0.1588-0.130.0911-0.095-0.09480.22860.008-0.06190.0391...0.0252-0.04680.00840.26690.2189-0.1864-0.13670.1246-0.0349-0.0911
Debt Service Coverage RatioNaN-0.04320.0256-0.04320.09440.04760.0107-0.0218-0.0920.001...-0.1034-0.0882-0.23460.0887-0.067-0.07940.2198-0.25360.3190.0397
Equity MultiplierNaN5.28760.0026-0.0112-0.0088-0.03960.02160.0424-0.0113-0.0129...-0.01720.02090.02990.05660.07060.0227-0.04150.0010.0231-0.0398
Free Cash Flow YieldNaN0.47220.42770.04851.32350.2188-0.2567-0.09180.0505-0.2448...-0.1244-0.0579-0.041-0.2366-0.2920.7797-0.5556-0.0036-0.2581-0.256
Net-Debt to EBITDA RatioNaN0.179-0.13290.1493-0.1451-0.09210.19150.0559-0.05510.0815...0.0901-0.0340.07860.20150.2944-0.3233-0.13880.3786-0.1742-0.0884
Cash Flow Coverage RatioNaN-0.06030.1351-0.11840.20350.1587-0.2537-0.04240.0412-0.1314...-0.03280.252-0.1159-0.2156-0.27080.6358-0.26050.16050.19020.0405
CAPEX Coverage RatioNaN0.03770.0630.05870.47720.0702-0.1358-0.03570.1052-0.1062...0.02310.2425-0.0548-0.0483-0.12070.4897-0.475-0.07270.0134-0.1162
Dividend CAPEX Coverage RatioNaN0.03710.05720.00650.38170.0541-0.138-0.05270.0724-0.1382...-0.00350.2135-0.0688-0.0368-0.10670.4609-0.4299-0.00010.064-0.1047
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36 rows × 21 columns

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" ], "text/plain": [ "date 2005 2006 2007 2008 2009 \\\n", "AAPL Debt-to-Assets Ratio NaN NaN NaN NaN NaN \n", " Debt-to-Equity Ratio NaN NaN NaN NaN NaN \n", " Debt Service Coverage Ratio NaN -0.1921 0.248 0.1625 0.8474 \n", " Equity Multiplier NaN 2.5006 0.0523 -0.0376 -0.0713 \n", " Free Cash Flow Yield NaN -0.4425 0.2018 3.2557 -0.574 \n", " Net-Debt to EBITDA Ratio NaN 0.2458 -0.171 -0.1137 -0.7594 \n", " Cash Flow Coverage Ratio NaN NaN NaN NaN NaN \n", " CAPEX Coverage Ratio NaN -0.6534 0.6418 0.4426 0.0465 \n", " Dividend CAPEX Coverage Ratio NaN -0.6534 0.6418 0.4426 0.0465 \n", "AMZN Debt-to-Assets Ratio NaN -0.2773 -0.2772 -0.6608 -0.7444 \n", " Debt-to-Equity Ratio NaN -0.513 -0.6132 -0.8051 -0.7838 \n", " Debt Service Coverage Ratio NaN -0.3248 0.1484 0.0057 -0.1359 \n", " Equity Multiplier NaN 51.3253 -0.4402 -0.426 -0.2704 \n", " Free Cash Flow Yield NaN 0.0919 0.0404 1.0388 -0.2048 \n", " Net-Debt to EBITDA Ratio NaN -0.5167 -4.1695 0.4749 0.0984 \n", " Cash Flow Coverage Ratio NaN 0.1226 0.863 1.7769 3.5585 \n", " CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Dividend CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", "META Debt-to-Assets Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Debt-to-Equity Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Debt Service Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Equity Multiplier NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Free Cash Flow Yield NaN -0.0955 0.9299 -0.1875 -inf \n", " Net-Debt to EBITDA Ratio NaN -0.0955 0.9299 -0.1875 -inf \n", " Cash Flow Coverage Ratio NaN -0.0955 0.9299 -0.1875 -inf \n", " CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 -0.0783 \n", " Dividend CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 -0.0783 \n", "WMT Debt-to-Assets Ratio NaN 0.0848 -0.0817 0.0614 -0.0545 \n", " Debt-to-Equity Ratio NaN 0.1588 -0.13 0.0911 -0.095 \n", " Debt Service Coverage Ratio NaN -0.0432 0.0256 -0.0432 0.0944 \n", " Equity Multiplier NaN 5.2876 0.0026 -0.0112 -0.0088 \n", " Free Cash Flow Yield NaN 0.4722 0.4277 0.0485 1.3235 \n", " Net-Debt to EBITDA Ratio NaN 0.179 -0.1329 0.1493 -0.1451 \n", " Cash Flow Coverage Ratio NaN -0.0603 0.1351 -0.1184 0.2035 \n", " CAPEX Coverage Ratio NaN 0.0377 0.063 0.0587 0.4772 \n", " Dividend CAPEX Coverage Ratio NaN 0.0371 0.0572 0.0065 0.3817 \n", "\n", "date 2010 2011 2012 2013 2014 \\\n", "AAPL Debt-to-Assets Ratio NaN NaN NaN inf 0.8584 \n", " Debt-to-Equity Ratio NaN NaN NaN inf 1.3044 \n", " Debt Service Coverage Ratio -0.1305 0.3617 0.1864 -0.217 -0.2627 \n", " Equity Multiplier -0.0044 -0.0031 -0.0251 0.0556 0.178 \n", " Free Cash Flow Yield 0.1832 0.4306 0.0361 0.0312 -0.135 \n", " Net-Debt to EBITDA Ratio 0.375 -0.5247 -0.3341 -1.2636 6.3326 \n", " Cash Flow Coverage Ratio NaN NaN NaN -1.0 -0.4653 \n", " CAPEX Coverage Ratio 0.0468 -0.4256 0.0741 0.0932 0.0291 \n", " Dividend CAPEX Coverage Ratio 0.0468 -0.4256 -0.1507 -0.3611 0.0437 \n", "AMZN Debt-to-Assets Ratio 0.8736 0.6422 1.1 0.0969 0.776 \n", " Debt-to-Equity Ratio 0.9499 0.9529 1.563 0.1371 1.1872 \n", " Debt Service Coverage Ratio -0.1155 -0.573 -0.3851 -0.0899 -0.8056 \n", " Equity Multiplier -0.0359 0.1205 0.2029 0.1179 0.1399 \n", " Free Cash Flow Yield -0.3752 -0.147 -0.8652 2.0833 0.2252 \n", " Net-Debt to EBITDA Ratio -0.2499 0.2472 -0.2427 -0.4204 -0.5171 \n", " Cash Flow Coverage Ratio -0.5828 -0.4941 -0.6043 -0.0318 -0.4816 \n", " CAPEX Coverage Ratio -0.5956 -0.3963 -0.4876 0.4394 -0.1204 \n", " Dividend CAPEX Coverage Ratio -0.5956 -0.3963 -0.4876 0.4394 -0.1204 \n", "META Debt-to-Assets Ratio -1.0179 -0.3243 0.4593 -0.8295 -0.782 \n", " Debt-to-Equity Ratio -1.0248 -0.3684 0.4501 -0.8463 -0.789 \n", " Debt Service Coverage Ratio -1.3005 -0.2637 -0.7382 3.9846 0.3758 \n", " Equity Multiplier -1.3005 -0.5024 -0.0251 -0.0583 -0.0707 \n", " Free Cash Flow Yield NaN NaN -1.0 3.75 -0.1627 \n", " Net-Debt to EBITDA Ratio -1.0 -0.6416 -0.9412 30.6229 -0.123 \n", " Cash Flow Coverage Ratio -1.0 0.5505 -0.701 11.9636 1.6405 \n", " CAPEX Coverage Ratio -0.4928 0.073 -0.4893 1.3749 -0.0386 \n", " Dividend CAPEX Coverage Ratio -0.4928 0.073 -0.4893 1.3749 -0.0386 \n", "WMT Debt-to-Assets Ratio -0.0612 0.1373 0.0015 -0.0351 0.0379 \n", " Debt-to-Equity Ratio -0.0948 0.2286 0.008 -0.0619 0.0391 \n", " Debt Service Coverage Ratio 0.0476 0.0107 -0.0218 -0.092 0.001 \n", " Equity Multiplier -0.0396 0.0216 0.0424 -0.0113 -0.0129 \n", " Free Cash Flow Yield 0.2188 -0.2567 -0.0918 0.0505 -0.2448 \n", " Net-Debt to EBITDA Ratio -0.0921 0.1915 0.0559 -0.0551 0.0815 \n", " Cash Flow Coverage Ratio 0.1587 -0.2537 -0.0424 0.0412 -0.1314 \n", " CAPEX Coverage Ratio 0.0702 -0.1358 -0.0357 0.1052 -0.1062 \n", " Dividend CAPEX Coverage Ratio 0.0541 -0.138 -0.0527 0.0724 -0.1382 \n", "\n", "date ... 2016 2017 2018 2019 \\\n", "AAPL Debt-to-Assets Ratio ... 0.2207 0.1394 0.0156 0.0198 \n", " Debt-to-Equity Ratio ... 0.259 0.2717 0.2381 0.1175 \n", " Debt Service Coverage Ratio ... -0.1402 -0.199 0.0051 -0.0113 \n", " Equity Multiplier ... 0.093 0.075 0.1562 0.1598 \n", " Free Cash Flow Yield ... -0.2786 -0.2996 0.4089 -0.4707 \n", " Net-Debt to EBITDA Ratio ... 0.8015 0.4138 -0.1884 -0.285 \n", " Cash Flow Coverage Ratio ... -0.3976 -0.2704 0.2183 -0.0506 \n", " CAPEX Coverage Ratio ... -0.3089 0.0268 0.1588 0.1368 \n", " Dividend CAPEX Coverage Ratio ... -0.269 -0.0252 0.1405 -0.0161 \n", "AMZN Debt-to-Assets Ratio ... -0.1667 0.5833 -0.2943 0.3768 \n", " Debt-to-Equity Ratio ... -0.2551 0.7349 -0.4439 0.3381 \n", " Debt Service Coverage Ratio ... 0.5068 -0.286 1.5614 -0.0881 \n", " Equity Multiplier ... -0.0826 0.0075 -0.0971 -0.1097 \n", " Free Cash Flow Yield ... 0.2512 -0.5682 1.0702 0.0042 \n", " Net-Debt to EBITDA Ratio ... 0.641 -4.3791 -0.9551 13.8665 \n", " Cash Flow Coverage Ratio ... 0.3314 -0.5718 0.9143 -0.3425 \n", " CAPEX Coverage Ratio ... -0.0136 -0.3031 0.4895 -0.0017 \n", " Dividend CAPEX Coverage Ratio ... -0.0136 -0.3031 0.4895 -0.0017 \n", "META Debt-to-Assets Ratio ... -1.0 inf 4.6667 14.1765 \n", " Debt-to-Equity Ratio ... -1.0 inf 4.9 16.322 \n", " Debt Service Coverage Ratio ... 0.3366 0.2431 -0.3392 -0.5512 \n", " Equity Multiplier ... -0.0086 0.0122 0.0252 0.0857 \n", " Free Cash Flow Yield ... 0.6878 -0.0318 0.209 -0.1062 \n", " Net-Debt to EBITDA Ratio ... 0.0274 -0.4282 -0.0551 -0.0958 \n", " Cash Flow Coverage Ratio ... inf -1.0 -0.8259 -0.9399 \n", " CAPEX Coverage Ratio ... 0.0524 0.0028 -0.4151 0.143 \n", " Dividend CAPEX Coverage Ratio ... 0.0524 0.0028 -0.4151 0.143 \n", "WMT Debt-to-Assets Ratio ... 0.017 -0.0786 -0.016 0.1641 \n", " Debt-to-Equity Ratio ... 0.0252 -0.0468 0.0084 0.2669 \n", " Debt Service Coverage Ratio ... -0.1034 -0.0882 -0.2346 0.0887 \n", " Equity Multiplier ... -0.0172 0.0209 0.0299 0.0566 \n", " Free Cash Flow Yield ... -0.1244 -0.0579 -0.041 -0.2366 \n", " Net-Debt to EBITDA Ratio ... 0.0901 -0.034 0.0786 0.2015 \n", " Cash Flow Coverage Ratio ... -0.0328 0.252 -0.1159 -0.2156 \n", " CAPEX Coverage Ratio ... 0.0231 0.2425 -0.0548 -0.0483 \n", " Dividend CAPEX Coverage Ratio ... -0.0035 0.2135 -0.0688 -0.0368 \n", "\n", "date 2020 2021 2022 2023 2024 \\\n", "AAPL Debt-to-Assets Ratio 0.1826 0.0302 -0.0342 -0.0642 -0.072 \n", " Debt-to-Equity Ratio 0.5673 0.1563 0.2082 -0.2373 0.0483 \n", " Debt Service Coverage Ratio 0.0402 0.3804 -0.1066 0.0141 -0.112 \n", " Equity Multiplier 0.193 0.2362 0.1772 0.0106 -0.0363 \n", " Free Cash Flow Yield -0.265 -0.0188 0.6901 -0.3781 -0.1398 \n", " Net-Debt to EBITDA Ratio 0.4073 -0.2244 -0.0133 -0.1042 -0.1138 \n", " Cash Flow Coverage Ratio 0.0274 0.155 0.2098 -0.0325 0.1135 \n", " CAPEX Coverage Ratio 0.6694 -0.1497 0.2154 -0.1158 0.241 \n", " Dividend CAPEX Coverage Ratio 0.3378 0.0795 0.1742 -0.1102 0.1262 \n", "AMZN Debt-to-Assets Ratio -0.0638 0.0537 0.0939 -0.1516 -0.1845 \n", " Debt-to-Equity Ratio -0.1128 -0.0682 0.1396 -0.2998 -0.3187 \n", " Debt Service Coverage Ratio 0.0942 -0.0348 -0.5495 1.8363 0.7105 \n", " Equity Multiplier -0.043 -0.089 -0.0297 -0.0836 -0.17 \n", " Free Cash Flow Yield -0.3291 -1.5472 1.2644 -2.0457 -0.3058 \n", " Net-Debt to EBITDA Ratio 0.1762 0.5435 0.1749 -0.5429 -0.4098 \n", " Cash Flow Coverage Ratio 0.2847 -0.4916 -0.1616 0.8771 0.4132 \n", " CAPEX Coverage Ratio -0.2795 -0.5389 -0.0319 1.193 -0.1334 \n", " Dividend CAPEX Coverage Ratio -0.2795 -0.5389 -0.0319 1.193 -0.1334 \n", "META Debt-to-Assets Ratio -0.1357 0.2496 0.7129 0.1327 0.0956 \n", " Debt-to-Equity Ratio -0.1879 0.3386 0.9037 0.1494 0.1049 \n", " Debt Service Coverage Ratio 0.3686 0.0144 -0.5158 0.3658 0.4117 \n", " Equity Multiplier 0.0243 0.0068 0.0923 0.0611 0.0111 \n", " Free Cash Flow Yield -0.163 0.363 0.4262 -0.1834 -0.2432 \n", " Net-Debt to EBITDA Ratio -0.4054 -0.715 -7.3427 -1.2524 -1.7622 \n", " Cash Flow Coverage Ratio 0.034 0.1433 -0.5435 0.0062 -0.0253 \n", " CAPEX Coverage Ratio 0.0661 0.2119 -0.4831 0.6241 -0.0601 \n", " Dividend CAPEX Coverage Ratio 0.0661 0.2119 -0.4831 0.6241 -0.1727 \n", "WMT Debt-to-Assets Ratio 0.1576 -0.1822 -0.0655 0.035 0.0029 \n", " Debt-to-Equity Ratio 0.2189 -0.1864 -0.1367 0.1246 -0.0349 \n", " Debt Service Coverage Ratio -0.067 -0.0794 0.2198 -0.2536 0.319 \n", " Equity Multiplier 0.0706 0.0227 -0.0415 0.001 0.0231 \n", " Free Cash Flow Yield -0.292 0.7797 -0.5556 -0.0036 -0.2581 \n", " Net-Debt to EBITDA Ratio 0.2944 -0.3233 -0.1388 0.3786 -0.1742 \n", " Cash Flow Coverage Ratio -0.2708 0.6358 -0.2605 0.1605 0.1902 \n", " CAPEX Coverage Ratio -0.1207 0.4897 -0.475 -0.0727 0.0134 \n", " Dividend CAPEX Coverage Ratio -0.1067 0.4609 -0.4299 -0.0001 0.064 \n", "\n", "date 2025 \n", "AAPL Debt-to-Assets Ratio 0.0 \n", " Debt-to-Equity Ratio 0.0 \n", " Debt Service Coverage Ratio 0.0 \n", " Equity Multiplier 0.0 \n", " Free Cash Flow Yield 0.0 \n", " Net-Debt to EBITDA Ratio 0.0 \n", " Cash Flow Coverage Ratio 0.0 \n", " CAPEX Coverage Ratio 0.0 \n", " Dividend CAPEX Coverage Ratio 0.0 \n", "AMZN Debt-to-Assets Ratio 0.0 \n", " Debt-to-Equity Ratio 0.0 \n", " Debt Service Coverage Ratio 0.0 \n", " Equity Multiplier 0.0 \n", " Free Cash Flow Yield 0.0 \n", " Net-Debt to EBITDA Ratio 0.0 \n", " Cash Flow Coverage Ratio 0.0 \n", " CAPEX Coverage Ratio 0.0 \n", " Dividend CAPEX Coverage Ratio 0.0 \n", "META Debt-to-Assets Ratio 0.0 \n", " Debt-to-Equity Ratio 0.0 \n", " Debt Service Coverage Ratio 0.0 \n", " Equity Multiplier 0.0 \n", " Free Cash Flow Yield 0.0 \n", " Net-Debt to EBITDA Ratio 0.0 \n", " Cash Flow Coverage Ratio 0.0 \n", " CAPEX Coverage Ratio 0.0 \n", " Dividend CAPEX Coverage Ratio 0.0 \n", "WMT Debt-to-Assets Ratio -0.0514 \n", " Debt-to-Equity Ratio -0.0911 \n", " Debt Service Coverage Ratio 0.0397 \n", " Equity Multiplier -0.0398 \n", " Free Cash Flow Yield -0.256 \n", " Net-Debt to EBITDA Ratio -0.0884 \n", " Cash Flow Coverage Ratio 0.0405 \n", " CAPEX Coverage Ratio -0.1162 \n", " Dividend CAPEX Coverage Ratio -0.1047 \n", "\n", "[36 rows x 21 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_solvency_ratios(diluted=False, growth=True)" ] }, { "cell_type": "markdown", "id": "e7ec2674", "metadata": {}, "source": [ "For all ratios, it is also possible to show the growth instead. E.g. if you are interested in the growth of the Price-to-Book ratio you can use the following:" ] }, { "cell_type": "code", "execution_count": 6, "id": "48b75204", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Date2005200620072008200920102011201220132014...2016201720182019202020212022202320242025
AAPLNaN-0.10160.6245-0.71480.74910.0327-0.2069-0.14-0.0060.4321...-0.02770.33460.11031.04921.35960.3335-0.11810.17020.38310.0
AMZNNaN-0.5251-0.1544-0.74760.36730.0567-0.14020.34890.3719-0.2983...-0.21870.1057-0.1712-0.12980.1851-0.3015-0.52820.34750.04160.0
METANaN-0.5251-0.1544-0.74760.3673-1.0NaNinf0.227-0.3524...-0.15810.2341-0.35120.28340.05270.2523-0.66411.34890.37930.0
WMTNaN-0.1002-0.11550.0986-0.0845-0.08270.07820.03860.05110.0586...0.13050.431-0.08860.34070.147-0.0806-0.06160.17650.55450.0368
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" ], "text/plain": [ "Date 2005 2006 2007 2008 2009 2010 2011 2012 2013 \\\n", "AAPL NaN -0.1016 0.6245 -0.7148 0.7491 0.0327 -0.2069 -0.14 -0.006 \n", "AMZN NaN -0.5251 -0.1544 -0.7476 0.3673 0.0567 -0.1402 0.3489 0.3719 \n", "META NaN -0.5251 -0.1544 -0.7476 0.3673 -1.0 NaN inf 0.227 \n", "WMT NaN -0.1002 -0.1155 0.0986 -0.0845 -0.0827 0.0782 0.0386 0.0511 \n", "\n", "Date 2014 ... 2016 2017 2018 2019 2020 2021 2022 \\\n", "AAPL 0.4321 ... -0.0277 0.3346 0.1103 1.0492 1.3596 0.3335 -0.1181 \n", "AMZN -0.2983 ... -0.2187 0.1057 -0.1712 -0.1298 0.1851 -0.3015 -0.5282 \n", "META -0.3524 ... -0.1581 0.2341 -0.3512 0.2834 0.0527 0.2523 -0.6641 \n", "WMT 0.0586 ... 0.1305 0.431 -0.0886 0.3407 0.147 -0.0806 -0.0616 \n", "\n", "Date 2023 2024 2025 \n", "AAPL 0.1702 0.3831 0.0 \n", "AMZN 0.3475 0.0416 0.0 \n", "META 1.3489 0.3793 0.0 \n", "WMT 0.1765 0.5545 0.0368 \n", "\n", "[4 rows x 21 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.get_price_to_book_ratio(growth=True)" ] }, { "cell_type": "markdown", "id": "bfedee0b", "metadata": {}, "source": [ "By default, the lag is set to 1 (one period) but it is possible to change this and add multiple lags as well." ] }, { "cell_type": "code", "execution_count": 7, "id": "8dae792f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Lag 2NaNNaN-0.1990.17280.1591-0.2385-0.4135-0.25630.0436-0.2779...0.25230.1509-0.16250.20690.2036-0.3023-0.3551-0.0805-0.0137-0.1222
Lag 3NaNNaNNaN-0.10590.2179-0.1499-0.391-0.4546-0.1654-0.3285...-0.19420.18140.02180.13860.0686-0.0515-0.429-0.2754-0.1929-0.0137
AMZNLag 1NaN-0.13630.0437-0.0670.0255-0.0038-0.1141-0.0455-0.04380.0408...-0.0084-0.00470.0559-0.001-0.04270.0814-0.16830.10630.01790.0
Lag 2NaNNaN-0.0985-0.0262-0.04320.0217-0.1174-0.1544-0.0873-0.0049...-0.0632-0.0130.0510.0549-0.04360.0353-0.1005-0.07980.12610.0179
Lag 3NaNNaNNaN-0.1589-0.0013-0.0468-0.0949-0.1576-0.1915-0.0501...-0.025-0.06750.04220.050.00990.0343-0.1389-0.0049-0.06340.1261
METALag 1NaNNaNNaNNaNNaNNaN-0.1131.09130.1094-0.2086...0.06380.0794-0.443-0.38850.1481-0.3755-0.30150.21220.11490.0
Lag 2NaNNaNNaNNaNNaNNaNNaN0.8551.3201-0.122...0.27250.1483-0.3988-0.6594-0.2979-0.283-0.5638-0.15320.35150.1149
Lag 3NaNNaNNaNNaNNaNNaNNaNNaN1.05790.8361...0.0070.3736-0.3604-0.6323-0.6089-0.5615-0.4992-0.4712-0.05590.3515
WMTLag 1NaN-0.00240.0037-0.08850.0762-0.02140.0263-0.0058-0.05420.0572...-0.0387-0.0754-0.11850.0514-0.00550.2236-0.0456-0.11560.0138-0.011
Lag 2NaNNaN0.0013-0.0851-0.01910.05310.00430.0204-0.0596-0.0001...0.0565-0.1111-0.1849-0.07310.04560.21690.1677-0.1559-0.10340.0026
Lag 3NaNNaNNaN-0.0874-0.0155-0.04010.0808-0.0015-0.0349-0.0059...0.117-0.0231-0.2164-0.143-0.07820.27940.16130.0328-0.1443-0.1133
\n", "

12 rows × 21 columns

\n", "
" ], "text/plain": [ "date 2005 2006 2007 2008 2009 2010 2011 2012 \\\n", "AAPL Lag 1 NaN -0.2376 0.0506 0.1163 0.0384 -0.2666 -0.2003 -0.07 \n", " Lag 2 NaN NaN -0.199 0.1728 0.1591 -0.2385 -0.4135 -0.2563 \n", " Lag 3 NaN NaN NaN -0.1059 0.2179 -0.1499 -0.391 -0.4546 \n", "AMZN Lag 1 NaN -0.1363 0.0437 -0.067 0.0255 -0.0038 -0.1141 -0.0455 \n", " Lag 2 NaN NaN -0.0985 -0.0262 -0.0432 0.0217 -0.1174 -0.1544 \n", " Lag 3 NaN NaN NaN -0.1589 -0.0013 -0.0468 -0.0949 -0.1576 \n", "META Lag 1 NaN NaN NaN NaN NaN NaN -0.113 1.0913 \n", " Lag 2 NaN NaN NaN NaN NaN NaN NaN 0.855 \n", " Lag 3 NaN NaN NaN NaN NaN NaN NaN NaN \n", "WMT Lag 1 NaN -0.0024 0.0037 -0.0885 0.0762 -0.0214 0.0263 -0.0058 \n", " Lag 2 NaN NaN 0.0013 -0.0851 -0.0191 0.0531 0.0043 0.0204 \n", " Lag 3 NaN NaN NaN -0.0874 -0.0155 -0.0401 0.0808 -0.0015 \n", "\n", "date 2013 2014 ... 2016 2017 2018 2019 2020 \\\n", "AAPL Lag 1 0.1222 -0.3566 ... 0.22 -0.0566 -0.1122 0.3594 -0.1146 \n", " Lag 2 0.0436 -0.2779 ... 0.2523 0.1509 -0.1625 0.2069 0.2036 \n", " Lag 3 -0.1654 -0.3285 ... -0.1942 0.1814 0.0218 0.1386 0.0686 \n", "AMZN Lag 1 -0.0438 0.0408 ... -0.0084 -0.0047 0.0559 -0.001 -0.0427 \n", " Lag 2 -0.0873 -0.0049 ... -0.0632 -0.013 0.051 0.0549 -0.0436 \n", " Lag 3 -0.1915 -0.0501 ... -0.025 -0.0675 0.0422 0.05 0.0099 \n", "META Lag 1 0.1094 -0.2086 ... 0.0638 0.0794 -0.443 -0.3885 0.1481 \n", " Lag 2 1.3201 -0.122 ... 0.2725 0.1483 -0.3988 -0.6594 -0.2979 \n", " Lag 3 1.0579 0.8361 ... 0.007 0.3736 -0.3604 -0.6323 -0.6089 \n", "WMT Lag 1 -0.0542 0.0572 ... -0.0387 -0.0754 -0.1185 0.0514 -0.0055 \n", " Lag 2 -0.0596 -0.0001 ... 0.0565 -0.1111 -0.1849 -0.0731 0.0456 \n", " Lag 3 -0.0349 -0.0059 ... 0.117 -0.0231 -0.2164 -0.143 -0.0782 \n", "\n", "date 2021 2022 2023 2024 2025 \n", "AAPL Lag 1 -0.212 -0.1817 0.1236 -0.1222 0.0 \n", " Lag 2 -0.3023 -0.3551 -0.0805 -0.0137 -0.1222 \n", " Lag 3 -0.0515 -0.429 -0.2754 -0.1929 -0.0137 \n", "AMZN Lag 1 0.0814 -0.1683 0.1063 0.0179 0.0 \n", " Lag 2 0.0353 -0.1005 -0.0798 0.1261 0.0179 \n", " Lag 3 0.0343 -0.1389 -0.0049 -0.0634 0.1261 \n", "META Lag 1 -0.3755 -0.3015 0.2122 0.1149 0.0 \n", " Lag 2 -0.283 -0.5638 -0.1532 0.3515 0.1149 \n", " Lag 3 -0.5615 -0.4992 -0.4712 -0.0559 0.3515 \n", "WMT Lag 1 0.2236 -0.0456 -0.1156 0.0138 -0.011 \n", " Lag 2 0.2169 0.1677 -0.1559 -0.1034 0.0026 \n", " Lag 3 0.2794 0.1613 0.0328 -0.1443 -0.1133 \n", "\n", "[12 rows x 21 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.get_current_ratio(growth=True, lag=[1, 2, 3])" ] }, { "cell_type": "markdown", "id": "4408750c", "metadata": {}, "source": [ "It is also possible to get trailing results. E.g. the TTM Earnings per Share ratio can be acquired by setting trailing to 4 (quarters). Note that this does not lead to meaningful results when using yearly data and therefore this image now shows the 4 year trailing result. Set `quarterly=True` in the Toolkit initialization to use quarterly data." ] }, { "cell_type": "code", "execution_count": 8, "id": "f28ffcb0", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "companies.ratios.get_earnings_per_share(trailing=4).T.dropna().plot(\n", " figsize=(15, 3),\n", " title=\"4 Year Trailing Earnings per Share for Apple, Amazon, META and Walmart\",\n", " grid=True,\n", " linestyle=\"-\",\n", " linewidth=2,\n", " xlabel=\"Date\",\n", " ylabel=\"Earnings per Share\",\n", ")\n", "\n", "companies.ratios.get_earnings_per_share(trailing=4, growth=True).T.dropna().plot(\n", " figsize=(15, 3),\n", " title=\"4 Year Trailing Earnings per Share Growth for Apple, Amazon, META and Walmart\",\n", " grid=True,\n", " linestyle=\"-\",\n", " linewidth=2,\n", " xlabel=\"Date\",\n", " ylabel=\"Earnings per Share Growth\",\n", ")" ] }, { "cell_type": "markdown", "id": "658d7f7b", "metadata": {}, "source": [ "It is possible to define custom ratios if the current ratio calculations are not sufficient. Define how each custom ratio needs to be calculated. This can be any of the following structures:\n", "\n", "- **Simple operations such as:** `'Quick Assets': 'Cash and Short Term Investments + Accounts Receivable'`\n", "- **Working with multiple operations:** `'Cash Op Expenses':'Cost of Goods Sold + Selling, General and Administrative Expenses - Depreciation and Amortization'`,\n", "- **Using curly brackets:** `'WC / Net Income as %': '(Working Capital / Net Income) * 100'`,\n", "- **Defining a criteria:** `'Large Revenues': 'Revenue > 1000000000'`,\n", "- **Using actual numbers:** `'Daily Cash Op Expenses': 'Cash Op Expenses / 365'`,\n", "- **Combining earlier defined formulas:** `'Defensive Interval':'Quick Assets / Daily Cash Op Expenses'`\n", "\n", "Not that it is important you follow the NAME - FORMULA format and that you adhere to the financial statement naming. See some of the available fields you can use below, shrunken down for readability." ] }, { "cell_type": "code", "execution_count": 9, "id": "ee2da2f7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2025-09-09 16:40:22 - financetoolkit - INFO - The following names are available to be used in the Custom Ratios calculations.\n" ] }, { "data": { "text/plain": [ "['Asset Turnover Ratio',\n", " 'Book Value per Share',\n", " 'CAPEX Coverage Ratio',\n", " 'CAPEX per Share',\n", " 'Capital Expenditure']" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_custom_ratios(options=True)[10:15]" ] }, { "cell_type": "markdown", "id": "19853ba6", "metadata": {}, "source": [ "Then create your custom ratios and add them to custom ratios function." ] }, { "cell_type": "code", "execution_count": 10, "id": "1fe66edb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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2005200620072008200920102011201220132014...2016201720182019202020212022202320242025
AAPLWC / Net Income as %513.0271405.5304362.6896385.7054243.4608149.546865.650845.793579.995712.8651...60.986757.560325.8857103.33966.74859.8807-18.6137-1.796-24.9691NaN
Large Revenues1.01.01.01.01.01.01.01.01.01.0...1.01.01.01.01.01.01.01.01.00.0
Quick Assets9156000000.011362000000.017023000000.024533000000.026825000000.031130000000.031321000000.040059000000.053648000000.042537000000.0...82909000000.092055000000.089487000000.0123483000000.0107063000000.088917000000.076488000000.091063000000.098581000000.0NaN
Cash Op Expenses11574000000.015925000000.018498000000.024686000000.029098000000.044031000000.070216000000.094609000000.0110679000000.0116305000000.0...135065000000.0146152000000.0169558000000.0167480000000.0178419000000.0223670000000.0237536000000.0227550000000.0225004000000.0NaN
Daily Cash Op Expenses31709589.041143630136.986350679452.054867632876.712379720547.9452120632876.7123192372602.7397259202739.726303230136.9863318643835.6164...370041095.8904400416438.3562464542465.7534458849315.0685488819178.0822612794520.5479650783561.6438623424657.5342616449315.0685NaN
Defensive Interval288.7455260.4163335.8955362.7378336.4879258.0557162.8142154.547176.9217133.4939...224.0535229.8982192.6347269.1145219.0237145.1008117.5322146.069159.9174NaN
AMZNWC / Net Income as %286.9081442.6316304.6218218.7597269.7339292.9688411.0935-5882.0513600.365-1343.5685...82.876476.294166.613773.541629.759557.8887316.017624.433919.3019NaN
Large Revenues1.01.01.01.01.01.01.01.01.01.0...1.01.01.01.01.01.01.01.01.00.0
Quick Assets2274000000.02418000000.04522000000.05381000000.07354000000.010349000000.012147000000.015265000000.017214000000.023028000000.0...34320000000.044150000000.057927000000.075837000000.0108938000000.0128940000000.0112386000000.0139033000000.0156653000000.0NaN
Cash Op Expenses6694000000.08508000000.011815000000.015370000000.019608000000.027492000000.038493000000.047116000000.055190000000.063890000000.0...89814000000.0114199000000.0141965000000.0167828000000.0236803000000.0279285000000.0301039000000.0312262000000.0328759000000.0NaN
Daily Cash Op Expenses18339726.027423309589.041132369863.013742109589.041153720547.945275320547.9452105460273.9726129084931.5068151205479.4521175041095.8904...246065753.4247312873972.6027388945205.4795459802739.726648775342.4658765164383.5616824764383.5616855512328.7671900709589.0411NaN
Defensive Interval123.9931103.7341139.6978127.7856136.8936137.3994115.1808118.2555113.8451131.5577...139.4749141.1111148.9336164.9338167.9133168.5128136.2644162.5143173.9218NaN
METAWC / Net Income as %NaNNaNNaNNaNNaN461.9403370.519273.5849798.0407.0068...308.5642281.1786196.5673276.8299208.2241115.649140.1853136.5927106.5571NaN
Large Revenues0.00.00.00.00.01.01.01.01.01.0...1.01.01.01.01.01.01.01.01.00.0
Quick AssetsNaNNaNNaNNaNNaN2158000000.04455000000.010345000000.012558000000.012877000000.0...33442000000.047543000000.048701000000.064373000000.073289000000.062037000000.054204000000.081572000000.094809000000.0NaN
Cash Op ExpensesNaNNaN196000000.0280000000.0350000000.0659000000.01244000000.02503000000.02642000000.03563000000.0...6950000000.09671000000.016337000000.027370000000.027985000000.038554000000.043641000000.038490000000.035750000000.0NaN
Daily Cash Op ExpensesNaNNaN536986.3014767123.2877958904.10961805479.45213408219.17816857534.24667238356.16449761643.8356...19041095.890426495890.41144758904.109674986301.369976671232.8767105627397.2603119564383.5616105452054.794597945205.4795NaN
Defensive IntervalNaNNaNNaNNaNNaN1195.25041307.13421508.55971734.92431319.1426...1756.30651794.35371088.074858.4635955.8865587.3192453.3457773.5459967.98NaN
WMTWC / Net Income as %-42.1545-44.5196-45.7816-82.1459-48.1354-52.2686-40.216-46.659-69.8747-50.93...-29.8081-67.7197-191.2087-233.5832-107.4121-19.0822-46.142-141.6353-100.1741-88.1148
Large Revenues1.01.01.01.01.01.01.01.01.01.0...1.01.01.01.01.01.01.01.01.01.0
Quick Assets7203000000.08768000000.010607000000.09134000000.011180000000.012051000000.012484000000.012487000000.014549000000.013958000000.0...14329000000.012702000000.012370000000.014005000000.015749000000.024257000000.023040000000.016558000000.018663000000.019012000000.0
Cash Op Expenses266713000000.0288671000000.0322694000000.0350486000000.0376070000000.0377107000000.0388666000000.0412262000000.0432860000000.0440552000000.0...448571000000.0453029000000.0469377000000.0481770000000.0492409000000.0525451000000.0536154000000.0579916000000.0609260000000.0638664000000.0
Daily Cash Op Expenses730720547.9452790879452.0548884093150.6849960235616.43841030328767.12331033169863.01371064838356.16441129484931.50681185917808.21921206991780.8219...1228961643.83561241175342.46581285964383.56161319917808.21921349065753.42471439591780.82191468915068.49321588810958.90411669205479.45211749764383.5616
Defensive Interval9.857411.086411.99769.512210.850911.664111.723811.055512.268111.5643...11.659410.23389.619210.610511.67416.849915.68510.421611.180810.8655
\n", "

24 rows × 21 columns

\n", "
" ], "text/plain": [ " 2005 2006 2007 \\\n", "AAPL WC / Net Income as % 513.0271 405.5304 362.6896 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 9156000000.0 11362000000.0 17023000000.0 \n", " Cash Op Expenses 11574000000.0 15925000000.0 18498000000.0 \n", " Daily Cash Op Expenses 31709589.0411 43630136.9863 50679452.0548 \n", " Defensive Interval 288.7455 260.4163 335.8955 \n", "AMZN WC / Net Income as % 286.9081 442.6316 304.6218 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 2274000000.0 2418000000.0 4522000000.0 \n", " Cash Op Expenses 6694000000.0 8508000000.0 11815000000.0 \n", " Daily Cash Op Expenses 18339726.0274 23309589.0411 32369863.0137 \n", " Defensive Interval 123.9931 103.7341 139.6978 \n", "META WC / Net Income as % NaN NaN NaN \n", " Large Revenues 0.0 0.0 0.0 \n", " Quick Assets NaN NaN NaN \n", " Cash Op Expenses NaN NaN 196000000.0 \n", " Daily Cash Op Expenses NaN NaN 536986.3014 \n", " Defensive Interval NaN NaN NaN \n", "WMT WC / Net Income as % -42.1545 -44.5196 -45.7816 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 7203000000.0 8768000000.0 10607000000.0 \n", " Cash Op Expenses 266713000000.0 288671000000.0 322694000000.0 \n", " Daily Cash Op Expenses 730720547.9452 790879452.0548 884093150.6849 \n", " Defensive Interval 9.8574 11.0864 11.9976 \n", "\n", " 2008 2009 2010 \\\n", "AAPL WC / Net Income as % 385.7054 243.4608 149.5468 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 24533000000.0 26825000000.0 31130000000.0 \n", " Cash Op Expenses 24686000000.0 29098000000.0 44031000000.0 \n", " Daily Cash Op Expenses 67632876.7123 79720547.9452 120632876.7123 \n", " Defensive Interval 362.7378 336.4879 258.0557 \n", "AMZN WC / Net Income as % 218.7597 269.7339 292.9688 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 5381000000.0 7354000000.0 10349000000.0 \n", " Cash Op Expenses 15370000000.0 19608000000.0 27492000000.0 \n", " Daily Cash Op Expenses 42109589.0411 53720547.9452 75320547.9452 \n", " Defensive Interval 127.7856 136.8936 137.3994 \n", "META WC / Net Income as % NaN NaN 461.9403 \n", " Large Revenues 0.0 0.0 1.0 \n", " Quick Assets NaN NaN 2158000000.0 \n", " Cash Op Expenses 280000000.0 350000000.0 659000000.0 \n", " Daily Cash Op Expenses 767123.2877 958904.1096 1805479.4521 \n", " Defensive Interval NaN NaN 1195.2504 \n", "WMT WC / Net Income as % -82.1459 -48.1354 -52.2686 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 9134000000.0 11180000000.0 12051000000.0 \n", " Cash Op Expenses 350486000000.0 376070000000.0 377107000000.0 \n", " Daily Cash Op Expenses 960235616.4384 1030328767.1233 1033169863.0137 \n", " Defensive Interval 9.5122 10.8509 11.6641 \n", "\n", " 2011 2012 2013 \\\n", "AAPL WC / Net Income as % 65.6508 45.7935 79.9957 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 31321000000.0 40059000000.0 53648000000.0 \n", " Cash Op Expenses 70216000000.0 94609000000.0 110679000000.0 \n", " Daily Cash Op Expenses 192372602.7397 259202739.726 303230136.9863 \n", " Defensive Interval 162.8142 154.547 176.9217 \n", "AMZN WC / Net Income as % 411.0935 -5882.0513 600.365 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12147000000.0 15265000000.0 17214000000.0 \n", " Cash Op Expenses 38493000000.0 47116000000.0 55190000000.0 \n", " Daily Cash Op Expenses 105460273.9726 129084931.5068 151205479.4521 \n", " Defensive Interval 115.1808 118.2555 113.8451 \n", "META WC / Net Income as % 370.5 19273.5849 798.0 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 4455000000.0 10345000000.0 12558000000.0 \n", " Cash Op Expenses 1244000000.0 2503000000.0 2642000000.0 \n", " Daily Cash Op Expenses 3408219.1781 6857534.2466 7238356.1644 \n", " Defensive Interval 1307.1342 1508.5597 1734.9243 \n", "WMT WC / Net Income as % -40.216 -46.659 -69.8747 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12484000000.0 12487000000.0 14549000000.0 \n", " Cash Op Expenses 388666000000.0 412262000000.0 432860000000.0 \n", " Daily Cash Op Expenses 1064838356.1644 1129484931.5068 1185917808.2192 \n", " Defensive Interval 11.7238 11.0555 12.2681 \n", "\n", " 2014 ... 2016 \\\n", "AAPL WC / Net Income as % 12.8651 ... 60.9867 \n", " Large Revenues 1.0 ... 1.0 \n", " Quick Assets 42537000000.0 ... 82909000000.0 \n", " Cash Op Expenses 116305000000.0 ... 135065000000.0 \n", " Daily Cash Op Expenses 318643835.6164 ... 370041095.8904 \n", " Defensive Interval 133.4939 ... 224.0535 \n", "AMZN WC / Net Income as % -1343.5685 ... 82.8764 \n", " Large Revenues 1.0 ... 1.0 \n", " Quick Assets 23028000000.0 ... 34320000000.0 \n", " Cash Op Expenses 63890000000.0 ... 89814000000.0 \n", " Daily Cash Op Expenses 175041095.8904 ... 246065753.4247 \n", " Defensive Interval 131.5577 ... 139.4749 \n", "META WC / Net Income as % 407.0068 ... 308.5642 \n", " Large Revenues 1.0 ... 1.0 \n", " Quick Assets 12877000000.0 ... 33442000000.0 \n", " Cash Op Expenses 3563000000.0 ... 6950000000.0 \n", " Daily Cash Op Expenses 9761643.8356 ... 19041095.8904 \n", " Defensive Interval 1319.1426 ... 1756.3065 \n", "WMT WC / Net Income as % -50.93 ... -29.8081 \n", " Large Revenues 1.0 ... 1.0 \n", " Quick Assets 13958000000.0 ... 14329000000.0 \n", " Cash Op Expenses 440552000000.0 ... 448571000000.0 \n", " Daily Cash Op Expenses 1206991780.8219 ... 1228961643.8356 \n", " Defensive Interval 11.5643 ... 11.6594 \n", "\n", " 2017 2018 2019 \\\n", "AAPL WC / Net Income as % 57.5603 25.8857 103.339 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 92055000000.0 89487000000.0 123483000000.0 \n", " Cash Op Expenses 146152000000.0 169558000000.0 167480000000.0 \n", " Daily Cash Op Expenses 400416438.3562 464542465.7534 458849315.0685 \n", " Defensive Interval 229.8982 192.6347 269.1145 \n", "AMZN WC / Net Income as % 76.2941 66.6137 73.5416 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 44150000000.0 57927000000.0 75837000000.0 \n", " Cash Op Expenses 114199000000.0 141965000000.0 167828000000.0 \n", " Daily Cash Op Expenses 312873972.6027 388945205.4795 459802739.726 \n", " Defensive Interval 141.1111 148.9336 164.9338 \n", "META WC / Net Income as % 281.1786 196.5673 276.8299 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 47543000000.0 48701000000.0 64373000000.0 \n", " Cash Op Expenses 9671000000.0 16337000000.0 27370000000.0 \n", " Daily Cash Op Expenses 26495890.411 44758904.1096 74986301.3699 \n", " Defensive Interval 1794.3537 1088.074 858.4635 \n", "WMT WC / Net Income as % -67.7197 -191.2087 -233.5832 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12702000000.0 12370000000.0 14005000000.0 \n", " Cash Op Expenses 453029000000.0 469377000000.0 481770000000.0 \n", " Daily Cash Op Expenses 1241175342.4658 1285964383.5616 1319917808.2192 \n", " Defensive Interval 10.2338 9.6192 10.6105 \n", "\n", " 2020 2021 2022 \\\n", "AAPL WC / Net Income as % 66.7485 9.8807 -18.6137 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 107063000000.0 88917000000.0 76488000000.0 \n", " Cash Op Expenses 178419000000.0 223670000000.0 237536000000.0 \n", " Daily Cash Op Expenses 488819178.0822 612794520.5479 650783561.6438 \n", " Defensive Interval 219.0237 145.1008 117.5322 \n", "AMZN WC / Net Income as % 29.7595 57.8887 316.0176 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 108938000000.0 128940000000.0 112386000000.0 \n", " Cash Op Expenses 236803000000.0 279285000000.0 301039000000.0 \n", " Daily Cash Op Expenses 648775342.4658 765164383.5616 824764383.5616 \n", " Defensive Interval 167.9133 168.5128 136.2644 \n", "META WC / Net Income as % 208.2241 115.649 140.1853 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 73289000000.0 62037000000.0 54204000000.0 \n", " Cash Op Expenses 27985000000.0 38554000000.0 43641000000.0 \n", " Daily Cash Op Expenses 76671232.8767 105627397.2603 119564383.5616 \n", " Defensive Interval 955.8865 587.3192 453.3457 \n", "WMT WC / Net Income as % -107.4121 -19.0822 -46.142 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 15749000000.0 24257000000.0 23040000000.0 \n", " Cash Op Expenses 492409000000.0 525451000000.0 536154000000.0 \n", " Daily Cash Op Expenses 1349065753.4247 1439591780.8219 1468915068.4932 \n", " Defensive Interval 11.674 16.8499 15.685 \n", "\n", " 2023 2024 2025 \n", "AAPL WC / Net Income as % -1.796 -24.9691 NaN \n", " Large Revenues 1.0 1.0 0.0 \n", " Quick Assets 91063000000.0 98581000000.0 NaN \n", " Cash Op Expenses 227550000000.0 225004000000.0 NaN \n", " Daily Cash Op Expenses 623424657.5342 616449315.0685 NaN \n", " Defensive Interval 146.069 159.9174 NaN \n", "AMZN WC / Net Income as % 24.4339 19.3019 NaN \n", " Large Revenues 1.0 1.0 0.0 \n", " Quick Assets 139033000000.0 156653000000.0 NaN \n", " Cash Op Expenses 312262000000.0 328759000000.0 NaN \n", " Daily Cash Op Expenses 855512328.7671 900709589.0411 NaN \n", " Defensive Interval 162.5143 173.9218 NaN \n", "META WC / Net Income as % 136.5927 106.5571 NaN \n", " Large Revenues 1.0 1.0 0.0 \n", " Quick Assets 81572000000.0 94809000000.0 NaN \n", " Cash Op Expenses 38490000000.0 35750000000.0 NaN \n", " Daily Cash Op Expenses 105452054.7945 97945205.4795 NaN \n", " Defensive Interval 773.5459 967.98 NaN \n", "WMT WC / Net Income as % -141.6353 -100.1741 -88.1148 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 16558000000.0 18663000000.0 19012000000.0 \n", " Cash Op Expenses 579916000000.0 609260000000.0 638664000000.0 \n", " Daily Cash Op Expenses 1588810958.9041 1669205479.4521 1749764383.5616 \n", " Defensive Interval 10.4216 11.1808 10.8655 \n", "\n", "[24 rows x 21 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "custom_ratios = {\n", " \"WC / Net Income as %\": \"(Working Capital / Net Income) * 100\",\n", " \"Large Revenues\": \"Revenue > 1000000000\",\n", " \"Quick Assets\": \"Cash and Short Term Investments + Accounts Receivable\",\n", " \"Cash Op Expenses\": \"Cost of Goods Sold + Selling, General and Administrative Expenses \"\n", " \"- Depreciation and Amortization\",\n", " \"Daily Cash Op Expenses\": \"Cash Op Expenses / 365\",\n", " \"Defensive Interval\": \"Quick Assets / Daily Cash Op Expenses\",\n", "}\n", "\n", "companies.ratios.collect_custom_ratios(custom_ratios_dict=custom_ratios)" ] }, { "cell_type": "markdown", "id": "4306cd49", "metadata": {}, "source": [ "It is also relatively straight forward to use the actual models provided you have the data available to flow through these functions. While the `Toolkit` class itself parses data from Financial Modeling Prep, if you utilize the individual models you can provide your own data as well while reaching the same results." ] }, { "cell_type": "code", "execution_count": 11, "id": "c38bb4b6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Asset TurnoverQuick RatioReturn on AssetsDebt to AssetsPrice to Earnings
00.21.23076923076923080.53333333333333330.560.0
10.2751.16666666666666670.20.785714285714285727.5
20.41.63636363636363650.133333333333333330.75120.0
30.651.13333333333333330.0750.81259.09090909090909
40.81.60.040.2666666666666666625.0
\n", "
" ], "text/plain": [ " Asset Turnover Quick Ratio Return on Assets Debt to Assets \\\n", "0 0.2 1.2307692307692308 0.5333333333333333 0.5 \n", "1 0.275 1.1666666666666667 0.2 0.7857142857142857 \n", "2 0.4 1.6363636363636365 0.13333333333333333 0.75 \n", "3 0.65 1.1333333333333333 0.075 0.8125 \n", "4 0.8 1.6 0.04 0.26666666666666666 \n", "\n", " Price to Earnings \n", "0 60.0 \n", "1 27.5 \n", "2 120.0 \n", "3 9.09090909090909 \n", "4 25.0 " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from financetoolkit.ratios import (\n", " efficiency_model,\n", " liquidity_model,\n", " profitability_model,\n", " solvency_model,\n", " valuation_model,\n", ")\n", "\n", "# Note: this is dummy data, not actual data\n", "\n", "asset_turnover = efficiency_model.get_asset_turnover_ratio(\n", " sales=pd.Series([100, 110, 120, 130, 80]),\n", " average_total_assets=pd.Series([500, 400, 300, 200, 100]),\n", ")\n", "\n", "quick_ratio = liquidity_model.get_quick_ratio(\n", " cash_and_equivalents=pd.Series([100, 110, 120, 130, 80]),\n", " accounts_receivable=pd.Series([30, 20, 30, 20, 40]),\n", " marketable_securities=pd.Series([30, 10, 30, 20, 40]),\n", " current_liabilities=pd.Series([130, 120, 110, 150, 100]),\n", ")\n", "\n", "return_on_assets = profitability_model.get_return_on_assets(\n", " net_income=pd.Series([80, 40, 40, 30, 20]),\n", " average_total_assets=pd.Series([150, 200, 300, 400, 500]),\n", ")\n", "\n", "debt_to_assets = solvency_model.get_debt_to_assets_ratio(\n", " total_debt=pd.Series([100, 110, 120, 130, 80]),\n", " total_assets=pd.Series([200, 140, 160, 160, 300]),\n", ")\n", "\n", "price_to_earnings = valuation_model.get_price_to_earnings_ratio(\n", " stock_price=pd.Series([30, 11, 12, 10, 30]),\n", " earnings_per_share=pd.Series([0.5, 0.4, 0.1, 1.1, 1.2]),\n", ")\n", "\n", "components = {\n", " \"Asset Turnover\": asset_turnover,\n", " \"Quick Ratio\": quick_ratio,\n", " \"Return on Assets\": return_on_assets,\n", " \"Debt to Assets\": debt_to_assets,\n", " \"Price to Earnings\": price_to_earnings,\n", "}\n", "\n", "\n", "pd.DataFrame(components)" ] } ], "metadata": { "kernelspec": { "display_name": "financetoolkit-rvLLqrVB-py3.12", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.1" } }, "nbformat": 4, "nbformat_minor": 5 }