How to find the Right Price of any Stock – Value Investing Unleashed – Part II
BEHAVIORAL SCIENCE Trading
Here’s a simple question: How good a driver are you? Think of the other drivers you encounter on the road and estimate your driving ability on a scale of 1 to 10, with 10 being the best. Feel free to use any reasonable set of criteria to evaluate yourself: reaction time, years of experience, driving record, adherence to traffic rules, courtesy, maneuvering skills, and so on. After weighing these factors, what number did you assign yourself?
If you rated yourself a 7 or better, you are a typical respondent. If you ranked your driving skill as greater than 5, you are in the overwhelming majority. Regardless of your actual driving ability, it is highly unlikely that your self-appraisal was 4 or less. When researchers pose this question to virtually any group, the average answer is generally around 8 or 9. Think about that for a moment: On a scale of 1 to 10, the average answer is 8 or 9. In other words, a majority of participants all believe they are substantially above average—which, of course, is statistically impossible.
This example illustrates one of many systematic errors of judgment that impede our daily decision making. Psychologists have studied these biases for decades to better understand human behavior.
So what does this have to do with value investing?
Despite theories that the markets are efficient I believe that most people make investment decisions that include these psychological biases, generally without realizing they’re doing so. Often, these biases influence a substantial proportion of market participants in the same direction, contributing to the short-term irrationality of stock prices that value investors see as an opportunity. But (and this is a key point), value investors can only profit from this if they are able to resist the same biases that are influencing everyone else. That means they must be aware of these influences, and they must set up their own investment disciplines to make sure they don’t fall victim to them.
Let’s take a look at what these behavioral biases actually are. The studies of investor psychology have led to the development of what is known as behavioral finance. The results of numerous studies reveal that a variety of biases, including flaws such as optimism, hindsight, extrapolation, anchoring, and faulty intuition, cause investors to become susceptible to surprise or disappointment. And when surprise or disappointment occurs, investors tend to overreact, resulting in poor decisions. As I’ve said, to counter such biases, investors must follow a disciplined approach that stresses a pre established rational process rather than personal preference or out-of context judgments.
Human nature is far more predictable over time than the day-today swings of the stock market.
By understanding and applying the lessons of behavioral finance, investors can apply a rational approach in a market crowded with irrational participants, and expect much improved results.
Remember that value investing—essentially, buying and holding inexpensive, out-of-favor common stocks—seeks to combine company specific fundamental research and an objective, unbiased approach that exploits innate human shortcomings. This approach has proved its merit for decades, long before behavioral finance became a topic of study. As you read on, you’ll see that many aspects of this field of investor psychology always have been part of the value investor’s discipline. All that’s new is that now we’re able to understand in more detail why these disciplines work. In my opinion, you’re always better off understanding why something works, rather than just applying the process blindly. It improves both your confidence and your judgment within the framework of the discipline.
THE DANGERS OF FAULTY INTUITION, EXTRAPOLATION, AND OPTIMISM
Why value investing has delivered such solid results by briefly examining faulty intuition, extrapolation, and optimism. For all three, I’ll share real-world examples and market-related applications. Hopefully, by better understanding these tendencies, you can guard yourself against their potentially adverse influences.
Suppose we conducted two experiments. In the first, we flipped a coin nine times and recorded the outcomes of each flip. The results — heads (H) or tails (T)—were as follows:
In the second experiment, we took the same coin and flipped it again. This time, the results were as follows:
Which do you believe is a more probable outcome? If we do this experiment another 1000 times, which pattern would repeat itself more frequently — the first result or the second?
When most people see these two results, they believe the first pattern is more likely to occur. Is that the one you picked? To many, the first result seems more likely, even though they may have no definitive evidence to support their belief. It just feels right. The second pattern seems too contrived to recur with any frequency.
Well, actually, both outcomes are equally probable. The results in the first experiment are no more likely to occur than the results in the second experiment.
Now, if we extended the first experiment and said we were going to flip the coin a tenth time, most people would say it’s virtually impossible to predict the result of the next flip. Yet, in the second experiment, many people would make a prediction. They might predict heads as a continuation of the trend or tails for a trend reversal. Either way, they believe they can see a pattern in these random outcomes and make an accurate prediction of the future. This misperception is the essence of faulty intuition.
This cognitive error—seeing a pattern or predictability in random, short-term events—is so common and so imbedded in stock market analysis that we practically take it for granted. In fact, there’s an entire school of investment thought devoted to finding patterns in the short-term movement of stock prices. It’s called technical analysis. Market participants (I refrain from calling them investors) who use this approach study patterns and trends in past stock prices in order to predict future price movements. They may look for patterns such as “head and shoulders” or “ascending triangles” or spend time on trend analysis. I don’t recognize this as investing. To me, it is purely speculation and has about as much chance at long-term success as consistently predicting the results of coin flips.
Attempting to establish patterns to explain random events with the hope of predicting the future can lead to yet another important behavioral bias—extrapolation.
For example, while sitting in a traffic jam, maybe you’ve thought, “It took me 30 minutes to go 2 Km. At this pace, I’ll get home tomorrow afternoon.” Or perhaps, while playing golf, you made a birdie putt on the thirteenth hole and thought, “If I keep that up, I’ll shoot a 33 on the back nine!”
These are examples of extrapolation—basing a longer-term forecast on an emotional reaction to short-term developments. Over the years at my firm, my colleagues and I repeatedly have seen the dangerous effects of extrapolation.
Market participants often look at negative short-term performance and think, “If this continues, I’ll lose all my money in 3 weeks.” Or if performance is good, they may say, “At this rate, I’ll quadruple my money in 6 months!”
Much like the example of being stuck in traffic or playing golf, the results are rarely as good, or as bad, as we envision. We often set ourselves up for disappointment or surprises when reality differs from our expectations.
It’s a quirk of human nature—and one that consistently has surfaced in the investment industry.
For example, market analysts often project historical trends too far into the future. They project sales, earnings, stock prices, and many other statistics for years or decades despite evidence that these quantities are inherently difficult to predict. In forecasting the future growth of rapidly expanding companies, their expectations are often tied to the recent past even though growth rates usually revert toward an average. Remember two things about market analysts’ predictions. First, they are rewarded for doing a “thorough job,” and extending a growth rate projection for a few more years in today’s world of computerized spreadsheets is a very easy way of looking impressively thorough.
Second, and even more important, be especially wary of any projection that extends beyond the time that the analyst expects to be in that job!
Example from NASDAQ US : Near the peak of the technology stock boom in early 2000, an analyst at a major Wall Street firm predicted the price for shares of QUALCOMM, a telecommunications company based in the same city as my firm, would climb to $250 from its then-current price of around $125. (Both prices have been adjusted for a subsequent stock split.) The analyst based his prediction on the extrapolation of cell phone sales over 20 years. He failed to consider the possibility that the firm’s technology would be replaced, or that cell phone usage might level off, or that other competitors would chip away at QUALCOMM’s customers, or that the cost of cell phones would decline.
Basing a long-term forecast of the company’s prospects by extending what it’s done in the recent past is dangerous, as evidenced by what happened to QUALCOMM’s stock price. After climbing to $150 per share in early 2000, it fell below $30 in 2002.
The QUALCOMM example also helps illustrate the dangers of optimism.
We tend to think of optimism as a desirable trait and, in most cases, it can be. However, when investing, dispassionate analysis often proves more profitable. Decisions should be based on the relationship between business value and stock price. Period. All investors should be wary of becoming too optimistic as the desire to win on Wall Street / Dalal Street may have quite the opposite effect. In addition to guarding against personal optimism, be wary of adopting others’ optimistic views on particular companies even if those others are professional analysts.
Exhibit 1-1 illustrates the perennial over optimism of Wall Street analysts and economists.
Based on one research, analysts have, on average, predicted an earnings growth rate roughly four times that of the average rate observed. Economists, far from being the pessimistic “dismal scientists” we might have expected, have predicted a growth rate nearly three times the actual rate.
A striking characteristic of this optimistic pattern is its persistence, even when the forecasters may have seen that their predictions were overshooting the mark year after year. Observing that their predictions bore little resemblance to reality, they might have reassessed the inherent predictability of earnings and adjusted their predictions downward, closer to the long-term historical average. Truly rational forecasters might have adopted a more regressive approach: the lower the inherent predictability, the closer the prediction should be to the long-term average. But there does not seem to be any evidence that the forecasters are recalibrating their estimates.
Why should analysts be systematically overly optimistic?
A 2002 study shows Wall Street analysts get paid more if they are. Research by Harrison Hong, an associate professor at Stanford Business School, and Jeffrey
Kubik of Syracuse University found that analysts who deliver optimistic earnings forecasts (not necessarily accurate forecasts) are more likely to be promoted. This is yet another reason to be cautious when analyzing businesses and acting on information provided by “experts.”
Faulty intuition, extrapolation, and optimism can set the stage for overconfidence and subsequent overreaction. While overconfidence in intuitive models can lead to losses, it also may cause investors to miss opportunities for gains. For example, an incorrect model might lead to the belief that a poorly performing business will never recover. In the late 1970s and early 1980s, expectations of continued “stagflation” led to a general negative overreaction by investors. The resulting low stock prices prompted BusinessWeek magazine to proclaim the “Death of Equities” in a cover story published on August 13, 1979. As it turned out, within a few years, stocks
began what would become the greatest bull market in U.S. history.
( Source Google)
EXHIBIT 1-1 Congenital Optimism: Earnings Growth for the S&P 500
Year Analysts’ Estimate Economists’ Estimate Actual Growth
1982 26.2% 5.3% –17.8%
1983 32.2% 24.7% 11.4%
1984 34.2% 27.7% 18.4%
1985 10.8% 12.9% –12.2%
1986 22.8% 22.9% –0.9%
1987 32.6% 18.8% 20.9%
1988 29.8% 14.5% 35.8%
1989 10.5% 4.4% –3.7%
1990 13.8% 12.0% –6.7%
1991 1.9% 6.7% –25.2%
1992 38.0% 48.7% 19.5%
1993 22.8% 36.4% 14.7%
1994 38.9% 28.6% 39.8%
1995 10.9% 4.8% 11.0%
1996 18.2% 11.7% 14.1%
1997 13.7% 5.8% 2.6%
1998 13.6% 6.7% –5.1%
1999 14.6% 4.5% 27.7%
2000 16.0% 0.0% 3.8%
2001 16.0% 7.7% –50.6%
2002 17.0% 10.1% 13.4%
Average 20.7% 15.0% 5.3%
Value investors recognize tendencies such as faulty intuition, extrapolation, and optimism and establish predetermined processes based on objective analysis rather than personal preference or out-of-context judgments to guide their investment decisions.
VALUE INVESTING: EXPLOITING MARKET BEHAVIOR
Investors who strictly adhere to value disciplines have earned favorable performance results with limited risk over the long term because they seize opportunities created by flaws that are inherent in human nature. These emotional biases often cause stock prices to fluctuate in the short term much more than the intrinsic value of businesses. It is precisely these exaggerated price movements that create opportunities for astute investors. Virtually by definition, value investors take a course of action that runs counter to popular trends. When many market participants are selling, value investors often are buying, and vice versa. Value investors realize that achieving better-than-average returns depends upon thinking and acting differently than the average investor.
Value investment strategies tend to work because the majority of investors remain captive to judgmental errors or emotional biases that adversely influence their decisions.
Even when objective facts contradict their biased views, investors often continue to overreact, sending market prices to extreme highs or lows. As illustrated, human behavior is not always dictated by rational thought. It is, however, often predictable. Remember the simple question that opened this article: How good a driver are you? Ask members of your family, friends, or coworkers this question and note their responses. With the knowledge you have already acquired about human behavior, you will probably not be surprised by their answers.
The same principles, applied to investing in the stock market, can limit your vulnerability to overreact to short-term developments. The key is to adhere to investment policies and procedures that circumvent bias and reflect sustained objectivity. As a value investor, you don’t want to fall victim to the very behaviors you seek to exploit.
I hope I haven’t made this sound too easy, because it isn’t. As Ben Graham wrote, “To achieve satisfactory investment results is easier than most people realize; to achieve superior results is harder than it looks.”
Merely accepting that these ideas make sense doesn’t mean they are simple to apply in today’s challenging financial markets. If you’ve ever been on a diet, you know how easy it is to decide that tomorrow you’ll eat less. (It’s usually easiest to decide that right after dinner today!) But the next time you’re offered a piece of chocolate cake, there’s usually some excuse to deviate from your dieting plans: You don’t want to offend your host, or it’s just so tempting. The temptations of human behavior are well ingrained in all of us. They are difficult to keep in check. In upcoming Article on this subject I am going to Put simply, the reason a value approach works is not because investors benefit from predicting fluctuations in interest rates or economic output.
Success for value investing isn’t predicated upon the strength of corporate earnings or which political party holds the upper hand in Indian Govt.. Value investors first, last, and always, think of buying the business, not the stock. Value investing works for two reasons: It reflects a consistent focus on the relationship between value and price, and it takes advantage of innate human foibles.
EFFICIENT MARKET THEORY: DEBUNKING THE MYTH
Many academics, observers, and Gurus argue that the stock market acts efficiently. That’s portfolio-speak for the theory that stock prices always accurately reflect everything known about a company’s prospects. According to this view, studying fundamentals such as earnings and book values is as useless and unreliable as reading tarot cards or tea leaves. The reason?
Undervalued stocks—or so it is claimed—don’t actually exist, because security analysts and other market participants already have harvested all available information and thereby ensured unfailingly appropriate prices.
Proponents of this notion have embellished their belief with jazzy computer printouts and a three-letter acronym, EMT (efficient market theory, or EMH, efficient market hypothesis). EMT is divided into three parts:
weak, semi-strong, and strong.
The weak version of the efficient market theory holds that past prices have no bearing on future prices. In other words, what investors will pay to own shares of a company in the future is essentially independent of their past actions; price patterns over the long haul are completely random.
Generally, value investors have no quarrel with this weak form of the theory. Technical analysis of price behavior, the approach to forecasting future returns based on the study of past price movements, has not served adequately as a substitute for fundamental company-specific analysis, in my view. Studies have revealed that a weak link between past and future prices may exist, although certainly not enough of a link to generate trading profits after transaction costs.
The semi-strong form states that markets are efficient because of the rapid way that knowledge is dispersed in the Information Age. There is no denying that as information about companies, industries, and the economy arrives at the marketplace, prices reflect the quick assimilation of this new data.
Transmitting information quickly, however, doesn’t guarantee that the conclusions drawn are accurate. Rapidly transmitted information may suggest one picture, but a significantly different picture may emerge as the ideas are interpreted over time.
This version of the efficient market theory holds that, at any given moment, security prices already accurately reflect all knowable public and private information. In other words, there can never be a difference between underlying business value and stock price. The margin of safety addressed in Part I, or the gap between a company’s intrinsic value and its share price that creates a bargain-priced stock, is an illusion. No amount of skilled interpretation of available public data would enable any investor to profit from discrepancies between business value and stock price. In this view, the efforts of security analysts to identify mis pricings are entirely successful in creating market efficiency.
However, the theory is predicated on a world where every investor has all available knowledge, understands it, and is able to act logically on it.And as I have already reviewed, markets aren’t orderly or logical. Regarding the flaws associated with EMT, Clifford F. Pratten of the University of Cambridge writes, “Irrational influences, hope, fear, and so on, do play a part: the oft-quoted statement that the market is driven by altering bouts of greed and fear sums up the position.”
The Internet stock bubble of the late 1990s provides ample examples of real-world opportunities created by market illogic. Excessive optimism and greed pushed prices for dot-com companies well beyond their underlying values. Many investors assumed the Internet would have a major impact on every business, and dot-com companies appeared to be best positioned to benefit. Accordingly, these investors clamored for Internet-related stocks and shunned much of the rest of the market.
Experts found that emotions play an important role in stock prices. “Overwhelming evidence is piling up that investors overreact to the past performance of stocks, pricing growth stocks—stocks which are expected to grow faster than average—too high and value stocks—stocks which are expected to grow slower than average—too low.
Subsequent to these overreactions, growth stocks produce low returns for the investors who buy them at high prices, and similarly, value stocks produce high returns for their investors.”
In India you can see Correction without any reason i.e In Dec 2014 Correction without any reason … Indian market is more about FII investments.. & according to Few experts they tell us No banks Or DII & FII never loss money…
Losers are always Investors!
Best of Luck & safe Trading