Thushal (Shaun) Karunamuni

This study examines the spatial distribution of companies listed in the NASDAQ Composite Index from 2010 to 2019. The aim of this study is to understand how Tobler's First Law of Geography is reflected on the spatial pattern of headquarters of companies where their stock prices increased or decreased. The first research question is (1) if there is clustering of publicly traded companies (headquarters) associated with growth stocks and publicly traded companies associated with non-growth stocks in the mainland US. The second research question is (2) where are hotspots located in the US on a State-level? The values of daily mean change in closing price that was greater than 0 was considered a growth stock and a value less than 0 was considered a non-growth stock for this research. A test for spatial autocorrelation (Global Moran's I) was done using R, and local spatial autocorrelation (Getis Ord Gi*) was conducted to find hot spots using R with a distance threshold of 2000km. Of 1496 stocks, 1028 stocks grew while 468 did not. The Global Moran's I for growth stocks is -0.0016 and 0.0001 in non-growth stocks. In addition, at a 2000 km threshold, California is the only hot spot in the US. Therefore, there was no spatial autocorrelation of publicly traded companies from 2010 to 2019. Spatial Autocorrelation in this study for the 1496 stocks has provided evidence that there is randomness of company locations in relation to the stock performance. The NASDAQ is a formidable marker of stock performance from 2010 to 2019 and location of the company relative to the stock is not an influence of how well the stock performs. Therefore, this study delivers empirical evidence based on the NASDAQ to confirm Tobler's second law of geography. Another possible theorization is that artificial features in space may not be related to one another either nearer or more distant and further research on man-made phenomena could be studied in future research.