Why has market sentiment become the "invisible hand"?

Under the dominance of rational expectations and the efficient market hypothesis, early finance rarely focused on sentiment as a non-quantifiable variable. But reality often contradicts this: technology bubbles, subprime crises, emerging market panics... each significant fluctuation cannot be explained solely by changes in economic fundamentals, but rather resembles a shift in collective mentality.

Keynes vividly likened the stock market to a "beauty contest," where participants do not choose their favorites but predict what others are most likely to prefer. This game-theoretic logic inherently places sentiment and expectations at the core. Every investor in the market speculates on the psychology of others before acting, ultimately leading to amplified collective sentiment that diverges from value.

The pathways through which sentiment influences the market generally include cognitive biases (such as anchoring and overconfidence), herd imitation (such as the herd effect), and distorted risk perception. In the short term, even if a fundamental piece of information remains unchanged, shifts in sentiment can be enough to move stock indices by hundreds of points. Hedge fund manager Howard Marks points out that market sentiment constantly oscillates between "greed" and "fear," with prices fluctuating between overheating and overcooling.

Does the emotional cycle have identifiable stages?

Although emotions are highly subjective and dynamic, long-term observations have found that emotions in financial markets often exhibit a phased structure, possessing a certain recognizable “cyclical profile.” The Merrill Lynch investment pendulum theory once divided market emotions into nine stages: from skepticism and gradual acceptance to euphoria, collapse, and then reflection and a fresh start.

In this process, prices and emotions intertwine. Emotions drive prices upward, and rising prices in turn stimulate higher emotions—until a certain peak arrives, the bubble bursts, emotions reverse, entering a phase of panic and sell-off. Ultimately, as prices tend toward rationality and negative sentiment is exhausted, the market warms up again, entering the next cycle.

For example, the evolution of the U.S. real estate market from 2006 to 2008 fits this model: from the greed of “housing prices never falling” triggered by loose credit, to the abuse of financial derivatives, and then to the comprehensive collapse triggered by the bankruptcy of Bear Stearns and Lehman Brothers. Subsequently, the Federal Reserve's easing policies gradually rebuilt market confidence, initiating a new cycle of asset price increases.

Of course, the emotional cycle does not mean that one can accurately “predict market turning points,” but it provides a thinking model for “identifying the path of bubbles,” helping investors remain calm amidst collective frenzy.

Is the behavior pattern of market participants stable?

If emotional cycles are regular, does it mean that investor behavior is also repetitive? The answer seems to be affirmative. In the research of behavioral economists like Daniel Kahneman and Richard Thaler, a large number of experiments and empirical evidence indicate that investors' irrationality is not incidental, but rather a repeatable psychological response.

A typical example is “loss aversion”: the pain of loss for investors is much greater than the pleasure of gain, which leads to a tendency to “cut losses” when the market declines rather than to go against the trend, thereby reinforcing the downward trend. Conversely, during an upward trend, overconfidence and herd mentality can exacerbate the inflation of bubbles.

Consider the “anchoring effect” — investors often view historical highs as psychological anchors, mistakenly expecting prices to “return” during corrections. For example, after the collective surge of the new energy sector in 2021, many investors firmly believed during the significant drop in 2022 that it was “just a technical adjustment,” ultimately getting trapped.

These behavior patterns are not only widespread among individual investors, but institutional investors are also not immune. Especially in the context of high-frequency trading and the prevalence of algorithmic models, emotional fluctuations are amplified by programs, leading to more severe peaks and troughs. In a sense, it is the irrational stability of human behavior that constitutes the soil for emotional cycles to replicate themselves.

Can technical analysis and sentiment indicators “predict cycles”?

Since sentiment has a certain periodicity, market analysts naturally attempt to quantify and identify it through indicators. Some technical investors rely on sentiment indicators such as the VIX volatility index, the AAII investor sentiment survey, and the Put/Call ratio as references to find points of “extreme greed or fear” in the market.

The VIX index, known as the “fear index,” typically rises when investors' uncertainty about the future increases. When the VIX spikes to historical highs, it often corresponds to market bottom areas. For example, in 2008, during the week of Lehman Brothers' collapse, the VIX briefly surpassed 80, and although the market experienced fluctuations afterward, it indeed reached a bottom in the medium to long term.

Another example is the “Bull-Bear Index,” which is used to track the position changes and sentiment tendencies of institutional investors. Historical data shows that when this index falls to extreme pessimistic values, it often indicates that the market is building a bottom.

However, these indicators are not “universal oracles”; their responses are more lagging and are significantly affected by short-term information. Therefore, the greatest significance of sentiment indicators lies not in “predicting turning points,” but in providing investors with a “sentiment thermometer” to remind people whether they are currently caught in collective overreaction.

Does the historical financial crisis support the theory of "emotional cycles"?

From the South Sea Bubble, the Tulip Mania, to the Great Crash of 1929, the Internet Bubble of 2000, and the Subprime Mortgage Crisis of 2008, every major rise and fall in financial history has been accompanied by a cyclical alternation of extreme emotions.

Taking the Internet Bubble of 2000 as an example, from the Nasdaq index taking off in 1997 to peaking in March 2000, in just three years, the market value of tech stocks inflated several times. At that time, the myth of "clicking equals wealth" and "burning money to gain market share" dominated public opinion, and many companies went public successfully without profits or even products. Greed reached a frenzied state.

However, after the bubble burst, in just one year, the Nasdaq fell by nearly 80%, many tech companies went bankrupt, and layoffs surged in Silicon Valley. It wasn't until 2004 that market sentiment gradually warmed up.

Similar cases have also emerged in emerging markets. The "leveraged bull market" of China's A-shares in 2015 and the subsequent "stock market crash" saw a rapid transition from widespread account openings to thousands of stocks hitting the limit down, all in just six months; emotions shifted from mania to panic, and the market mechanism simply could not keep up with the speed of emotional changes. This structural imbalance of "emotions leading, systems lagging" is precisely a common characteristic in cyclical cycles.

Can emotional patterns be used as a reference for investment strategies?

Although "using emotions as indicators" is not a mainstream investment method, there are already many investment strategies in the market attempting to operate based on emotional cycles, with "contrarian investing" and "emotional timing" being the most typical.

The core logic of contrarian investing is: be greedy when others are fearful, and be cautious when others are greedy. Buffett's famous saying is an investment expression of the emotional cycle. The points at which most people flee often signal the bottom area, and vice versa. For example, in the early stages of the COVID-19 pandemic in 2020, there was a panic sell-off in global markets, but it was followed by unprecedented liquidity injections and market rebounds.

Another type of strategy is the "emotional timing model," which uses emotional indicators as buy and sell signals, supplemented by technical patterns or capital flow analysis, to determine whether the market is at a turning point. For instance, some quantitative funds adjust their short-term allocations to hot sectors by capturing the frequency of keywords and investment enthusiasm on social media.

Of course, any strategy based on emotions must recognize that while emotions have patterns, they never repeat mechanically. Their phases, amplitudes, and durations are often disturbed by external variables, including policies, wars, natural disasters, and so on. Therefore, emotional patterns should not be seen as a "controllable" tool, but rather understood as a "background logic that must be respected."