3. Single Stock Selection Strategy
3.1 Interpretation
The above study shows that the conventional theories such as size effect and diversification could be a myth. Even if the small caps might yield higher returns than large caps according to the result of statistics, it doesn’t mean it is good to invest our money into those small caps which we barely know their fundamental details and risks, regardless to say which one would be considered to be our best single stock target. In my view, it is meaningless to compare the average return between large caps and small caps before making an investment decision given we still don’t know which stock would be the best idea after testing the size effect. The strategic thinking should be focused on how to find a good stock which is more easily to beat the index fund.
The below study emerged from something interesting I found during the process of examining the size effect. The individual stocks with the leading market capitals seem have excess returns in some cases, if comparing with the index fund. By only picking those top market caps as our single stock targets and applying periodic rebalance to eliminate those in the downturn trend, could it be a useful tool for us in equity investment?
3.2 Data Collection and Methodology
This is a single stock selection strategy idea which only invests in the leading market cap firm to see whether it outperforms than the index fund or not. I decide not to include too many large cap stocks but only the top 2 to keep it clean and simple.
I choose the S&P 500 as my database. The reason I sourcing the market data from the United States rather than from Taiwan or other Asian countries is because 1) the largest market cap stock trading in the Taiwan, Hong Kong or Japanese Stock Market has been always occupied by single company for a very long time, which is difficult to observe the
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rotation effect, 2) the stock with the top market cap in the S&P500 has changed around 10 times in the past 20 years, which is good to examine my strategy. I also believe the U.S. stock market has the highest efficiency well to do sampling.
The share prices and market value data was sourced from the Bloomberg that spanned from 1996/12/30 to 2017/6/30. The initial date was targeted at end-1996 given a more precise period in calculating 20-year total returns. Monthly total stock returns are calculated by the share prices of the last trading day on each month.
All stocks in S&P500 are ranked by market values in descending order on every rebalance day in order to find which one has the largest market caps. 9 companies are selected into the pool given 4 of them were ranked as the top market-value stocks during different time whilst the rest were the 2nd largest market caps in the S&P 500 during different periods.
The initial fund is assumed to be $1m and fully invested without considering the extra expenses of trading costs or tax. The rebalance date is set to be end-Jun and end-Dec. The frequencies of 6-month rebalancing are based on the reasons that, firstly, the top 2 companies ranked by market values only changes once a while within one or two years, or even longer because of the super huge market values are hardly to be outpaced by other stocks. Hence, 6-month rebalances should be long enough to reflect in-time ranking changes.
Secondly, most of the momentum portfolios are formed based on past 6-month returns, and hold the position for 6 months, as we can find from the research conducted by Jegadeesh and Titman (1993) and Moskowitz and Grinblatt (1999). It would be ideally to adopt the similar approach since my strategy is elaborated from the concept of momentum strategy.
There are 3 kinds of single stock portfolio. Portfolio A is always to hold the stock that has the largest market values. Portfolio B is to own the second largest market cap stock.
Portfolio C is to equal weight the holdings of Portfolio A and B.
The methodology underlying the portfolio construction is described as below:
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Portfolio A: In the beginning day (30/Dec/1996) of investment, I buy the stock X1 that has the top market values in the S&P500 and hold it until the next rebalance day, which would be 30/Jun/1997, six month later. If X1 remains the top cap stock by the rebalance day, then no action will be taken. However, if X1 is replaced by another company, let’s say X2, I will do stock switch to X2 from X1 on the rebalance day. The selling/buying prices of X1 and X2 are defined to be their last prices of the rebalance day for the purpose of quick and dirty calculation.
Portfolio B: The rebalance mechanism is the same as Portfolio A but the target stock Y1 is the one with the second largest market cap.
Portfolio C: The fund is split into 50:50 that invests in both Portfolio A and Portfolio B with equal weight.
The total return, annualized return and the standard deviation of Portfolio A, B, C will then be compared with that of S&P 500 index fund, S&P 100 index and Russell 2000 index during four kinds of time interval: 1997~2017, 2007~2017, 2012~2017, and 2015~2017. This is for the purpose of comparing what might be changed in different periods. We then can understand my single stock selection strategy works or not.
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deviation and Sharpe Ratio during four different holding periods for Portfolio A, B, C versus S&P 500 index fund, S&P 100 index, and Russell 2000 index.Portfolio A doesn’t prove to be successful as the 20-years, 10-years and 5-year annualized returns are all below those of S&P 500 index fund by 1.03%, 1.12% and 6.67%, respectively. Only the investment during 2015~2017 generates a significant excess return of 4.52% (Table 4-1).
Surprisingly, Portfolio B shows a contrary result that the excess returns are all positive in different periods. The average annualized excess return increased considerably over time, from 0.85% over the 20-year period, to 12.43% over the period 2015~2017. It is also worth noting the numbers during 2012~2017 comparing with Portfolio A, which has the worst performance of negative excess return of -6.67%, whilst Portfolio B reaches a very good excess return of 9.77%.
As for the Portfolio C, the excess returns are in between of Portfolio A and B as expected since it is an equally weighted portfolio. This balance strategy offsets the poor performance of Portfolio A and delivers positive 10-years, 5-year and 2.5-year excess returns of 1.56%, 1.12%, and 8.95%, respectively. Only the 20-year performance is almost the same as the benchmark without excess return.
The comparison of Sharpe Ratio, which is used to measure the risk-adjusted return, also shows an interesting result that Portfolio B is ranked top 1 both in the period 2007-2107 and period 2015-2017. Not surprisingly, Portfolio A has the worst Sharpe Ratio during mid-to-long-term period including Year 1997-2017, Year 2007-2017, and Year 2012-2017. It is