This project investigates the statistical properties of four exchange-traded funds (ETFs): AGG, VAW, IWN, and SPY. This will be done using a descriptive analysis and a statistical analysis of the weekly return in the period 2006-2015. The results show that the selected ETFs do not follow a strict normal distribution, that the mean weekly return of AGG is not significantly different from zero, and that there is no significant difference between the mean weekly return of AGG and VAW. Furthermore, a strong correlation between VAW and IWN is found.
This project investigates whether it is possible to predict the future geometric average rate of return in the stock market based on data from the past. This will be tested using a multiple linear regression model based on a dataset of 95 exchange-traded funds (ETFs) and their volatility and maximum time under water (maxTuW) as predictors. Statistical analysis found maxTuW to be an insignificant predictor, leading to its removal from the model. The results show that it is not possible to reliably predict future returns based on these parameters.