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@tomGdow
Created February 26, 2016 15:21
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h2><center>Portfolio Optimization using the Sharpe Ratio</center></h2>\n",
"<h3><center>Murtaza Nazir</center></h3>\n",
"<h3><center>The National College of Ireland</center></h3>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Introduction"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This Juputer notebook shows how a portfolio may be optimized using the Annualize Sharpe Ratio (expand) [give reference to Sharpe]. The 'proof of concept' portfolio optimized here will consist of four just stocks (['Apple', 'fill-in', fill-in', fill-in] or, abbreviated, ['AAPL', 'BRCM', 'TXN', 'ADI']). It is proposed to write programs in Python that allows the methods described here to be extended to portfolios containing up to 100 stocks. It is not possible to do this with the Python programs given below as they are too slow. Methods for optimization are discussed."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Materials and Methods"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- All the programs used here are taken from the QSTK QuantSoftware ToolKit toolkit, or are modifications and extensions of those programs that run in a Jupyter notebook environment. This open-source Python framework is specficially designed for portfolio construction and optimization (see [here](http://wiki.quantsoftware.org/index.php?title=QuantSoftware_ToolKit) for a review of the QSTK toolkit)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- As far as possible, all software used will be open-souce. An exception it that the program\n",
"[Mathematica](https://www.wolfram.com/mathematica/) (Wolfram Research) will be used to construct 3-dimensional plots as this functionality\n",
"is apparently not available in python."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Version Control. All programs and functionality developed here will be posted to github\n",
"(give link to github repo), and will be freely available"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The Jupyter notebook will be posted on-line, allowing anyone to access and interact with (but not change) the code. See [here] for a read-only version of this notebook, for example"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The programs will be developed on a Virtual Machine running Ubuntu (as this gives easy access to a Unix-like operating sytem on a 'Windows' PC )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- A brief description of the progams used to generate this notebook are as follows\n",
"\n",
"Fill these in ....\n",
" - simulate2()\n",
" - datagen()\n",
" - optimizer2()\n",
" - getdata()\n",
" - formatSimulate()\n",
" - fundstats2()\n",
" - numTradingDays()\n",
" - calcSharpe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The programs above calculate the annualized Sharpe ratio according to the following formula\n",
"\n",
" $$Annualized\\ Sharpe\\ Ratio = {\\sqrt{Number\\ Trading\\ Days}\\ \\times\\ {{Average\\ Daily\\ Return}\\over {Standard\\ Deviation}}}$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The progams are written in Python version 2.7, and run in the Jupyter notebook environment"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Preliminaries"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Load the programs"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%run optimizeProgs.py"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The code make be inspected within the environment of the current notebook by un-commenting and running the following comand (optional)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#%load optimizeProgs.py"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Portfolio Optimization"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" **1 Raw Data**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Read in the 'raw' stock prices for 2010"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"importDataAAPL = getData(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31),['AAPL'])\n",
"importDataBRCM = getData(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31),['BRCM'])\n",
"importDataTXN = getData(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31),['TXN'])\n",
"importDataADI = getData(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31),['ADI'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" Plots of the Raw Data"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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/8cgjNph8/jl89hmEh8Of/2z3qUpeHkTrWLtKqUYUsOaxxpiUynYWkdTanLQu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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd91566c2d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(importDataAAPL)\n",
"plt.plot(importDataBRCM)\n",
"plt.plot(importDataTXN)\n",
"plt.plot(importDataADI)\n",
"plt.ylabel('Price (dollars)')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.legend(['AAPL', 'BRCM', 'TXN','ADI'], loc=4)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"** 2 Normalized Data**"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"normalizeAAPL = importDataAAPL/importDataAAPL[0,:]\n",
"normalizedBRCM =importDataBRCM /importDataBRCM[0,:]\n",
"normalizedTXN = importDataTXN /importDataTXN[0,:]\n",
"normalizedADI = importDataADI /importDataADI[0,:]"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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DwsIIq8UEN41GY5noaNuFA8B774GbW/XPB+CB1Q/w1ZGvuLvr3Sy9bWnJ/oKi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\nHEIIIVSI5BBCCKHCP4oV1vatkqyuAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd915349090>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(normalizeAAPL)\n",
"plt.plot(normalizedBRCM)\n",
"plt.plot(normalizedTXN)\n",
"plt.plot(normalizedADI)\n",
"plt.ylabel('Normalized Price')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.legend(['AAPL', 'BRCM', 'TXN','ADI'], loc=2)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"** 3 Generate the Portfolio**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The portfolio will first be generated by creating a single 'portfolio' stock from the above four stocks by giving each stock an equal weighting factor. As there are four stocks, the ls_allocations or weighting factors are therefore [0.25, 0.25, 0.25, 0.25]. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The normalized daily price for the portfolio stock is generated by multiplying the daily normalized price FOR EACH INDIVIDUAL stock by 0.25, and then adding them together."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- In general, the normalized daily price for the portfolio stock will be generated by mulitiplying the normalized daily price by the weighting factor for that stock"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- The purpose the the optimization procedure outlined here is to find the weighting factors for the individual stocks that give the **highest Sharpe ratio** for the portfolio stock. Such a portfolio may be considered optimized."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"** 4 The Unoptimized Portfolio**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**(a) Plots**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"fundstats2() may be used to generate both the normalized daily price for the portfolio stock,\n",
"and the cumulative daily returns for the portfolio stock, based on an initial weighting factor of 0.25 for each stock."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"fund_stats_guess=fundStats2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0.25, 0.25, 0.25, 0.25])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's have a look at the data:"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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5VWhwEJFawBCgpapeISIdRKSTqk4Iv3iutEVrDmBB4tFHrfllwIBg6/r26QPv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\nAjw4OOecK+D/AfWBW6oUG6n+AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd9177d0910>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(fund_stats_guess[:,[0]])\n",
"\n",
"plt.legend(['Unoptimized'], loc=2)\n",
"plt.ylabel('Normalized Price of Fund')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On a Percentage Basis"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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AhwDXpCxiuazz1lvWVt+mDUybVrR/1SprM+/Xr/jzO3Swq8R+/awZp35966Bt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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd91559f190>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(fund_stats_guess[:,[1]])\n",
"\n",
"plt.legend(['Unoptimized'], loc=2)\n",
"plt.ylabel('Normalized Price of Fund (%)')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The cumulative daily returns for the unoptimized portfolio:"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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LiOj9MRz7SACvKKXWK6VGAfwMwAd825wC4DYAUEo9CqCViDqUUtuUUk+nPu8D8CKA2TGU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\nQRDUSjiWIAiCoFY+AZKiuQ5I1HUnAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd91554a4d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(fund_stats_guess[:,[2]])\n",
"\n",
"plt.legend(['Unoptimized'], loc=4)\n",
"plt.ylabel('Cumulative Daily Return')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**(b) Sharpe Ratio and Cumulative Returns**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The program simuate() may be used to calculate the Sharpe ratio and other useful statistics on the unoptimized portfolio as follows (where formatSimulate() is merely a 'wrapper' function that formats the output)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.0157864029377\n",
"Avg Daily Return: 0.00131242333752\n",
"Sharpe Ratio: 1.31712690579\n",
"Cumulative Return: 1.34724538783\n",
"ls_allocations [0.25, 0.25, 0.25, 0.25]\n"
]
}
],
"source": [
"formatSimulate(\n",
" simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0.25, 0.25, 0.25, 0.25], \n",
" initial_allocation=1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So, the unoptimized portfolio stock has a Sharpe ratio of 1.34 and a cumulative return of 1.34.\n",
"Can this be bettered? That is the subject of the next section"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"** 5 Optimize the Portfolio**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**(a) Data**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The portfolio may be optimized using the following strategy. Systematically generate sets of weighting factors and check (programatically) check to see which gives the highest Sharpe ratio by running simulate2() on each set. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The function datagen() will systematically generate the possibilities. For example:"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[[0.0, 0.0, 0.0, 1.0],\n",
" [0.0, 0.0, 0.5, 0.5],\n",
" [0.0, 0.0, 1.0, 0.0],\n",
" [0.0, 0.5, 0.0, 0.5],\n",
" [0.0, 0.5, 0.5, 0.0],\n",
" [0.0, 1.0, 0.0, 0.0],\n",
" [0.5, 0.0, 0.0, 0.5],\n",
" [0.5, 0.0, 0.5, 0.0],\n",
" [0.5, 0.5, 0.0, 0.0],\n",
" [1.0, 0.0, 0.0, 0.0]]"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datagen(5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The function optimizer() will check each possibility by calling simulate2() on each set, \n",
"and returning the set of weighting factors which produces the highest Sharpe ratio. (As currently implemented, this can be very slow)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's optimize the stock using a step size of 2 in datagen()"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(datetime.datetime(2010, 1, 1, 0, 0),\n",
" datetime.datetime(2010, 12, 31, 0, 0),\n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'],\n",
" [1.0, 0.0, 0.0, 0.0])"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"optimized_data = optimizer2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31),\n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], datagen(2),quiet = True)\n",
"optimized_data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So, in this rather trivial example of portfolio optimization, the highest Sharpe ratio will be\n",
"will be obtained by giving AAPL a weighting factor of 1 and all other stocks a weighting factor of zero"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's check that with simulate2()"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.0168315943362\n",
"Avg Daily Return: 0.0017905981418\n",
"Sharpe Ratio: 1.68542617642\n",
"Cumulative Return: 1.51234162365\n",
"ls_allocations [1, 0, 0, 0]\n"
]
}
],
"source": [
"formatSimulate(\n",
" simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [1, 0, 0, 0], \n",
" initial_allocation=1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So the optimized portfolio has a Sharpe ratio of 1.68 with a cumulative return of 1.68. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's also get the weighting factors that give the **worst** Sharpe ratio. This can be done\n",
"using a similar approach using deoptimizer()"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(datetime.datetime(2010, 1, 1, 0, 0),\n",
" datetime.datetime(2010, 12, 31, 0, 0),\n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'],\n",
" [0.0, 0.0, 0.0, 1.0])"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"deoptimized_data = deoptimizer(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31),\n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], datagen(2),quiet = True)\n",
"deoptimized_data"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.018527929613\n",
"Avg Daily Return: 0.00100496461527\n",
"Sharpe Ratio: 0.859331514553\n",
"Cumulative Return: 1.23266142808\n",
"ls_allocations [0, 0, 0, 1]\n"
]
}
],
"source": [
"formatSimulate(\n",
" simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0, 0, 0, 1], \n",
" initial_allocation=1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the 'worst-case-scenario', assigning a weighting factor of 1 to ADI and weighting\n",
"factor of zero to all other stocks gives a protfolio stock with a Sharpe ratio of 1.68 with a cumulative return of 1.23"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**(b) Plots**"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"fund_stats_optimized=fundStats2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [1, 0, 0, 0])\n",
"fund_stats_deoptimized=fundStats2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0, 0, 0, 1])"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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94osvivW91mhsRUJGAp5Onvi4+ZRZOeyP30+r+q1wqeNi9JzClUNp7IrexebIzRy9eJTO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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd9152f9490>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(fund_stats_guess[:,[0]])\n",
"plt.plot(fund_stats_optimized[:,[0]])\n",
"plt.plot(fund_stats_deoptimized[:,[0]])\n",
"plt.legend(['Guess', 'Optimized', 'Worst'], loc=2)\n",
"plt.ylabel('Normalized Price of Fund')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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E3GzczCGqyYiKAl9fzWFtKH36QMuWsHYt2Nho0VGurtCpEzz3HNx3n2bKGjQI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"text/plain": [
"<matplotlib.figure.Figure at 0x7fd9156db050>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(fund_stats_guess[:,[1]])\n",
"plt.plot(fund_stats_optimized[:,[1]])\n",
"plt.plot(fund_stats_deoptimized[:,[1]])\n",
"plt.legend(['Guess', 'Optimized', 'Worst'], loc=2)\n",
"plt.ylabel('Normalized Price of Fund (%)')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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TH3Is88n7MXJgYyz0pfuBY0lbRcIyimNxPBtXHxk1JnyPHEnu23Xz2Oe+DgqO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UXfuGT9GLnzAr1mk0xCWjNgFfWQ3dakGvTkO6w/f8xYqqoilRVhMuRqmKHi65Ta+lhUt0mXXVvz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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd9153f1c50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"plt.plot(fund_stats_guess[:,[2]])\n",
"plt.plot(fund_stats_optimized[:,[2]])\n",
"plt.plot(fund_stats_deoptimized[:,[2]])\n",
"plt.legend(['Guess', 'Optimized', 'Worst'], loc=2)\n",
"plt.ylabel('Cumulative Return (%)')\n",
"plt.xlabel('Trading Days (2010)')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Discussion"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Although the approach above is very seductive, it cannot be used in any 'real' situation as it is too slow. A typical portfolio might contain 100 stocks, for example"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- One of the ais of this thesis is to develop a method which allows the **annualized Sharpe Ratio of the portfolio** to generated quickly for any portfolio"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- How might this be done?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- As presently implemented, the algorithm for calculation the Sharpe ratio uses the data for \n",
"all trading days. Perhaps it would make little difference to the overall Sharpe ratio if only\n",
"one-tenth or one-hundred of data points were used? A function that implements this idea would be expected to be much quicker and could be used in optimizer2() instead of simulate2() (and simuate2() could still be used to calculate the annualized Sharpe ratio of the stock using the optimized weighting factors)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Is it possible to calculate the annualized Sharpe ratio of the (optimized) stock from the annualized Sharpe ratios of each individual stock? If so, a database of annualized Sharpe ratios could be created which a fund manager could then access to optimize a portfolio. This would be exptected to be\n",
"much, much quicker"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Let's calculate the annualized Sharpe ratio for each of the four stocks"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.0168315943362\n",
"Avg Daily Return: 0.0017905981418\n",
"Sharpe Ratio: 1.68542617642\n",
"Cumulative Return: 1.51234162365\n",
"ls_allocations [1, 0, 0, 0]\n"
]
}
],
"source": [
"aapl_data=(simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [1, 0, 0, 0], \n",
" initial_allocation=1))\n",
"formatSimulate(aapl_data)"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.0222327890438\n",
"Avg Daily Return: 0.0015018414268\n",
"Sharpe Ratio: 1.07020504341\n",
"Cumulative Return: 1.37077217613\n",
"ls_allocations [0, 1, 0, 0]\n"
]
}
],
"source": [
"brcm_data=(simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0, 1, 0, 0], \n",
" initial_allocation=1))\n",
"formatSimulate(brcm_data)"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.0165894191866\n",
"Avg Daily Return: 0.00110006202161\n",
"Sharpe Ratio: 1.05056481367\n",
"Cumulative Return: 1.27320632347\n",
"ls_allocations [0, 0, 1, 0]\n"
]
}
],
"source": [
"txn_data=(simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0, 0, 1, 0], \n",
" initial_allocation=1))\n",
"formatSimulate(txn_data)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"Results:\n",
"Volatility (Std Dev): 0.018527929613\n",
"Avg Daily Return: 0.00100496461527\n",
"Sharpe Ratio: 0.859331514553\n",
"Cumulative Return: 1.23266142808\n",
"ls_allocations [0, 0, 0, 1]\n"
]
}
],
"source": [
"adi_data=(simulate2(dt.datetime(2010, 1, 1), dt.datetime(2010, 12, 31), \n",
" ['AAPL', 'BRCM', 'TXN', 'ADI'], [0, 0, 0, 1], \n",
" initial_allocation=1))\n",
"formatSimulate(adi_data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we now add these together and multiply the result by by 0.25, does it give the same value as obtained above for the unoptimized Share Ratio"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"1.3472453878341921"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(aapl_data[3] + brcm_data[3] + txn_data[3] + adi_data[3])/4"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- It does! "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- This suggests that a much faster approach to portfolio optimization using the Sharpe ratio is to create a database of annualized Sharpe ratios for all major stocks that could be used by a fund manager as a 'repository of information' in portfolio optimization"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- A major theme of this thesis is to create such a database (proof-of-concept scale) and to make it publicly available"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- A second major theme is to create an Python program that allows a portfolio of up to 100 stocks to be quicly optimized with respect to the Sharpe ratio using such a database"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- A third major theme is to critically analyze the Sharpe ratio and the usefulness (if any) of a database of annualized Sharpe ratios in portfolio optimization. In short, what is the value of annualized Sharpe ratio of the portfolio **to the fund manager**, what are the advantages of being able to create it quickly for any portfolio, and what is its predictive value in portfolio creation. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- For example, the Sharpe ratio of AAPL for twelve years (2000 -2012) may be calculated as follows \n",
"and then, if the results are deposited in a database, need not be calcualted any more"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[-0.93904334765251041,\n",
" 0.97277269499193475,\n",
" -0.80979975389743264,\n",
" 1.1659624486930709,\n",
" 2.9658383823909986,\n",
" 2.3150902550685979,\n",
" 0.52024589363877627,\n",
" 2.507595011527894,\n",
" -1.1037245228671726,\n",
" 2.7114807424428973,\n",
" 1.6854261764221505,\n",
" 0.91996571936467764]"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"aapl_sharpe_twelve = []\n",
"for i in range(2000, 2012,1): \n",
" aapl_sharpe_twelve.append(\n",
" calcSharpe(dt.datetime(i, 1, 1), dt.datetime(i, 12, 31),\n",
" ['AAPL'], [1],initial_allocation=1))\n",
"aapl_sharpe_twelve "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Similarly, for BRCM"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[-0.086946180850975233,\n",
" 0.077264493616767557,\n",
" -0.78394208098393425,\n",
" 1.5312962892721236,\n",
" 0.11693536369014458,\n",
" 1.3732163056925446,\n",
" 0.23781107627444428,\n",
" -0.38842888656871399,\n",
" -0.34089730702220333,\n",
" 1.4576300692577016,\n",
" 1.0702050434120307,\n",
" -0.80329450934529167]"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"BRCM_sharpe_twelve = []\n",
"for i in range(2000, 2012,1): \n",
" BRCM_sharpe_twelve.append(\n",
" calcSharpe(dt.datetime(i, 1, 1), dt.datetime(i, 12, 31),\n",
" ['BRCM'], [1],initial_allocation=1))\n",
"BRCM_sharpe_twelve "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Concluding thoughts ...."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## References"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Insert ref to qstk\n",
"- Give Sharpe ref\n",
"- Give ref to annualized Sharpe\n",
"- Quote Marko-whoever-he-is\n",
"- Ref Jupyter"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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