This course introduces the construction and evaluation of crypto indices as market benchmarks. It explains how token selection, liquidity screening, weighting, and rebalancing shape index exposure, and compares different basket designs using correlations, MDS, BTC beta, R^2, tail-risk measures, and crash-period performance. The results show that index methodology strongly affects Bitcoin dependence and diversification, while market-wide crypto crash risk remains difficult to eliminate.
This courselet explains how crypto indices transform a fragmented market of individual tokens into a structured and measurable benchmark. It introduces the main components of index construction, including the eligible asset universe, liquidity screening, price selection, weighting rules, and periodic rebalancing. A liquidity-coverage approach is used to dynamically select the smallest number of cryptocurrencies needed to represent most of the market.
The empirical section compares Bitcoin, Ethereum, and several basket designs, including equal-weighted, market-cap-weighted, and capped-weight indices. Their return profiles are evaluated using rolling correlations, correlation heatmaps, multidimensional scaling, Bitcoin beta regressions, R^2, Value-at-Risk, Expected Shortfall, maximum drawdown, and crash-period performance. The results demonstrate that index methodology is not neutral: capitalisation-weighted indices can behave almost like Bitcoin proxies, while equal-weighted and capped approaches provide broader exposure but cannot fully eliminate market-wide crypto crash risk.