{ "cells": [ { "cell_type": "markdown", "id": "f78e12b6", "metadata": {}, "source": [ "![Finance Toolkit](https://github.com/JerBouma/FinanceToolkit/assets/46355364/198d47bd-e1b3-492d-acc4-5d9f02d1d009)\n", "\n", "The Finance Toolkit can take in any dataset which means it works very well with the software and APIs from any other provider let is be Intrinio, OpenBB, Yahoo Finance, Quandl, etc. For this illustration, I have collected custom statements and have imported them as a CSV file but as you can imagine this would also work with direct API calls. This dataset is obtained from Yahoo Finance, which can be collected via `yfinance`. Note that the `yfinance` library is not part of the Finance Toolkit and needs to be installed separately." ] }, { "cell_type": "code", "execution_count": 1, "id": "b256daa1", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "\n", "from financetoolkit import Toolkit" ] }, { "cell_type": "markdown", "id": "9e6cf4ea", "metadata": {}, "source": [ "First, let's read in the custom dataset obtained from Yahoo Finance." ] }, { "cell_type": "code", "execution_count": 2, "id": "2bcdac0d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
2024-12-312023-12-312022-12-312021-12-312020-12-31
TaxEffectOfUnusualItems-1.368000e+080.000000e+00-1.408000e+072.970000e+06NaN
TaxRateForCalcs2.000000e-012.100000e-018.000000e-021.100000e-01NaN
NormalizedEBITDA1.539200e+101.479600e+101.783300e+109.598000e+09NaN
TotalUnusualItems-6.840000e+080.000000e+00-1.760000e+082.700000e+07NaN
TotalUnusualItemsExcludingGoodwill-6.840000e+080.000000e+00-1.760000e+082.700000e+07NaN
NetIncomeFromContinuingOperationNetMinorityInterest7.130000e+091.499900e+101.258300e+105.524000e+09NaN
ReconciledDepreciation5.368000e+094.667000e+093.747000e+092.911000e+09NaN
ReconciledCostOfRevenue8.024000e+107.911300e+106.060900e+104.021700e+10NaN
EBITDA1.470800e+101.479600e+101.765700e+109.625000e+09NaN
EBIT9.340000e+091.012900e+101.391000e+106.714000e+09NaN
NetInterestIncome1.219000e+099.100000e+081.060000e+08-3.150000e+08NaN
InterestExpense3.500000e+081.560000e+081.910000e+083.710000e+08NaN
InterestIncome1.569000e+091.066000e+092.970000e+085.600000e+07NaN
NormalizedIncome7.677200e+091.499900e+101.274492e+105.499970e+09NaN
NetIncomeFromContinuingAndDiscontinuedOperation7.130000e+091.499900e+101.258300e+105.524000e+09NaN
TotalExpenses8.993000e+108.788200e+106.763000e+104.732700e+10NaN
RentExpenseSupplemental1.003000e+091.268000e+091.509000e+099.780000e+08NaN
TotalOperatingIncomeAsReported7.076000e+098.891000e+091.365600e+106.523000e+09NaN
DilutedAverageShares3.498000e+093.482750e+093.475000e+093.386000e+09NaN
BasicAverageShares3.197000e+093.173500e+093.130000e+092.959000e+09NaN
DilutedEPS2.040000e+004.310000e+003.620000e+001.630000e+00NaN
BasicEPS2.230000e+004.725697e+004.020000e+001.870000e+00NaN
DilutedNIAvailtoComStockholders7.130000e+091.499900e+101.258400e+105.533000e+09NaN
AverageDilutionEarnings0.000000e+000.000000e+001.000000e+069.000000e+06NaN
NetIncomeCommonStockholders7.130000e+091.499900e+101.258300e+105.524000e+09NaN
OtherunderPreferredStockDividendNaNNaNNaN-5.000000e+0631000000.0
NetIncome7.130000e+091.499900e+101.258300e+105.524000e+09NaN
MinorityInterests-2.300000e+072.500000e+07-4.000000e+06-1.200000e+08NaN
NetIncomeIncludingNoncontrollingInterests7.153000e+091.497400e+101.258700e+105.644000e+09NaN
NetIncomeContinuousOperations7.153000e+091.497400e+101.258700e+105.644000e+09NaN
TaxProvision1.837000e+09-5.001000e+091.132000e+096.990000e+08NaN
PretaxIncome8.990000e+099.973000e+091.371900e+106.343000e+09NaN
OtherIncomeExpense1.100000e+071.720000e+08-2.190000e+081.620000e+08NaN
OtherNonOperatingIncomeExpenses6.950000e+081.720000e+08-4.300000e+071.350000e+08NaN
SpecialIncomeCharges-6.840000e+080.000000e+00-1.760000e+082.700000e+07NaN
RestructuringAndMergernAcquisition6.840000e+080.000000e+001.760000e+08-2.700000e+07NaN
NetNonOperatingInterestIncomeExpense1.219000e+099.100000e+081.060000e+08-3.150000e+08NaN
InterestExpenseNonOperating3.500000e+081.560000e+081.910000e+083.710000e+08NaN
InterestIncomeNonOperating1.569000e+091.066000e+092.970000e+085.600000e+07NaN
OperatingIncome7.760000e+098.891000e+091.383200e+106.496000e+09NaN
OperatingExpense9.690000e+098.769000e+097.021000e+097.110000e+09NaN
ResearchAndDevelopment4.540000e+093.969000e+093.075000e+092.593000e+09NaN
SellingGeneralAndAdministration5.150000e+094.800000e+093.946000e+094.517000e+09NaN
GrossProfit1.745000e+101.766000e+102.085300e+101.360600e+10NaN
CostOfRevenue8.024000e+107.911300e+106.060900e+104.021700e+10NaN
TotalRevenue9.769000e+109.677300e+108.146200e+105.382300e+10NaN
OperatingRevenue9.769000e+109.677300e+108.146200e+105.382300e+10NaN
\n", "
" ], "text/plain": [ " 2024-12-31 \\\n", "TaxEffectOfUnusualItems -1.368000e+08 \n", "TaxRateForCalcs 2.000000e-01 \n", "NormalizedEBITDA 1.539200e+10 \n", "TotalUnusualItems -6.840000e+08 \n", "TotalUnusualItemsExcludingGoodwill -6.840000e+08 \n", "NetIncomeFromContinuingOperationNetMinorityInte... 7.130000e+09 \n", "ReconciledDepreciation 5.368000e+09 \n", "ReconciledCostOfRevenue 8.024000e+10 \n", "EBITDA 1.470800e+10 \n", "EBIT 9.340000e+09 \n", "NetInterestIncome 1.219000e+09 \n", "InterestExpense 3.500000e+08 \n", "InterestIncome 1.569000e+09 \n", "NormalizedIncome 7.677200e+09 \n", "NetIncomeFromContinuingAndDiscontinuedOperation 7.130000e+09 \n", "TotalExpenses 8.993000e+10 \n", "RentExpenseSupplemental 1.003000e+09 \n", "TotalOperatingIncomeAsReported 7.076000e+09 \n", "DilutedAverageShares 3.498000e+09 \n", "BasicAverageShares 3.197000e+09 \n", "DilutedEPS 2.040000e+00 \n", "BasicEPS 2.230000e+00 \n", "DilutedNIAvailtoComStockholders 7.130000e+09 \n", "AverageDilutionEarnings 0.000000e+00 \n", "NetIncomeCommonStockholders 7.130000e+09 \n", "OtherunderPreferredStockDividend NaN \n", "NetIncome 7.130000e+09 \n", "MinorityInterests -2.300000e+07 \n", "NetIncomeIncludingNoncontrollingInterests 7.153000e+09 \n", "NetIncomeContinuousOperations 7.153000e+09 \n", "TaxProvision 1.837000e+09 \n", "PretaxIncome 8.990000e+09 \n", "OtherIncomeExpense 1.100000e+07 \n", "OtherNonOperatingIncomeExpenses 6.950000e+08 \n", "SpecialIncomeCharges -6.840000e+08 \n", "RestructuringAndMergernAcquisition 6.840000e+08 \n", "NetNonOperatingInterestIncomeExpense 1.219000e+09 \n", "InterestExpenseNonOperating 3.500000e+08 \n", "InterestIncomeNonOperating 1.569000e+09 \n", "OperatingIncome 7.760000e+09 \n", "OperatingExpense 9.690000e+09 \n", "ResearchAndDevelopment 4.540000e+09 \n", "SellingGeneralAndAdministration 5.150000e+09 \n", "GrossProfit 1.745000e+10 \n", "CostOfRevenue 8.024000e+10 \n", "TotalRevenue 9.769000e+10 \n", "OperatingRevenue 9.769000e+10 \n", "\n", " 2023-12-31 \\\n", "TaxEffectOfUnusualItems 0.000000e+00 \n", "TaxRateForCalcs 2.100000e-01 \n", "NormalizedEBITDA 1.479600e+10 \n", "TotalUnusualItems 0.000000e+00 \n", "TotalUnusualItemsExcludingGoodwill 0.000000e+00 \n", "NetIncomeFromContinuingOperationNetMinorityInte... 1.499900e+10 \n", "ReconciledDepreciation 4.667000e+09 \n", "ReconciledCostOfRevenue 7.911300e+10 \n", "EBITDA 1.479600e+10 \n", "EBIT 1.012900e+10 \n", "NetInterestIncome 9.100000e+08 \n", "InterestExpense 1.560000e+08 \n", "InterestIncome 1.066000e+09 \n", "NormalizedIncome 1.499900e+10 \n", "NetIncomeFromContinuingAndDiscontinuedOperation 1.499900e+10 \n", "TotalExpenses 8.788200e+10 \n", "RentExpenseSupplemental 1.268000e+09 \n", "TotalOperatingIncomeAsReported 8.891000e+09 \n", "DilutedAverageShares 3.482750e+09 \n", "BasicAverageShares 3.173500e+09 \n", "DilutedEPS 4.310000e+00 \n", "BasicEPS 4.725697e+00 \n", "DilutedNIAvailtoComStockholders 1.499900e+10 \n", "AverageDilutionEarnings 0.000000e+00 \n", "NetIncomeCommonStockholders 1.499900e+10 \n", "OtherunderPreferredStockDividend NaN \n", "NetIncome 1.499900e+10 \n", "MinorityInterests 2.500000e+07 \n", "NetIncomeIncludingNoncontrollingInterests 1.497400e+10 \n", "NetIncomeContinuousOperations 1.497400e+10 \n", "TaxProvision -5.001000e+09 \n", "PretaxIncome 9.973000e+09 \n", "OtherIncomeExpense 1.720000e+08 \n", "OtherNonOperatingIncomeExpenses 1.720000e+08 \n", "SpecialIncomeCharges 0.000000e+00 \n", "RestructuringAndMergernAcquisition 0.000000e+00 \n", "NetNonOperatingInterestIncomeExpense 9.100000e+08 \n", "InterestExpenseNonOperating 1.560000e+08 \n", "InterestIncomeNonOperating 1.066000e+09 \n", "OperatingIncome 8.891000e+09 \n", "OperatingExpense 8.769000e+09 \n", "ResearchAndDevelopment 3.969000e+09 \n", "SellingGeneralAndAdministration 4.800000e+09 \n", "GrossProfit 1.766000e+10 \n", "CostOfRevenue 7.911300e+10 \n", "TotalRevenue 9.677300e+10 \n", "OperatingRevenue 9.677300e+10 \n", "\n", " 2022-12-31 \\\n", "TaxEffectOfUnusualItems -1.408000e+07 \n", "TaxRateForCalcs 8.000000e-02 \n", "NormalizedEBITDA 1.783300e+10 \n", "TotalUnusualItems -1.760000e+08 \n", "TotalUnusualItemsExcludingGoodwill -1.760000e+08 \n", "NetIncomeFromContinuingOperationNetMinorityInte... 1.258300e+10 \n", "ReconciledDepreciation 3.747000e+09 \n", "ReconciledCostOfRevenue 6.060900e+10 \n", "EBITDA 1.765700e+10 \n", "EBIT 1.391000e+10 \n", "NetInterestIncome 1.060000e+08 \n", "InterestExpense 1.910000e+08 \n", "InterestIncome 2.970000e+08 \n", "NormalizedIncome 1.274492e+10 \n", "NetIncomeFromContinuingAndDiscontinuedOperation 1.258300e+10 \n", "TotalExpenses 6.763000e+10 \n", "RentExpenseSupplemental 1.509000e+09 \n", "TotalOperatingIncomeAsReported 1.365600e+10 \n", "DilutedAverageShares 3.475000e+09 \n", "BasicAverageShares 3.130000e+09 \n", "DilutedEPS 3.620000e+00 \n", "BasicEPS 4.020000e+00 \n", "DilutedNIAvailtoComStockholders 1.258400e+10 \n", "AverageDilutionEarnings 1.000000e+06 \n", "NetIncomeCommonStockholders 1.258300e+10 \n", "OtherunderPreferredStockDividend NaN \n", "NetIncome 1.258300e+10 \n", "MinorityInterests -4.000000e+06 \n", "NetIncomeIncludingNoncontrollingInterests 1.258700e+10 \n", "NetIncomeContinuousOperations 1.258700e+10 \n", "TaxProvision 1.132000e+09 \n", "PretaxIncome 1.371900e+10 \n", "OtherIncomeExpense -2.190000e+08 \n", "OtherNonOperatingIncomeExpenses -4.300000e+07 \n", "SpecialIncomeCharges -1.760000e+08 \n", "RestructuringAndMergernAcquisition 1.760000e+08 \n", "NetNonOperatingInterestIncomeExpense 1.060000e+08 \n", "InterestExpenseNonOperating 1.910000e+08 \n", "InterestIncomeNonOperating 2.970000e+08 \n", "OperatingIncome 1.383200e+10 \n", "OperatingExpense 7.021000e+09 \n", "ResearchAndDevelopment 3.075000e+09 \n", "SellingGeneralAndAdministration 3.946000e+09 \n", "GrossProfit 2.085300e+10 \n", "CostOfRevenue 6.060900e+10 \n", "TotalRevenue 8.146200e+10 \n", "OperatingRevenue 8.146200e+10 \n", "\n", " 2021-12-31 2020-12-31 \n", "TaxEffectOfUnusualItems 2.970000e+06 NaN \n", "TaxRateForCalcs 1.100000e-01 NaN \n", "NormalizedEBITDA 9.598000e+09 NaN \n", "TotalUnusualItems 2.700000e+07 NaN \n", "TotalUnusualItemsExcludingGoodwill 2.700000e+07 NaN \n", "NetIncomeFromContinuingOperationNetMinorityInte... 5.524000e+09 NaN \n", "ReconciledDepreciation 2.911000e+09 NaN \n", "ReconciledCostOfRevenue 4.021700e+10 NaN \n", "EBITDA 9.625000e+09 NaN \n", "EBIT 6.714000e+09 NaN \n", "NetInterestIncome -3.150000e+08 NaN \n", "InterestExpense 3.710000e+08 NaN \n", "InterestIncome 5.600000e+07 NaN \n", "NormalizedIncome 5.499970e+09 NaN \n", "NetIncomeFromContinuingAndDiscontinuedOperation 5.524000e+09 NaN \n", "TotalExpenses 4.732700e+10 NaN \n", "RentExpenseSupplemental 9.780000e+08 NaN \n", "TotalOperatingIncomeAsReported 6.523000e+09 NaN \n", "DilutedAverageShares 3.386000e+09 NaN \n", "BasicAverageShares 2.959000e+09 NaN \n", "DilutedEPS 1.630000e+00 NaN \n", "BasicEPS 1.870000e+00 NaN \n", "DilutedNIAvailtoComStockholders 5.533000e+09 NaN \n", "AverageDilutionEarnings 9.000000e+06 NaN \n", "NetIncomeCommonStockholders 5.524000e+09 NaN \n", "OtherunderPreferredStockDividend -5.000000e+06 31000000.0 \n", "NetIncome 5.524000e+09 NaN \n", "MinorityInterests -1.200000e+08 NaN \n", "NetIncomeIncludingNoncontrollingInterests 5.644000e+09 NaN \n", "NetIncomeContinuousOperations 5.644000e+09 NaN \n", "TaxProvision 6.990000e+08 NaN \n", "PretaxIncome 6.343000e+09 NaN \n", "OtherIncomeExpense 1.620000e+08 NaN \n", "OtherNonOperatingIncomeExpenses 1.350000e+08 NaN \n", "SpecialIncomeCharges 2.700000e+07 NaN \n", "RestructuringAndMergernAcquisition -2.700000e+07 NaN \n", "NetNonOperatingInterestIncomeExpense -3.150000e+08 NaN \n", "InterestExpenseNonOperating 3.710000e+08 NaN \n", "InterestIncomeNonOperating 5.600000e+07 NaN \n", "OperatingIncome 6.496000e+09 NaN \n", "OperatingExpense 7.110000e+09 NaN \n", "ResearchAndDevelopment 2.593000e+09 NaN \n", "SellingGeneralAndAdministration 4.517000e+09 NaN \n", "GrossProfit 1.360600e+10 NaN \n", "CostOfRevenue 4.021700e+10 NaN \n", "TotalRevenue 5.382300e+10 NaN \n", "OperatingRevenue 5.382300e+10 NaN " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Balance Sheet Statements\n", "tsla_balance = pd.read_csv(\"external_datasets/TSLA_balance.csv\", index_col=0)\n", "googl_balance = pd.read_csv(\"external_datasets/GOOGL_balance.csv\", index_col=0)\n", "\n", "# Income Statements\n", "tsla_income = pd.read_csv(\"external_datasets/TSLA_income.csv\", index_col=0)\n", "googl_income = pd.read_csv(\"external_datasets/GOOGL_income.csv\", index_col=0)\n", "\n", "# Cash Flow Statements\n", "tsla_cash = pd.read_csv(\"external_datasets/TSLA_cash.csv\", index_col=0)\n", "googl_cash = pd.read_csv(\"external_datasets/GOOGL_cash.csv\", index_col=0)\n", "\n", "# Show one of the datasets\n", "tsla_income" ] }, { "cell_type": "markdown", "id": "63b7f2ff", "metadata": {}, "source": [ "Then, it's time to acquire the normalization files via the Toolkit to be used to normalize the results." ] }, { "cell_type": "code", "execution_count": 3, "id": "060d49af", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2025-04-27 21:53:31 - financetoolkit - INFO - Files are being saved to /Users/jeroenbouma/Downloads. Please see the following: https://www.jeroenbouma.com/projects/financetoolkit/external-datasets to understand how to work with these files. In essence, all it requires is to match up the rows in your dataframe with the normalization format.\n" ] } ], "source": [ "Toolkit(\"TSLA\").get_normalization_files()" ] }, { "cell_type": "markdown", "id": "0ff2648e", "metadata": {}, "source": [ "With this information, by copying over each name as defined by Yahoo Finance for the balance, income and cash flow statements as also defined above, the normalisation files can be filled. The result can be found within the `examples/external_datasets` folder of the project as found [here](https://github.com/JerBouma/FinanceToolkit/tree/main/examples).\n", "\n", "The way you should be filling these sheets is by looking at the index names of the DataFrame depicted above and placing the name at the correct position of the first column of the CSV (Column A). As an example the name `Total revenue` can be matched in the `income.csv` with `Revenue`. Do not change the names in Column B since the FinanceToolkit is dependent on those. So for the `income.csv` this will look like:\n", "\n", "| Income | Generic |\n", "| :----------------------------------------- | :------------------------------------------ |\n", "| TotalRevenue | Revenue |\n", "| OperatingRevenue | Operating Revenue |\n", "| CostOfRevenue | Cost of Goods Sold |\n", "| GrossProfit | Gross Profit |\n", "| OperatingExpense | Operating Expenses |\n", "| SellingGeneralAndAdministration | Selling, General and Administrative Expenses |\n", "| ResearchAndDevelopment | Research and Development Expenses |\n", "| OperatingIncome | Operating Income |\n", "| NetNonOperatingInterestIncomeExpense | Net Non Operating Interest Income Expense |\n", "| InterestIncomeNonOperating | Interest Income Non Operating |\n", "| InterestExpenseNonOperating | Interest Expense Non Operating |\n", "| OtherIncomeExpense | Total Other Income Expenses |\n", "| OtherNonOperatingIncomeExpenses | Other Non Operating Income Expenses |\n", "| PretaxIncome | Income Before Tax |\n", "| TaxProvision | Income Tax Expense |\n", "| NetIncomeCommonStockholders | Net Income Common Stockholders |\n", "| DilutedNIAvailtoComStockholders | Diluted NI Available to Common Stockholders |\n", "| BasicEPS | EPS |\n", "| DilutedEPS | EPS Diluted |\n", "| BasicAverageShares | Weighted Average Shares |\n", "| DilutedAverageShares | Weighted Average Shares Diluted |\n", "| TotalOperatingIncomeAsReported | Total Operating Income as Reported |\n", "| TotalExpenses | Cost and Expenses |\n", "| NetIncomeFromContinuingAndDiscontinuedOperation | Net Income from Continuing and Discontinued Operation |\n", "| NormalizedIncome | Normalized Income |\n", "| NetIncome | Net Income |\n", "| InterestIncome | Interest Income |\n", "| InterestExpense | Interest Expense |\n", "| EBIT | EBIT |\n", "| EBITDA | EBITDA |\n", "| ReconciledCostOfRevenue | Reconciled Cost of Revenue |\n", "| ReconciledDepreciation | Reconciled Depreciation |\n", "| NetIncomeFromContinuingOperationNetMinorityInterest | Net Income from Continuing Operation Net Minority Interest |\n", "| NormalizedEBITDA | Normalized EBITDA |\n", "| TaxRateForCalcs | Tax Rate for Calcs |\n", "\n", "Now it's time to convert each dataset in the right format." ] }, { "cell_type": "code", "execution_count": 4, "id": "78bd727e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
2024-12-312023-12-312022-12-312021-12-312020-12-31
GOOGLTreasurySharesNumberNaN0.0NaNNaNNaN
OrdinarySharesNumber12211000000.012460000000.012849000000.013242420000.0NaN
ShareIssued12211000000.012460000000.012849000000.013242420000.0NaN
TotalDebt25461000000.027121000000.029679000000.028395000000.0NaN
TangibleBookValue293199000000.0254181000000.0227184000000.0227262000000.0NaN
.....................
TSLACashCashEquivalentsAndShortTermInvestments36563000000.029094000000.022185000000.017707000000.0NaN
OtherShortTermInvestments20424000000.012696000000.05932000000.0131000000.0NaN
CashAndCashEquivalents16139000000.016398000000.016253000000.017576000000.0NaN
CashEquivalents1753000000.0495000000.02288000000.09548000000.0NaN
CashFinancial14386000000.015903000000.013965000000.08028000000.0NaN
\n", "

156 rows × 5 columns

\n", "
" ], "text/plain": [ " 2024-12-31 \\\n", "GOOGL TreasurySharesNumber NaN \n", " OrdinarySharesNumber 12211000000.0 \n", " ShareIssued 12211000000.0 \n", " TotalDebt 25461000000.0 \n", " TangibleBookValue 293199000000.0 \n", "... ... \n", "TSLA CashCashEquivalentsAndShortTermInvestments 36563000000.0 \n", " OtherShortTermInvestments 20424000000.0 \n", " CashAndCashEquivalents 16139000000.0 \n", " CashEquivalents 1753000000.0 \n", " CashFinancial 14386000000.0 \n", "\n", " 2023-12-31 \\\n", "GOOGL TreasurySharesNumber 0.0 \n", " OrdinarySharesNumber 12460000000.0 \n", " ShareIssued 12460000000.0 \n", " TotalDebt 27121000000.0 \n", " TangibleBookValue 254181000000.0 \n", "... ... \n", "TSLA CashCashEquivalentsAndShortTermInvestments 29094000000.0 \n", " OtherShortTermInvestments 12696000000.0 \n", " CashAndCashEquivalents 16398000000.0 \n", " CashEquivalents 495000000.0 \n", " CashFinancial 15903000000.0 \n", "\n", " 2022-12-31 \\\n", "GOOGL TreasurySharesNumber NaN \n", " OrdinarySharesNumber 12849000000.0 \n", " ShareIssued 12849000000.0 \n", " TotalDebt 29679000000.0 \n", " TangibleBookValue 227184000000.0 \n", "... ... \n", "TSLA CashCashEquivalentsAndShortTermInvestments 22185000000.0 \n", " OtherShortTermInvestments 5932000000.0 \n", " CashAndCashEquivalents 16253000000.0 \n", " CashEquivalents 2288000000.0 \n", " CashFinancial 13965000000.0 \n", "\n", " 2021-12-31 2020-12-31 \n", "GOOGL TreasurySharesNumber NaN NaN \n", " OrdinarySharesNumber 13242420000.0 NaN \n", " ShareIssued 13242420000.0 NaN \n", " TotalDebt 28395000000.0 NaN \n", " TangibleBookValue 227262000000.0 NaN \n", "... ... ... \n", "TSLA CashCashEquivalentsAndShortTermInvestments 17707000000.0 NaN \n", " OtherShortTermInvestments 131000000.0 NaN \n", " CashAndCashEquivalents 17576000000.0 NaN \n", " CashEquivalents 9548000000.0 NaN \n", " CashFinancial 8028000000.0 NaN \n", "\n", "[156 rows x 5 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from financetoolkit import helpers\n", "\n", "balance_sheets = helpers.combine_dataframes(\n", " {\n", " \"TSLA\": tsla_balance,\n", " \"GOOGL\": googl_balance,\n", " },\n", ")\n", "income_statements = helpers.combine_dataframes(\n", " {\n", " \"TSLA\": tsla_income,\n", " \"GOOGL\": googl_income,\n", " },\n", ")\n", "cash_flow_statements = helpers.combine_dataframes(\n", " {\"TSLA\": tsla_cash, \"GOOGL\": googl_cash},\n", ")\n", "\n", "# Show the Results\n", "balance_sheets" ] }, { "cell_type": "markdown", "id": "e1f148f9", "metadata": {}, "source": [ "With this done, it's now time to initialize the Toolkit and start using the Finance Toolkit with these custom datasets. By looking at the Balance Sheet Statement you can see that the column names have changed to the normalisation files.\n", "\n", "**Note:** It is important to always ensure that dates go from left to right. For example this dataset starts at 2024 and ends at 2020. This should be reversed to accommodate shifting the DataFrames accordingly throughout the Toolkit. E.g. for growth metrics or specific ratios that require current and past values." ] }, { "cell_type": "code", "execution_count": 5, "id": "a977bdfb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
20202021202220232024
GOOGLTreasury Shares NumberNaNNaNNaN0.0NaN
Ordinary Shares NumberNaN13242420000.012849000000.012460000000.012211000000.0
Share IssuedNaN13242420000.012849000000.012460000000.012211000000.0
Total DebtNaN28395000000.029679000000.027121000000.025461000000.0
Tangible Book ValueNaN227262000000.0227184000000.0254181000000.0293199000000.0
.....................
TSLAMinority InterestNaN1394000000.01194000000.0975000000.0767000000.0
Current DebtNaN1088000000.01016000000.01975000000.02343000000.0
Other Current BorrowingsNaN1088000000.01016000000.01975000000.02343000000.0
Cash EquivalentsNaN9548000000.02288000000.0495000000.01753000000.0
Cash FinancialsNaN8028000000.013965000000.015903000000.014386000000.0
\n", "

128 rows × 5 columns

\n", "
" ], "text/plain": [ " 2020 2021 2022 \\\n", "GOOGL Treasury Shares Number NaN NaN NaN \n", " Ordinary Shares Number NaN 13242420000.0 12849000000.0 \n", " Share Issued NaN 13242420000.0 12849000000.0 \n", " Total Debt NaN 28395000000.0 29679000000.0 \n", " Tangible Book Value NaN 227262000000.0 227184000000.0 \n", "... ... ... ... \n", "TSLA Minority Interest NaN 1394000000.0 1194000000.0 \n", " Current Debt NaN 1088000000.0 1016000000.0 \n", " Other Current Borrowings NaN 1088000000.0 1016000000.0 \n", " Cash Equivalents NaN 9548000000.0 2288000000.0 \n", " Cash Financials NaN 8028000000.0 13965000000.0 \n", "\n", " 2023 2024 \n", "GOOGL Treasury Shares Number 0.0 NaN \n", " Ordinary Shares Number 12460000000.0 12211000000.0 \n", " Share Issued 12460000000.0 12211000000.0 \n", " Total Debt 27121000000.0 25461000000.0 \n", " Tangible Book Value 254181000000.0 293199000000.0 \n", "... ... ... \n", "TSLA Minority Interest 975000000.0 767000000.0 \n", " Current Debt 1975000000.0 2343000000.0 \n", " Other Current Borrowings 1975000000.0 2343000000.0 \n", " Cash Equivalents 495000000.0 1753000000.0 \n", " Cash Financials 15903000000.0 14386000000.0 \n", "\n", "[128 rows x 5 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# initialize the Toolkit\n", "companies = Toolkit(\n", " tickers=[\"TSLA\", \"GOOGL\"],\n", " balance=balance_sheets,\n", " income=income_statements,\n", " cash=cash_flow_statements,\n", " format_location=\"external_datasets\",\n", " reverse_dates=True, # Important when the dates are descending\n", ")\n", "\n", "# Show the Balance Sheet\n", "companies.get_balance_sheet_statement()" ] }, { "cell_type": "markdown", "id": "7d1c961c", "metadata": {}, "source": [ "With this, it is now possible to do ratio calculations on these custom datasets. Let's have a look at the output of the extended Dupont model." ] }, { "cell_type": "code", "execution_count": 6, "id": "5195ca1f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining historical data: 100%|██████████| 3/3 [00:00<00:00, 9.02it/s]\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
20202021202220232024
GOOGLInterest Burden RatioNaN0.86751.04930.98340.938
Tax Burden RatioNaN0.96590.80130.87550.8908
Operating Profit MarginNaN0.35220.25220.27890.3423
Asset TurnoverNaNNaN0.78070.80090.821
Equity MultiplierNaNNaN1.42691.42281.4013
Return on EquityNaNNaN0.23620.27360.3291
TSLAInterest Burden RatioNaN1.02411.00820.89150.8632
Tax Burden RatioNaN0.85040.90971.6870.9188
Operating Profit MarginNaN0.11780.16840.10310.092
Asset TurnoverNaNNaN1.12771.02430.8544
Equity MultiplierNaNNaN1.86461.72551.6657
Return on EquityNaNNaN0.32480.27390.1039
\n", "
" ], "text/plain": [ " 2020 2021 2022 2023 2024\n", "GOOGL Interest Burden Ratio NaN 0.8675 1.0493 0.9834 0.938\n", " Tax Burden Ratio NaN 0.9659 0.8013 0.8755 0.8908\n", " Operating Profit Margin NaN 0.3522 0.2522 0.2789 0.3423\n", " Asset Turnover NaN NaN 0.7807 0.8009 0.821\n", " Equity Multiplier NaN NaN 1.4269 1.4228 1.4013\n", " Return on Equity NaN NaN 0.2362 0.2736 0.3291\n", "TSLA Interest Burden Ratio NaN 1.0241 1.0082 0.8915 0.8632\n", " Tax Burden Ratio NaN 0.8504 0.9097 1.687 0.9188\n", " Operating Profit Margin NaN 0.1178 0.1684 0.1031 0.092\n", " Asset Turnover NaN NaN 1.1277 1.0243 0.8544\n", " Equity Multiplier NaN NaN 1.8646 1.7255 1.6657\n", " Return on Equity NaN NaN 0.3248 0.2739 0.1039" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.models.get_extended_dupont_analysis()" ] }, { "cell_type": "markdown", "id": "9ce41a5c", "metadata": {}, "source": [ "This can also be extended into the area of efficiency ratios." ] }, { "cell_type": "code", "execution_count": 7, "id": "5eb89c8d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
2021202220232024
GOOGLDays of Inventory Outstanding3.12235.553NaNNaN
Days of Sales OutstandingNaN51.337452.377552.2987
Operating CycleNaN56.8904NaNNaN
Days of Accounts Payable OutstandingNaN16.145517.275219.3095
Cash Conversion CycleNaN40.7448NaNNaN
Cash Conversion Efficiency0.35570.32350.3310.358
Receivables TurnoverNaN0.14070.14350.1433
Inventory Turnover Ratio116.900965.7307NaNNaN
Accounts Payable Turnover RatioNaN22.606921.128618.9026
SGA-to-Revenue Ratio0.14140.14950.14430.12
Fixed Asset TurnoverNaN1.52231.42531.353
Asset Turnover RatioNaN0.78070.80090.821
Operating Ratio0.69450.73540.72580.6789
TSLADays of Inventory OutstandingNaN55.994561.050258.3231
Days of Sales OutstandingNaN10.899112.182614.807
Operating CycleNaN66.893673.232873.1301
Days of Accounts Payable OutstandingNaN76.120768.480561.1935
Cash Conversion CycleNaN-9.22714.752311.9367
Cash Conversion Efficiency0.21360.18070.1370.1528
Receivables TurnoverNaN0.02990.03340.0406
Inventory Turnover RatioNaN6.51855.97876.2582
Accounts Payable Turnover RatioNaN4.7955.335.9647
SGA-to-Revenue Ratio0.08390.04840.04960.0527
Fixed Asset TurnoverNaN2.13121.96651.6185
Asset Turnover RatioNaN1.12771.02430.8544
Operating Ratio0.87930.83020.90810.9206
\n", "
" ], "text/plain": [ " 2021 2022 2023 2024\n", "GOOGL Days of Inventory Outstanding 3.1223 5.553 NaN NaN\n", " Days of Sales Outstanding NaN 51.3374 52.3775 52.2987\n", " Operating Cycle NaN 56.8904 NaN NaN\n", " Days of Accounts Payable Outstanding NaN 16.1455 17.2752 19.3095\n", " Cash Conversion Cycle NaN 40.7448 NaN NaN\n", " Cash Conversion Efficiency 0.3557 0.3235 0.331 0.358\n", " Receivables Turnover NaN 0.1407 0.1435 0.1433\n", " Inventory Turnover Ratio 116.9009 65.7307 NaN NaN\n", " Accounts Payable Turnover Ratio NaN 22.6069 21.1286 18.9026\n", " SGA-to-Revenue Ratio 0.1414 0.1495 0.1443 0.12\n", " Fixed Asset Turnover NaN 1.5223 1.4253 1.353\n", " Asset Turnover Ratio NaN 0.7807 0.8009 0.821\n", " Operating Ratio 0.6945 0.7354 0.7258 0.6789\n", "TSLA Days of Inventory Outstanding NaN 55.9945 61.0502 58.3231\n", " Days of Sales Outstanding NaN 10.8991 12.1826 14.807\n", " Operating Cycle NaN 66.8936 73.2328 73.1301\n", " Days of Accounts Payable Outstanding NaN 76.1207 68.4805 61.1935\n", " Cash Conversion Cycle NaN -9.2271 4.7523 11.9367\n", " Cash Conversion Efficiency 0.2136 0.1807 0.137 0.1528\n", " Receivables Turnover NaN 0.0299 0.0334 0.0406\n", " Inventory Turnover Ratio NaN 6.5185 5.9787 6.2582\n", " Accounts Payable Turnover Ratio NaN 4.795 5.33 5.9647\n", " SGA-to-Revenue Ratio 0.0839 0.0484 0.0496 0.0527\n", " Fixed Asset Turnover NaN 2.1312 1.9665 1.6185\n", " Asset Turnover Ratio NaN 1.1277 1.0243 0.8544\n", " Operating Ratio 0.8793 0.8302 0.9081 0.9206" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_efficiency_ratios()" ] }, { "cell_type": "markdown", "id": "f13f7c92", "metadata": {}, "source": [ "Optional parameters can also be used, as an example to see the growth of each item in the financial statement." ] }, { "cell_type": "code", "execution_count": 8, "id": "2537373e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
20202021202220232024
GOOGLTreasury Shares NumberNaNNaNNaNNaNNaN
Ordinary Shares NumberNaNNaN-0.0297-0.0303-0.02
Share IssuedNaNNaN-0.0297-0.0303-0.02
Total DebtNaNNaN0.0452-0.0862-0.0612
Tangible Book ValueNaNNaN-0.00030.11880.1535
.....................
TSLAMinority InterestNaN0.9148-0.1435-0.1834-0.2133
Current DebtNaN0.4945-0.06620.94390.1863
Other Current BorrowingsNaN0.4945-0.06620.94390.1863
Cash EquivalentsNaN12.1154-0.7604-0.78372.5414
Cash FinancialsNaN10.02750.73950.1388-0.0954
\n", "

128 rows × 5 columns

\n", "
" ], "text/plain": [ " 2020 2021 2022 2023 2024\n", "GOOGL Treasury Shares Number NaN NaN NaN NaN NaN\n", " Ordinary Shares Number NaN NaN -0.0297 -0.0303 -0.02\n", " Share Issued NaN NaN -0.0297 -0.0303 -0.02\n", " Total Debt NaN NaN 0.0452 -0.0862 -0.0612\n", " Tangible Book Value NaN NaN -0.0003 0.1188 0.1535\n", "... ... ... ... ... ...\n", "TSLA Minority Interest NaN 0.9148 -0.1435 -0.1834 -0.2133\n", " Current Debt NaN 0.4945 -0.0662 0.9439 0.1863\n", " Other Current Borrowings NaN 0.4945 -0.0662 0.9439 0.1863\n", " Cash Equivalents NaN 12.1154 -0.7604 -0.7837 2.5414\n", " Cash Financials NaN 10.0275 0.7395 0.1388 -0.0954\n", "\n", "[128 rows x 5 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.get_balance_sheet_statement(growth=True)" ] }, { "cell_type": "markdown", "id": "d57bfa61", "metadata": {}, "source": [ "And you can look into performance and risk measurements as well." ] }, { "cell_type": "code", "execution_count": 9, "id": "38fa9e62", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "beta_plot = companies.performance.get_beta(period=\"monthly\").plot(\n", " figsize=(15, 5), title=\"Beta of Tesla and Apple compared to the S&P 500\"\n", ")\n", "beta_plot.axhline(y=1.0, color=\"red\", linestyle=\"--\")" ] }, { "cell_type": "code", "execution_count": 10, "id": "f93251fd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "companies.risk.get_maximum_drawdown(period=\"quarterly\").plot.area(\n", " figsize=(15, 5), title=\"Maximum Drawdown for each Quarter\", stacked=False\n", ")" ] }, { "cell_type": "markdown", "id": "ba148217", "metadata": {}, "source": [ "And lastly, the historical data can be viewed which includes OHLC, Volume, Dividends, Volatility and (Cumulative) Returns." ] }, { "cell_type": "code", "execution_count": 11, "id": "664513bf", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
OpenHighLowClose...VolatilityExcess ReturnExcess VolatilityCumulative Return
TSLAGOOGLBenchmarkTSLAGOOGLBenchmarkTSLAGOOGLBenchmarkTSLA...BenchmarkTSLAGOOGLBenchmarkTSLAGOOGLBenchmarkTSLAGOOGLBenchmark
Date
2020-04-2853.042763.8547270.584353.666763.9323270.937650.44661.2263265.358951.2747...0.0114NaNNaNNaN0.04360.02440.01821.01.01.0
2020-04-2952.67866.93271.058653.546767.6839274.173352.210766.0209270.017253.3673...0.01140.03450.08260.01990.04360.02440.01821.04081.08891.0262
2020-04-3057.012766.2513271.225957.98867.1788272.722950.965.7606268.32552.1253...0.0114-0.0295-0.0028-0.01550.04360.02440.01821.01661.09261.0166
2020-05-0150.333365.8895265.275351.51867.25270.249645.53665.1714261.751446.7547...0.0114-0.1094-0.0282-0.03290.04360.02440.01820.91181.06870.9897
2020-05-0446.733365.0953261.026250.865.9084263.964346.533364.4922259.529250.746...0.01140.079-0.0022-0.00360.04360.02440.01820.98971.07330.9924
..................................................................
2025-04-21230.26148.88521.16232.21148.95521.7222.79146.1508.46227.5...0.0114-0.1016-0.0672-0.06790.04360.02440.01824.43692.40751.9343
2025-04-22230.96148.89520.14242.79152.19529.3229.85148.54519.19237.97...0.01140.0021-0.0182-0.01790.04360.02440.01824.64112.46951.9846
2025-04-23254.86155.61540.43259.45157.53545.43244.43153.81533.88250.74...0.01140.0098-0.0183-0.02840.04360.02440.01824.89012.53282.0154
2025-04-24250.5156.15536.72259.54159.59547.43249.2155.79535.45259.51...0.0114-0.008-0.0177-0.0220.04360.02440.01825.06122.59682.0578
2025-04-25261.69165.07546.65286.85166.1551.05259.63161.04543.69284.95...0.01140.0553-0.0259-0.03550.04360.02440.01825.55732.64052.0727
\n", "

1256 rows × 36 columns

\n", "
" ], "text/plain": [ " Open High Low \\\n", " TSLA GOOGL Benchmark TSLA GOOGL Benchmark TSLA \n", "Date \n", "2020-04-28 53.0427 63.8547 270.5843 53.6667 63.9323 270.9376 50.446 \n", "2020-04-29 52.678 66.93 271.0586 53.5467 67.6839 274.1733 52.2107 \n", "2020-04-30 57.0127 66.2513 271.2259 57.988 67.1788 272.7229 50.9 \n", "2020-05-01 50.3333 65.8895 265.2753 51.518 67.25 270.2496 45.536 \n", "2020-05-04 46.7333 65.0953 261.0262 50.8 65.9084 263.9643 46.5333 \n", "... ... ... ... ... ... ... ... \n", "2025-04-21 230.26 148.88 521.16 232.21 148.95 521.7 222.79 \n", "2025-04-22 230.96 148.89 520.14 242.79 152.19 529.3 229.85 \n", "2025-04-23 254.86 155.61 540.43 259.45 157.53 545.43 244.43 \n", "2025-04-24 250.5 156.15 536.72 259.54 159.59 547.43 249.2 \n", "2025-04-25 261.69 165.07 546.65 286.85 166.1 551.05 259.63 \n", "\n", " Close ... Volatility Excess Return \\\n", " GOOGL Benchmark TSLA ... Benchmark TSLA GOOGL \n", "Date ... \n", "2020-04-28 61.2263 265.3589 51.2747 ... 0.0114 NaN NaN \n", "2020-04-29 66.0209 270.0172 53.3673 ... 0.0114 0.0345 0.0826 \n", "2020-04-30 65.7606 268.325 52.1253 ... 0.0114 -0.0295 -0.0028 \n", "2020-05-01 65.1714 261.7514 46.7547 ... 0.0114 -0.1094 -0.0282 \n", "2020-05-04 64.4922 259.5292 50.746 ... 0.0114 0.079 -0.0022 \n", "... ... ... ... ... ... ... ... \n", "2025-04-21 146.1 508.46 227.5 ... 0.0114 -0.1016 -0.0672 \n", "2025-04-22 148.54 519.19 237.97 ... 0.0114 0.0021 -0.0182 \n", "2025-04-23 153.81 533.88 250.74 ... 0.0114 0.0098 -0.0183 \n", "2025-04-24 155.79 535.45 259.51 ... 0.0114 -0.008 -0.0177 \n", "2025-04-25 161.04 543.69 284.95 ... 0.0114 0.0553 -0.0259 \n", "\n", " Excess Volatility Cumulative Return \\\n", " Benchmark TSLA GOOGL Benchmark TSLA \n", "Date \n", "2020-04-28 NaN 0.0436 0.0244 0.0182 1.0 \n", "2020-04-29 0.0199 0.0436 0.0244 0.0182 1.0408 \n", "2020-04-30 -0.0155 0.0436 0.0244 0.0182 1.0166 \n", "2020-05-01 -0.0329 0.0436 0.0244 0.0182 0.9118 \n", "2020-05-04 -0.0036 0.0436 0.0244 0.0182 0.9897 \n", "... ... ... ... ... ... \n", "2025-04-21 -0.0679 0.0436 0.0244 0.0182 4.4369 \n", "2025-04-22 -0.0179 0.0436 0.0244 0.0182 4.6411 \n", "2025-04-23 -0.0284 0.0436 0.0244 0.0182 4.8901 \n", "2025-04-24 -0.022 0.0436 0.0244 0.0182 5.0612 \n", "2025-04-25 -0.0355 0.0436 0.0244 0.0182 5.5573 \n", "\n", " \n", " GOOGL Benchmark \n", "Date \n", "2020-04-28 1.0 1.0 \n", "2020-04-29 1.0889 1.0262 \n", "2020-04-30 1.0926 1.0166 \n", "2020-05-01 1.0687 0.9897 \n", "2020-05-04 1.0733 0.9924 \n", "... ... ... \n", "2025-04-21 2.4075 1.9343 \n", "2025-04-22 2.4695 1.9846 \n", "2025-04-23 2.5328 2.0154 \n", "2025-04-24 2.5968 2.0578 \n", "2025-04-25 2.6405 2.0727 \n", "\n", "[1256 rows x 36 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.get_historical_data()" ] }, { "cell_type": "markdown", "id": "848c7f3d", "metadata": {}, "source": [ "It is also possible to still include your Financial Modeling Prep key and run the related functionality." ] }, { "cell_type": "code", "execution_count": null, "id": "25cb560c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining analyst estimates: 100%|██████████| 2/2 [00:00<00:00, 9.59it/s]\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
date2020202120222023202420252026202720282029
TSLAEstimated Revenue Low27692715855.047198352032.074600636515.096190538085.097428250435.091146512832.0110561414259.0146667643453.0149505762863.0185861949076.0
Estimated Revenue High34928362656.059530497666.092343265986.098865824947.0101090063914.0110903340060.0129538653445.0151894272219.0201196375475.0250122468704.0
Estimated Revenue Average31102527304.053009897638.082141808957.097458304621.099659355369.0100623658162.0121968395401.0149280957836.0171831760593.0213617089571.0
Estimated EBITDA Low15740985249.06222540492.08451256459.09503646657.016231004792.015184502236.018418916861.024434013883.024906828796.030963567268.0
Estimated EBITDA High23611477872.09333810739.012676884692.014255469991.016841042557.018475879798.021580419390.025304741174.033518197442.041669012531.0
Estimated EBITDA Average19676231561.07778175616.010564070576.011879558324.016602694469.016763341952.020319256493.024869377529.028626215879.035587419348.0
Estimated EBIT Low6292253089.010078959157.012587376985.013981202161.010835675371.010137039512.012296306135.016311931754.016627578811.020671003894.0
Estimated EBIT High9438379634.015118438736.018881065481.020971803245.011242931192.012334334088.014406897286.016893221599.022376452424.027817864551.0
Estimated EBIT Average7865316362.012598698947.015734221234.017476502703.011083812115.011191058955.013564956080.016602576676.019110608761.023757846683.0
Estimated Net Income Low1746428838.03641422676.05460936341.011999199998.08102956982.06399779391.09022124932.08289674512.015446452984.023001391026.0
Estimated Net Income High2619643259.05462134014.08191404512.017998800001.09159885822.08954528192.012850590453.023864181466.022714720356.033824606829.0
Estimated Net Income Average2183036049.04551778345.06826170427.014999000000.08631421402.07612652012.010024789490.012739367220.018585727185.027676117087.0
Estimated SGA Expense Low12365515385.02939271443.03049942310.03455119556.06516170552.06096037034.07394539352.09809386651.09999205005.012430769863.0
Estimated SGA Expense High18548273078.04408907166.04574913468.05182679336.06761078995.07417407943.08663770058.010158952658.013456362926.016728624991.0
Estimated SGA Expense Average15456894232.03674089305.03812427889.04318899447.06665390724.06729884969.08157458056.09984169654.011492406497.014287081851.0
Estimated EPS Average0.81522.14523.95583.06652.45422.16453.13074.33685.28457.8692
Estimated EPS High0.94552.48834.59453.18292.60452.54613.65386.78546.45869.6175
Estimated EPS Low0.6991.83953.48372.93062.30391.81972.56532.3574.39196.5401
Number of Analysts18.016.013.027.031.025.029.021.012.016.0
GOOGLEstimated Revenue Low174947208573.0249147657584.0278552166517.0304903702067.0348444826629.0370882882005.0406622803402.0476123716308.0503764431611.0574319393759.0
Estimated Revenue High181344295878.0258257944798.0285920346254.0307642573868.0352653556963.0444398566708.0488143718446.0483865744645.0569055189548.0648754479215.0
Estimated Revenue Average177785668701.0253189995257.0282140117275.0306237100181.0350477857384.0389721702043.0432634114197.0479994730477.0526961027771.0600764800000.0
Estimated EBITDA Low36199309683.064461779570.078387338355.086226072190.0121791376461.0129634114939.0142126233888.0166418779512.0176079995595.0200740961405.0
Estimated EBITDA High54298964526.096692669355.0117581007534.0129339108285.0123262447406.0155329937483.0170620112100.0169124838594.0198900972322.0226758140659.0
Estimated EBITDA Average45249137105.080577224463.097984172945.0107782590238.0122501978528.0136218818306.0151217926757.0167771809053.0184187865650.0209984382977.0
Estimated EBIT Low24208375544.048990664306.064812498549.071293748403.0104119793869.0110824573283.0121504121276.0142271887569.0150531288656.0171614018414.0
Estimated EBIT High36312563316.073485996460.097218747826.0106940622607.0105377416601.0132792005004.0145863618740.0144585305169.0170041006518.0193856178900.0
Estimated EBIT Average30260469430.061238330383.081015623188.089117185505.0104727289596.0116453854906.0129276635348.0143428596370.0157462729809.0179516245786.0
Estimated Net Income Low23401409380.047335069755.056411506308.059035999999.097933991767.099420910387.0116252864019.0124636540870.0154254426312.0191088086595.0
Estimated Net Income High35102114072.071002604636.084617259463.088554000000.0103409302598.0126016041880.0133113943630.0191960372355.0180608459414.0223735073957.0
Estimated Net Income Average29251761726.059168837196.070514382886.073795000000.0100671647182.5110978572238.0122068492020.0135909023359.0163617557593.0202686948016.0
Estimated SGA Expense Low17790419858.022821906759.031573740728.034731114799.049757758058.052961901858.058065545896.067990243710.071937324910.082012540463.0
Estimated SGA Expense High26685629787.034232860140.047360611093.052096672201.050358762779.063459907204.069706694386.069095801731.081260814567.092641835806.0
Estimated SGA Expense Average22238024823.028527383450.039467175911.043413893500.050048073898.055652076537.061779948895.068543022720.075249787979.085788932089.0
Estimated EPS Average2.61685.42874.71715.74488.0188.916110.215811.770613.145116.284
Estimated EPS High2.68495.56994.79935.88418.30810.124210.694515.422214.510217.975
Estimated EPS Low2.56255.3164.63925.57557.86817.98759.339810.013412.392915.3521
Number of Analysts18.021.024.037.042.034.038.029.018.016.0
\n", "
" ], "text/plain": [ "date 2020 2021 \\\n", "TSLA Estimated Revenue Low 27692715855.0 47198352032.0 \n", " Estimated Revenue High 34928362656.0 59530497666.0 \n", " Estimated Revenue Average 31102527304.0 53009897638.0 \n", " Estimated EBITDA Low 15740985249.0 6222540492.0 \n", " Estimated EBITDA High 23611477872.0 9333810739.0 \n", " Estimated EBITDA Average 19676231561.0 7778175616.0 \n", " Estimated EBIT Low 6292253089.0 10078959157.0 \n", " Estimated EBIT High 9438379634.0 15118438736.0 \n", " Estimated EBIT Average 7865316362.0 12598698947.0 \n", " Estimated Net Income Low 1746428838.0 3641422676.0 \n", " Estimated Net Income High 2619643259.0 5462134014.0 \n", " Estimated Net Income Average 2183036049.0 4551778345.0 \n", " Estimated SGA Expense Low 12365515385.0 2939271443.0 \n", " Estimated SGA Expense High 18548273078.0 4408907166.0 \n", " Estimated SGA Expense Average 15456894232.0 3674089305.0 \n", " Estimated EPS Average 0.8152 2.1452 \n", " Estimated EPS High 0.9455 2.4883 \n", " Estimated EPS Low 0.699 1.8395 \n", " Number of Analysts 18.0 16.0 \n", "GOOGL Estimated Revenue Low 174947208573.0 249147657584.0 \n", " Estimated Revenue High 181344295878.0 258257944798.0 \n", " Estimated Revenue Average 177785668701.0 253189995257.0 \n", " Estimated EBITDA Low 36199309683.0 64461779570.0 \n", " Estimated EBITDA High 54298964526.0 96692669355.0 \n", " Estimated EBITDA Average 45249137105.0 80577224463.0 \n", " Estimated EBIT Low 24208375544.0 48990664306.0 \n", " Estimated EBIT High 36312563316.0 73485996460.0 \n", " Estimated EBIT Average 30260469430.0 61238330383.0 \n", " Estimated Net Income Low 23401409380.0 47335069755.0 \n", " Estimated Net Income High 35102114072.0 71002604636.0 \n", " Estimated Net Income Average 29251761726.0 59168837196.0 \n", " Estimated SGA Expense Low 17790419858.0 22821906759.0 \n", " Estimated SGA Expense High 26685629787.0 34232860140.0 \n", " Estimated SGA Expense Average 22238024823.0 28527383450.0 \n", " Estimated EPS Average 2.6168 5.4287 \n", " Estimated EPS High 2.6849 5.5699 \n", " Estimated EPS Low 2.5625 5.316 \n", " Number of Analysts 18.0 21.0 \n", "\n", "date 2022 2023 \\\n", "TSLA Estimated Revenue Low 74600636515.0 96190538085.0 \n", " Estimated Revenue High 92343265986.0 98865824947.0 \n", " Estimated Revenue Average 82141808957.0 97458304621.0 \n", " Estimated EBITDA Low 8451256459.0 9503646657.0 \n", " Estimated EBITDA High 12676884692.0 14255469991.0 \n", " Estimated EBITDA Average 10564070576.0 11879558324.0 \n", " Estimated EBIT Low 12587376985.0 13981202161.0 \n", " Estimated EBIT High 18881065481.0 20971803245.0 \n", " Estimated EBIT Average 15734221234.0 17476502703.0 \n", " Estimated Net Income Low 5460936341.0 11999199998.0 \n", " Estimated Net Income High 8191404512.0 17998800001.0 \n", " Estimated Net Income Average 6826170427.0 14999000000.0 \n", " Estimated SGA Expense Low 3049942310.0 3455119556.0 \n", " Estimated SGA Expense High 4574913468.0 5182679336.0 \n", " Estimated SGA Expense Average 3812427889.0 4318899447.0 \n", " Estimated EPS Average 3.9558 3.0665 \n", " Estimated EPS High 4.5945 3.1829 \n", " Estimated EPS Low 3.4837 2.9306 \n", " Number of Analysts 13.0 27.0 \n", "GOOGL Estimated Revenue Low 278552166517.0 304903702067.0 \n", " Estimated Revenue High 285920346254.0 307642573868.0 \n", " Estimated Revenue Average 282140117275.0 306237100181.0 \n", " Estimated EBITDA Low 78387338355.0 86226072190.0 \n", " Estimated EBITDA High 117581007534.0 129339108285.0 \n", " Estimated EBITDA Average 97984172945.0 107782590238.0 \n", " Estimated EBIT Low 64812498549.0 71293748403.0 \n", " Estimated EBIT High 97218747826.0 106940622607.0 \n", " Estimated EBIT Average 81015623188.0 89117185505.0 \n", " Estimated Net Income Low 56411506308.0 59035999999.0 \n", " Estimated Net Income High 84617259463.0 88554000000.0 \n", " Estimated Net Income Average 70514382886.0 73795000000.0 \n", " Estimated SGA Expense Low 31573740728.0 34731114799.0 \n", " Estimated SGA Expense High 47360611093.0 52096672201.0 \n", " Estimated SGA Expense Average 39467175911.0 43413893500.0 \n", " Estimated EPS Average 4.7171 5.7448 \n", " Estimated EPS High 4.7993 5.8841 \n", " Estimated EPS Low 4.6392 5.5755 \n", " Number of Analysts 24.0 37.0 \n", "\n", "date 2024 2025 \\\n", "TSLA Estimated Revenue Low 97428250435.0 91146512832.0 \n", " Estimated Revenue High 101090063914.0 110903340060.0 \n", " Estimated Revenue Average 99659355369.0 100623658162.0 \n", " Estimated EBITDA Low 16231004792.0 15184502236.0 \n", " Estimated EBITDA High 16841042557.0 18475879798.0 \n", " Estimated EBITDA Average 16602694469.0 16763341952.0 \n", " Estimated EBIT Low 10835675371.0 10137039512.0 \n", " Estimated EBIT High 11242931192.0 12334334088.0 \n", " Estimated EBIT Average 11083812115.0 11191058955.0 \n", " Estimated Net Income Low 8102956982.0 6399779391.0 \n", " Estimated Net Income High 9159885822.0 8954528192.0 \n", " Estimated Net Income Average 8631421402.0 7612652012.0 \n", " Estimated SGA Expense Low 6516170552.0 6096037034.0 \n", " Estimated SGA Expense High 6761078995.0 7417407943.0 \n", " Estimated SGA Expense Average 6665390724.0 6729884969.0 \n", " Estimated EPS Average 2.4542 2.1645 \n", " Estimated EPS High 2.6045 2.5461 \n", " Estimated EPS Low 2.3039 1.8197 \n", " Number of Analysts 31.0 25.0 \n", "GOOGL Estimated Revenue Low 348444826629.0 370882882005.0 \n", " Estimated Revenue High 352653556963.0 444398566708.0 \n", " Estimated Revenue Average 350477857384.0 389721702043.0 \n", " Estimated EBITDA Low 121791376461.0 129634114939.0 \n", " Estimated EBITDA High 123262447406.0 155329937483.0 \n", " Estimated EBITDA Average 122501978528.0 136218818306.0 \n", " Estimated EBIT Low 104119793869.0 110824573283.0 \n", " Estimated EBIT High 105377416601.0 132792005004.0 \n", " Estimated EBIT Average 104727289596.0 116453854906.0 \n", " Estimated Net Income Low 97933991767.0 99420910387.0 \n", " Estimated Net Income High 103409302598.0 126016041880.0 \n", " Estimated Net Income Average 100671647182.5 110978572238.0 \n", " Estimated SGA Expense Low 49757758058.0 52961901858.0 \n", " Estimated SGA Expense High 50358762779.0 63459907204.0 \n", " Estimated SGA Expense Average 50048073898.0 55652076537.0 \n", " Estimated EPS Average 8.018 8.9161 \n", " Estimated EPS High 8.308 10.1242 \n", " Estimated EPS Low 7.8681 7.9875 \n", " Number of Analysts 42.0 34.0 \n", "\n", "date 2026 2027 \\\n", "TSLA Estimated Revenue Low 110561414259.0 146667643453.0 \n", " Estimated Revenue High 129538653445.0 151894272219.0 \n", " Estimated Revenue Average 121968395401.0 149280957836.0 \n", " Estimated EBITDA Low 18418916861.0 24434013883.0 \n", " Estimated EBITDA High 21580419390.0 25304741174.0 \n", " Estimated EBITDA Average 20319256493.0 24869377529.0 \n", " Estimated EBIT Low 12296306135.0 16311931754.0 \n", " Estimated EBIT High 14406897286.0 16893221599.0 \n", " Estimated EBIT Average 13564956080.0 16602576676.0 \n", " Estimated Net Income Low 9022124932.0 8289674512.0 \n", " Estimated Net Income High 12850590453.0 23864181466.0 \n", " Estimated Net Income Average 10024789490.0 12739367220.0 \n", " Estimated SGA Expense Low 7394539352.0 9809386651.0 \n", " Estimated SGA Expense High 8663770058.0 10158952658.0 \n", " Estimated SGA Expense Average 8157458056.0 9984169654.0 \n", " Estimated EPS Average 3.1307 4.3368 \n", " Estimated EPS High 3.6538 6.7854 \n", " Estimated EPS Low 2.5653 2.357 \n", " Number of Analysts 29.0 21.0 \n", "GOOGL Estimated Revenue Low 406622803402.0 476123716308.0 \n", " Estimated Revenue High 488143718446.0 483865744645.0 \n", " Estimated Revenue Average 432634114197.0 479994730477.0 \n", " Estimated EBITDA Low 142126233888.0 166418779512.0 \n", " Estimated EBITDA High 170620112100.0 169124838594.0 \n", " Estimated EBITDA Average 151217926757.0 167771809053.0 \n", " Estimated EBIT Low 121504121276.0 142271887569.0 \n", " Estimated EBIT High 145863618740.0 144585305169.0 \n", " Estimated EBIT Average 129276635348.0 143428596370.0 \n", " Estimated Net Income Low 116252864019.0 124636540870.0 \n", " Estimated Net Income High 133113943630.0 191960372355.0 \n", " Estimated Net Income Average 122068492020.0 135909023359.0 \n", " Estimated SGA Expense Low 58065545896.0 67990243710.0 \n", " Estimated SGA Expense High 69706694386.0 69095801731.0 \n", " Estimated SGA Expense Average 61779948895.0 68543022720.0 \n", " Estimated EPS Average 10.2158 11.7706 \n", " Estimated EPS High 10.6945 15.4222 \n", " Estimated EPS Low 9.3398 10.0134 \n", " Number of Analysts 38.0 29.0 \n", "\n", "date 2028 2029 \n", "TSLA Estimated Revenue Low 149505762863.0 185861949076.0 \n", " Estimated Revenue High 201196375475.0 250122468704.0 \n", " Estimated Revenue Average 171831760593.0 213617089571.0 \n", " Estimated EBITDA Low 24906828796.0 30963567268.0 \n", " Estimated EBITDA High 33518197442.0 41669012531.0 \n", " Estimated EBITDA Average 28626215879.0 35587419348.0 \n", " Estimated EBIT Low 16627578811.0 20671003894.0 \n", " Estimated EBIT High 22376452424.0 27817864551.0 \n", " Estimated EBIT Average 19110608761.0 23757846683.0 \n", " Estimated Net Income Low 15446452984.0 23001391026.0 \n", " Estimated Net Income High 22714720356.0 33824606829.0 \n", " Estimated Net Income Average 18585727185.0 27676117087.0 \n", " Estimated SGA Expense Low 9999205005.0 12430769863.0 \n", " Estimated SGA Expense High 13456362926.0 16728624991.0 \n", " Estimated SGA Expense Average 11492406497.0 14287081851.0 \n", " Estimated EPS Average 5.2845 7.8692 \n", " Estimated EPS High 6.4586 9.6175 \n", " Estimated EPS Low 4.3919 6.5401 \n", " Number of Analysts 12.0 16.0 \n", "GOOGL Estimated Revenue Low 503764431611.0 574319393759.0 \n", " Estimated Revenue High 569055189548.0 648754479215.0 \n", " Estimated Revenue Average 526961027771.0 600764800000.0 \n", " Estimated EBITDA Low 176079995595.0 200740961405.0 \n", " Estimated EBITDA High 198900972322.0 226758140659.0 \n", " Estimated EBITDA Average 184187865650.0 209984382977.0 \n", " Estimated EBIT Low 150531288656.0 171614018414.0 \n", " Estimated EBIT High 170041006518.0 193856178900.0 \n", " Estimated EBIT Average 157462729809.0 179516245786.0 \n", " Estimated Net Income Low 154254426312.0 191088086595.0 \n", " Estimated Net Income High 180608459414.0 223735073957.0 \n", " Estimated Net Income Average 163617557593.0 202686948016.0 \n", " Estimated SGA Expense Low 71937324910.0 82012540463.0 \n", " Estimated SGA Expense High 81260814567.0 92641835806.0 \n", " Estimated SGA Expense Average 75249787979.0 85788932089.0 \n", " Estimated EPS Average 13.1451 16.284 \n", " Estimated EPS High 14.5102 17.975 \n", " Estimated EPS Low 12.3929 15.3521 \n", " Number of Analysts 18.0 16.0 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# initialize the Toolkit\n", "companies = Toolkit(\n", " tickers=[\"TSLA\", \"GOOGL\"],\n", " balance=balance_sheets,\n", " income=income_statements,\n", " cash=cash_flow_statements,\n", " api_key=\"FMP_KEY\",\n", " format_location=\"external_datasets\",\n", " reverse_dates=True, # Important when the dates are descending\n", ")\n", "\n", "# Show the Analyst Estimates from Financial Modeling Prep\n", "companies.get_analyst_estimates()" ] } ], "metadata": { "kernelspec": { "display_name": "financetoolkit-rvLLqrVB-py3.10", "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": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 5 }