Financetoolkit

This release adds a minor, but important, function (`get_historical_statistics`) that shows in what currency the historical data is denoted. Besides that, it also gives some insights since when the product was traded and in what timezone it belongs.

<img width="1149" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/bfec8f7b-b971-434c-82c4-f9c305ccc8d6">

This version introduces ISIN support. If you submit an ISIN, it will find the relevant symbol and use that instead. It will also mention to what symbol it made the conversion so it is clear what ticker to look at. I've also added some dependencies, mostly a clean-up (I was struggling with getting SciPy to work, now this is built in with Pandas). Next to that, I've added the Finance Database as a dependency as in the future the Finance Toolkit will feature functionality from this database.

<img width="1210" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/2c3bbb15-5530-4b5c-aebd-2bb8e91ff513">

This is a minor release getting some bugfixes in and making the code a bit more robust. Less errors should now occur when you do not have the correct API key set and someone noticed that if you call the Statistics functionality before anything else it returns an error. This is now fixed.

**If you feel like any functionality is missing, definitely let me know and we can start adding them in!**

This release introduces two new models which are the **Weighted Average Cost of Capital (WACC)** and the **Intrinsic Valuation**.

As an example, see the WACC below. For the method of calculation please see [here](https://www.jeroenbouma.com/projects/financetoolkit/docs/models).

<img width="665" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/822ed488-02f2-495b-8008-4abc27b94cad">

Furthermore, the Intrinsic Valuation attempts to calculate the intrinsic value of an asset. This does require some manual input through which are growth, perpetual growth and WACC numbers given that this model is highly subjective and asset dependent.

<img width="516" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/2902ccde-a729-4bb3-b000-d7b5ef9337d0">

The growth numbers can be specified for each asset individually as well. For the method of calculation please see [here](https://www.jeroenbouma.com/projects/financetoolkit/docs/models).

<img width="421" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/c5dce5ad-1c5c-4f3b-9709-8904227eddc5">

Next to that, I've introduced trailing calculations for the Financial Statements and Ratios. As an example, you can now see the Trailing P/E ratio with the following code. Note that you need to have `quarterly=True` to get the actual TTM (otherwise you will take the trailing value over 4 years).

<img width="1191" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/b5460b51-c451-42dd-82ce-52c40bfd4943">

This new release features a whole lot of new features yet again. This includes the following:

Performance Metrics

There is now a large list of performance metrics to be found in the `performance` class in similar fashion as e.g. `ratios`. This gets you the following:

- Alpha
- Jensen's Alpha
- Beta
- Capital Asset Pricing Model (CAPM)
- Treynor Ratio
- Sharpe Ratio
- Sortino Ratio
- Ulcer Performance Index (UPI)
- M2 Ratio
- Tracking Error
- Information Error

This is an extra powerful class as you can get these ratios "within" periods. This means that if you select the period "quarterly", it will calculate the ratios for the days within each quarter. As an example:

<img width="736" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/95c3eb94-4e3f-494d-99f3-262fdca5fe2f">

Risk Metrics

Not only Performance Metrics are added in but courtesy of northern-64bit, it is now also possible to observe the following risk metrics:

- Value at Risk (VaR) with distributions Historical, Gaussian, Student-t, Cornish-Fisher.
- Conditional Value at Risk (cVaR) with distributions Historical, Gaussian, Laplace, Logistic.
- Entropic Value at Risk (eVaR) with a Gaussian distribution.
- Ulcer Index (UI)
- Maximum Drawdown (MDD)
- Skewness
- Kurtosis

Just like with the performance metrics, you can view these for within each period as well. E.g. on a weekly basis:

<img width="683" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/3e933b4e-0f74-41f6-a651-67619ed06950">

Risk Free Rates and Benchmarks

Within the Toolkit class (upon initialisation) a benchmark can be defined. By default this is set to "^GSPC" which is the S&P 500 index. This benchmark is required to calculate metrics such as CAPM, Beta and (Jensens Alpha) and is very neat to have when you wish to analyze and compare tickers. It is of course possible to change this benchmark ticker to anything (or disable it by setting it to None).

Next to that, it is also possible to define a risk free rate, this can be '13w', '5y', '10y' or '30y' and defaults to '10y'. Both settings will lead to different results for some of the calculations and it is therefore important you set a benchmark and risk free rate that matches your beliefs and analysis. As an example:

<img width="927" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/ad9160c7-3659-49ca-889c-dcd15b89f78d">

Other than that, many improvements behind the scenes were made. E.g. it is now really easy to add new ratios since all the data has been prepared properly and some fixes have been made to data that could sometimes mess up in niche scenarios. Next to that, the documentation has been greatly extended: https://www.jeroenbouma.com/projects/financetoolkit/docs.

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<b><div align="center">Find a variety of How-To Guides including Code Documentation for the FinanceToolkit <a href="https://www.jeroenbouma.com/projects/financetoolkit">here</a>.</div></b>
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This release focusses on numerous smaller enhancements that make the quality of the data better. For example, through grouping of historical data, I've noticed that it resulted in numerous NaN values given that for that particular stock there is no data available. These were minor details but it slightly messed up any form of charting. Next to that, technical indicators falsely calculated with NaN values.

Next to that, I noticed that if you input a ticker that had no data outside of the defined period (with start and end) it gave an error. This has now been tackled. **Much more is upcoming with a new Risk class (for Value at Risk, Conditional Value at Risk and much more) currently in the works!**

All in all, you can now generate charts like these with relative ease through collecting data from the [FinanceDatabase](https://github.com/JerBouma/FinanceDatabase) and [FinanceToolkit](https://github.com/JerBouma/FinanceToolkit) incredibly quickly being able to do really proper investment research.

As an example, these are companies found through the Finance Database:

<img width="1183" alt="image" src="https://github.com/JerBouma/FinanceToolkit/assets/46355364/a14b5e19-845d-453e-a261-8285b5ad1b20">

Which, once data is collected through the Finance Toolkit, can return:


Also did you notice that really any asset works and not only companies? :)