Retire Rich: Buy Low And Sell High Consistently

Retire Rich: Buy Low And Sell High Consistently

The paraphrase “buy low and sell high” is often used in Wall Street jargon, but it does sound a bit over the top and, at times, too good to be true. However, this would be the dream of most investors to be able to buy low and sell high on a consistent basis. Obviously, it’s easier said than done, and most folks active in the stock market fail to achieve this. As a matter of fact, the record of retail investors is worse than any other category. Most retail investors vastly underperform the broad market due to several reasons, for example, being too conservative, sitting on lots of cash for long periods, buying at the top, and then selling at the bottom, etc.

Anyone can get lucky some of the time by buying and selling a stock at the right time. That quick profit certainly feels very good in the beginning, but that won’t make anyone rich in the long term. Before they know it, they would lose it all in the next trade. So, the question would be if it was possible to “buy low and sell high” on a consistent basis? In the first instance, it sounds like market timing, and certainly, we are not recommending market timing. But we believe there are ways that could allow you to buy low and sell high without indulging in market timing. Most of these methods fall into the realm of a systematic investing approach. The main advantage of a systematic approach is that it eliminates the emotional response that can impact our judgment, especially during market corrections or crashes.

We first wrote an article on this topic in early 2018, introducing a systematic approach that may allow buying low and selling high on a consistent basis. We wanted to re-visit this topic, first for the benefit of new readers, and secondly, we wanted to see how the system worked during the last couple of years and as a whole since 1995. However, we have modified the stock selection approach a bit compared to the last time.



Who Should Use This Strategy?

We want to clarify that the strategy discussed in this article may not be suitable for everyone. If all of your investable cash is ready to be deployed today, this strategy may not work best for you. This strategy will work best for folks who are in the accumulation phase and likely to contribute significant sums periodically. If your entire savings and contributions are within a 401(k) type of account, you may still be in luck, since many 401(k) providers/managers (like Fidelity) allow a part of the assets to be self-managed inside a brokerage-type account. Lastly, this can work even for folks who may not be in the accumulation phase, but they are able to transfer some of their assets from other passive accounts to this strategy.

We could broadly divide the investors into three types. We are not including traders in our definition of investors.

  • Most Passive Investors:

Most passive investors should stick to investing in broad indexes or ETFs, and if they can tolerate the market gyrations, over time, they will probably do fine.

  • Passive-Active investors:

These are the investors who are basically in the middle. Even though they are passive due to lack of time, expertise, or any other reason, they still like to invest in individual stocks. We think these investors should stick to DGI investing, meaning investing in large, blue-chip, dividend-paying, and dividend growing companies and holding them for long durations. They also could invest a small amount of capital in growth companies.

  • Active-Investors:

These are the investors who like to be on top of their investments. For some, it may even border on a part-time hobby. They always are in search of alpha in the market. They are open to looking at and trying new strategies.

Normally, we advocate investment in multiple strategies for such investors. By combining many strategies, we are able to bring diversification, improve returns, and reduce overall volatility and risks. Not all strategies are going to behave in the same manner at all times. When one strategy zigs, some others will zag.

With this spirit of looking for alpha, we are always experimenting and backtesting new ideas.

Buy-Low Sell-High Strategy [“BLSH”] Using DGI Stocks

Assumptions:

It may be best suited for folks who are in the accumulation phase and are still 10-20 years away from retirement. That said, it can still be used by anyone who is investing regularly in the stock market. This strategy may not be suitable for people who already are in the withdrawal phase since they will be selling and not buying most of the time. However, if they only withdraw the dividends, the strategy could still work for them. But everyone’s situation is different, and we recommend readers should judge the suitability based on their own situation.

This strategy does not require you to invest all of the money upfronts in a lump sum. It would require you to invest gradually over a period of time, likely many years. How much you invest depends again on your personal situation, but the strategy provides a lot of flexibility. The strategy would not compare or work well if your goal was to invest the entire amount in lump sum upfront.

Buy Strategy:

The strategy will invest for the long term in the following kind of stocks:

  • The selected companies should be fairly large, having a market capitalization of at least $10 billion.
  • The companies pay a good dividend and have a dividend history of at least ten years.
  • We want to fill at least half of our portfolio with dividend aristocrats (or champions) – those that have at least 25 years of dividend history with continual dividend growth.
  • For the rest of the portfolio, we should look at companies that may have a shorter dividend history, but still, we would want at least ten years of history.

For each stock, on a daily basis, we will calculate the average price of the previous 252 days (which is approximately one year in terms of trading days). We multiply this average price by a factor like 0.90 or 0.85, etc., giving us the “target price.” We will call this multiplication factor, the “Buy-Low-Factor.” We will provide the details below as to how we determine this factor. Thereafter, at the end of each day or week, we will compare the current price with the target price. If the current price is lower than the target price, we will buy the next lot of shares. We also determine the maximum number of shares that we want to have in any single company.

Buy-Low Factor:

For any given stock, we should look at the annual volatility. For low volatility stocks, the Buy-Low Factor would be 0.90. For stocks with higher volatility, it should be 0.85. Our strategy will rely mostly on low or medium volatility stocks. You can measure the volatility for a given stock over the past year and compare it with the S&P 500. But you could just make a guess generally based on the stock, the gap between its 52-week high and low, and the industry in which it operates. A good example of the low, medium and high volatility stock would be KO, HD, and AMZN in that order (though AMZN pays no dividend and would not be considered for our strategy). However, for the purpose of this backtesting, we have used the buy-low factor as 0.90 for all the stocks in the sample.

Example:

Stock: Procter & Gamble (PG)

Volatility: Low

Buy-low-factor: 0.90

Initial shares to buy: 50 (the split-adjusted number could be higher multiple)

Incremental shares to buy: 50

Maximum shares to hold at any time: 250-300 shares (this does not include the shares acquired from reinvested dividends).

Sell Strategy:

The “sell” strategy is optional. If the investor really believes in the stock/company and wants to retain the investment for the long term as buy and hold, there’s no need to adopt the “sell” strategy. Investors who may like to sell partially when the prices are high, and valuations are rich should adopt this “sell” strategy. However, without the “sell” strategy, you may not have additional or enough funds to invest when prices are low.

As in the “buy” strategy, for each stock, on a daily (or weekly) basis, we will calculate the average price of the previous 252 days (approximately one year in trading days). However, we will use multiple criteria to determine the sell decision.

  • Current shares match or exceed the target-allocation
  • And current-price > 1.15 times 252-days-average-price
  • And current-price > 1.10 times last-buy-price (most recent buy)
  • And current-price > 1.50 times our average-cost-basis in the stock.

When all four conditions are met, we will sell a partial quantity (generally the same number of shares that we bought last time). As you see, the “sell” strategy is more strict compared to the “buy” strategy. However, some investors may not like to sell at all and may just use the buy-and-hold approach. Some others may like to sell a partial quantity if a position has become overweight in the portfolio and thus may like to reduce the exposure.

Example:

Stock: PG

Volatility: Low

Target allocation: 250-300 shares (only sell when 300 or more shares or the invested sum has exceeded a certain threshold, excluding the reinvested dividends)

Sell-high-factor: Combination of multiple criteria as defined above.

No of shares to sell in one lot: 50

Back-Testing (1995-2020) Results

Stock Selection:

The strategy will have no meaning if it does not show promise in the backtesting results. Even then, there are no guarantees that it will deliver similar results in the future.

For our backtesting in this article, we will select stocks that tend to do well during recessions and big corrections. We published a recent article to highlight such stocks that you can read here. This article highlighted 10 top recession-proof stocks, which were as below:

Clorox (CLX), Fastenal (FAST), Digital Realty (DLR), Walmart (WMT), Kimberly-Clark (KMB), Amgen (AMGN), NextEra Energy (NEE), Johnson & Johnson (JNJ), Verizon (VZ), and American Tower (AMT).

These stocks are selected from many sectors/industries, but at the same time, they are all solid blue-chip companies with a long history of paying dividends. Since our period of backtesting is 1995-2020, a couple of these companies did not exist in 1995 or did not pay dividends in 1995. We could eliminate such companies and replace them with some others that we think could have qualified in 1995. By no means can we remove the selection bias 100%, and there will always be some importance of how good or bad our initial selections are. But if we are able to select some winners, some mediocre performers, and a couple of losers, overall, we will still do fine.

To further remove the impact of selection bias, if any, we have included a few stocks to our list that did not perform very well either recently or in the past. Two of such stocks are Bank of America (BAC) and Altria (MO). Even though both companies have paid dividends for a long time, and one of them, MO, is actually a dividend aristocrat, so they would have otherwise satisfied our selection criteria. BAC was dragged down due to the subprime mortgage crisis to the extent that its survival was at stake. BAC’s dividend was cut from 32 cents to just 1 cent a quarter during the financial crisis. It eventually survived and recovered, but its share price still trades much below its pre-recession level even after the prolonged bull market.

The second company, Altria, is another example of poor performance from a former top performer. It has performed miserably in recent years. Besides, we have some moderate performers like Verizon (VZ) and Walmart (WMT).

Our backtesting model kept the same 15 companies for the entire period of roughly 25 years. However, in a real-life portfolio, one could add new companies from time to time and keep the portfolio well-diversified and balanced.

The final list of 15 stocks:

Back-testing: Buy Low and Sell High Strategy

For back-testing purposes, we will buy a maximum of up to 250-300 shares (only 50 shares at one time) of any single stock before initiating the “sell” strategy. If the number of shares falls below 200, generally, no sale will occur, except if the total value of the invested amount in the stock has crossed a threshold (> $25,000). The back-testing model assumes that we started investing in January of 1995 and ran the model until Sep. 04, 2020.

Rules and Assumptions:

Period of testing: January 1995 – Sep. 04, 2020

Buy rules:

  • Buy the first 50 shares of each stock on the first day of the test period (Jan. 03, 1995) or as early as possible. Please note that the number of shares is assumed to be a pre-split basis. For example, if we bought 50 shares on 01/03/1995, and then there was a 2:1 split in 1997, and again in 2004, these 50 shares would become 200 (50*2*2) shares.
  • Buy any subsequent shares when the current price is less than 90% (or 85% for higher volatility stocks) of the average price of the past year (that is 252 days).
  • Also, after the first buy, all subsequent purchases will be at least 252 trading days apart.

Sell rules:

  • Do not sell unless the total shares in a company have reached 250 or the invested-amount, excluding the reinvested dividends, has exceeded $25,000.
  • Sell if the current price is > 1.15 times of the average price of the past year (that is 252 days) and > 1.10 times the price of last (most recent) purchase and > 1.50 times the average purchase price of the stock in our portfolio.
  • Subsequent sales will be at least 252 trading days apart.

The system will run the check for buy and sell signals on a daily basis using end-of-day data.

Below are the tables of buy-sell transactions as determined by our system during the period from 01/01/1995 until 09/04/2020 for each stock in our portfolio. Prices shown are split-adjusted prices.

Note: Column “Split-Ratio” – If there were two splits of 2:1 after the purchase-date, the shares prior to two splits will be considered to have a split ratio of 4:1 (2*2:1) and so on. The total-shares shown are on pre-split basis.

(ADP)

(AMGN)

(BAC):

(CLX)

(CNI)

(FAST)

(JNJ)

(LOW)

(MCD)

(MO)

(NEE)

(PG)

(TXN)

(VZ)

(WMT)

Performance:

Below is the performance of the portfolio (with 15 securities) assuming all dividends were reinvested in the respective securities. Please note that this portfolio outperformed the S&P 500 during every time-period, but outperformance is outstanding when you compare the long-term performance (25-year period). Sure, we admit that in real life, an investor could have picked a few more losing stocks than our example portfolio, but the overall impact would not have been very significant.

Period

Buy Low, Sell High [BLSH] Model

S&P 500

Since 1995, Annualized Return (returns were calculated as investments were made)

15.57%

10.24%

YTD Return

9.85%

7.48%

10-Year Annualized Return

16.28%

14.39%

5-Year Annualized Return

15.45%

14.00%

Amounts invested over the years in the 15-stock portfolio:

We invested roughly $361,000 over the years but sold stocks worth $286,000 as well. This works out to a net investment capital of roughly $75,000 invested gradually in 15 stocks over the years. However, the first 5-8 years saw larger investments due to the fact that the strategy does not sell until a threshold is reached. The portfolio grew into a large sum of over $2.5 million over 25 years, providing a CAGR of roughly 15.5%, compared to 10.25% of S&P 500.

Here’s the portfolio, as shown in today’s prices. As shown in the table below, some stocks have given outsized returns, some mediocre, and a few have performed below expectations.

*Cost-basis = This cost basis is calculated by taking into account the actual money spent to buy the shares. This does not include reinvested dividends. It also does not subtract/add any profits/loss received by selling partial shares.

**Adjusted Cost basis = This cost basis is calculated without taking account of any re-invested dividends. In addition, any profit/loss by selling a partial lot of shares is subtracted/added from/to the cost basis.

Conclusion

This portfolio is based on a predetermined, systematic approach. The portfolio does not require the entire investment upfront; rather, it allows us to invest periodically at different times. The system is flexible, and we can decide how much we want to be invested in each stock. We can see that even if we were to select a few stocks that may not do very well along the way, the overall results would still have been outstanding.

Over a period of 25 years, we had a total of 216 transactions (142 purchases, 74 sales), on an average of fewer than ten transactions a year.

As stated earlier, the stock selection process (for backtesting purposes) cannot be 100% free from selection bias. In order to make the strategy more reliable, the first step is to pick mostly large-cap, blue-chip dividend-paying companies that are known to do well during recessionary periods. We did select a few stocks like Bank of America and Altria that have not performed well in the recent past, just to see how much of a negative impact they would have. So, in spite of some selection bias, saying that our selection was filled with top performers would be an overstatement. In fact, we have plenty of underperformers in the mix. But that does not stop the overall portfolio from providing excellent returns over the long term.

Essentially this portfolio strategy uses the concept of dollar-cost averaging (“DCA”), but instead of buying at a regular interval irrespective of the price, it only buys when the price is relatively cheap and sells when the price is relatively high. We will like to emphasize that more work and research may be needed to gain confidence in the strategy. The idea is to provide a basic framework to do further research and due diligence to formulate a coherent investment strategy.

Disclosure: I am/we are long ABT, ABBV, JNJ, PFE, NVS, NVO, UNH, CL, CLX, GIS, UL, NSRGY, PG, KHC, ADM, MO, PM, BUD, KO, PEP, D, DEA, DEO, ENB, MCD, BAC, PRU, UPS, WMT, WBA, CVS, LOW, AAPL, IBM, CSCO, MSFT, INTC, T, VZ, VOD, CVX, XOM, VLO, ABB, ITW, MMM, LMT, LYB, ARCC, AWF, CHI, DNP, EVT, FFC, GOF, HCP, HQH, HTA, IIF, JPC, JPS, JRI, KYN, MAIN, NBB, NLY, NNN, O, OHI, PCI, PDI, PFF, RFI, RNP, STAG, STK, UTF, TLT. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Additional disclosure: Disclaimer: The information presented in this article is for informational purposes only and in no way should be construed as financial advice or recommendation to buy or sell any stock. Please always do further research and do your own due diligence before making any investments. Every effort has been made to present the data/information accurately; however, the author does not claim 100% accuracy. Any stock portfolio or strategy presented here is only for demonstration purposes.


Originally published on Seeking Alpha

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