As anyone who has paid attention to the stock market over the past six months could attest, the amount of price variation on any given day has been overwhelming. Although I am more of a boring index-fund guy, I often find myself daydreaming of investing my son’s college fund in Tesla shares and watching it go to the moon.
Given the task of evaluating hypothetical stock market investment returns, such as my Tesla scenario, one must begin by gathering specific price data. That data is a key aspect of the analysis to model out the gain or loss over a set period. Although the price information is readily available on the web, it would be a very tedious process to gather the information manually each time you want to model a different scenario.
However, one can make use of data analytics tools such as Python or Alteryx to automate the data gathering and manipulation process. For example, using Alteryx, one can put together a repeatable visual workflow that downloads investment data from Yahoo Finance for a period and organizes the data for analysis. Once the workflow is set up, it is an effortless process to update the inputs for other requirements such as adding more reference dates or stock tickers.
In this case, having an easily repeatable workflow reduces the amount of time spent pulling the data. Whether one would need information for 10 stocks or 1000 stocks, the automated workflow gathers the data in seconds instead of hours. In addition, if the analysis needs to then be updated for a later period, one needs only to update their workflow to pull the added data and rerun the workflow to obtain it in a useable format.
By using external data sources and process automation, one can enhance analysis and remove manual processes when obtaining the data, allowing for more time in value-added areas of analysis. External data gathered using process automation could include economic information, population data, or even things such as social media statistics. In cases like this, it is beneficial to have a tool available that can gather a large amount of data efficiently and effectively.
If you have any questions about using data analytics to solve your business problems, please contact Andrew Trettel, CPA, CFE, CVA at 412-697-5436 or Brian Webster, CPA/ABV/CFF, CVA, CFE, CMA at 412-697-5307 of the Business Advisory Group at Schneider Downs.
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Material discussed is meant for informational purposes only, and it is not to be construed as investment, tax, or legal advice. Please note that individual situations can vary. Therefore, this information should be relied upon when coordinated with individual professional advice.
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