by Stephen Malinak.
From tulip mania in the Netherlands in the 1630s to the Internet bubble of the 1990s, people have wondered what causes prices of collectibles, investments, real estate, stocks, bonds, currencies, commodities and other assets to go up and down in such unpredictable and chaotic ways.
There is no definitive answer to that question, but academics, investors, speculators, customers and our own research team have quite a few theories. Below I’ve created a fairly simple diagram to summarize various theories and worldviews encountered in 20 years of studying financial markets and from conversations with over 700 professional investment management and trading customers in the past 10 years.
Figure 1. A Map of Market Participants and Worldviews That Influence Market Action/Stock Prices
Source: Fundamental Security Analysis (“Bottom-Up”)
Fundamental Security Analysis is a “bottom-up” approach, so I have it at the bottom of the chart. Market participants in this group typically think of themselves as investors and like to look at fundamental data, such as company earnings and dividend payments. This is the Warren Buffett view of the world, wherein stocks have an intrinsic value that can be calculated and serves as a firm foundation for prices. Chartered Financial Analysts (CFAs) spend a great deal of time looking at earnings, cash flows and other fundamentals through this lens. Fundamental quants have historically focused on this area with traditional quant models, but are starting to branch out.
Valuation theory developed on the heels of the Great Depression and was popularized by Benjamin Graham back in the 1930s. Investors most closely associated with value call themselves contrarians because they buy when most people are selling and sell when most people are buying. Long-term investors typically focus on valuation and quality factors such as earnings yield and return on assets.
To avoid “value traps” that just keep going down in price, investors will frequently turn to momentum type signals and/or price chart patterns for entry and exit signals. One simple signal is price momentum — it’s a good time to buy when the price starts going up. Analyst revisions are perhaps an underappreciated fundamental signal, as analysts raising their estimates increase both perceived value and positive momentum and provide an excellent timing signal for entering and exiting long-term positions based on valuation and quality.
Another perspective is the top-down global macro approach, favored by George Soros and his Quantum Fund cofounder (and frequent Reuters Insider guest) Jim Rogers. These market participants (and commentators) often call themselves economists or strategists or global macro funds. The theory is that if you get the macro view right, everything else will eventually fall in line, and exact timing of stock purchases matters less. “All boats rise with the tide.” The challenge here is twofold, both forecasting the macro environment and relating the various macro indicators to their impact on tradable instruments.
Long cycles of under- and over-valuation of industries, countries and markets play out much like business cycles and economic expansion cycles. The macro approach is a big picture version of value and/or momentum investing. The best time to buy is when a country has been severely beaten down and is starting to turn around; the best time to sell is at the top of a massive bubble. Jim Rogers gives a ﬁrsthand view of this approach in his novels describing his travels around the world to investigate macro conditions in person and directly from the black markets that represent capitalism in its most raw form.
If the macro or fundamentals aren’t driving a stock’s price, then what is? Large amounts of money moving around create both short-term disruptions and speculative bubbles. Speculators, chartists and trend followers track money ﬂows causing signiﬁcant price movements, as do many Commodity Trading Advisors (CTAs) and Chartered Market Technicians (CMTs). Speculative gurus like to compare markets to waves, and recommend visiting the beach to understand how market activity works.
“Reading the tape” is an example of this approach, explained vividly in Reminiscences of a Stock Operator from the 1930s. Certain skilled people have an ability to read which way the herd is stampeding and when it is changing direction by looking at patterns in trade ﬂow. Bubbles have developed and popped repeatedly over the centuries once large crowds get in on the game, as explained in Extraordinary Popular Delusions and the Madness of Crowds.
Looking at the action of select groups of participants can lead to additional insight. Many people talk about “following the smart money.” Our research team has built three varieties of “smart money” models. The ﬁrst looks at the buying and selling patterns of company insiders, such as ofﬁcers and directors. The second looks at the major bets of professional investors such as hedge funds who short stocks, measuring their aggregate activity as the level of “short interest.” The third examines the holdings and recent purchases of major funds and ﬁgures out what factors they are using to screen and buy stocks at any given point in time. Fund ﬂows provide yet another level of insights.
Our team’s research has shown that much of what has been called “abnormal returns” can be traced back to a wide variety of disruptive events that have been captured to various degrees in separate databases. People who favor these strategies often view themselves as event-driven traders or engaging in an arbitrage strategy such as merger arbitrage or dividend arbitrage. Their positions are not long-term views; rather, they are focused around events with discrete and typically short-term horizons.
For example, the biggest downside risk for an equity is going to zero, also known as bankruptcy. We’ve built four world-class default prediction models that have proven to be additive to classic valuation approaches. Some of the biggest moves to the upside result from sudden deal announcements that can cause a stock to pop 30% literally overnight.
Classic event-driven strategies such as trading around earnings surprises and arbitraging dividend changes fit in here. New data sets like environmental, social, and governance provide an opportunity to identify new kinds of events that drive abnormal returns. Supply chain is a major initiative for many firms looking to understand the downstream impacts of disruptions to supply.
Finally, there are the statistical aspects to trading, including crises that change all correlations to 1 for a brief period. Statistical correlation analysis works well enough under normal conditions, and scenario analysis focuses on what can happen in extreme crisis situations. Statistical Arbitrage or “stat arb” funds seek to make money here from semi-stable correlations. Strategies such as minimum volatility or “min vol” also work at the portfolio level rather than focusing on individual securities.
Long Term Capital Management profited strongly from statistical modeling for awhile, until they got taken out by one of Nassim Taleb’s “black swans” when Russia defaulted in 1998. The 2008 global financial crisis disrupted many people’s trading strategies, including those that were still profitable as investors were forced to pull their money out to cover losses elsewhere.
These sudden large money outflows actually reversed expected correlations, leading to further losses and further outflows and eventually the bankruptcy of several major financial institutions.
So what can we learn by examining this wide variety of market participants and theories about what drives stock prices? There are many answers — each explains a part of the grander truth and each works from time to time. The general public is also most likely to hear about any of these theories right after they have been on a hot run of performance, and crucially, right before they hit a drawdown and result in major losses. Looking at the bigger picture suggests incorporating a range of diverse points of view, relying on multiple strategies and being as prepared as possible for the next “black swan” that will differ from all previous ones in some crucial way.
While presenting his Efﬁcient Market Hypothesis back in 1952, Harry Markowitz explained, “Diversiﬁcation is the only free lunch on Wall Street.” We’ve found that this applies not only at the level of portfolios but also strategies and worldviews. Some of the most successful hedge funds are those that incorporate the broadest possible range of diversiﬁed strategies.
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