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Market Complexity Could Trigger the Next Crash

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How Market Complexity Could Trigger the Next Crash

How Market Complexity Could Trigger the Next Crash

Complex systems are all around us.

By one definition, a complex system is any system that features a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear (not derivable from the summations of the activity of individual components) and typically exhibits hierarchical self-organization under selective pressures.

In today’s infographic from Meraglim we use accumulating snow and an impending avalanche as an example of a complex system – but really, such systems can be found everywhere. Weather is another complex system, and ebb and flow of populations is another example.

Markets are Complex Systems

Just like in the avalanche example, where various factors at the top of a mountain (accumulating volumes of snow, weather, temperature, geology, gravity, etc.) make up a complex system that is difficult to predict, markets are similarly complex.

In fact, markets meet all the properties of complex systems, as outlined by scientists:

1. Diverse
System actors have different points of view. (i.e. bullish, bearish, long, short, leveraged, non-leveraged, etc.)

2. Connected
Capital markets are over-connected, and information spreads fast. (i.e. chat rooms, phone calls, emails, Thomson Reuters, Dow Jones, Bloomberg, trading systems, order entry systems, etc.)

3. Interaction
Trillions of dollars of securities are exchanged in transactions every day (i.e. stocks, bonds, currencies, derivatives, etc.)

4. Adaptive Behavior
Actors change their behavior based on the signals they are getting (i.e. making or losing money, etc.)

And like the avalanche example, where a single snowflake can trigger a much bigger event, there are increasing signs that the complexity behind the stock market has also reached a critical state.

Markets in a Critical State

Here are just some examples that show how the market has entered into an increasingly critical state:

Record-Low Volatility
The VIX, an index that aims to measure the volatility of the market, hit all-time lows this summer.

Bull Market Length
Meanwhile, the current bull market (2009-present) is the second-longest bull market in modern history at 3,109 days. The only bull market that was longer went from the 1987 crash to the Dot-com bust.

Valuations at Highs
Stock valuations, based on Robert Schiller’s CAPE ratio (which looks at cyclically-adjusted price-to-earnings), are approaching all-time highs as well. Right now, it sits 83.3% higher than the historical mean of 16.8. It was only higher in 1929 and 2000, right before big crashes occurred.

Market Goes Up
Investor overconfidence leads investors to believe the market only goes up, and never goes down. Indeed, in this bull market, markets have gone up 67 of the months (an average gain of 3.3%), and have gone down only 34 months (average drop of -2.6%).

Here are some additional signs of systemic risk that make complex markets less stable:

  • A densely connected network of bank obligations and liabilities
  • Over $70 trillion in debt added since Financial Crisis
  • Over $1 quadrillion in notional value of derivatives
  • Non-bank shadow finance through hedge funds and securitization make risk impossible to measure
  • Increased leverage of banks in some markets
  • Greater concentration of financial assets in fewer companies

In other words, there are legitimate reasons to be concerned about “snow” accumulation – and any such “snowflake” could trigger the avalanche.

In complex dynamic systems that reach the critical state, the most catastrophic event that can occur is an exponential function of scale. This means that if you double the system, you do not double the risk; you increase it by a factor of five or 10

– Jim Rickards, author of Road to Ruin

The Next Snowflake

What could trigger the next avalanche? It could be anything, including the failure of a major bank, a natural disaster, war, a cyber-financial attack, or any other significant event.

Such “snowflakes” come around every few years:

1987: Black Monday
The Dow fell 508 points (-22.6%) in one day.

1994-95: The Mexican peso crisis
Systemic collapse narrowly avoided when the U.S. government bailed out Mexico using the controversial $20 billion “Exchange Stabilization Fund”.

1997: Asian financial crisis
East Asian currencies fell in value by as much as -38%, and international stocks by as much as -60%.

1998: Long Term Capital Management
Hedge fund LTCM was in extreme distress, and within hours of shutting down every market in the world.

2000: The Dotcom crash
Nasdaq fell -78% in 30 months after early Dotcom companies crashed and burned.

2008: Lehman Brothers bankruptcy
Morgan Stanley, Goldman Sachs, Bank of America, and J.P. Morgan were days away from same fate until government stepped in.

Shelter from the Avalanche

The Fed and mainstream economists use equilibrium theory, regressions, and correlations to quantify the markets. And while they pay lip-service to black swans, they don’t have a good way of forecasting them or predicting them.

Markets are complex – and only complexity theory and predictive analytics can help to shed light on their next move.

Alternatively, investors can seek shelter from the storm by investing in assets that cannot be digitally frozen (bank accounts, brokerage accounts, etc.) or have their value inflated away (cash, fixed-income). Such assets include land, precious metals, fine art, and private equity.

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AI

Just 20 Stocks Have Driven S&P 500 Returns So Far in 2023

From Apple to NVIDIA, megacap stocks are fueling S&P 500 returns. The majority of these firms are also investing heavily in AI.

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Just 20 Stocks Have Driven Most of S&P 500 Returns

Just 20 firms—mainly AI-related stocks—are propping up the S&P 500 and driving it into positive territory, signaling growing risk in the market.

The above graphic from Truman Du shows which stocks are making up the vast majority of S&P 500 returns amid AI market euphoria and broader market headwinds.

Big Tech Stock Rally

Tech and AI stocks have soared as ChatGPT became a household name in 2023.

The below table shows data from last month, highlighting that just a small collection of companies drove most of the action on the U.S. benchmark index.

Company RankNameContribution to S&P 500 ReturnAverage Weight
1Apple1.49%6.61%
2Microsoft1.15%5.72%
3NVIDIA 1.00%1.62%
4Meta0.66%1.15%
5Amazon0.51%2.56%
6Tesla0.50%1.39%
7Alphabet (Class A Shares)0.34%1.72%
8Alphabet (Class C Shares)0.31%1.53%
9Salesforce0.19%0.51%
10Advanced Micro Devices0.16%0.39%
11General Electric0.10%0.28%
12Visa0.10%1.08%
13Broadcom0.09%0.73%
14Intel0.09%0.35%
15Walt Disney0.08%0.55%
16Booking Holdings0.07%0.28%
17Exxon Mobil0.06%1.37%
18Netflix0.06%0.44%
19Oracle0.06%0.40%
20Adobe0.06%0.49%
Top 20 Companies7.05%29.17%
S&P 500*7.55%100.00%

*Based on the Vanguard S&P 500 ETF as of April 11, 2023. Source: Vanguard S&P500 ETF, Bloomberg.

Microsoft invested $10 billion into OpenAI, the creators of ChatGPT. It has also integrated generative AI into its search engine Bing. This large language model is designed specifically to make search capabilities faster, generate text, and perform other automations.

Also of interest is NVIDIA, which is the most valuable chipmaker in America. It sells $10,000 chips called A100s that allow machine learning models to run. These models perform multiple tasks simultaneously to develop neural networks and train AI systems, including OpenAI’s ChatGPT. Companies that are developing AI-related services, such as chatbots or image generation, may use up to thousands of these chips.

Despite being the world’s most valuable company and a key driver of returns, Apple is an outlier among tech giants with no major projects announced in AI (so far).

Implications of Market Divergence

The problem with the strong gains seen in a few select AI-related stocks is that it clouds wider stock market performance.

Without the AI-led rally, the S&P 500 would be returning -1.4%. as of May 17, 2023.

This form of steep divergence, known as market breadth, often signals higher risk in the market.

When more companies experience positive returns it is less risky than a small handful seeing the majority of the gains. Today market breadth is very narrow, and these companies make up over 29% of the entire index’s market capitalization.

How long AI-related firms mask the broader performance of the S&P 500 remains to be seen. A growing number of market pressures, from higher interest rates to banking uncertainty could add further challenges.

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