Navigating Personal Trading as a Quant: Strategies and Considerations
In the world of quantitative trading, many professionals find that their day-to-day work is just the beginning. The ability to leverage one's expertise gained from a quantitative role for personal trading can be both a daunting and rewarding endeavor. In this piece, we explore the strategies and considerations that quants face when trading their own accounts, with a focus on both quantitative and qualitative methods.
The Quantitative Perspective
One quant, who led a medium-sized desk, opted to invest all his salary and bonus into real estate. He did very well, but he expressed reservations about trading his personal account. His concern was rooted in tail risk, referring to the potential for extreme, rare events that can significantly impact the portfolio. This cautionary tale highlights how the strictures of institutional trading can limit personal experiences.
For individuals with a solid quantitative background, personal trading can be approached with a range of strategies. Many, like myself, an ex-quantitative prop-trader, have developed algorithms and statistical models that they use for both institutional and personal trading. However, the challenges of implementing these strategies differ significantly between a professional setting and personal trading.
Algorithmic Strategies in Cryptocurrency Trading
Cryptocurrency has emerged as a particularly attractive arena for quants due to its less developed market and the absence of strict rate limits. My experience has led me to develop two statistical arbitrage-based algorithms specifically for trading cryptocurrencies. By focusing on sister currencies with high correlation and bear/bull coin pairs, I have been able to profit in the past few years. Additionally, the flexibility and high leverage opportunities in cryptocurrencies allow me to amplify my returns, which is not possible in traditional markets.
To give an example of the kinds of algorithms I use, I identify assets with consistent price swings through a custom algorithm and analyze catalysts driving these swings. For instance, in the airline industry, when strikes are announced, there are predictable price movements that I can capitalize on. This qualitative pattern recognition, combined with quantitative analysis, forms the backbone of my personal trading strategies.
Resource Limitations and Qualitative Aspects
While my quantitative skills are robust, the reality of personal trading presents significant resource limitations compared to institutional settings. Access to the same level of perpetual developer support, data access, and enforcement of leverage laws is simply not feasible. Conclusion of my work, whether at my previous job or personal trading, involves adhering to a fundamental rule: ride your winners and sell your losers. Additionally, selling when an asset falls below the 200-day moving average is a key decision criterion.
Popular Trading Strategies for Quants
Many quants, like myself, gravitate towards value and momentum-based trading algorithms. The restrictions and resources available to personal trading can lead to the development of simple rapid trading algorithms. For those with significant time and flexibility, incorporating more complex strategies, including statistical arbitrage and algorithmic trading, becomes more viable.
The term quant can encompass a wide range of financial professionals. Some definitions include anyone who uses math in a financial job, while others reserve the term for those with PhDs in math or physics conducting quantitative research. Regardless of the definition, the core of a quant is the ability to make precise calculations and bet on the outcomes.
Strategies and Considerations for Personal Trading
For individuals facing restrictions from their job, a popular approach is to create a factor portfolio based on various market factors. This strategy can offer a balanced approach without the necessity for complex algorithmic trading. With fewer restrictions and more access to time, quants might explore more sophisticated strategies, combining quantitative models with qualitative insights for a nuanced approach.
Ultimately, the success in personal trading for quants lies in the ability to adapt and leverage their expertise in creative ways. Whether through simple, rapid trading algorithms or more intricate quantitative models, the key is to understand the unique challenges and opportunities of personal trading.