SOCR EduMaterials Activities ApplicationsActivities StockSimulation

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(New page: == A Model for Stock prices == * '''Description''': You can access the stock simulation applet at http://www.socr.ucla.edu/htmls/app/ . * Process for Stock Prices: Assumed a drift rate...)
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\frac{\Delta S}{S}=0.14 \Delta t + 0.20 \epsilon \sqrt{\Delta t}
\frac{\Delta S}{S}=0.14 \Delta t + 0.20 \epsilon \sqrt{\Delta t}
</math>
</math>
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* Find the distribution of the change in <math>S<math> divided by <math>S<math> at the end of the first year.  That is, find the distribution of <math>\frac{\Delta S}{S}</math>. <br>
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* Find the distribution of the change in <math>S</math> divided by <math>S</math> at the end of the first year.  That is, find the distribution of <math>\frac{\Delta S}{S}</math>. <br>
<math>
<math>
\frac{\Delta S}{S} \sim N\left(0.10 \Delta t, 0.20 \sqrt{\Delta t}\right).
\frac{\Delta S}{S} \sim N\left(0.10 \Delta t, 0.20 \sqrt{\Delta t}\right).
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\Delta S_1 = S_0 +  \Delta S_1 = 20 + 0.26=20.26.
\Delta S_1 = S_0 +  \Delta S_1 = 20 + 0.26=20.26.
</math>
</math>
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We continue in the same fashion until we reach the end of the year.
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We continue in the same fashion until we reach the end of the year.  Here is the SOCR applet.
<center>[[Image: Christou_stock_simulation.jpg|600px]]</center>
<center>[[Image: Christou_stock_simulation.jpg|600px]]</center>

Revision as of 16:06, 3 August 2008

A Model for Stock prices

  • Process for Stock Prices: Assumed a drift rate equal to μS where μ is the expected return of the stock, and variance σ2S2 where σ2 is the variance of the return of the stock. From Weiner process the model for stock prices is:


\Delta S = \mu S \Delta t + \sigma S \epsilon \sqrt{\Delta t}
or 
\frac{\Delta S}{S} = \mu \Delta t + \sigma \epsilon \sqrt{\Delta t}.
Therefore 
\frac{\Delta S}{S} \sim N(\mu \Delta t, \sigma \sqrt{\Delta t}).
S Price of the stock. ΔS Change in the stock price. Δt Small interval of time. ε Follows N(0,1).


  • Example: The current price of a stock is S_0=\$100. The expected return is μ = 0.10 per year, and the standard deviation of the return is σ = 0.20 (also per year).
  • Find an expression for the process of the stock.


\frac{\Delta S}{S}=0.14 \Delta t + 0.20 \epsilon \sqrt{\Delta t}

  • Find the distribution of the change in S divided by S at the end of the first year. That is, find the distribution of \frac{\Delta S}{S}.


\frac{\Delta S}{S} \sim N\left(0.10 \Delta t, 0.20 \sqrt{\Delta t}\right).

  • Divide the year in weekly intervals and find the distribution of \frac{\Delta S}{S} at the end of each weekly interval.


\frac{\Delta S}{S} \sim N\left(0.10 \frac{1}{52}, 0.20 \sqrt{\frac{1}{52}}\right).

  • Therefore, sampling from this distribution we can simulate the path of the stock. The price of the stock at the end of the first interval will be S1 = S0 + ΔS1, where ΔS1 is the change during the first time interval, etc.


  • Using the SOCR applet we will simulate the stock's path by dividing one year into small intervals each one of length \frac{1}{100} of a year, when S_0=\$20<math>, annual mean and standard deviation: <math>\mu=0.14, \sigma=0.20.


  • The applet will select a random sample of 100 observations from N(0,1) and will compute


\frac{\Delta S}{S} =  0.14 (0.01) + 0.20 \epsilon \sqrt{0.01}.
Suppose that ε1 = 0.58. Then

\frac{\Delta S}{S} =  0.14 (0.01) + 0.20 (0.58) \sqrt{0.01}= 0.013 \Rightarrow  \Delta S_1= 20(0.013)=0.26.
Therefore ΔS1 = S0 + ΔS1 = 20 + 0.26 = 20.26. We continue in the same fashion until we reach the end of the year. Here is the SOCR applet.

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