A stable index is a basket of assets used to represent the current state of the market. In order to accurately depict the overall health of the market, it is important that the index has minimal variance so that it is not prone to excessive fluctuations or risk. For the final project of STA 2202 - Time Series Analysis, we construct a stable minimum variance index using a basket of currencies, cryptocurrencies, and precious metals. The index is updated on a quarterly basis as more data is crystallized. Prior to constructing the index, we begin by pre-processing the data, exploring the data to understand its structure, and analysing the assets individually and as a collection from a statistical perspective. Using our findings, we optimize the weights of the basket to minimize the variance of the index. This process requires the covariance matrix for the group of assets to represent the structure of the data. The construction of this covariance matrix is rooted in the findings of the exploratory and preliminary analysis. Finally, we consider the predictive power of ARIMA models as applied to individual assets and we explore the idea of whether the random walk hypothesis holds true. The findings and process can be found in the report here.