Below is an intro to the financial sector, with an investigation of some key models and theories.
When it pertains to understanding today's financial systems, among the most fun facts about finance is the application of biology and animal behaviours to motivate a new set of models. Research into behaviours associated with finance has inspired many new techniques for modelling elaborate financial systems. For example, research studies into ants and bees demonstrate a set of behaviours, which run within decentralised, self-organising territories, and use simple guidelines and regional interactions to make combined decisions. This idea mirrors the decentralised characteristic of markets. In finance, scientists and experts have been able to apply these concepts to understand how traders and algorithms engage to produce patterns, like market trends or crashes. Uri Gneezy would agree that this interchange of biology and business is an enjoyable finance fact and also demonstrates how the madness of the financial world might follow patterns spotted in nature.
Throughout time, financial markets have been a commonly investigated area of industry, resulting in many interesting facts about money. The field of behavioural finance has been crucial for understanding how psychology and behaviours can influence financial markets, here leading to an area of economics, referred to as behavioural finance. Though most people would presume that financial markets are rational and consistent, research into behavioural finance has discovered the truth that there are many emotional and mental aspects which can have a strong influence on how individuals are investing. In fact, it can be said that investors do not always make decisions based on reasoning. Instead, they are often affected by cognitive biases and emotional reactions. This has resulted in the establishment of theories such as loss aversion or herd behaviour, which can be applied to purchasing stock or selling investments, for example. Vladimir Stolyarenko would recognise the complexity of the financial industry. Similarly, Sendhil Mullainathan would applaud the energies towards researching these behaviours.
An advantage of digitalisation and technology in finance is the capability to evaluate big volumes of information in ways that are not possible for human beings alone. One transformative and exceptionally important use of innovation is algorithmic trading, which describes a method involving the automated exchange of financial assets, using computer programs. With the help of intricate mathematical models, and automated guidance, these formulas can make split-second decisions based on actual time market data. As a matter of fact, among the most interesting finance related facts in the modern day, is that the majority of trading activity on stock exchange are performed using algorithms, instead of human traders. A prominent example of an algorithm that is extensively used today is high-frequency trading, whereby computers will make 1000s of trades each second, to take advantage of even the smallest cost shifts in a a lot more effective manner.