Keith Black

Quantitative investors have long used traditional data sources, such as income statements and balance sheets of public firms, to drive stock selection models. With the explosion in the amount and diversity of data in the last five years, alternative data sources are quickly revolutionizing quantitative investing. Alternative data sources can include natural language processing of news and social media content, review of credit card transactions and consumer emails, and geolocation data using cell phone signals and satellite images. Alternative data is more complex to process, moves in a different time frame than traditional data, and may provide a new window into information availability for private companies.

The digital asset market seeks an innovative solution to build a global, decentralized, and secure network that facilitates payments and other transactions. We will explore how proof-of-work, such as Bitcoin mining, and proof-of-stake protocols, such as Cardano, are used to secure networks and complete transactions. Behind many of these currencies are real businesses, such as Ethereum smart contracts that facilitate borrowing and lending as well as options and futures trading. Stablecoins pegged to USD or EUR can earn yields of up to 7% with minimal volatility. Returns and volatility data will be presented, as well as evidence on how digital assets can add return to a diversified portfolio without adding to portfolio volatility. Risks of digital assets will also be discussed, including regulatory risks, technology risk, and valuation risk.

There are currently over 11,000 cryptocurrencies and digital assets. With many experiencing price volatility of over 100% per year, or five times the volatility of stocks, there is substantial disagreement on how to value these assets. Some valuation models used for traditional equity valuation can be used to price these assets. Investors may also find it useful to understand business models, emerging industries, and oligopolistic models.