Cryptocurrency risk problem
Many ICO companies raised a significant amount of capital through Ethereum, Bitcoin, or other cryptocurrencies in 2017 and 2018. The problem is that these firms need to meet the expenses of their projects by paying in fiat, like USD or EUR. This exposes that to high and unwanted cryptocurrency price risk.
Similarly, many crypto miners get most of their revenues by mining and potentially selling cryptocurrencies, but have to meet their electricity costs and operating expenses in fiat. These large crypto holdings expose them to significant crypto price risk and potential inability to meet their fixed and recurring expenses.
Cryptocurrencies are characterized by extreme levels of volatility compared to traditional asset classes like equities and fixed income. The average annualized volatility for Bitcoin is in fact around 80%, while for Ethereum is around 115%. Equity markets in comparison have an average annualized volatility level of around 15%.
Managing all types of risks for our clients and invested capital is of primary importance to us. We developed a sophisticated risk management framework with the objective of monitoring and keeping under predefined limits various types of risks embedded in our investment portfolios.
In the first phase of our investment process we collect data from a variety of traditional and alternative sources. In order to maximize our chances of finding new sources of alpha, we consider multiple datasets, including financial, fundamental, macroeconomic, government, and alternative sources. This allows us to develop a deeper understanding of how financial markets work by testing our hypotheses in a more comprehensive and extensive way in the following phases of our strategy development framework.
We use proprietary automated algorithms to clean the vast amounts of data at our disposal. Thereafter, our data scientists review and check the automated cleaning procedures to make sure that the data sets are clean and can be used thereafter by our quantitative researchers. Then we analyze the data sets processed in the previous step using sophisticated and advanced statistical methods in order to find alpha signals. Having confirmed that pilot trading returns are consistent with the backtest and what we expected, our investment team allows our clients to invest in the new investment product.