One of the most talked-about strategies in quantitative trading is investing in "Small Caps". This article aims to enlighten those seeking to develop algorithmic trading strategies focused on Small Caps.
What are Small Caps?
The term "Small Cap" refers to a company's capitalization, determined by the total value of its publicly traded shares. Small Cap stocks are generally defined as the shares of publicly traded companies with a market capitalization ranging from $300 million to around $2 billion. These stocks are considered to offer better returns, due to investors' lack of knowledge of their growth potential and lack of institutional interest.
From 1928 to 2016, the S&P 500 index rose by 9.7%, while Small Cap value stocks rose by 13.5%. However, the quest for higher returns entails higher risk, although this risk can be controlled by long-term investors.
Take your algo trading strategies to the next level
Use our strategy database to develop quantitative strategies faster.
✔️ Research papers
✔️ Trading rules
✔️ Performance metrics
✔️ Python code
The Small Caps premium
The relationship between size and returns is essential for several reasons. It has become one of the main points of discussion concerning market efficiency. In addition, the size factor has become one of the essential elements of current asset pricing models used in the literature.
Small caps have not always offered a stable premium. In the 1960s and 1970s, a strong premium was observable, but it disappeared in the 1980s and 1990s, only to reappear in the 2000s. This phenomenon shows that the Small Caps premium is influenced by behavioral rather than risk factors.
Several explanations have been proposed for this size premium. Some believe that this premium represents investors' compensation for higher systematic risk. Other theories suggest that the premium may be due to low Small Caps liquidity, survivorship bias, market frictions, or other behavioral factors.
Small Caps and Algo Trading
With the advent of algo trading, Small Caps have gained in popularity among algorithmic traders. Algorithms can be designed to quickly identify investment opportunities in Small Caps using historical data and market indicators. These algorithms can help traders navigate the complex Small-caps landscape and maximize their returns.
Small Caps offer a unique opportunity for investors seeking to maximize their returns. Although these stocks present higher risks, they also offer higher potential returns. Thanks to algo trading, investors can harness the power of algorithms to successfully navigate the world of Small Caps. Ultimately, as with any trading strategy, thorough research and rigorous analysis are essential for success in small-caps trading.
💡 Read more:
- Trading strategies papers with code on Equities, Cryptocurrencies, Commodities, Currencies, Bonds, Options
- A curated list of awesome libraries, packages, strategies, books, blogs, and tutorials for systematic trading
- A bunch of datasets for quantitative trading
- A website to help you become a quant trader and achieve financial independence