This study, among many others, provides an initial quantitative contribution to the emerging literature as well as existing empirical evidence regarding contagion risks across cryptocurrency markets over time. Using VAR (Vector Autoregressive) and SVAR (Structural Vector Autoregressive) models with Granger causality, along with Student’s t-copulas, we find that Bitcoin is likely to act as an independent asset in this market, while Ripple and Litecoin tend to be recipients of contagion effects, and Ethereum appears to be a primary source of contagion. Our study offers additional insight into the investigation of contagion risks between both historical and future cryptocurrency values by employing Student’s t-copulas for joint distribution analysis and aims to determine whether these contagion effects remain consistent over time. The results suggest, in both cases, that all cryptocurrencies tend to move negatively in extreme value conditions. Investors are therefore encouraged to pay closer attention to “bad news” and market movement patterns in order to make timely decisions regarding buying, holding, and selling. Note: This thesis reflects the state of cryptocurrency markets and related quantitative models as of 2019-2021. The findings and conclusions are intended to preserve the integrity of the research conducted during this specific time period. I acknowledges that this field evolves rapidly, and an updated analysis may be presented in a forthcoming research paper.