## Instructions

### Objective

Write a python assignment program to predict stock prices.

## Requirements and Specifications

**Source Code**

```
from functions import *
### beta calculations
get_beta('data.csv')
### simulation function
data=simulate(120,0.6,0.5,10)
data
### Calculating probability
c=0
for i in range(10000):
data=simulate(T=120,alpha=0.6,p=0.5,x0=10)
drop=(data[-1]-data[0])/data[0]
if drop<=-0.1:
c+=1
c/10000
c=0
for i in range(10000):
data=simulate(T=120,alpha=0.6,p=0.5,x0=10)
drop=(data[-1]-data[0])/data[0]
if drop<=-0.25:
c+=1
c/10000
### Visualization
data=simulate(120,0.6,0.5,10)
plt.figure(figsize=(10,8))
plt.plot(data)
plt.grid()
plt.xlabel('time steps',fontsize=20)
plt.ylabel('price',fontsize=20)
plt.title('stock price simulation',fontsize=20)
plt.ylim(0,20)
plt.savefig('MITID_Figure1.pdf')
plt.show()
```

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