Why should someone start factor investing
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February 2024 · 5 min read

Why Use Factor Investing


Why factor investing ?

Factors have been employed for decades, but retail investors are only beginning to lift the lid on this investment approach. The world is becoming increasingly more quantified. People are tracking everything from sleep, caloric intake, light exposure, step count, and so on. It is only natural that we start to quantify our investments. Institutional money managers have been using data to guide their investments for decades and it’s about time that retail investors hop on this trend.

Of course, not every professional investor has adopted the data-driven approach. There are still many actively traded funds, but their services are expensive and the majority do not outperform the market. A 2007 study by Andrew Ang found that the primary driver of returns for the active fund in question was simple style factors.

70% of all active returns on the overall Fund can be explained by exposures to systematic factors over the sample

The active manager's underperformance has continued through the last two decades - new 2022 CNBC report finds almost 80% of active fund managers are falling behind the major indexes.

The message is simple - don't pay exorbitant fees for something you can achieve yourself, through factor investing.

Let’s dive in and start with some definitions.

What is factor investing?

It is a strategy that chooses investments based on common elements that drive higher returns. It is as simple as that. You might be wondering, “what are these common elements?” We’ll focus on style factors in this post, but there is another category known as macroeconomic factors. Style factors are derived from the fundamental and market data that relate to an individual stock. They are generated from

  • A company’s financial reports such as balance sheet, cash flow, and income statements
  • Market data such as price, volume, and other statistical data

From this vast expanse of data, we can then create thousands of derived metrics that are grouped together into the subsequent factor "styles".

  • value
  • quality
  • momentum
  • low-volatility
  • dividend

If you’d like to read more about the construction of these factors and what the styles represent, then visit our beginner topic or our slightly more in-depth tutorial on factors.

What are the benefits of using factors?


The single most important utility of factors is their long-term outperformance over the market. This has been well-documented by an endless number of investors and academics. Factor investing falls between active and passive investing as it is low-cost and structured but also aims to outperform a market-cap-weighted index. While the S&P 500 has outperformed almost every asset class over the past decade, driven by large-cap tech stocks, the pendulum is swinging back in favour of alternatives like the value and dividend factors. Let’s take a look at the results of some factor portfolios.


Smart-beta ETFs are rules-based investments. They are a cost-efficient way of getting exposure to factors. Let’s do some simple analysis. We’ve selected the highest market cap ETF for each style factor at the beginning of our data to avoid any look-ahead bias. We’ll use the S&P 500 (SPY) as our benchmark.

Performance of smart-beta ETFs versus the S+P 500 during the bull market run from 2010 onwards.
Performance of smart-beta ETFs versus the S+P 500 during the bull market run from 2010 onwards.

As we can see in the above chart since 2010 only the quality factor has outperformed the S&P 500 on the basis of a raw return.

Now, measuring performance by risk-adjusted returns shows a different picture as quality, dividend, and low-vol have outperformed the S&P 500 over the past ~13 years. Not every factor will not outperform over every period we measure. In the long run, they are expected to produce excess returns.

STRATxAI Factor Strategies

We’ve taken factor investing a step further at STRATxAI. We enable users to research and build their own factor-based strategies using our data, research environment and backtest engine. STRATxAI provides some pre-packaged strategies of various blends of factors.

Performance of smart-beta ETFs versus the S+P 500 during bull market run from 2010 onwards.
Performance of smart-beta ETFs versus the S+P 500 during bull market run from 2010 onwards.

Using these simple concentrated long-only factor-blends, we can see the total return of the portfolios outperforms the benchmark. Note the higher volatility, it’s important to remember that these strategies should be employed for their long-term benefits.


Investing is tough, and without a clear and defined approach, it is easy to get lost chasing returns in the hottest new stock or asset class. Discretional retail investors could be defined as momentum chasers, driven by behavioural bias and emotion. Short-term success trading meme-stocks is not a repeatable formula to consistently outperform over a longer term. The transparency of factors enables us to build long-term and sustainable financial independence. It gives you the data and confidence to back your decisions, which helps investors navigate drawdowns and the volatility of trading stocks.


When using factors in your investing strategy, rather than going in and out of factors, consider starting with a portfolio that is well diversified across key factors - Andrew Ang [Blackrock]

You don’t want to put all your eggs in one particular basket or investment. Diversification allows you to capture the performance of many factors at once. As we can see in the above charts, factors performance is very variable across time. The best way to address this is to have exposure to many factors at once. We can achieve this with a blended strategy of various factors.


Have you ever thought about how you might test an investment idea or hypothesis? Given the widespread availability of financial data, we can easily create and backtest a factor-based strategy. Using this framework, we can tailor our investments to those strategies that have an optimal historical returns.

How can we use factors ?

So with all this information in mind, how can we invest in factors? While there are thousands of research papers outlining the benefits of factor investing, going from the academic setting to the practical application of these factors is what confuses many people.


One option is to invest in smart-beta ETFs. As we said previously, they are a quick way to get exposure to a broad range of factors. While the performance and cost structure of the ETFs vary significantly by provider, they are an easy way to get started with factor investing.

Do it yourself

It’s never been easier to build your own investment strategy. While there are some barriers to entry, there are lots of tools available that make this process accessible to retail investors. Data providers like Alpha Vantage and Polygon.io offer cheap and readily consumable APIs for stocks and ETFs. API-first brokers like Alpaca Markets offer user-friendly trading APIs.

You can test with paper trading accounts before putting any capital at risk. Python allows you to import and analyse data, backtest and live-trade your strategy with little coding experience. There are an abundance of resources available online to guide you through developing your own factor-based investment strategy. You could start by checking out our easy to read educational content.


We’ve been working hard for almost three years to make factor investing mainstream. STRATxAI combines world-class data, a no-code research and backtest environment, and easy broker integration so that you can focus on the exciting part - investing in your future. Use our pre-built strategies or create your own with our factor playground. You can paper trade as many portfolios as you like and once you’re confident you can live trade via IBKR or Alpaca.

Visit STRATxAI today to start your factor investing journey.

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