Econophysics is the utilization of the laws of physics to the research of financial markets, under the theory that the business world functions as a sea of electrons or a group of water molecules that interact with each other. Econophysicists are securing a questionable inauguration at tearing up some difficult economics with modern tools of mathematical physics and the current discoveries in learning turbulent practices and decreasing them to a few elegant general principles.

The term econophysics was presented with similar terms, which depicts applications of physics in various fields, such as astrophysics, geophysics, and biophysics. Econophysics was first introduced by the famous theoretical physicist, Eugene Stanley in 1995, at the conference on Dynamics of Complex Systems. It was held in Calcutta, later recognized as Kolkata, as a mandated meeting to the Statphys 19 conference in China. The field of econophysics uses the theory of probabilities, and mathematical methods emerged in statistical physics. It was done to study statistical properties of twisted economic systems consisting of a substantial quantity of obscure units or population (firms, families, households, etc.) made of small groups or humans. Especially significant in defining econophysics is the apparent disparity between statistical physics and mathematical statistics in its center, methods, and results. It is a sociological explanation, based on physicists who are working on economic problems.

Why is econophysics not a multidisciplinary science but an interdisciplinary one? Multidisciplinary implies discrete disciplines in the study, as with an economist and a physicist speaking to each other. On the other hand, interdisciplinary indicates a narrow specialty formed out of elements of each separate discipline, for instance, a “water economist” who understands hydrology and economics. Multidisciplinary discipline remains usually defined in terms of the ideas or techniques that it deals with, for example, political economy or biophysics. However, transdisciplinary recommends a broader combination of methods and ideas from the disciplines involved. It is the term approved by the ecological economists for what they are trying to develop. Yakovenko (2009) stated that econophysics is an “interdisciplinary research field applying methods of statistical physics to problems in economics and finance.” It is yet another, more relevant and synthetic definition of econophysics.

There are some essential differences between econophysics and sociophysics. The first emphasizes the confined subject of the economic behavior of humans, where quantitative data is accessible, while the second looks into an extensive range of social issues. However, the barrier between econophysics and sociophysics is not transparent, and the two fields have good harmony. Econophysics is still a foreign word even after 17 years. Moreover, it is used to represent work done by physicists, in which financial and economic systems remain used as complex systems. Thus, for physicists, studying the economy indicates studying a stock of data on a well-defined complex system. The contemporary way to depict econophysics is in terms of the concepts it includes, in effect physicists doing economics with theories from physics. This medium demands the question of how the two disciplines compare to each other, and it describes interest rates and changes in stock market prices. These theories map analogies to turbulence, earthquakes, fractals, sand piles, radioactivity, energy states in nuclei, and the structure of elementary particles.

Technologically, econophysicists have incorporated their slot by creating models much more straightforward than most economists now choose to consider. They even used a reasonable association between economic or financial terms and crucial points in statistical mechanics, where the acknowledgment of a physical system to a small external disturbance becomes eternal. It is because all the subparts of the system answer accordingly, even though some economists claim that it is a disrespect to the intelligence of the market to conjure the presence of a noise term. Many diverse approaches and techniques from physics and the other sciences have been examined by econophysicists, including pattern recognition, chaos theory, and neural networks. Another impressive definition holds econophysics as a scientific method to the quantitative economy using models, ideas, conceptual and computational techniques of statistical physics. In the current years, many physical hypotheses like the theory of turbulence, random matrix theory, scaling, or renormalization group, were successfully applied to the economy. These hypotheses gave a boost to advanced computational techniques of data analysis, risk management, artificial markets, macroeconomy. And thus econophysics became a traditional discipline comprising a vast spectrum of obstacles of the modern economy. A comprehensive description of econophysics explains it as a unique area, acquired recently by the interaction between economists, physicists, and mathematicians, which implements ideas, methods, and models in statistical physics and complexity to interpret data from the economic phenomena.

Econophysics is nothing more than the combination of physics and economics. It is a link between the two entirely separate disciplines that lie within the individual behavior displayed by financial markets, similar to other recognized physical systems. Econophysics aims to illustrate the models of the universal practices of an exchange, as a free system, where new external data remains merged with new investments. There are different types of econophysics as well. One is an experimental or observational type, which attempts to analyze real data from real markets and make sense of them. Another is an ideal type, which tries to attain microscopic models giving some quantities of good agreement with the experimental evidence. The first econophysics models, which were published by physicists in a physics journal, were those of Takayasu et al. (1992) and Mantegna (1991), though they produced them several years ahead. But in 1964, Stigler from the Chicago economics school had published a Monte Carlo simulation of a market already. In 1989, the Nobel laureate of Economics H.M. Markowitz with Kim, published a model about the Wall Street crash in 1987, with two types of investors, similar to many succeeding models of physicists. After the year 2000, econophysics evolved enough to acknowledge generalized utilization. This field is sometimes known as Econo-engineering.

Without being likewise determined, econophysics continues to be the science that utilizes models – taken especially from statistical physics – to represent some economic features, an interdisciplinary research field, applying theories and methods initially generated by physicists to solve problems in economics. Generally, those include stochastic factors or conjecture and nonlinear dynamics. Primary tools of econophysics are probabilistic and mathematical techniques, often taken from statistical physics. Most econophysics models, papers and approaches that have been written so far indicate to the economic methods which comprise systems with a wide range of elements, such as financial or banking markets, production or product’s sales, stock markets, incomes, and individual incomes. In these cases, statistical physics approaches are mainly applied.

Today it is feasible for methods and concepts of statistical physics to have substantial influence in economic thought. However, it is also likely that economical methods and ideas can impact the physics thought as well. The process of econophysics illustrates its central intent in applying a system of statistical physics and other mathematical practices implemented in physics to economic data and economic processes. Why can the processes and procedures from statistical physics be favorably executed to social, economic, and financial problems? Could it be the result of the great experience of physicists working with experimental data? Does it give them a sole advantage to reveal quantitative laws in the statistical data accessible in social sciences, economics, and finance? Is econophysics indeed bringing fresh insights viewpoints, which are likely to transform the old social sciences and classical economics?

The study of dynamic systems remains substantially based on expressing them in terms of (partial) differential equations which are moreover worked out by analytical processes (or numerically). However, this is somehow opposite to our intuitions: we never come across the life density distributions of our cars, utility functions, friends, etc. We have transformed integrals into real numbers by equalizing over specific areas. These real numbers can be achieved either by averaging over high enough volumes or over a prolonged period of times. Statistical physics is a framework which lets systems, consisting of many independent particles, to be rigorously examined. Inside econophysics, these procedures remain implemented on economic particles, namely investors, traders, and consumers. Markets then observed as complex systems (macroscopic) with an enclosed structure consisting of many of these particles (microscopic). These then interact to produce the systemic features (the microstructural elements are reactive in this circumstance, as discussed already, thus resulting in an adaptive complex system). Initially, when the physicists attempted to analyze financial markets, by applying the method of statistical physics, they did not look into these markets as individually exceptional examples of complex systems. Few of them have even believed they are discovering laws or some establishment proof in the pattern of the scaling laws that Pareto first studied.

In contrast, that has discovered a much broader category of economic observables. In all honesty, the establishment evidence found is not a steady or a conclusive one, because all the markets act portrayed by nonstationarity. It is a common feature of complex adaptive systems. McCauley (2004) asserted that “the empirical distribution is not fixed once and for all by any law of nature [but] is also subject to change with agents’ collective behavior.”

Theory verifies that the attributes of complex systems include three necessary conditions:

- Complex systems must carry many subunits (the exact number left vague).
- Subunits must be interdependent (at least at some point of the time).
- Interactions among the subunits must be nonlinear (at least some of the time).

These properties are said to be emanating when they amount to new complex or systemic composition, and a complex adaptive system adds the following requirement:

Individual subunits adjust their properties and behavior concerning a dynamic environment resulting in the generation of new systemic characteristics.

Finally, the organizing adaptive complex system adds another necessary condition:

Individual subunits alter their properties and behavior concerning the features and functioning of the unit system they jointly determine. Sometimes they do it by including a network performance model for what is pointed to, by physicists, in particular, as complex networks.

In comparison to classical statistical thought, econophysics has disclosed that heterogeneous in reality is explained with homogeneous in theory. And this is the principal role of the method of analytical physics – to consolidate and clarify economics. Some of the success stories related to econophysics include:

More than anything, physicists have encouraged to discover empirical facts about financial markets. For instance, the probability of significant market movements (up or down) contracts, following an inverse cubic power law in many distinct markets (stocks, derivatives, currencies, bonds, and in many nations). Aforementioned is a straightforward mathematical pattern. It apprehends in particular form, the general phenomenon of large market outbreaks much more commonly than would be anticipated by ordinary Bell Curve statistics. These “fat tails” appear to be a more or less universal result. Work by physicists has also discovered other nonexclusive market patterns, such as the self-similar structure of market volatility.

Did physicists inaugurate this kind of work? Of course not. The Father of Fractals Benoit Mandelbrot found the first proof for fat-tailed patterns in the early 1960s. Moreover, Nobel Prize winner Eugene Fama even wrote about that work long ago in his first paper. But the study by physicists has made our knowledge of these empirical routines much more accurate. This study is essential for proper risk management, among other things. Furthermore, to create theories explain how markets work, one first needs to ascertain exactly how they work with data. In this way, they can explicitly establish what needs to be solved.

Physicists have also distinguished informative links between markets and other natural aspects. For example, in the period following a massive market crash, markets show lingering activity. Also, that obeys the famous Omori law for earthquake aftershocks (events become less likely in uncomplicated opposite proportion to the time after the main shock). Such connections impose that the definition of such market dynamics may well not be dependent on facts which are particular to finance and economics. Therefore, more extensive dynamical principles may be involved.