FIN5615_Project_2_Neil_Yejjey.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<h2>FIN5615 Project #2\n",
    "    <p class=\"text-primary\">Random Walk Simulaton (Part I)</p>\n",
    "</h2>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<div class = \"panel panel-success\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:black\"><b>Project Introduction</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    In this project we will try to address some of the shortcomings of modeling stock price as a simple random walk. We will compare the simulated option prices from our random walk model against that of the Black-Scholes options pricing formula.\n",
    "    </div>\n",
    "</div>\n",
    "<div class = \"panel panel-info\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:black\"><b>Instructions</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    Please code you solutions directly in this Notebook under each task in the cells provided below. Include all code used to produce your results, and support your answers with textual explanations if neccessary. You may feel free to add additional Code and/or Markdown cells as needed. Code must be written using <b>Python 3</b>.\n",
    "    <br><br>Please order the cells in your Notebook in the order in which they are intended to run! It is expected that your Notebook is able to run in sequence from start to finish without any errors (before submitting check by: <code>Kernel > Restart & Run All</code>).\n",
    "    <br><br>Once ready, please submit your assignment as an <b>.ipynb file</b> (<code>File > Download as > Notebook</code>). You must name your files in the following format: <b><code>FIN5615_Project_1_Richard_Lee_tuc12345.ipynb</code></b>.\n",
    "    </div>\n",
    "</div>\n",
    "\n",
    "---\n",
    "<div class = \"alert alert-block alert-warning\">\n",
    "    <b>Note</b>: Import all libraries that you plan on using in the code block below.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import random"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<div class = \"panel panel-primary\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:white\"><b>Task 1</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    Continue with the example of Ford (F) stock price from the end of Lecture 3. Assume that daily price movements of F follow a simple random walk, and that the price of F today is \\$5.\n",
    "    <ul>\n",
    "        <li>Simulate the price of F over the next year (250 trading days) for 1000 trials.</li>\n",
    "        <li>Plot the histogram of the probability distribution of F's stock price at the end of the year.</li>\n",
    "    </ul>\n",
    "    <br>Set the random seed to 5615 at the beginning of your code.\n",
    "    <br><br>Your simulation should be a list of length 1000 (i.e. 1000 trials), with each element being a list of length 251 (i.e. price at time 0 plus 250 future time steps). Your histogram should have a bell shape and centered at approximately \\$5.\n",
    "    <p style=\"text-align:right;\">[15pts]</p>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###Use code below\n",
    "random.seed(5615)\n",
    "\n",
    "starting_value = 5.\n",
    "steps = 250\n",
    "trials = 1000\n",
    "\n",
    "sims = []\n",
    "for trial in range(trials):\n",
    "    random_path = [starting_value]\n",
    "    for step in range(steps) :\n",
    "        if random.random() < .5:\n",
    "            price_change = 1 \n",
    "        else:\n",
    "            price_change = -1\n",
    "        random_path.append(random_path[-1] + price_change)\n",
    "    sims.append(random_path)\n",
    "len(sims)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "251"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sims[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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ORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ending_prices = [trial[-1] for trial in sims]\n",
    "ending_prices\n",
    "plt.hist(ending_prices)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<div class = \"panel panel-primary\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:white\"><b>Task 2</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    One problem that arises when naively modeling stock price as a random walk is that simulated prices are not guarenteed to be positive. In the case of a simple random walk, we are assuming stock prices change by an arbitrary +\\$1 or -\\$1 at each time step.\n",
    "    <br><br>Instead of assuming a price movement of +\\$1 or -\\$1, modify the random walk's possible price movement to be either +1% or -1% (equivalently, a mutiplicative factor of 1.01 or 0.99):\n",
    "    <br><br>\n",
    "    $$X_{t+1} = \\left\\{\n",
    "        \\begin{array}{ll}\n",
    "            X_t \\times 1.01 & \\quad p = 0.5 \\\\\n",
    "            X_t \\times 0.99 & \\quad p = 0.5\n",
    "        \\end{array}\n",
    "    \\right.$$\n",
    "    <ul>\n",
    "        <li>Simulate the price of F under this new dynamic over the next year (250 trading days) for 1000 trials.</li>\n",
    "        <li>Plot a histogram of the probability distribution of F's stock price at the end of the year.</li>\n",
    "        <li>Explain why making this adjustment prevents the stock price from becoming negative.</li>\n",
    "    </ul>\n",
    "    <br>Set the random seed to 5615 at the beginning of your code.\n",
    "    <br><br>Your simulation should still have the same length as the previous task, but the histogram should now be skewed to the right.\n",
    "    <p style=\"text-align:right;\">[20pts]</p>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###Use code below\n",
    "random.seed(5615)\n",
    "\n",
    "starting_value = 5.\n",
    "steps = 250\n",
    "trials = 1000\n",
    "###\n",
    "\n",
    "sims = []\n",
    "for trial in range(trials):\n",
    "    random_path = [starting_value]\n",
    "    for step in range(steps):\n",
    "        if random.random() < .5:\n",
    "            price_change = 1.01\n",
    "        else:\n",
    "            price_change = .99\n",
    "        random_path.append(random_path[-1]*price_change)\n",
    "    sims.append(random_path)\n",
    "len(sims)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ending_prices = [trial [-1] for trial in sims]\n",
    "ending_prices\n",
    "plt.hist(ending_prices)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Your written response here*\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<div class = \"panel panel-primary\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:white\"><b>Task 3</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    Another issue with our current random walk model is that the magnitude of the stock price's movement is the same regardless of the frequency of our simulation.\n",
    "    <br><br>For example, if we simulate quarterly increments, then the stock price can exhibit only 4 up or down movements of 1% within one year, whereas if we simulate in daily increments the stock price can have 250 up or down movements of 1% within one year, resulting in a much wider distribution of ending prices. This type of behavior is unreasonable.\n",
    "    <br><br>We can try to remedy this by adjusting the magnitude of the stock price movement by the \"step size\" (h) of our simulation:\n",
    "    <br><br>\n",
    "    $$X_{t+1} = \\left\\{\n",
    "        \\begin{array}{ll}\n",
    "            X_t \\times (1 + 0.01\\sqrt{h}) & \\quad p = 0.5 \\\\\n",
    "            X_t \\times (1 - 0.01\\sqrt{h}) & \\quad p = 0.5\n",
    "        \\end{array}\n",
    "    \\right.$$\n",
    "    <br>Under this new model specification, we can interpret 1% as the percentage movement in stock price over an annual period, and multiplying it by $\\sqrt{h}$ scales it for the length of time for a single period of our simulated random walk, where $h = \\frac{1}{steps}$. For example, under daily increments, $h = \\frac{1}{250}$.\n",
    "    <ul>\n",
    "        <li>Simulate the price of F under this new dynamic over the next year (250 trading days) for 1000 trials.</li>\n",
    "        <li>Plot a histogram of the probability distribution of F's stock price at the end of the year.</li>\n",
    "    </ul>\n",
    "    Set the random seed to 5615 at the beginning of your code.\n",
    "    <p style=\"text-align:right;\">[20pts]</p>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ynuZixbcdZt2dlhkmyR8CVNXfAn8KfDzJQ/Tesv1JVf0gycuBe3qfs3IJ8Kmq+sJa1bzUkjG8CvhEknPAI8Dt3bqZ/mqHccYAXMlszMPAOpaM4T56V5scA/6b3rvCWZqHZY9h2LarW/5PjRxHkl8EFoGfB55N8g56V8U8vV7mYtgY6H1T5IrOhXeoSlKD1t1pGUnSaIa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkN+j9/5aOOK66ChwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "###Use code below\n",
    "random.seed(5615)\n",
    "\n",
    "starting_value = 5.\n",
    "steps = 250\n",
    "trials = 1000\n",
    "###\n",
    "\n",
    "sims = []\n",
    "for trial in range (trials):\n",
    "    random_path = [starting_value]\n",
    "    for step in range(steps):\n",
    "        if random.random() < .5:\n",
    "            price_change = 1 + .01*np.sqrt(1/steps)\n",
    "        else:\n",
    "            price_change = 1 - .01*np.sqrt(1/steps)\n",
    "        random_path.append(random_path[-1]*price_change)\n",
    "    sims.append(random_path)\n",
    "\n",
    "\n",
    "ending_prices = [trial[-1] for trial in sims]\n",
    "ending_prices\n",
    "plt.hist(ending_prices)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sims)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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   "source": [
    "ending_prices"
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   "source": [
    "<div class = \"panel panel-primary\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:white\"><b>Task 4</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    Another issue with our current random walk model is that our assumed annual magnitude of the stock price's movement is the same 1% regardless of the risk profile of the company. For example, an annual movement of 1% might seem reasonable for F, but definitely not for TSLA stock.\n",
    "    <br><br>We can try to account for this by including the stock's annual volaility as another input parameter to our random walk simulation. Recall that the volatility is a measure of the disperson (a.k.a. standard deviation) on a stock's *continuously compounded returns*.\n",
    "    <br><br>So, we can replace our arbitrary value of 1% with a change in the stock's return in that time step in terms of its annual volatility ($\\sigma$), applied as continuously compounded factors, $u$ and $d$:\n",
    "    <br><br>\n",
    "    $$X_{t+1} = \\left\\{\n",
    "        \\begin{array}{ll}\n",
    "            X_t \\times u = X_te^{\\sigma\\sqrt{h}} & \\quad p = 0.5 \\\\\n",
    "            X_t \\times d = X_te^{-\\sigma\\sqrt{h}} & \\quad p = 0.5\n",
    "        \\end{array}\n",
    "    \\right.$$\n",
    "    <br>Assume that the annual volatility of F's returns is 10%:\n",
    "    <ul>\n",
    "        <li>Simulate the price of F under this new dynamic over the next year (250 trading days) for 1000 trials.</li>\n",
    "        <li>Calculate F's simulated annual rate of return for each of the 1000 trials. Plot this distribution of annual returns in a histogram.</li>\n",
    "        <li>Calculate F's average simulated annual rate of return.</li> \n",
    "    </ul>\n",
    "    Set the random seed to 5615 at the beginning of your code.\n",
    "    <br><br>The histogram of simulated annual returns should be bell shaped with a mean of approximately 0%.\n",
    "    <p style=\"text-align:right;\">[20pts]</p>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###Use code below\n",
    "random.seed(5615)\n",
    "\n",
    "starting_value = 5.\n",
    "sigma = .1\n",
    "\n",
    "steps = 250\n",
    "trials = 1000\n",
    "\n",
    "u = np.exp(sigma * np.sqrt(1/steps))\n",
    "d = np.exp(-sigma * np.sqrt(1/steps))\n",
    "\n",
    "sims = []\n",
    "for trial in range(trials):\n",
    "    random_path = [starting_value]\n",
    "    for step in range(steps):\n",
    "        if random.random() < .5:\n",
    "            price_change = u\n",
    "        else:\n",
    "            price_change = d\n",
    "        random_path.append(random_path[-1] * price_change)\n",
    "    sims.append(random_path)\n",
    "len(sims)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "251"
      ]
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     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sims[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "annual_return = [((trial[-1] - starting_value)/starting_value) for trial in sims]\n",
    "annual_return\n",
    "plt.hist(annual_return)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0016874375378452355"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "average = np.mean(annual_return)\n",
    "\n",
    "average"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<div class = \"panel panel-primary\">\n",
    "    <div class = \"panel-heading\"> \n",
    "    <span style=\"color:white\"><b>Task 5</b>\n",
    "    </div>\n",
    "    <div class = \"panel-body\"> \n",
    "    It is not very realistic to model 0% rates of return on stock prices. It is generally the investor's belief that stock prices will increase over time, although at what rate is unclear. For now, let's assume that the expected return on the stock is equal to the risk-free rate.\n",
    "    <br><br>We can achieve this by adjusting the probabilities associated with an up or down movement in the stock price from 50% to a varying value of $p$, such that on average we receive the risk free rate of return (I will skip over the math here, but this is the idea of risk-neutral pricing):\n",
    "    <br><br>\n",
    "    $$X_{t+1} = \\left\\{\n",
    "        \\begin{array}{ll}\n",
    "            X_t \\times u = X_te^{\\sigma\\sqrt{h}} & \\quad p = \\frac{e^{rh} - d}{u - d} \\\\\n",
    "            X_t \\times d = X_te^{-\\sigma\\sqrt{h}} & \\quad 1 - p\n",
    "        \\end{array}\n",
    "    \\right.$$ \n",
    "    <br>Notice that the value of $p$ is now set by a formula, and depends on the values of $u$ and $d$, which are just the multiplicative factors on the stock price that we defined previously.\n",
    "    <br><br>Assume that the annual volatility of F's returns is 10% and a risk-free rate of 1%:\n",
    "    <ul>\n",
    "        <li>Simulate the price of F under this new dynamic over the next year (250 trading days) for 1000 trials.</li>\n",
    "        <li>Plot a sample of 100 paths from the simulation on a single line plot. Your plot should look something like this: ![Task_5_Plot.JPG](attachment:Task_5_Plot.JPG)</li>\n",
    "        <li>Calculate the average path for F's stock price over the 1000 trials. Plot this as a line plot.</li>\n",
    "        <li>Calculate F's average simulated annual rate of return. Is it close to our assumed risk-free rate?</li>\n",
    "    </ul>\n",
    "    <br>Set the random seed to 5615 at the beginning of your code.\n",
    "    <br><br>Note that the values for $u$, $d$, and $p$ do not vary by time step. Check that they are approximately equal to 1.0063, 0.9937, and 0.5016, respectively.\n",
    "    <p style=\"text-align:right;\">[25pts]</p>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###Use code below\n",
    "random.seed(5615)\n",
    "\n",
    "starting_value = 5.\n",
    "sigma = .1\n",
    "risk_free = .01\n",
    "\n",
    "steps = 250\n",
    "trials = 1000\n",
    "\n",
    "p = (np.exp(risk_free*(1/250)) - d) /(u-d)\n",
    "u = np.exp(sigma * np.sqrt(1/steps))\n",
    "d = np.exp(-sigma*np.sqrt(1/steps))\n",
    "\n",
    "sims = []\n",
    "for trial in range(trials):\n",
    "    random_path = [starting_value]\n",
    "    for step in range(steps):\n",
    "        if random.random() < p:\n",
    "            price_change = u\n",
    "        else:\n",
    "            price_change = d\n",
    "        random_path.append(random_path[-1] * price_change)\n",
    "    sims.append(random_path)\n",
    "len(sims)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(100):\n",
    "    plt.plot(sims[i])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "average_path = []\n",
    "for step in range(steps):\n",
    "    average_price = np.mean([trial[step] for trial in sims])\n",
    "    average_path.append(average_price)\n",
    "plt.plot(average_path)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.031835840527049"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ending_price = [trial[-1] for trial in sims]\n",
    "average_price1 = np.mean(ending_price)\n",
    "average_price1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0063671681054099415"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annual_return = [((trial[-1] - starting_value)/starting_value)for trial in sims]\n",
    "average_price2 = np.mean(annual_return)\n",
    "average_price2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}