Learn how to use pandas to call a finance API for stock data and easily calculate moving averages. Please check back later!
Less than a decade ago, financial instruments called derivatives were at the height of popularity. Fast forward nine years later and things have changed. The financial crisis has proven to be an as-to-yet derivatives-nemesis. But there is a new player in town… Python! Python has been gaining significant traction in the financial industry over the last years and with good reason.
In this series of tutorials we are going to see how one can leverage the powerful functionality provided by a number of Python packages to develop and backtest a quantitative trading strategy. In detail, in the first of our tutorials, we are going to show how one can easily use Python to download financial data from free online databases, manipulate the downloaded data and then create some basic technical indicators which will then be used as Que es importar yahoo dating basis of our quantitative strategy.
To accomplish that, we are going to use one of the most powerful Que es importar yahoo dating widely used Python packages for data manipulation, pandas. Pandas and matplotlib are included in the more popular distributions of Python for Windows, such as Anaconda.
In case it's not included in your Python distribution, just simply use pip or conda install. Once Que es importar yahoo dating, to use pandas, all one needs to do is import it. Having imported the appropriate tools, getting market data from a free online source, such as Yahoo Finance, is super easy. Yahoo finance has changed the structure of its website and as a result the most popular Python packages for retrieving data have stopped functioning properly.
Until this is resolved, we will be using Google Finance for the rest this article so that data is taken from Google Finance instead. Please note that there has been some issues with missing data in Google's API, as well as frequent, random errors that occur when pulling a lot of data.
DataReader returns a Panel "Que es importar yahoo dating," which can be thought of as a 3D matrix. The first dimension consists of the various fields Yahoo Finance returns for a given instrument, namely, the OpenHighLowClose and Adj Close prices for each date.
The second dimension contain the dates. The third one contains the instrument identifiers. Let us assume we are interested in working with the Close prices which have been already been adjusted by Google finance to account for stock splits. We want to make sure that all weekdays are included in our dataset, which is very often desirable for quantitative trading strategies.
Of course, some of the weekdays might be public holidays in which case no price will be available. For this reason, we will fill the missing prices with the latest available prices:.
Initially, close contains all the closing prices for all instruments and all the dates that Google returned. Some of the week days might be missing from the data Google provides. This function return a DatetimeIndex which is shown below:.