Bubbles are notoriously hard to predict and many neo-classical economists even deny their existence. There are some notable bubbles such as the Nikkei bubble in the 80s, the dotcom bubble in the late 90s, and the American real estate bubble leading to the recent Great Recession. Now the question being asked is whether Apple's spectacular rise (NASDAQ:AAPL), which began in the second quarter of 2009, was also a bubble. Can Apple's boom and bust be compared to those of Microsoft (MSFT), Cisco (CSCO), Intel (INTC) , and other tech companies during the dotcom bubble? When the general economy was just exiting the recession and experiencing sluggish growth, Apple's stock began to take off. Was this spectacular growth a bubble, the result of strong fundamentals, or a combination of both? What made Apple unique during the past decade, allowing it to defy market trends and generate so much interest?
Apple's Incredible Success
Apple began to take off after the Great Recession ended in mid-2009. Many experts attributed Apple's growth to strong fundamentals such as smart pricing and marketing, rising revenue, the promising future of new technologies such as the iPad, and rising international demand for computers and smartphones. In 2011 Apple overtook Exxon Mobile (XOM) to become the world's most valuable company in terms of market capitalization; and in 2012 it overtook Microsoft to become the most valuable company in history. At the time there were many experts who argued that Apple was still undervalued and predicted that the stock would continue to increase all the way up to a $1000 valuation. Although there were other experts who suggested that Apple was reaching its peak, these analysts were in the minority and were given little voice.
Was Apple's 21st Century Rise a Bubble?
It is hard to determine whether or not Apple's recent growth and decline was truly a bubble - "when an asset trades above its fundamental value" - as there are infinite ways to calculate the fundamental value of a company. However, both Apple bulls and bears believed that people's misinterpretations of the company's fundamental variables were artificially moving the stock. Regardless of whether Apple experienced a bubble or not, the stock movement was heavily influenced by irrational behavior.
Why Didn't More Experts Spot the Bubble?
In retrospect all bubbles seem obvious. Many have asked how esteemed Yale professor, Irving Fisher, could have believed just a week before Black Thursday (10/24/1929) that "Stock prices have reached what looks like a permanently high plateau" and how Federal Reserve Chairman, Alan Greenspan, could have asserted that a decline in US home prices "likely would not have substantial macroeconomic implications." However, as demonstrated by these experts' lack of foresight, bubbles are difficult if not impossible to predict. Perhaps with regard to Apple, the confusion stemmed from a plethora of concurrent data that suggested that Apple would both continue to increase and begin to decline. Even without conflicting data, investors are irrational and therefore one cannot predict the direction of the stock market based on fundamentals alone.
Harvard's Professor Laibson explains that bubbles can still occur when positive fundamental catalysts exist. The 1990s were ushered in on a wave of euphoria stemming from the end of the Cold War, deregulation, high productivity growth, weakened labor unions, low energy prices, the IT revolution, and low interest rates - all important stimuli for economic growth. However, sound impetuses for economic growth can often be fused with irrational euphoria and bullishness leading to bubbles. Therefore, those who trade solely based upon the fundamentals without concern for investor behavior are bound to fail, just as neoclassical economists who adhere strictly to their models without taking into account human behavior, are also likely to fail.
During the dotcom era the whole tech industry faced a bubble, but in the past five years, only Apple experienced a bubble. What differentiated Apple from the rest of its competitors? I Know First co-founder, Dr. Lipa Roitman, explains that people often invest in companies they are familiar with rather than those with the strongest financial foundations. This often leads to bubbles as those stocks become inflated with investor capital and their share prices rise to levels that exceed the stocks' fundamental values.
Apple fits this category perfectly. It has a zealously loyal user base that has been enraptured with the brand and its iconic founder, Steve Jobs, awed by the continuous introduction of novel gadgets, and convinced that a growing portion of the world would come to rely on Apple electronics. Apple's expensive premium products have become so ubiquitous in the lives of upper-middle class consumer/investors that many have been persuaded that the company will continuously innovate and seize an ever-increasing market share. Many of them ignored important variables such as the fact that Apple's projected innovation and its anticipated release of its latest iPhone and iPad models had already been factored into its stock price, that its market had already begun to saturate, and that competitors were beginning to introduce comparable products at lower prices. Furthermore, while Apple's loyal upper-middle class fan base may have money to invest, it often does not have access to the powerful computers and algorithms that Hedge Funds and Investment Banks use. These individual investors therefore, are at a disadvantage and often invest in stocks with which they are familiar rather than more conservative, more reliable alternatives.
Apple's popularity can be seen in Chart 1, which shows how potential investors were more interested in Apple's stock, based on its volume of Google searches, than those of similarly sized companies. And while there are other reasons to search "Apple" on Google, Google Trends also shows that "Apple" is more searched by Americans than comparable companies. Additionally, Apple is the most searched stock on SeekingAlpha and Forbes ranked it the world's most powerful brand. The popularity and interest in Apple can help explain what fueled the bubble.
How Did These Phenomena Lead to a Bubble?
In his Tel Aviv University lecture, Dr. Roitman explains that stock markets are erratic and alternate between positive feedback, negative feedback, and randomness. Irrational investors cause the market to fluctuate in ways that make fundamental analysis less relevant, as these investors may still continue to drive up the stock price even if a company is empirically overvalued. Therefore, even if people may have suspected an Apple bubble, it would have been difficult to predict precisely when it would burst; and only the gutsiest analysts would have dared to advise against it. Dr. Roitman explains that when investors cease to behave rationally and give way to assessing stocks through strong, unfounded biases, then chaos begins to overtake fundamental variables as the major driver of the movement in price. This phenomenon is compounded by the many people who believe they can game the system, consequently increasing the volume of trade in both the long and short directions. Because these variables are impossible for individuals to analyze, many of the financial analysts who presaged Apple's bubble, advised investors to avoid trading the stock.
Do Hedge Funds Have an Advantage When Trading Apple?
Because Apple's stock is heavily influenced by irrational investors, it has become an especially risky and volatile asset; however, many hedge funds believe that their formulas and algorithms can factor in investor behavior and have consequently elevated Apple to their most traded stock. Can Hedge Funds' computers and data crunchers really predict the trajectory of Apple better than individual investors? Well, I Know First, an Israeli financial engineering startup company, recently released its Apple stock forecast for September 21st, Apple's peak; its algorithm correctly predicted the collapse by exhibiting strong sell signals since August 24, see Chart 2. Not only had it been correct in predicting Apple's decline, but it also correctly predicted Apple's pre-crash ascent.
I Know First's algorithm ignores traditional 'fundamental' indicators, focusing instead on tracing trends in the raw historical data. The algorithm is self-learning and impartial, allowing it to be unswayed by the hysteria in the market. Chart 2 shows the actual price of Apple stock (bold) and I Know Firsts' algorithm's signals for future movements (colorful lines). When the signals lie below the line of the actual stock price, one should view that as an indication to sell Apple stock. As we can see, there were strong signals to begin selling Apple stock less than a month before the crash.
The Advantages of an Impartial Algorithm
Bubbles are difficult to predict and even harder to track because many irrational and illogical factors skew the data. Therefore, one shouldn't expect to correctly predict the stock's future through traditional data analytics and fundamental analysis alone. When an asset fails to follow the normal rules of valuation and instead appears to be influenced by emotional factors, one may attempt to read into the public psyche and try to predict its complex attitude. But that usually magnifies the irrationality of the market as it introduces more investors who are lured into the market by behavioral predictions and not fundamental analysis of efficient markets. If one wants to invest and capitalize on such confusion and turmoil, one should use an impartial algorithm that relies on the detection of historical trends in present data, and is immune to the hysterics of the economy and arbitrary conceptions of efficient markets. Even though an algorithm can't determine whether an asset is traditionally overvalued or undervalued, it can detect whether a certain asset is experiencing a trend similar to that of another asset and can forecast the current asset's trajectory by comparing it to the other asset's historical fluctuations. This impartial quality is essential, as the valuations and fundamental targets are subjective. Essentially, it is too difficult to try to predict and track bubbles and other hysteria-driven stock movements; however, if one wants to capitalize on market turmoil, an impartial algorithm is one of the most reliable ways to track the market.
Is Apple Poised to Make a Comeback: A Fundamental Perspective
In the past month Apple's stock has increased over 12% and many are wondering whether Apple's stock is going to continue to rise. Many argue that Apple is undervalued and has much more ground to make up after its tremendous crash. However, if we consider Apple's crash, not as a cyclical decrease, but rather as the puncturing of a bubble, then Apple didn't lose any fundamental value, but rather just its unreasonable premium. Now Apple is in the same boat as its competitors. It has P/E ratio of 11.73 comparable to those of its competitors: Samsung's is 7.47, HTC's is 10.02, Microsoft's is 12.20, and Dell's (DELL) is 12.86. In the past five years many believed that Apple deserved to be traded at a premium because of its ability to constantly churn out new, innovative products; however, there appears to be no blockbuster new product in the near future to warrant such a premium today. According to a simple industry wide examination it would seem that Apple is trading right where it belongs.
Is Apple Poised to Make a Comeback: An Algorithmic Perspective
I Know First's algorithm analyzes how chaos, a non-linear evolving system, accounts for much of the movement in the stock market. Though chaos is not random, it is often counterintuitive and thus often misinterpreted. Quasi-deterministic chaos is responsible for creating waves in the market that are predictable and analyzable with processes developed in complex mathematics and quantum physics. Even though the Heisenberg Uncertainty Principle states that it is impossible to record precisely both the momentum and position of an electron at the same time, the properties of an agglomeration of multiple electrons, or waves, is well understood. Similarly, it is difficult to analyze individual transactions in the stock market (quanta), but it much easier to interpret long-term trends (waves). I Know First's market prediction algorithm uses artificial intelligence, machine learning, artificial neural networks, and genetic algorithms to track waves between the recent trajectory of a specific stock and the historical movement of an aggregate of other assets; and as the algorithm is self-learning, it constantly updates itself and improves its forecasts. The algorithm predicts the direction that stocks will move as well as the magnitude that they will move in that direction. The magnitude of the movement is measured by the "signal strength" - the higher the signal, the more upward potential for the stock.
The light red shades in Chart 3 indicate that the stock is expected to decrease slightly. Because the signals' magnitudes are relatively low, the algorithm does not believe that Apple's stock will fall by much more in the near future; however, it does believe that the stock will decrease somewhat in the next three months.
There is an old joke that asserts that those who continuously prophesize are bound to be right eventually; pessimists who constantly predict recessions and bubbles may only be correct a fraction of the time, but when such events do occur these pessimists may be perceived as sages. Such naysayers, such as the Street's Scott Moritz not only predicted the iPad would be a flop, but also recommended selling Apple stock in March 2010, when the stock was below $220; though we can joke about the uselessness of analyzing the stock market with an hindsight bias, there is much merit in doing so to help us forecast the future. Chart 4 shows Apple's steady climb from late 2009 to late 2012.
In his Tel Aviv University lecture, Dr. Lipa Roitman explains that there are two general feedback modes: positive and negative. In a positive feedback mode a rise in price attracts more buyers, in a negative feedback a rise in price attracts more sellers. During Apple's climb there was a basic positive trend (a non-zero slope), that is a positive feedback, interspersed with periods of negative feedback (zero slopes). Dr. Roitman emphasizes that stocks are hardest to predict during an extended period of negative trends, as this tends to be when the stock changes its steady long-term positive trend.
Chart 5 displays Apple stock's performance in the past year. After its precipitous decline, it seems to have plateaued for an extended period of time. Similarly, after the Dotcom Bubble, Cisco's stock plateaued with a prolonged negative feedback trend for a few years (Chart 6). Though there were some slight movements in Cisco's stock it never increased considerably nor even came close to reaching its pre-bubble highs.
(Click to enlarge)
This should be an indicator that Apple may vary slightly, but is not likely to move drastically for time to come. In conclusion, I advise avoiding trading Apple stock for now. Its post-bubble behavior suggests that there is little upside for the stock and its current prolonged negative feedback warns that the trajectory of Apple stock in the near future will be less predictable.
Business relationship disclosure: I Know First Research is the analytic branch of I Know First, a financial startup company that specializes in quantitatively predicting the stock market. This article was written by Ethan Fried (Harvard College '16) one of our interns. We did not receive compensation for this article (other than from Seeking Alpha), and we have no business relationship with any company whose stock is mentioned in this article.
Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. 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.
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