Who Wants to Lose a Million?
Technical analysis focuses on "timing the market" to help avoid loss.
New types of mutual funds can affect how technical analysis is used in the stock market.
No one invests in the stock market with the goal of losing money. Despite the best of intentions, however, it has been known to happen. Consequently, there have been innumerable attempts to discover a magic formula that will allow the investor to successfully “buy low and sell high.” While that formula has proved elusive, many people continue to seek it. In general, the approaches taken can be divided between fundamental analysis and technical analysis.
Fundamental analysis considers the earnings potential of the company and estimates the direction of the macro-economic environment over some period of time. As such, it is based on “hard” financial and economic data. Fundamental analysts do not try to time the market in terms of short-term swings. If the long-term trend is up, the investor is willing to experience some short-term “paper losses” in the portfolio in the belief that as long as the fundamental situation holds, stock prices will increase. When fundamental factors change, then it may be time to sell, or even sell short.
Fundamental analysis has been well accepted in the investment community because the U.S. economy has continued to grow over the long-term, and many of those who have invested on the basis of fundamentals have done well. Most of us would not mind having the success rate of Warren Buffet for example.
Market Volatility: Can Anyone Make Money?
When the market is volatile, however, many people get very nervous about a buy-and-hold approach. In the past 24 months, for example, the market has endured large swings in most of the popular indexes as well as in many individual stocks. Most people would agree that these dramatic swings were directly related to uncertainty about interest rates and monetary policy, and the unknown future financial environment that higher rates can create.
Yet, while the general market, as measured by the Standard and Poors 500 Index, was essentially flat during the first three quarters of 2000, there was substantial industry rotation as investors reacted to the potential impact of changing interest rates on industries they deemed vulnerable. Prices of many individual stocks seemed to rise and fall almost randomly. Traditional fundamental analysis often did not seem to help. This was, incidentally, also the case in 1994, the last period in which interest rates were increased.
The casual observer may conclude, therefore, that it is nearly impossible to make money in periods of restrictive monetary policy such as 1994 or 2000. However, there is an alternative strategy that is often utilized during volatile times as well as stable ones — technical analysis.
Technical analysis is a strategy often used for short-term trading. It is directed almost exclusively toward the observation and interpretation of price movement and can be applied to indexes, individual stocks, options, or commodities. Technical analysis attempts to discount the fundamental and macro-economic variables discussed earlier by assuming that most factors that can influence the stock market are ultimately reflected (or discounted) in the closing prices at the end of the day. Most technical analyses are based on some mathematical model of price movement that includes assumptions about human behavior and decision-making. The key is to discern the pattern in the behavior of the stock or index and be able to “time the market” — to be able to predict the movement well enough to get out of the market before suffering losses, and, of course, to get back in at a price lower than where the stock or index fund was sold. Thus followers of these strategies might argue that the careful daily interpretation of price behavior of, say, the S&P 500 Index could provide a potential defense against major portfolio losses for those invested in index funds.
Why Losses Are Bad:
Losses can be more damaging to one’s investment goals than is commonly understood. To dramatize this point, assume that a hypothetical investor begins with $1,000 and is able by careful investing to achieve a consistent 17% annual return over a ten-year period. (For purposes of the illustration, we will ignore transaction costs and tax consequences, although in real life they would have a significant impact.) At the end of the tenth year, the value of the portfolio would be $4,807.
Now, assume that the same investor lost 10% of the value of the portfolio every other year but was able to earn 27% in the alternate years. Intuitively it might seem that the end result would be similar, but it is not. At the end of the tenth year under this scenario, the value of the portfolio would be $1,950 — less than half the value of the consistent no-loss strategy. In fact, to achieve approximately the same value as afforded by the consistent 17% annual return, the investor who lost 10% on alternate years would need to earn 52% during the positive years! The three scenarios are contrasted in Table 1.
Table 1: Contrasting Scenarios
|End of Year||Consistent 17% Gain Scenario||27% Gain/10% Loss Scenario||52% Gain/10% Loss Scenario|
This mathematical example illustrates how periodic losses to one’s portfolio require gains that are much larger than the losses themselves in order to offset them. The sooner losses are cut, the easier it is to recoup. This is the philosophy that underlies the short-term trading strategy. It is an approach to both enhancing returns and reducing risk.
A Strategy for Limiting Losses:
While there hasn’t been a single strategy discovered that can consistently eliminate losses, this has not stopped investors from trying to figure one out. Intrigued by the challenge, this author experimented with various forms of technical analysis in an effort to develop a methodology that had the potential to minimize losses over the long term while utilizing an index fund as an investment vehicle. After extensive experimentation, the technique decided upon involved the New York Stock Exchange Advance/Decline Line and the S&P 500 Index.
The NYSE Advance/Decline Line is determined by subtracting the total number of NYSE stocks that have declined that day from the total number that have had a price increase. (If there are more declines than advances, the figure is negative.) This final net figure is added to the previous day’s figure and the results are plotted daily to create the A/D Line. The A/D Line is a measure of how investors feel about the market over time. It is assumed that when the line is advancing, investors are optimistic about the broad market. Therefore the risk of remaining in the market is reduced. If the line is declining, it is assumed to be a signal that investors are skeptical or pessimistic, and this could mean one should get out of the market. The final formula can be stated as follows:
- A = Number of Stocks on the NYSE that have advanced
- D = Number of Stocks on the NYSE that have declined
- ADL = Advance/Decline Line
- ADL = ADL (last) + (A – D)
- Buy: ADL > ADL yesterday
- Sell: ADL < ADL yesterday
- Hold: ADL = ADL yesterday
In the technique developed for this exercise, the investor purchases and holds a position in an S&P 500 index fund as long as the current day’s ADL is equal to, or greater than, the previous day’s ADL. When the ADL is negative, the investor would sell his or her entire position and place the proceeds into an interest-bearing money market fund and wait for the next buy signal to repurchase the index fund.
In an effort to test the validity of this approach, the hypothetical return using this formula was calculated for the period of January 2, 1950, through August 8, 2000, using an assumed S&P 500 Index Fund as the portfolio. The S&P 500 Index was 16.66 on January 2, 1950, and 1,491.72 on August 8, 2000, for a total return (passive buy-and-hold strategy including dividends) of 8,853.9%, with an “Ulcer Index” of 11.26%. (The Ulcer Index measures the draw-downs or price declines from peaks to troughs during the entire test period.)
By contrast, back testing the ADL formula over the same time frame revealed a very different picture. This technique would have required an actively involved investor completing a total of 2,498 round-trip trades (buys and sells), or an average of 49.35 round-trip trades per year, during the test period. Results differ dramatically depending on whether the trade was calculated using the closing figures for the day the signal was given or the next day’s close.
If a trader had utilized the ADL formula but could not execute the trade until the day after it gave a signal, 46.88% winning trades resulted based on the value of the fund at the end of that day. The largest gain would have been 13.04%, the largest loss -7.45%, and the average gain 0.9%. The total gain would have been 1,618.15%, with an ulcer index of 9.97%. Although the Ulcer Index is lower than under the buy-and-hold strategy, the returns are lower.
However, if one had been able to execute a trade the same day of a signal with that day’s closing price, the results would have been different from either of the above outcomes. Same-day trading resulted in 52% winning trades, with the largest single trade gaining 14.6%, and the largest loss equal to -6.12%. The total return was 1,156,995.12%, including interest earned at the going T-bill rate while money was held in a hypothetical money market account during sell periods. Dividends were not included when the signal was in a buy mode however. The Ulcer Index dropped to 2.3%, suggesting a much lower downside risk as well. What a difference a day makes!
Interestingly, recent years that were associated with an economic recession or restrictive monetary policy fared well under this formula as well. For example, during the infamous crash year of 1987, a buy-and-hold approach (for an index fund) would have returned 0.26% for the year, while use of the ADL Same-Day Indicator produced a hypothetical 23.96% return for the year. During 1990, the last recorded U.S. recession, the buy-and-hold strategy yielded -8.19%, while the timing model produced a hypothetical gain of 1.98%. Finally, 1994 was a restrictive monetary policy period. The buy-and-hold strategy that year would have yielded a -1.33% return, while the ADL approach would have produced a 6.40% gain.
|Ulcer Index||Return*||Ulcer Index||Return*||Ulcer Index||Return*|
|Buy & Hold||13.14%||.26%||9.78%||-8.19%||4.86%||-1.33%|
|Same Day Trade||2.66%||23.96%||5.04%||1.98%||1.19%||6.40%|
|Next Day Trade||4.16%||22.09%||6.72%||-1.77%||4.90%||-2.01%|
While this exercise demonstrates the concept of technical analysis and shows that it could help avoid loss, it must be noted that the real life consequences would not have been nearly as positive as the foregoing paragraphs suggest. For one thing, in real life there would have been transaction costs and tax consequences that would have diminished the returns significantly. The impact would have been cumulative, much as loss has a cumulative effect. During much of the time under analysis capital tax rates were higher than they are now. (For additional discussion of the tax consequences of differing strategies for building wealth, see “Building Up Wealth: Capitalizing on Tax Planning Opportunities” in the Fall 2000 issue of GBR.)
In addition, trading as frequently as required by this technique simply would not have been allowed by mutual funds during the period covered, and still would not be permitted by most mutual fund families. For the above approach to work, the investor would need a family of funds that would allow him or her to move from one fund to another within the family of funds as often as desired without cost or penalty, including intra-day trading. Until very recently these did not exist. However, in mid-2000, a newly-created index fund family was offered to the public that does allow frequent intra-day or same-day trades without commission charges. These mutual funds also are leveraged by 200%, which dramatically adds to volatility. (It should be noted that the above results were calculated without leverage.) The traditional annual administration fee for these funds does apply, as is the case for all open-ended mutual funds. This would lower the returns.
Even with intra-day trading, there are some practical issues that would prevent replicating this technique exactly. Waiting until the end of the trading day to calculate the ADL means that one could not actually buy or sell the index fund until the next morning, and the price would be different by the time one could make that trade. Alternatively, one might track the ADL line in the last couple of hours of the day and make a decision an hour or so before the close as to whether there is a buy-or-sell signal and execute the trade. However, in recent years the last hour of trading has often proved very volatile, so there is not guarantee that the direction would be the same. The author has not tested the consequences of decision-making prior to the end of the day. Other practical considerations that must be observed include the actual number of trades required, and the time involved. These may be excessive for most investors.
Summary and Conclusions:
A traditional buy-and-hold strategy has made sense for decades and has been a profitable approach for investing, but it is not without risks. Although very short-term timing of stock market cycles may reduce the potential for large losses, it, too, has risks. However, the above findings illustrate that if losses can be held to a minimum, there is a greater potential for achieving profits over the long term. If one assumes that the closing market prices discount most of the external factors that influence them, the need to be continuously concerned with economic events may also be reduced, especially if a very short -time strategy is assumed.
The results discussed in this article are for academic interest and demonstration only. They are not a recommendation by either the author or the Graziadio Business Review. The model assumes an investor who would be actively involved in the market on a daily basis and would, in fact, act on each and every signal. Human emotions often preclude the latter. And, as noted above, there are pragmatic reasons why it could not be executed exactly according to the technique — and those differences could significantly affect the results of the strategy. Additionally, the period covered by the research included a time when the NASDAQ was not a major factor, as it is today. This could affect the correlation between the NYSE and the S&P measures.
Nevertheless, the point is valid that there are several ways to approach investing, some of which can be effective even in volatile times. These can include technical analyses of various sorts, particularly when they help you avoid losses.
About the Author(s)
Marshall Nickles, EdD, has been instrumental in the development of Pepperdine's School of Business and Management. He has also been a consultant to several corporations such as Volkswagen of North America, 3M Corporation and Loctite Corporation. In addition, he has served as a board member to The China Economy Consultancy Co. in the People's Republic of China, The China American Technology Investment Group, vice president and board member of The American-China Association for Science and Technology Exchange, and advisory board member for Irwin Duskin Press. Dr. Nickles has also been a frequent presenter and discussant of professional papers at national and international academic associations. He has been a former financial columnist for The Orange County Business Journal and Business to Business Magazine. Prof. Nickles is the author of an economics text and more than 45 articles. Dr. Nickles has been quoted on television, and in several newspapers and magazines, such as The Wall Street Journal, USA Today, the New York Times, the Orange County Register, Barron’s Weekly, Stocks & Commodities Magazine, and the Los Angeles Times . He has been an invited guest on KNX 1070 radio, KTLA Channel 5, Fox Television, CNBC, and as the principal speaker at the national conference of the State Bureau of Statistics in Beijing, China. Prof. Nickles was the recipient of the Howard A. White distinguished teaching award at Pepperdine’s Graziadio School of Business and Management.