“Rocket science” in finance is a metaphor for activity carried out by specialized information technology staff to provide executive managers with the detailed output of mathematical modeling programs to inform investment decisions. Their work depends on use of simulated mathematical models Implemented in complex IT environments.  
For instance, a firm that invests its money in funds of investment is the result of a mix of scientific questions and hazards. Different decisions in how to divide the financial resources into the funds lead to different sets of probabilities of return. Advising the investor on the consequences of each possible decision in the risk-return context is one of the typical roles of a rocket scientist.
Although the financial rocket science is found mostly in banks and financial enterprises,  this area is emerging in firms with other kinds of core activities.  References External links An example of the first case is the one of an insurance firm that needs to calculate sets of probabilities of expenses, from probabilities of accident of its customers. The other one is advising about what every organization needs, or even every individual, has decently what to do with the money.
The goal of a financial rocket scientist is to survey the high administration of a firm with The Most precise scenario can result of the probabilities in choosing decisions like investing , trading and borrowing .  It is not only a matter of research , but also of the fact that it is not a question of the future.
The required skills of a financial rocket scientist are broadly based. These include knowledge of microeconomics , macroeconomics ,  pure mathematics ,  statistics , information technologies and financial market practice. 
The microeconomics knowledge is necessary because the firm itself is an entity subject to microeconomics laws.  Macroeconomics are the most widely used and widely accepted methods of measuring the response of a group of entities.  Pure mathematics and statistics are required to solve the problems arising from questions submitted to the tech workers. Finally, financial market practice is needed to determine the possible decisions built into the financial models. Also, skill with Information Technology is required to prepare effective data-entry into complex computer systems.
Some concepts and tools found in this area are the Pareto optimum , the Value at Risk , and the Monte Carlo simulation . 
It’s not rocket science
ALTHOUGH this sentence very Often found in sources of every kind, Seems To deny the ontological existence of the theme here in approach, it means clustering Actually context-dependently Some That matter is not in difficulty To Understand some level of depth. The term Rocket Science was originally derived from the WWII rocket developments by Warner Von Braun and later by the NASA aerospace engineering program in the 1960’s with the objective of reaching the moon. Davis Mathews  It was later coined in 1995 by the child of comedian .
Some professions or activities are similar but not identified with rocket science, and they are lied by common outcomes and mean-goal relationships , these areas are basically the financial engineering and risk analysis , according to some sources.    Nonetheless, a second and smaller set of sources found in this research identifies them as a unique matter.  
- Computational Finance
- Mathematical Finance
- Financial modeling
- Investment management
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