Hafner, ChristianMajeri, SabrineSabrineMajeri2025-05-142025-05-142025-05-142021https://hdl.handle.net/2078.2/23037Using a spillover index approach and its variants, we examine the connectedness between 39 cryptocurrencies (among the world's top 400 by market cap as of February 2021). As the main feature, we use the so-called Network to Transaction (NVT) ratio, which is the market capitalization divided by an estimate of the on-chain transaction volume, which makes different cryptos comparable and serves as an indicator for their usefulness. We build a connectedness network connecting these 39 cryptocurrencies based on the framework of variance decompositions in a vector autoregression model. We also use LASSO to reduce the number of parameters in the VAR model due to the large dimensionality of the data. We find that NVT connectedness or spillover effect is not necessarily related to market capitalization, as we have large and small cryptocurrencies by market cap that propagate large NVT shocks ( eg Litecoin, Dogecoin, Bitcoin Cash, OMG Network and Decentraland ). More importantly, the largest issuer of NVT shocks for other cryptocurrencies is OMG Network (small cryptocurrency by market cap), which receives less public attention. We also find that bitcoin is not the dominant cryptocurrency when it comes to NVT shocks, as it has a small contribution to the spillover on other altcoins. Therefore, the NVT values of altcoins are not determined by bitcoin. Additionally, our work provides new insights about cryptocurrencies; those relying on Proof of Stake and Delegated Proof of Stake as a consensus mechanism are the smallest receivers of NVT spillovers from other cryptocurrencies. These assets are also the least interconnected with each other. Therefore, market participants may be interested in investing in this group of altcoins to obtain diversified risk. Mining cryptocurrencies that are relying on PoS is more efficient because they do not require high electricity costs or high material purchase costs to verify transactions. We also find that the cryptocurrencies used for privacy are the least interconnected and receive small spillovers from other assets, which may also attract the attention of market participants.Vector AutoregressionsICALASSONetworksCryptocur-renciestext::thesis::master thesisthesis:30063