Here I would like to remind readers that the content of this article is slightly biased towards the financial major. If readers are not from financial background, they may encounter some unfamiliar concepts and terms. But you don't have to be too scared. The logic behind these technical terms is not complicated. I will try my best to make this problem clear in simple and understandable language.
The above picture vividly explains smart beta. In financial investment, there are two basic concepts called alpha and beta (friends who are not familiar with these two concepts can see my article "Explain alpha and beta: How do beginners choose funds?" -Zhihu). In the above picture, the green circle on the left represents beta (that is, market return) and the blue circle on the right represents alpha (that is, excess return).
Intelligent Beta is the circle in the middle of the above figure, which is between passive investment (Beta) and active investment (Alpha). Smart Beta has a very clear and transparent index ranking standard, and can help investors get higher than the average market return according to historical backtesting.
The investment idea of Smart Beta is based on factor investment. Speaking of factor investment, I need to introduce an academic genius named Eugene Fama.
Professor Fama, Professor of Finance at the University of Chicago, won the 20 13 Nobel Prize in Economics. He has many academic achievements, such as Efficient Market Theory (EMH). What I want to mention today is1968+the stock return model put forward by Professor Fama and another professor Kenneth French in the early 1990s, which is called Fama French three-factor model.
In this model, Fama and French believe that the stock returns in American history can be largely explained by three factors. These three factors are: the total return of the stock market (beta), the small excess return of small-cap stocks (small decrease) and the high excess return of value (high decrease).
Why is this model important? Because Fama and French decompose the stock returns to the factor level, they further reveal what kind of stocks can get the source of excess returns.
The above picture shows Fama and French's backtesting of the US stock market from 1928 to 2007, which has been nearly 80 years. In the 80-year stock history backtesting, we can see that the average return of the stock market is about 10% per year (blue TM circle above), the average return of small stocks (SC sky blue circle) is about 12% per year, and the average return of large-value stocks (purple LV circle above) is about1/kloc-per year. If the two are superimposed, the annual return of small value stocks (SV, the upper right corner of the above figure) is about 14%.
In other words, the excess return of small-scale factors is about 2% per year, and the excess return of value factors is about 1% per year.
Having said that, I believe you have a certain understanding of the strategy of stock hedge funds: that's how they choose stocks. So how many of these factors did they use in stock selection, what factors did they use in the end, and which factors had a more significant impact on the stock price? To illustrate this point, I need to introduce another great person: Barr Rosenberg.
Barr Rosenberg is an economics professor at the University of California, Berkeley. During the period of 1970, he began to do some financial research consulting work for Wells Fargo, mainly analyzing the correlation between the earnings of listed companies and the stock market. Later, Rosenberg founded a consulting company named BARRA based on his own research results (Barra was acquired by MSCI in 2004, and the new company was named MSCI BARRA), which mainly analyzed the return risk factors of the company's stock. What does this mean? Let me give a very simple example:
Suppose you choose some stocks as a fund manager, you need to know what factors will affect the returns of these stock portfolios. In other words, you need to know where your risks are. According to the research done by many professionals in the past, there are generally some factors: industry influence, price momentum, company size, company stock price fluctuation and so on.
The contribution of Rosenberg (and his partner Grenoble) is that they have developed a BARRA risk model, which can calculate the different effects of different factors on stock price changes according to historical prices. This model has now become an industry standard and has been adopted by almost all institutions. A very useful function of this risk system is that it can be used to test a fund manager's stock selection ability. For example, based on the stock portfolio selected by a fund manager, we can use this system to determine how much the return of the stock selected by the manager can be explained by some common risk factors (such as the small stocks mentioned above, momentum, value, etc.). ) and what is his real alpha?
Fama and Rosenberg's contribution to the financial investment industry is that their research reveals the source of excess returns in the stock market, that is, excess market returns (beta). For example, Fama's research shows that if we focus on choosing value stocks, investors can get better returns than the market over time. So, what factors have our researchers found that can provide excess returns?
1. Value: It is not Fama's initiative to choose stocks with low valuation and obtain excess returns. Friends who have read several stock books can cite Graham and Buffett's examples to support value investment. Here I need to expand some common misunderstandings of value investment.
First of all, investors face a question: what is the standard of low stock valuation? There is no standard answer to this question. For example, Fama uses the price-to-book ratio. But there are other different measures, such as the ratio of share price to equity, the ratio of share price to cash and so on. One of the important reasons why Fama and French's research is convincing is that they use the same index from beginning to end. The result of this back test is more convincing.
Another problem that value investors need to pay attention to is that patience and long-term persistence are the prerequisites for value investment to obtain excess returns. When we say that value investment can bring excess returns to investors, we mean long-term average (for example, Fama's historical backtesting of the United States in the past 70 years). But in those 70 years, the annual excess returns provided by value investment fluctuated greatly. In other words, in some years, value investment can give investors a higher return than the market; In other years, the return on investment of value investors will lag far behind the market return.
For example, the above chart shows the historical excess return value and momentum of US stocks from 197 1 to 2009. We can see that in terms of the excess returns provided by the value factor (the solid gray line at the bottom of the above figure), there is no guarantee that it will provide better returns than the market every year. For example, during the period of 1996-2000, value stocks were sold in large quantities. From 65438 to 0999, the share price of Buffett's Berkshire Hathaway Company fell by about 20%, which was one of the worst years in the company's history. Even the value investment concept that Buffett has always admired has been questioned by many people.
It is also worth mentioning that the excess returns provided by value investment are different in different countries, and the Fama research mentioned above is limited to the United States. Later, Fama and French extended their research to other countries in the world. Although there is a similar phenomenon of excess return on value investment in most countries, the return situation in each country is different.
2. Dividends: Many research documents point out that the dividend ratio of a company is a factor that can provide excess returns. In other words, if we focus on choosing companies with higher dividend rates, these stocks can provide higher than the average market return over time.
The chart above shows the historical rate of return of dividend aristocrats (red line) and the Standard & Poor's 500 Index (blue line). Standard & Poor's dividend index is composed of companies with high dividend distribution. If it is counted from 1990 to 20 14, the return of dividend index is much higher than the average market return. Of course, this higher return is not inevitable every year. For example, as can be seen from the above figure, during the period of 1998-200 1, the return of dividend index was lower than the market average return.
3. Momentum: If the price of a stock has risen a lot in the recent period (for example, in the past year), then we can buy this kind of stock and short the stock whose price has fallen a lot in the recent period, and we may get an excess return that exceeds the average market return.
On it, there is a historical return chart of American stock value and momentum factor. From the figure, we can see that from the year of 197 1, we can get excess returns by buying those stocks with positive momentum and shorting those stocks with negative momentum (that is, the dotted line in the above figure). Of course, it is worth mentioning that the yield curve assumes that the transaction cost is zero, so it is impossible to obtain such a high yield in actual transactions (because momentum strategy depends on very frequent trading frequency).
4. Low volatility: If you continue to choose to buy and hold stocks with low price volatility in history, investors can get higher than the average market return in the long run.
5. Quality: If we continue to choose companies with higher fundamental quality (such as companies with higher ROE), investors can get better returns than the average market return rate in the long run.
6. Scale: If you always choose a small company, investors may get higher than the market average in the long run.
It should be pointed out that all these return factors that can bring excess returns are unstable. For example, the above figure shows the returns of MSCI World Index from 1988 to 20 13. As you can see, the return of these factors can be described as the turn of the wind. For example, the value factor (the red line above) performs poorly in 1996- 1999. The momentum factor (yellow line above) was hit hard in 2007-09.
In other words, if you really want to get stable excess returns from factor investment, then investors need to predict in advance which factor will have better returns in the future (for example, 3-5 years), or establish an effective system to rotate among different factors. This is undoubtedly as difficult as stock selection.
Here are some institutions and researchers who have done well in factor research:
1) Fama and French: As I mentioned above, Fama and French put forward the three-factor model for the first time in the paper published in 1992. The three elements include market, small reduction and large reduction, and high reduction. Later, the three-factor model was applied to the international market outside the United States and extended to the five-factor model (adding two factors: profit rate and investment).
2)Carhart's four-factor model: Carhart increased the motivation on the basis of Fama and French's three-factor model, and put forward his four-factor model, which has been widely concerned.
3) Fundamental index model: This model was put forward by American economist Robert Arnot. Arnot Fundamental Index is a revision of the traditional index based on market value. In an index based on market value (such as Standard & Poor's 500), the weight of stocks in the index is determined by market value. For example, if the market value of Apple shares accounts for 5% of the total market value of 500 S&P stocks, then the weight of Apple shares in the S&P index is 5%. The advantage of arranging the indexes in this way is that the indexes do not need to be rebalanced, because price changes do not affect the changes of index components. But the disadvantage is that in the case of unreasonable market valuation, the more overvalued the stock, the greater its weight. For example, when the bubble of technology stocks peaked at 1999, the weight of technology stocks in major indexes was ridiculously high. In this case, the stock index held by investors may be overestimated or underestimated.
Arnot corrected the above shortcomings by changing the calculation method of the weight of constituent stocks in its index. Arnot abandoned the traditional method of calculating the weight of constituent stocks based on market value, and replaced it with fundamental quantitative standards, such as the company's sales, cash flow, dividends and market value. Using this method to calculate the weight of constituent stocks in the index can avoid including too many overvalued stocks in the index.
4) Cliff Asness: Cliff Asness is the founder of AQR, a famous American hedge fund, and a student of Eugene Fama mentioned above. The investment method of AQR's external publicity is based on four factors: value, momentum, low fluctuation and arbitrage.
So what does this research have to do with us ordinary investors? This is a big deal. To explain this problem in detail, I need to start with the factor index. Why start with the factor index? Because if there is a certain factor that can bring excess returns to investors, then firstly we should be able to create an index (such as the above-mentioned value index) based on this factor, and then we will create an index fund (the purpose of the index fund is very simple, that is, to copy the returns of the index) so that investors can invest.
In the field of factor index, several companies are global leaders. Let me give you a brief introduction.
The first is MSCI (Morgan Stanley Capital International). MSCI's predecessor was Morgan Stanley Capital International Index, and later it was separated from Morgan Stanley and acquired Barra, so now its full name is MSCI Barra(Barra was founded by Barr Rosenberg mentioned above).
If you are interested in financial news, you should know that whether MSCI lists A shares as its constituent stocks can always become big news every year. The main reason is that there are quite a few institutions and funds tracking MSCI index in the global financial sector. In other words, this is a benchmark in the industry. Whether MSCI decides to include A shares in its world stock index will directly affect the number of A shares purchased by international funds, so it is not surprising that people pay attention to it.
The factor index compiled by MSCI is comprehensive, including all the factors such as value, scale and momentum I mentioned above. The countries covered by its factor index are mainly developed countries in Europe and America, while the coverage of developing countries (including China) is very small.
Followed by Standard & Poor's Dow Jones. The flagship product of Standard & Poor's is the Standard & Poor's 500 Index, which is widely used by the industry as a benchmark to represent the American stock market. Dow Jones is the company with the longest history of compiling indexes, with a very famous Dow Jones Industrial and Commercial Index (30 blue chips). Standard & Poor's and Dow Jones merged to form Standard & Poor's Dow Jones. Their index is mainly in the American market.
FTSE Russell was formed by the merger of FTSE and Russell. The company's factor index is also diverse and covers many markets outside the United States. At the same time, the fundamental index proposed by Arnot mentioned above also belongs to the company.
After talking about the index companies that provide factor indexes, let's introduce the fund managers who track these indexes. The job of these fund managers is to copy these indexes according to the rules of index arrangement, so as to give investors a return similar to the index. Of course, the closer the return is to the exponential return, the better, but it can't be done in practice. Because the index does not consider transaction costs and fund management costs.
There are many companies that are more advanced in this field. The first is BlackRock IShares. In 2009, BlackRock acquired BGI for $65.438+0.35 billion, and also bought the IShares brand. Under BlackRock IShare, there are relatively comprehensive factor index funds, such as the value, momentum and low volatility funds in the above table. The total expense ratio of these funds is about 0. 15%, but it should be noted that most of them are limited to the US market.
Pioneer, pioneer, is another giant in the field of index funds. Pioneer does not provide many products in factor index, only dividend, low volatility and small stock index funds, and it is limited to the US market. Of course, if this field is the future development direction, I believe that major companies will launch more products one after another.
Jing Shun Energy and Charles Schwab also provide many factor index funds. The disadvantage is that their rates are relatively high, generally between 0.25% and 0.6% (as shown above). Arnot's Fundamental Index Fund is managed by Charles Schwab, with a rate of 0.32% per year, which means that the index needs to outperform Standard & Poor's by at least 0.28% per year (the Pioneer Standard & Poor's 500 Index Fund has a rate of 0.05%) to benefit investors.
abstract
The analysis of stock factor income is a great innovation and progress in the financial field. The greatest contribution of this study is to let investors know the source of possible excess returns, and let ordinary investors get these factor returns at a relatively low price (through factor index funds). In a world without factor index funds (such as China), investors can only get these factor returns through investment fund managers and pay relatively high fees (maybe 1.5%-2% per year, and in some private equity funds, they need 15%-20% profit sharing). These factor index funds only charge about 0. 15%-0.6% of the total cost, and there is no profit sharing, which is really good news for investors.
Another great contribution of factor return research is that it provides investors with the possibility to design their own hedge fund strategies. In most stock hedge funds, the job of the fund manager is nothing more than buying some factors and shorting others. If there is a factor-based index fund in the market and it can be sold short, then it is no longer a dream for our investors to trade their own hedge funds.
Of course, technological progress will never stop. I believe that the factor index fund in China market will appear sooner or later. By then, China investors will also have greater investment choices.
I hope it will help everyone.
References:
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Wu Zhijian: Little Turtle's investment wisdom: How to overcome the strong with the weak in investment?
Wu Zhijian: Little Turtle's Investment Wisdom II: The Survival Rule of Jungle Investment