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Factors are to securities, what nutrients are to food. Just as milk has fats and protein that contribute to its nutritional value, a stock might have value and quality attributes that drive its return. Just as there are six classes of nutrients in food (carbohydrates, lipids, proteins, vitamins, minerals, and water), there are 7 widely-accepted factors in investing (value, quality, size, volatility, momentum, dividend, and growth). The investing factors have been utilized for over 200 years, but only recently have been fully studied, understood, and properly utilized.
In this guide, I will give an overview of factor investing and delve into the history going back to 1960 of this fascinating area. By the end you should have a good understanding of what factor investing is, and why it is so important to utilize it.
I’m shane, an algorithmic investor on the road to financial independence, and the founder of Aikido Finance!
Now let’s hop in!
What is Factor Investing?
Factor investing has seen massive growth recently. It is starting to be used a lot by professional investors but is still very much underutilized by retail investors. As I see it, factor investing is pretty much the most overlooked and important concept in investing.
Factor investing is the scientific way to invest. It is a method of choosing securities based on attributes that historically have been associated with higher returns. With the aim of enhancing diversification, providing market outperformance (alpha), and managing risk.
Factor investing flies in the face of efficient market hypothesis. Efficient market hypothesis (EMH) is the widely accepted idea that you can’t beat the market, it’s impossible, there is no information you could possibly have as an investor that hasn’t already been priced into the security. Factor investing proves the hypothesis wrong.
Indeed, you very much can beat the market, it is possible. Stocks don’t take a random walk down Wall Street, they take purposeful strides – following the factors.
Macroeconomic Factors
There are two types of primary factors. There’s macroeconomic factors. And there are style factors.
Macroeconomic factors could include a fiscal or geopolitical event, that affects the regional, national or even global economy. For example the GDP growth of a country, the unemployment rate, the printing of money, or even an unforeseen event, a black swan event, like a tsunami, an earthquake, or covid.
While these can all have big effects on the stock market; they are usually really, really hard to to predict, and even more so to know how they’re going to affect economies in general. That’s really because there’s just not a huge amount of data out there on how a tsunami for instance, effects an economy.
The most famous macro economic factor investor is Ray Dalio, who was the founder of Bridgewater. He’s very much an expert in the field of macroeconomic factor investing.
Some of the key macroeconomic factors that we could look at are:
Economic growth
Interest rates
Inflation
Credit
Political risk
Liquidity
Style Factors
Macroeconomics is probably not the best form of factor investing for the retail investor to utilise. Instead, the style factors are very accessible and more easily understood.
The seven widely-accepted investing factors are:
Value
Quality
Size
Volatility
Momentum
Dividend
Growth
We’re going to go pretty deep on each of these seven in seperate guides.
But there’s actually potentially hundreds, if not 1000s, of teeny tiny factors that are not broadly accepted or understood. Some of these factors may not be human-understandable, but rather require machine learning to uncover.
However, the seven factors I mentioned above account for over 95% of market outperformance and are easiest for retail investors to utilize.
The History of Factor Investing
Capital Asset Pricing Model (CAPM)
In the 1960s, CAPM was introduced as the first factor model. It tries to explain the variance between the performance of different stocks. It contains a single factor; risk. CAPM says that investments should return the risk-free rate (US Treasury Bills) plus a risk premium, measured by the volatility (standard deviation) of returns. As a result, investors who want to achieve high returns should invest in more volatile stocks, according to this model. The volatility of a stock, relative to the market is known as beta (ß).
For the nerds
r = Rf + ß(E(Rm)-Rf)
where
r – the expected return
Rf – risk-free rate – US Treasury Bills, for example.
ß – the factors coefficient.
(E(Rm-Rf) – Excess risk relative to the market.
If you remember any linear algebra, it might look familiar. The intercept is (Rf), the risk-free rate while the slope is (ß) beta.
CAPM can be simply described as “The higher the risk, the higher the expected return.“
The Three-Factor Model
Quantitative investing progressed in 1981, a paper by Rolf Banz established the size factor in stocks: smaller company stocks outperform larger companies over long time periods, and had done so for at least the previous 40 years.
In 1993, Eugene Fama and Kenneth French wrote one of the most important economic papers of all time. They established the three-factor model which contained size, market risk, and value. They found that it accounted for over 90% of a stock’s returns.
For the nerds
r = CAPM + (ß2 * SMB) + (ß3 * HML) + ε
where
SMB – (Small minus Big) – The historic excess returns of small stocks over large stocks
HML – (High minus Low) – The historic excess returns of value stocks (low P/B) over growth stocks (high P/B)
ß – the factors coefficient
ε – error
The three factor model can be simply described as “Buy small, cheap stocks“.
The Four-Factor Model
In 1993, Sheridan Titman and N. Jegadeesh wrote a paper that showed that there was a premium for investing in high momentum stocks, laying the groundwork for the momentum factor. Momentum is the difference in price from one period to the next. 3, 6 & 12 months are the most common time periods used.
UMD – (Up minus Down) The historic excess return of high momentum stocks over low momentum stocks.
The four factor model can be simply described as “Buy small, cheap stocks, which are on the rise“.
The Five-Factor Model
In 2015, Fama and French improved their three-factor model by adding two additional quality factors. They used profitability and investment aggressiveness. Interestingly, they did not include momentum in their revised model.
For the nerds
r – Three-Factor model + ß4 * RMW + ß5 * CMA + ε
where
RMW – (Robust minus Weak) – The historic excess returns of assets with high operating profitability over ones with ones with low operating profitability.
CMA – (Conservative minus Aggressive) – The differences between firms that invest conservatively vs those who invest aggressively.
The five factor model can be simply described as “Buy small, cheap stocks,with high profitability, which reinvest earnings“.
Many investors question the exclusion of momentum in the Fama-French models, since its impact on return was widely accepted. Cliff Asness, founder of AQR and former student of Fama, argued for a six-factor model which also included momentum.
The dividend factor is also not included in the standard three, four, and five factor models. However, it has been found that over an 88 year period high dividend-paying stocks outperformed by 1.5% per year on average.
The Factors of the Future
The most important factors have already been discovered and are now being widely utilized by professionals. However, that’s not say that more will not be uncovered in the future, especially with the help of machine learning and AI.
As we’ve seen, factor investing is a new field that has completely changed how we understand the movement of stocks. It has blown efficient market hypothesis out of the water, and will continue to do so as it’s popularity increases.
In the next few guides, we are going to deep-dive on each of the investing style factors so that you can see first hand just how powerful these factors really are and get an idea of how you can start to utilize them.
Like stock prices, factors improve and deteriorate over time. Factors exhibit momentum. AQR Capital’s “Factor Momentum Everywhere” was named “Best Article” in the 2020 Bernstein Fabozzi/Jacobs Levy Awards. With this in mind, we will also look at how to choose which factor(s) to use at a given point in time.
In the meantime, if you want to adopt a factor-based approach into your investing, you can check out Aikido Finance.
In recent years, the use of algorithms has spread across all sorts of different industries and practices. While we think of algorithms as complex mathematical
An Overview and History of Factor Investing
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Index
Factors are to securities, what nutrients are to food. Just as milk has fats and protein that contribute to its nutritional value, a stock might have value and quality attributes that drive its return. Just as there are six classes of nutrients in food (carbohydrates, lipids, proteins, vitamins, minerals, and water), there are 7 widely-accepted factors in investing (value, quality, size, volatility, momentum, dividend, and growth). The investing factors have been utilized for over 200 years, but only recently have been fully studied, understood, and properly utilized.
In this guide, I will give an overview of factor investing and delve into the history going back to 1960 of this fascinating area. By the end you should have a good understanding of what factor investing is, and why it is so important to utilize it.
I’m shane, an algorithmic investor on the road to financial independence, and the founder of Aikido Finance!
Now let’s hop in!
What is Factor Investing?
Factor investing has seen massive growth recently. It is starting to be used a lot by professional investors but is still very much underutilized by retail investors. As I see it, factor investing is pretty much the most overlooked and important concept in investing.
Factor investing is the scientific way to invest. It is a method of choosing securities based on attributes that historically have been associated with higher returns. With the aim of enhancing diversification, providing market outperformance (alpha), and managing risk.
Factor investing flies in the face of efficient market hypothesis. Efficient market hypothesis (EMH) is the widely accepted idea that you can’t beat the market, it’s impossible, there is no information you could possibly have as an investor that hasn’t already been priced into the security. Factor investing proves the hypothesis wrong.
Indeed, you very much can beat the market, it is possible. Stocks don’t take a random walk down Wall Street, they take purposeful strides – following the factors.
Macroeconomic Factors
There are two types of primary factors. There’s macroeconomic factors. And there are style factors.
Macroeconomic factors could include a fiscal or geopolitical event, that affects the regional, national or even global economy. For example the GDP growth of a country, the unemployment rate, the printing of money, or even an unforeseen event, a black swan event, like a tsunami, an earthquake, or covid.
While these can all have big effects on the stock market; they are usually really, really hard to to predict, and even more so to know how they’re going to affect economies in general. That’s really because there’s just not a huge amount of data out there on how a tsunami for instance, effects an economy.
The most famous macro economic factor investor is Ray Dalio, who was the founder of Bridgewater. He’s very much an expert in the field of macroeconomic factor investing.
Some of the key macroeconomic factors that we could look at are:
Style Factors
Macroeconomics is probably not the best form of factor investing for the retail investor to utilise. Instead, the style factors are very accessible and more easily understood.
The seven widely-accepted investing factors are:
We’re going to go pretty deep on each of these seven in seperate guides.
But there’s actually potentially hundreds, if not 1000s, of teeny tiny factors that are not broadly accepted or understood. Some of these factors may not be human-understandable, but rather require machine learning to uncover.
However, the seven factors I mentioned above account for over 95% of market outperformance and are easiest for retail investors to utilize.
The History of Factor Investing
Capital Asset Pricing Model (CAPM)
In the 1960s, CAPM was introduced as the first factor model. It tries to explain the variance between the performance of different stocks. It contains a single factor; risk. CAPM says that investments should return the risk-free rate (US Treasury Bills) plus a risk premium, measured by the volatility (standard deviation) of returns. As a result, investors who want to achieve high returns should invest in more volatile stocks, according to this model. The volatility of a stock, relative to the market is known as beta (ß).
For the nerds
If you remember any linear algebra, it might look familiar. The intercept is (Rf), the risk-free rate while the slope is (ß) beta.
CAPM can be simply described as “The higher the risk, the higher the expected return.“
The Three-Factor Model
Quantitative investing progressed in 1981, a paper by Rolf Banz established the size factor in stocks: smaller company stocks outperform larger companies over long time periods, and had done so for at least the previous 40 years.
In 1993, Eugene Fama and Kenneth French wrote one of the most important economic papers of all time. They established the three-factor model which contained size, market risk, and value. They found that it accounted for over 90% of a stock’s returns.
For the nerds
The three factor model can be simply described as “Buy small, cheap stocks“.
The Four-Factor Model
In 1993, Sheridan Titman and N. Jegadeesh wrote a paper that showed that there was a premium for investing in high momentum stocks, laying the groundwork for the momentum factor. Momentum is the difference in price from one period to the next. 3, 6 & 12 months are the most common time periods used.
In 1997, Mark Carhart proposed a four-factor model, expanding on Fama-French’s work. Momentum, value, size, and market risk were the factors.
For the nerds
The four factor model can be simply described as “Buy small, cheap stocks, which are on the rise“.
The Five-Factor Model
In 2015, Fama and French improved their three-factor model by adding two additional quality factors. They used profitability and investment aggressiveness. Interestingly, they did not include momentum in their revised model.
For the nerds
The five factor model can be simply described as “Buy small, cheap stocks,with high profitability, which reinvest earnings“.
Many investors question the exclusion of momentum in the Fama-French models, since its impact on return was widely accepted. Cliff Asness, founder of AQR and former student of Fama, argued for a six-factor model which also included momentum.
The dividend factor is also not included in the standard three, four, and five factor models. However, it has been found that over an 88 year period high dividend-paying stocks outperformed by 1.5% per year on average.
The Factors of the Future
The most important factors have already been discovered and are now being widely utilized by professionals. However, that’s not say that more will not be uncovered in the future, especially with the help of machine learning and AI.
As we’ve seen, factor investing is a new field that has completely changed how we understand the movement of stocks. It has blown efficient market hypothesis out of the water, and will continue to do so as it’s popularity increases.
In the next few guides, we are going to deep-dive on each of the investing style factors so that you can see first hand just how powerful these factors really are and get an idea of how you can start to utilize them.
Like stock prices, factors improve and deteriorate over time. Factors exhibit momentum. AQR Capital’s “Factor Momentum Everywhere” was named “Best Article” in the 2020 Bernstein Fabozzi/Jacobs Levy Awards. With this in mind, we will also look at how to choose which factor(s) to use at a given point in time.
In the meantime, if you want to adopt a factor-based approach into your investing, you can check out Aikido Finance.
Until next time!
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