## So what is Chaos Theory?

Chaos theory is a mathematical idea that describes how conventional equations can produce random solutions.

The core tenet of this theory is the idea that minor occurrences can have

a large impact on the outcomes of seemingly unrelated events. Chaos

theory is also known as “nonlinear dynamics.”

Chaos theory is a complex mathematical theory that attempts to explain

the impact of seemingly small factors. Some believe that chaos theory

can explain chaotic or random phenomena, and it is frequently applied

to financial markets as well as other complex systems such as weather

prediction. Chaotic systems appear to be random after a period of

predictability.

## The Development of Chaos Theory

Edward Lorenz, a meteorologist, conducted the first practical experiment

in chaos theory. Lorenz used an equation technique to forecast the

weather. Lorenz set out in 1961 to replicate a past weather sequence

using a computer model based on 12 factors such as wind speed and

temperature. These variables, or values, were graphed with rising and

falling lines across time. Lorenz was reenacting a previous simulation

from 1961.

On this particular day, though, Lorenz rounded his variable values to

three decimal places rather than six. This minor modification radically

altered the entire pattern of two months of simulated weather. As a

result, Lorenz demonstrated that seemingly insignificant elements can

have a major impact on the final outcome.

Chaos theory investigates the consequences of minor occurrences on

the outcomes of seemingly unconnected events.

## The Stock Markets and Chaos Theory

There are two frequent misconceptions concerning the stock market.

The first is based on classical economic theory and asserts that markets

are completely efficient and unexpected. The other theory holds that

markets are predictable to some extent. Otherwise, how do large trading

firms and investors achieve consistent profits?

The truth is that markets are complicated and chaotic systems, with both

systematic and random components to their behavior. Stock market

forecasts can only be accurate to a certain extent.

As Lorenz proved, complex chaotic systems are subject to little

disturbances that can disrupt the system and cause it to deviate from its

equilibrium. The dynamics of the stock market can be represented as

two primary feedback and causal loops that influence many components

of the market. A positive feedback loop reinforces itself. A positive

influence in one variable, for example, raises the other variable, which in

turn enhances the first variable. This causes the system to grow

exponentially, causing it to lose its equilibrium and eventually collapse

into a bubble. A negative feedback loop, on the other hand, has a similar

effect in that the system responds to a change in the opposite direction.

Periods of significant uncertainty may be induced by factors other than

system dynamics. Natural calamities, earthquakes, and floods, as well

as abrupt losses in a single stock, can all cause markets to be volatile.

While some theorists believe that chaos theory can assist investors to

improve their performance, the application of chaos theory to the

financial world is debatable.

**Disclaimer: **There are potential risks relating to trading and investing and you should not

trade with money that you cannot afford to lose however, for those that educate themselves

and adopt appropriate risk management strategies, the potential update can be significant.

Please note that all opinions, research, analysis, and other information are provided as

general market commentary and not as specific investment advice.

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