Stochastic Modeling in Stock Market

Stochastic Modeling

Stochastic Modelling is a financial model that helps make financial decisions.

  • It incorporates random variables to produce many different outcomes under diverse conditions to predict the probability of results.
  • Unpredictability –

    Stochastic Modelling accounts for certain levels of unpredictability or randomness.

Use of Stochastic Modeling in Stock Market

  • Getting various projections of assets allocation outcomes based on various conditions.
  • Management of Liabilities. Insurance companies heavily rely on Stochastic Modeling to forecast and hence to calculate premium. Here is more detailed example of one of such model called Cramer -Lungberg Insurance Model.
  • Insurance companies also have to build reserve for their future payments which is usually done by deterministic methods; so there are many models which are Semi-Stochastic. You can checkout here.

Deterministic Modelling vs Stochastic Modelling

Deterministic Modelling

Deterministic modeling gives you the same exact results for a particular set of inputs, no matter how many times you re-calculate the model.

  • Produces Constant Results
  • Example – f(x) = x +1
  • Example – Moving Average [Or, Any indicator in Stock Market that is calculated based on past data]

Stochastic Modelling

Stochastic modeling, on the other hand, is inherently random, and the uncertain factors are built into the model.

  • Produces Variable Results
  • Inherently random
  • Example – Monte Carlo Simulation, Markov Models [Any models or simulations in Stock Market that does probabilistic forecasting.]
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