In the current climate, cryptocurrency trading is becoming increasingly more accessible through smartphones. Coupled with a high market value of cryptocurrency, it is essential to strategize trading and investment to make the most of the cryptocurrency boom. This paper provides a systematic survey on risk estimation methods for cryptocurrencies based on the empirical results of relevant academic literature. Volatility analysis revealed that cryptocurrency markets are highly volatile in comparison to stock and gold. Value-at-Risk (VaR) measures showed varied distributions. Tail risk analysis was commonly measured through VaR using quantile regression. Ratio-based estimations were part of the larger goal of portfolio optimization techniques. Single-objective and multi-objective optimizations relied on Omega and Sharpe ratio respectively. This survey provides useful guidance in assessing various empirical, statistical and advanced risk estimation for cryptocurrency markets. It also provides an insight into quantitative analysis for risk estimation and the utility of risk estimation in portfolio optimization.