UCLA

Corporations belonging to the biotechnology sector have the potential to provide investorswith high returns; between January 2020 and January 2021, the average share price for European and US biotechnology companies increased at more than twice the rate of the S&P 500, outperforming sister industries such as pharmaceuticals and many other industries which witnessed dwindling returns during the COVID-19 pandemic1.Thus, this research paper aims to formulate time series models that accurately predict the log returns of the stock price of Illumina, Inc. Seven time series models were formulated, including three naive models, two Autoregressive Integrated Moving Average models (ARIMA), one simple exponential smoothing model, and one ARIMA-GARCH model. Among the models, it was determined that the simple exponential smoothing model outperformed the other models on the basis of root mean square error (RMSE). This simple exponential smoothing model was then applied to three competing biotechnology companies to assess its applicability to other companies within the industry.