Quantitative research has been used in a variety of disciplines, such as physics, insurance, sports, and investing.
Quantitative investing is a systematic, structured, approach to investing which relies on data to make investment decisions rather than quantitative judgment which is prone to cognitive biases.
An overview of quantitative investing
I’m a quant fanatic, I truly believe (and evidence backs me) that relying on data to make your decisions in every aspect of life is the best way forward and will yield the best results. Not only can it improve investment returns, but it also helps drastically decrease stress and the amount of time you spend thinking about your investments.
It ranges in complexity from applying a couple of filters in a stock screener to using an AI to perform applied mathematics on a dataset.
Quantitative analysis analyzes the historical data available to determine risk and return indicators and suggests buying opportunities based on trade prices, fundamental ratios, alternative data, and a variety of other things. It can be a complex process usually done by a specialist. My goal at Aikido Finance is to help make quant investing more accessible!
The form of quantitative investing which is most accessible to the everyday investor is factor investing. Factor investing is a style of investing that chooses securities based on attributes that have historically been associated with higher returns. These strategies are built using a variety of filters which are put together like lego pieces.
The quantitative factors
- Value: Picking stocks that have low prices relative to their fundamental value.
- Size: Small-cap stocks exhibit higher returns
- Momentum: Stocks that have outperformed in the recent past tend to continue with strong returns going forward.
- Quality: Picking stocks with low debt, stable earnings, consistent asset growth, and strong corporate governance.
- Volatility: Picking stocks with low volatility earn greater risk-adjusted returns than highly volatile assets.
Creating a portfolio using a factor-based approach can be a great way to control the risk associated with investments and provide better returns. Also, it diversifies the portfolios. Factor Investing is not day trading, it’s more focused on long-term goals.
Generally, there is a 4 step process to building a factor-based quant strategy. We use this format at Aikido:
- Universe selection: We analyse the whole stock universe and cap the market, country-wise and industry-wise. Example: US micro-cap stocks (1500 stocks)
- Filters: We measure and filter the different factors of the stock which would be value, health, quality, dividend, and technical. Example: price/sales less then 1 & positive 3&6 month price momentum (92 stocks)
- Rank: We rank the remaining stocks based on 1 or more other metrics. eg. Highest 12-month price increase
- Pick: Create your portfolio using the companies at the top of the list, usually 10-20 stocks.
If you invested $10k using that strategy in 1965 and rebalanced yearly, today it would be worth $95M, an 18.1% return. To put that in comparison, the same $10k investment in the S&P500 in 1965 would be worth $1M, an 8.8% return. Of course, these are simulated returns determined by historical backtests. While historical returns are not indicative of future results, they can definitely help you in your investment decisions.
I suppose for me, why quant investing is so important is that it gives me the chance to outperform the market which helps me in reaching my goal of achieving FIRE – Financial Independence Retire Early. The difference of 8% per year and 15% per year return make a big difference to how long it takes to reach financial independence.
So let me know have you tried to implement a factor model?
If you’re interested in becoming a quant, check out Aikido Finance. We supply simple, evidence-based investing strategies, to help you build a performant portfolio. Our mission is to bring quantitative investing to everyone. For 10% off, enter the discount code purplecow at checkout.
So, until then, take it easy!