What is Stochastic Modelling?

Every decision you make, whether it is in business or the stock market, is responsible for the volume of profits you yield in the end. However, many investors lose a chunk of their investments if they decide to invest in a stock or choose a strategy that is not ideal in the long run. Successful Stock markets investors ensure that their investment decisions avoid any negative factors that can affect their profitability. But, how do they do it when there is so much uncertainty that can change the outcome of their investments at any time?

Professional investors such as portfolio managers who manage high-value investments make successful financial decisions by factoring-in random variations in the inputs using a financial model known as Stochastic Modelling.

What is Stochastic Modelling?

The Stochastic Modelling definition states that this is a form of financial model that helps investors and portfolio managers make informed financial or investment decisions. Stochastic Modelling is an advanced model that forecasts the probability of various financial outcomes under different market conditions. As these market conditions fluctuate frequently and are random, Stochastic Modelling uses random variables to forecast the investment outcomes.

Understanding the Stochastic Modelling process

If you are investing in a stock, you can look at its historical quarterly results to assume its future profitability and growth prospects. However, since the company operates in a free and competitive market, various random variables affect it, which can be operational, geographical, natural etc. These factors are beyond the prediction and control of investors at a personal level and can result in unfavourable negative outcomes.

Stochastic Modelling uses a model that merges historically available data with random variables that can affect the investment decision outcome and allows the investors or managers to better adjust their investment positions. The model uses numerous random factors, matches it with the constant (the initial investment decision made) and provides a clear picture of what the outcome would be if a certain random variable were to occur. Stochastic Modelling uses advanced algorithms to estimate the probability of each investment outcome by allowing one or more inputs to use random market factors. Only then, Stochastic Modelling can work to provide an estimate of the probability of various outcomes.

Example of Stochastic Modelling

Stochastic Modelling uses the initial command (decision) and provides various possible outcomes based on possible market factors. For example, suppose you are looking to invest in some stocks and are analysing the historical returns of the stocks to get an idea of how much you can profit in the next year. In that case, you can use Stochastic Modelling to predict the investment returns. While analysing the investment returns, Stochastic Modelling would use various uncertain and random inputs such as market volatility, trend reversal etc., to present various outcomes on how much you can profit if one of the added factors happens in the next year.

Typically, the random variable used by Stochastic Modelling uses time-series data which factors in the outcome that resulted in the past when a certain market factor happened, i.e. differences observed in historical data over time.

Difference between Stochastic Modelling and Deterministic Modelling

Stochastic Modelling provides outcomes by matching the constant factors (historical information that is already known) with random and uncertain factors (variable factors such as market volatility). Hence, almost every outcome provided by Stochastic Modelling is different from the others. Under Stochastic Modelling, the same process is repeated numerous times but with different random factors each time.

On the other hand, Deterministic Modelling is a financial model that provides the same outcomes each time. It is because Deterministic Modelling does not use random factors but provides results based on known historical data, which is a set of specific values.

Conclusion

Any investor or portfolio manager cannot predict or avoid uncertain factors that prevail in the market. You can invest in a good stock only to see unimaginable negative factors such as trend, volatility, natural calamities etc., forcing your investment to lose its value. In such cases, Stochastic Modelling makes up for an ideal financial model to help investors make informed investment decisions.

In the process of investing, investors can view a variety of possible outcomes under multiple conditions and factors by using Stochastic Modelling. Investors can also ensure they invest accordingly and are not affected negatively by a random market factor. By understanding what is Stochastic Modelling, you can use the model to establish an ideal financial and investment strategy along with an IIFL Demat and trading account