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Chaos theory and its applications in financial markets, psychology and management

Study guide

You may have heard the saying that a butterfly flying at one point can cause a huge storm elsewhere. This is one of the principles of chaos theory, which, although vulgarly written, expresses one of the important features of chaos theory. Chaos theory has gained special importance in scientific circles in recent years and is constantly evolving as a living theory. In the same year 2020, the Nobel Prize in Physics was awarded to three physicists whose work was entirely related to the theory of turbulence. In this article, we intend to examine chaos theory and some of its applications in financial markets, psychology and management.

What is Chaos Theory?

Chaos theory examines the behavior of chaotic systems. This theory has rules and principles, most of which were known until the mid-1980s. According to this theory, systems and phenomena are observed around us whose components have irregular interactions with each other and energy is distributed in them. Some examples of these chaotic phenomena are:

  • weather;
  • Habitats;
  • Gas inside a chamber;
  • Birds fly in large numbers such as starlings;
  • Organizations;
  • Urban communities.

Although these systems appear to be cluttered, with the help of mathematical knowledge and the dynamics of complex systems (a branch of physics), behavioral patterns can be identified and order can be found at the heart of apparent disorder.

Chaos theory eventually evolved into a more comprehensive theory called the “complexity” theory in the 1990s.

History of Chaos Theory

One of the first to talk about the behavior of turbulent systems was Henry Poincaré, a mathematician of the late nineteenth century. He was a mathematician who studied a lot about the topology and dynamics of systems. Poincaré had said of these systems: “It seems that a slight change in these sets will lead to major consequences for the whole set. A minor error in one component will cause a major error in the future. “It is impossible to predict the behavior of the collection.”

Henry Poincaré was the first to study the nature of chaos.

Unfortunately, after Poincaré’s death, the study of turbulent systems ceased for a long time until, in the early 1960s, some scientists again turned their attention to these systems. One of them was Edward Lawrence. Lawrence was a meteorologist at the Massachusetts Institute of Research and Technology who worked on computational models of atmospheric behavior. During his work he discovered one of the most important and famous principles of chaos theory, the principle known as the “butterfly effect”. You may have heard the saying that a butterfly flying in Tokyo can cause strong winds in Chicago. Although this definition is of the effect of the common butterfly, it well illustrates the effect of small factors on large changes.

To be more scientific, the butterfly effect indicates the effect of minor factors on the behavior of the entire system. What appears to be a minor change or anomaly at first can change the behavior of the entire system in the long run. On the other hand, the butterfly effect also makes it clear that the occurrence of accidental behaviors or disruptions in the system can be the result of minor fluctuations in the system itself, not just external forces entering the system from outside.

History of Chaos Theory
Edward Lorenz’s name is associated with the theory of chaos. He revived this forgotten theory in the 1960s.

Another pioneer of this theory is Mitchell Feigenbaum, a theoretical physicist working at the Los Alamos National Laboratory. He has devoted many years of his life to studying chaos theory and finding mathematical models to describe the behavior of these systems. In the 1970s, scientists in various sciences studied the theory of chaos, but the scientific community at that time was not very happy with these studies. Some universities and scientific institutes deliberately avoided examining this theory because they were not very sure about its applications.

But after the 90’s, this theory and its more developed form, the theory of complexity, gradually opened its place as an interdisciplinary, important and practical problem, and today many prominent academic centers and research institutes in the world give scholars in this field the opportunity and budget to study and research. they give.

Applications of chaos theory

As James Glick in his book Chaos; “The theory of chaos is the comprehensive science of systems,” he said. Therefore, many disciplines use the achievements of this discipline to describe the complex systems we deal with, including:

  • Physics;
  • biology;
  • chemistry;
  • Geology;
  • Meteorology;
  • Economy;
  • Sociology.

Let’s take a brief look at the applications of this theory in three different sections.

1. Chaos theory in financial markets

Chaos theory in financial markets

One application of chaos theory is to explain the behavior of financial markets such as the stock market. Stock exchanges and other similar markets are complex systems with chaotic behavior. All market analysis techniques rely in some way on the mathematical findings and models derived from chaos theory. Chaos theory tells us that all market analyzes are only partially correct and can not be 100% accurate because not all market components and variables can be predicted.

As Lorenz showed with the butterfly effect, chaotic systems are vulnerable to minor changes, meaning that a slight change can upset the balance of the entire set. Financial markets may also bubble or collapse based on this effect. For example, a small positive change in one stock can lead to consistent positive changes in all stocks, resulting in index growth. The opposite is also true when a stock drop can cause a wave of consistent losses. Chaos theory also shows that financial markets, in addition to the minor effects of systemic factors themselves, are also affected by forces outside the system, such as political events, environmental crises, and natural disasters.

There is disagreement among market analysts about the useful application of chaos theory in financial markets. Some argue that applying the principles of this theory is essential to improving shareholder performance. But others are not so sure about the useful applications of this theory. An important factor in determining the applicability of this theory in stock exchanges and financial markets is the processing power of computers. Analyzing turbulent variables is possible only with computers, and if the power of ordinary computers is so high one day that they can analyze all or at least a large number of variables, the predictions of stock market behavior and other markets will undoubtedly be more accurate and less accurate.

۲. Chaos theory in psychology and sociology

Application of chaos theory in psychology

Chaos theory is mostly used to describe natural or man-made phenomena, but recently psychologists have debated its applications to improve theories in the field. According to Ray Fortunato: “Chaos theory provides us with a framework for identifying and understanding human behavior. Freudian, Jungian, and behaviorist theories often examine human behavior linearly. “The human brain is a complex, nonlinear system.” Thus, according to the author, Adler’s view of man is more defensible because of his nonlinear view.

The application of chaos theory to psychology is not yet widespread, but the principles of this theory have the potential to be applied in this field. Using chaos theory, human behavior can be described on the basis that humans are nonlinear beings with complex brains. With the help of relationships and models of this theory and redefining these models based on psychological components, a more accurate description of the reasons for human behavior can be provided. Similarly, chaos theory in sociology can be used to study human collective behavior.

3. Chaos theory in management

Chaos theory in management and organizational behavior may seem a little strange, because most of us think of management in terms such as control and order. But the theory of turmoil in management has been around since the 1980s. Tom Peters, author of Prosperity in Chaos, was the first to mention the application of this theory to the management of organizations. “Managers need to be prepared to adapt to environmental and technological change,” he wrote.

Chaos theory emphasizes that the behavior of the employees of an organization or business can become a complex system, a system in which the disruption in the smallest detail can turn into major changes or disruptions in the whole body of the organization. According to the principles of this theory, stochastic events can be included in the organization’s risk calculations and management, and thus prepare the organization for stochastic events that disrupt the whole set.

However, convincing the leaders of the organization to use this theory is not easy, because most people’s mental models equate management with control and order, and the inclusion of chaos in decisions and calculations usually seems strange. Peters believes that pyramidal and dry organizational structures reduce the organization’s ability to adapt to random chaotic situations. He therefore suggested that organizations and businesses should prepare for turbulent conditions that upset the balance of the system (organization).

The first practical applications of chaos theory in management were identified in the late 1980s. That is, when flexible groups were formed. Depending on the situation, these groups could redefine the role of group members so that they could adapt to market changes in the shortest possible time. Gradually, in organizations, managers who relied on soft management seats also gave way to flexible managers who were able to lead the organization in a sea of ​​turmoil. The most successful managers have been and are those who understand the important point that organization is nothing but a mental phenomenon that is based on human relationships, and these relationships are constantly changing.






Chaos theory and its applications in financial markets, psychology and management

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