I recently got hired at a small SAaS company as an FP&A analyst. The girl I’m backfilling was a genius who went to an IVY league school with a heavy comp sci/data analytics background. However, she made her way into Finance at my company and created this crazy model in R to essentially do regression analysis on our historical bookings and use it to project future order intake. She’s pretty much using actuals and I think she has some slices on both products and segments/verticals. But I also think there is a component where she layers on pipeline data.
I’m in the process of learning how her model works but I started trying to do some of my own analysis. Basically, I wanted to see if some of the bookings in our verticals which house our customers from different industries (healthcare, telecom, energy) could match up against different stock price indices (SPDR S&P 500, Russell 3000, healthcare, telco, tickers etc.) as an example, I compared our ACV closes the past 2 years in our healthcare segment to the XLV healthcare ETF performance for the same period of time and did the regression in Excel. My R2 was basically 0, which essentially means that there is no correlation between the 2. I would’ve figured if our healthcare customers are doing well and growing revenues, that would be reflected in increases in the XLV healthcare etf price.
I did a separate regression on UPS and looked at their stock price and revenue for the last 15 years and the R2 came out to 0.9 which means there is a decent amount of correlation. So if growing revenue typically leads to higher company stock price, why were my results basically inconclusive?
Leave a Reply