The objective of this article is to facilitate the understanding of stochastic processes, how they work, as well as their types and utilities. In this article, we will also focus on the study of stochastic processes related to finance and economics. This knowledge is taught in one, all this is taught in a master in Financial Risk Management.
What are stochastic processes?
The statistical science and its theory of the probability is the one that lodges this type of processes applicable to innumerable fields. A stochastic process is a mathematical concept that is used to handle random magnitudes that vary with time or to characterize a succession of random variables called stochastics, which evolve as a function of another variable. A stochastic process is made up of randomly given variables that depend on arguments or parameters
Stochastic processes try to predict phenomena in the safest way. but never reach 100%. In the case of the stock market, it is usually analyzed second by second to increase the probabilities. However, no predictive model already invented is able to find out if a stock index will rise or fall effectively. Despite this, you can have more or less exact approximations.
Stochastic processes can be defined mathematically as:
- Sets of temporary relationships with temporary indexes
- As a set of random variables “X” indexed by a “t” index.
Some examples of time series could be:
- The weather
- The evolution of the population in a certain place and during a given period
- Stock indices, which we will focus on later.
If you want to learn more about stochastic processes, a master’s degree is a safe bet. It will allow you to understand and apply these methods to your daily work, predicting any type of statistical model. If you are interested, do not hesitate! Request information!.
Types of stochastic processes
Stochastic processes are divided into two types, which in general and essential terms can be defined as unpredictable or foreseeable.
- Stationary stochastic processes: those that the probability distribution is constant over long periods of time.
An example of a stationary stochastic process is the EUR / USD price. If we choose a period of time greater than 100 days, we will obtain that the quote of the EUR / USD is within + 1 / -1% daily. But this does not mean that we can affirm this trend with complete certainty, but if we intuit it.
- Non-stationary stochastic processes: those whose distribution varies in a non-constant way. That is, the data behaves in a totally chaotic way. Non-stationary stochastic processes are dominated by chance, are unpredictable. But that a process is stochastic, not stationary does not mean that it is totally chaotic. Non-stationary stochastic processes can be converted into stationary stochastic processes by transforming the series.
Utilities of stochastic processes
In this section, we will focus on the applications of stochastic processes and their usefulness in the workplace. The applications are diverse and very different: from applied application to engineering, sociology, finance, business, and medicine, to meteorology or the environment, through simulations of physical or chemical processes. … Of all of them, we will focus on the stochastic processes applied to finance.
The stochastic processes applied to finances, since they contain a random component, can be used to study the behaviour of various variables. Allowing thus to estimate the probable future behaviour.
Most of the applications of stochastic processes in finance occur in the stock market. The use of a stochastic process tries to study the effect of the ability to predict the performance of an underlying asset in the price of the options. As long as their returns are not related to their past tense they are predictable with respect to a larger set of information.
Given the importance of this method when trying to predict on the stock market, it is necessary to name the stochastic method also as a stock market indicator. Which is a type of oscillator that is used in conditions where markets move laterally? The side markets do not go up or down and send numerous false signals of buying and selling…
The stochastic stock index is constituted through the price quote of the last session of an asset or index with respect to its minimums and maximums. The results are given in numbers from 0 to 100. This means that the more oversold an asset has, the result will be closer to 0. The more overbought an asset has, the closer it will be to 100.
Understanding and knowing how to apply stochastic processes to the sector of quantitative finance, and even more, of investments, is highly recommended and essential. Therefore, it is also training in a master that helps to understand all these topics of great interest. If you want to train in quantitative finance and stochastic processes, sign up for a master’s degree in Financial Risk Management at the University of Alcalá. You will be trained in the application of statistical models in the finance sector. A sector on the rise and hungry for professionals awaits you!
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