Building a Python script to analyse company earning calls.

During this post, we will extract the main key points on the company recent and future performance as stated by management in the latest earning calls.

The code will be very simple. We will pass the ticker of any company of our interest and the outcome will be an amazing short summary of the earnings call.

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Why to Analyse Company Earning Calls

Company earning calls is one of the main sources of information to understand how businesses are doing and what are expectations for next quarters.

Company earning calls are publicly available. Normally, we can visit the website of the company and dial in to the call to hear what management has to say. Earnings call are normally scheduled the same day that company earnings are publicly released. The structure of the call is simple, management gives an overview of the last quarter operations and future guidance. …


Calculating a company degree of financial leverage

In this article, we are going to learn how to analyse companies leverage with Python. First, we will start with a short introduction on what is leverage and how to interpret it. Then, we will move to Python to learn how to calculate the degree of financial leverage. As we will see, it is super easy to code.

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Measuring Companies Leverage

All companies face two level of risk affecting stock prices. On one side, companies suffer from business risk which includes sales and operating risks. …


Valuing Google using the DCF method and Python.

During this post, we are going to use the Discounted Cash Flow method with Python to value a company. The DCF model that we will build is going to be dynamic. That is, we will be able to reuse it for any company that we want to estimate the stock price for.

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Introduction to the Discounted Cash Flow Method

The majority of valuation methods are based on net income. We have already seen a few of them in my previous posts, such as, price earnings with Python and the net current asset value per share among others. The discounted cash flow method is different. …


Building a model to estimate WACC using Python

In this post, we are going to learn how to build a model to calculate a firm weighted average cost of capital (WACC) with Python. We will learn what is WACC and how to calculate it step by step. Then, in a future post, we will apply WACC to estimate the value of a company using the Discounted Cash Flow method.

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What is the Weighted Average Cost of Capital (WACC)?

The WACC is a firm cost of capital. Is the capital rate that a firm is expected to pay on average to all its security holders.


Building a model based on financial ratios with Python

During this post, we are going to build an investment model to find out attractive stocks based on financial ratios using Python. We will screen all technology related stocks in the Nasdaq exchange. Then, we will get the main financial ratios for each stock. Finally, based on a custom ranking criteria, we will build a model to find the most attractive stocks.

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Let’s start with the Python code to build our investment model:

Investment Model with Python

As in my previous posts, I will be using financialmodelingprep API which offers a few free API calls per month upon registration. …


Building a financial dashboard with Dash, Plotly and Python

This post will be a bit different than my previous ones. We are not going to analyse financial data or value companies using Python. Instead, we are going to learn how to create a financial dashboard with Python using Plotly and Dash. Below is a sample of what we will build!

Financial Dashboard with Python
Financial Dashboard with Python
Financial Dashboard with Python

Interactive Dashboards with Python

Plotly is a great and free Python library to create interactive graphs and dashboards. The Plotly documentation is wonderful and it is more than enough in order to start creating our own interactive graphs without the need to know HTML, CSS or JavaScript. …


Learn how to use an iPad to create Python scripts

For all of you who have been reading my blog on Python for Finance and watching my videos, I wanted to share with you how to code in Python using an iPad.

Python in iPad
Python in iPad
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Why Python for iPad?

Some of you may be wondering why should I change my laptop for my iPad in order to code? From my point of view, I do not see the iPad replacing the laptop for coding purposes. At least not in the short term. However, it can be used as a great complement to the laptop for coding purposes.

For example, imagine that you are going for a weekend to visit your family somewhere in the lake and you do not feel like taking the computer and charger with you. In that case, if you want to keep coding during the weekend getaway, the only option left is to carry on an iPad. …


In my last few stories, we mostly retrieved financial data from an API. I would like to show you how to read CSV files in Python using Pandas read_csv since it is another useful way to read financial data for our analysis.

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Why to use pandas read csv?

Pandas read csv method is super useful to load any data in CSV format to a Pandas DataFrame. For example, I have a CSV file containing the last year of historical prices. I have downloaded the file from Apple in Yahoo Finance where you can download historical prices in CSV format for any company. The name of the files is ‘ AAPL.csv


Analysing account receivables is important to identify potential firm collection problems.

Account receivables are amounts owed to a company by its customers. In this story, we are going to use Python to analyse receivables for companies in the technology sector. The story will be split into two parts. First, we will start analysing account receivables for Apple. Then, we will move to analyse the receivables to sales ratio for a group of comparable companies in the Technological sector.

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How to Read Account Receivables

Account receivables are financial assets from a company since they represent amounts owned to the company for selling goods or services.

One of the ratios that investors often use to compare receivables across companies is the receivable to sales ratio. A high ratio of account receivables in terms of sales indicates that a firm has a big percentage of sales in credit. A high ratio poses certain risk in companies since debtors may not be able to pay their obligations. …


Currency exposure may be one of the biggest headaches for big companies.

From an investor’s perspective, it is important to understand the implications that changes in exchange rates have in company financials. In this post, we will first understand how exchange rates affect company profits. Then, we will analyse and plot multiple currency exchange rates with Python.

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How exchange rates impact companies

Exchange rates are an important factor to take into account when analysing a company. A company may have USD as functional currency (i.e. currency that a company prepares financial results) but have operations (e.g. sales, loans, suppliers, etc.) in a different currency.

When presenting financial results, firms must distinguish between monetary and non-monetary assets/liabilities:

  • Monetary assets/liabilities are those assets that are readily convertible to cash. These assets are retranslated from other currencies to the functional currency of the company at the reporting date. Any gains or losses on the revaluation will impact the profits of the company. For instance, receivables, payables, cash balances and loans are considered as monetary assets/liabilities.

About

Jose Manu (CodingFun)

Python for Finance. Learn step by step how to automate cool financial analysis tools. Writing at https://codingandfun.com/. Twitter: @CodingandF

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