{ "cells": [ { "cell_type": "markdown", "id": "dd18a44d", "metadata": {}, "source": [ "# An Epidemiological Model of Stock Investors\n", "\n", "[![econ-ark.org](https://img.shields.io/badge/Powered%20by-Econ--ARK-3e8acc.svg)](https://econ-ark.org)\n", "\n", "Source: [https://github.com/llorracc/EpiExp/blob/master/SIR_Ndlib.ipynb](https://github.com/llorracc/EpiExp/blob/master/SIR_Ndlib.ipynb)\n", "\n", "- This notebook is based on the model in [Shiller and Pound (1989)](https://www.sciencedirect.com/science/article/pii/0167268189900760) \n", "\n", "- Author: Tao Wang and Chris Carroll \n", "\n", "- Date: September, 2021\n" ] }, { "cell_type": "markdown", "id": "119e73ba", "metadata": {}, "source": [ "## Introduction\n", "\n", "This notebook uses [NDlib](https://ndlib.readthedocs.io/en/latest/#) to simulate the variant described in Carroll and Wang (2021) of the epidemiological model of expectations of [Shiller and Pound (1989)](https://www.sciencedirect.com/science/article/pii/0167268189900760).\n", "\n", "We exploit the fact that for a large population, a `random graph` of the kind that the underlying [NetworkX](https://networkx.org) library handles is a good approximation to the discrete-time SIR model, when appropriately parameterized. \n", "\n" ] }, { "cell_type": "markdown", "id": "8de9a707", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "## Model \n", "\n", "\n", "- $N$: A large population of investors, divided into three \"compartments\"\n", " 1. $I_t$: investors who have been \"infected\" with interest in a certain stock\n", " 2. $S_t$: investors who are \"susceptible\" to becoming interested in the stock\n", " 3. $R_t$: investors who have been \"infected\" may \"recover\" from the infection\n", " * interpreted as forgetting and losing interest in the stock\n", "- $\\beta$: what epidemiologists call the [`infection rate`]()\n", " * combines the consequences of `random mixing` and the disease transmission upon encounters between $I$ and $S$\n", " - of course, only the encounter of $S$ and $I$ may have real real consequences. \n", " * specifically, \n", "\n", " \\begin{equation}\n", " \\beta =\\underbrace{\\chi}_{\\text{contact rate}} \\times \\underbrace{\\tau}_{\\text{transmission probability}}\n", " \\end{equation}\n", " \n", " - $\\chi$: the number of contacts a person has per time period \n", " - $\\tau$: the probability of an encounter of an $S$ and an $I$ resulting in the transmission of the infection \n", "\n", "- $\\gamma$: recovery rate\n", " * every infected person recovers with a probability of $\\gamma$ per period" ] }, { "cell_type": "markdown", "id": "b816877c", "metadata": {}, "source": [ "Putting these together, the change in the population of infected persons is given by\n", "\n", "\\begin{equation}\n", "I_{t+1}- I_t = \\beta \\frac{S_t}{N}I_t - \\gamma I_t\n", "\\end{equation}\n", "\n", "The first term on the right hand side above captures the number of people who \"flow\" from 'compartment $S$' to 'compartment $I$', which is proportional to the infection rate $\\beta$, the fraction of people who are susceptible $\\frac{S_t}{N}$, and the number of the infected $I_t$. The second term captures the number of people who \"flow\" from $I$ to $R$ (See the flow diagram).\n", "\n", "Our treatment makes two modifications to the original model as described in Shiller and Pound (1989). First, for consistency with the software toolkit used below, we rewrite their originally continuous-time model in a discrete time form. Second, the original paper described an additional stochastic shock to the change in $I_t$ meant to capture a potential \"change in the 'source' of the infection or the nature of the contagion.\" Because that shock was not actually used for any results in the paper, we neglect it." ] }, { "cell_type": "markdown", "id": "43b17585", "metadata": {}, "source": [ "An analytical formula for the limiting size of the compartment $R$ exists under following assumptions. (See the [Wikipedia Page](https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology))\n", "\n", " - the basic reproductive ratio $\\frac{\\beta}{\\gamma}$ is strictly greater than 1\n", " - the initial fraction of the compartment $S_0/N$ is close to 1 \n", " \n", "See the Appendix for the detailed derivations. \n", "\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "221fd923", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "no display found. Using non-interactive Agg backend\n" ] } ], "source": [ "import ndlib # 'network dynamics library'\n", "import networkx as nx # built on top of networkx toolkit\n", "import matplotlib.pyplot as plt\n", "import ndlib.models.epidemics as ep\n", "import ndlib.models.ModelConfig as mc\n", "from ndlib.viz.mpl.DiffusionTrend import DiffusionTrend\n", "from ndlib.viz.mpl.DiffusionPrevalence import DiffusionPrevalence\n", "from ndlib.viz.bokeh.MultiPlot import MultiPlot\n", "%matplotlib inline\n", "from SIR import SIR, solve_r_ss\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "id": "536caae6", "metadata": { "code_folding": [] }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## plot the model \n", "\n", "model = nx.DiGraph()\n", "model.add_edges_from([(\"S\", \"I\"), (\"I\", \"R\")])\n", "plt.figure(figsize=(12, 3))\n", "pos = {'S':(0, 0.0), 'I':(10, 0.0), 'R':(20, 0.0)}\n", "nx.draw_networkx(model, \n", " pos = pos,\n", " arrows=True,\n", " node_size = 4000,\n", " node_shape ='s',\n", " node_color= 'gainsboro',\n", " alpha = 0.5,\n", " font_weight = 40,\n", " font_size = 35,\n", " arrowsize = 30,\n", " arrowstyle = 'fancy',\n", " )\n", "nx.draw_networkx_edge_labels(model,\n", " pos,\n", " edge_labels={('S','I'):r'$\\beta \\frac{S_t}{N}I_t$ ',\\\n", " ('I','R'):r'$\\gamma I_t$'},\n", " font_color='black',\n", " font_size = 35)\n", "\n", "# See if you can add a bit of space between the equations and the boxes\n", "# Add time subscripts in the flow diagram\n", "\n", "plt.savefig(\"./draft/chapter/figures/flow_diagram.png\",format=\"PNG\")" ] }, { "cell_type": "markdown", "id": "47a38731", "metadata": {}, "source": [ "To illustrate the model’s implications under such a setting, we parameterize the model with four such combinations of parameter values taken from Shiller and Pound (1989), characterizing two different kinds of investors and two categories of stocks. \n", " - 'INSRAND': instutional investors for a randomly selected stock\n", " - 'INSRPI': instutional investors for a rapidly rising stock\n", " - 'INDRAND': individual investors for a randomly selected stock \n", " - 'INDRPI': individual investors for a rapidly rising stock" ] }, { "cell_type": "markdown", "id": "914d033b", "metadata": {}, "source": [ "We convert all the continuous-time rates into discrete-time and from annual to weekly frequency. For instance, the recovery rate estimated from the decaying pattern of the time spent on studying a given stock for INSRPI is $g=1.39$ (a half-life of $ln(2)/g=0.50$ years). In discrete-time and at weekly frequency, this is equivalent to a probability of recovery $\\gamma = 1-\\exp^{-g/52} =0.02$. For the infection rate, under the assumption made by the paper that the fraction of susceptible is close to $1$ despite being time-varying, the estimated median infection rate of INSRPI is $b = 2.02$. It is converted to a weekly probability of $\\beta = 1-\\exp^{-b/52}=0.038$. We set the initial fraction of the infected to be $1$ percent." ] }, { "cell_type": "code", "execution_count": 3, "id": "133c220b", "metadata": {}, "outputs": [], "source": [ "## a function that converts continuous rate to discrete-time weekly rates\n", "\n", "def ct2dtw(rate):\n", " return 1-np.exp(-rate/52)" ] }, { "cell_type": "code", "execution_count": 4, "id": "0d717112", "metadata": {}, "outputs": [], "source": [ "## Shiller and Pound estimates \n", "types = ['INSRAND','INSRPI','INDRAND','INDRPI']\n", "gamma_continuous_ests = [1.84,1.39,3.72,1.73] ## directly take from the paper (page 58)\n", "beta_continuous_ests = [20.66,7.35,12.74,3.71] ## directly take from the paper (page 58)\n", "beta_sir_list = [round(ct2dtw(beta),2) for beta in beta_continuous_ests]\n", "gamma_list = [round(ct2dtw(gamma),2) for gamma in gamma_continuous_ests]" ] }, { "cell_type": "markdown", "id": "3a2e73f0", "metadata": {}, "source": [ "### Simulating the SIR model using NDlib \n", "\n", "The toolkit we are using, NDlib, implements a SIR model residing on a given simulated network from another scientific library NetworkX. \n", "\n", "Note that the network-based SIR model does not take the infection rate $\\beta$, as a catch-all parameter. Instead, it let the users configure the transmission probability $\\tau$ (what the program calls $\\beta$, which is not the $\\beta$ defined above), and the network structure that affects the contact rates $\\chi$, separately. In an N-sized random graph a la Erdos and Renyi (1960) with a connection probability $p$, we have the following relationship \n", "\n", "\\begin{equation}\n", "\\chi = \\underbrace{(N-1)p}_{\\text{average degree}}. \n", "\\end{equation}\n", "\n", "Hence, we can use the following equation to compute the underlying transmission probability $\\tau$ corresponding to the $\\beta$ in a random graph parameterized by $N$ and $p$. \n", "\n", "\\begin{equation}\n", " \\tau = \\frac{\\beta}{\\chi} = \\frac{\\beta}{(N-1)p}\n", "\\end{equation}\n", "\n", "Therefore, we write the following function to compute the value of $\\tau$ corresponding to a value of $\\beta$ we intend to use, depending on the contact rate $\\chi$." ] }, { "cell_type": "code", "execution_count": 5, "id": "e662478f", "metadata": { "code_folding": [ 4 ] }, "outputs": [], "source": [ "## beta in NDlib is not really beta in standard SIR\n", "## the infection probability tau = beta in SIR / χ, where χ is the number of contacts \n", "## χ = = average degree of a random graph = (N-1) x p \n", "\n", "def beta2tau(beta_sir,\n", " χ):\n", " return beta_sir/χ" ] }, { "cell_type": "markdown", "id": "082adb87", "metadata": {}, "source": [ "### Make a random graph " ] }, { "cell_type": "code", "execution_count": 6, "id": "a50f4f78", "metadata": {}, "outputs": [], "source": [ "## create the population residing at a random graph\n", "\n", "random_prb = 0.1\n", "population = 8000\n", "degree = random_prb*(population-1)\n", "χ = degree ## number of contacts per period per person is the degree in a random graph \n", "\n", "## get the corresponding τ values for the weekly infection rate β\n", "τ_list = [beta2tau(beta_sir,χ) for beta_sir in beta_sir_list]\n", "\n", "random_mix = nx.erdos_renyi_graph(population,random_prb) # agents are randomly connected " ] }, { "cell_type": "code", "execution_count": 7, "id": "c31222e4", "metadata": {}, "outputs": [], "source": [ "# SIR model to simulate the spread of economic opinions\n", "sir = ep.SIRModel(random_mix)" ] }, { "cell_type": "code", "execution_count": 8, "id": "e75cbeea", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Susceptible': 0, 'Infected': 1, 'Removed': 2}" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sir.available_statuses" ] }, { "cell_type": "code", "execution_count": 9, "id": "48e390ae", "metadata": { "code_folding": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|█████████████████████████████████████████| 208/208 [00:25<00:00, 8.22it/s]\n", "100%|█████████████████████████████████████████| 208/208 [00:35<00:00, 5.81it/s]\n", "100%|█████████████████████████████████████████| 208/208 [00:18<00:00, 11.29it/s]\n", "100%|█████████████████████████████████████████| 208/208 [00:42<00:00, 4.94it/s]\n" ] } ], "source": [ "## simulation periods \n", "iters = 208\n", "\n", "## prepare the simulation\n", "trends_list =[]\n", "\n", "## simulation \n", "\n", "nb = len(types)\n", "\n", "for x in range(nb):\n", " sir = ep.SIRModel(random_mix)\n", " cfg_sir = mc.Configuration()\n", " cfg_sir.add_model_parameter('beta', τ_list[x]) # transmission probability = infection rate/nb of contacts \n", " cfg_sir.add_model_parameter('gamma', gamma_list[x]) # removal rate\n", " cfg_sir.add_model_parameter(\"fraction_infected\", 0.01)\n", " sir.set_initial_status(cfg_sir)\n", " \n", " ## simulate the sir model for a particular configuration \n", " iterations = sir.iteration_bunch(iters, node_status=True)\n", " trends_sir = sir.build_trends(iterations)\n", " trends_list.append(trends_sir)\n" ] }, { "cell_type": "markdown", "id": "6a057ff8", "metadata": {}, "source": [ "### Simulation results " ] }, { "cell_type": "code", "execution_count": 10, "id": "b1abf156", "metadata": { "code_folding": [ 0 ] }, "outputs": [], "source": [ "## some parameters to testing \n", "beta = 0.1\n", "gamma = 0.03\n", "i0 = 0.01\n", "s0 = 1-i0\n", "r0 = 0.0 \n", "x0 = (s0,i0,r0)\n", "T = iters\n", "times = range(T)" ] }, { "cell_type": "code", "execution_count": 11, "id": "bb72428c", "metadata": { "code_folding": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## compare the paths from Ndlib and SIR \n", "\n", "lw = 5\n", "lbsize = 15\n", "\n", "## plot\n", "fig, axs = plt.subplots(4,1, \n", " figsize=(13, 22), \n", " facecolor='w', \n", " edgecolor='k')\n", "fig.subplots_adjust(hspace = 0.3, wspace=.1)\n", "\n", "axs = axs.ravel()\n", "nb = len(types)\n", "\n", "nbw1y = 52\n", "\n", "for x in range(nb):\n", " beta = beta_sir_list[x]\n", " gamma = gamma_list[x]\n", " s,i,r = SIR(beta, # infection rate\n", " gamma, # recovery rate \n", " T,\n", " x0)\n", " title = types[x]+': '+r'$\\beta={}$'.format(round(beta,2))+','+r'$\\gamma ={}$'.format(round(gamma,2))\n", " axs[x].set_title(title,\n", " fontsize=lbsize+5)\n", " \n", " r_ss = solve_r_ss(beta,gamma)\n", " axs[x].hlines(r_ss,\n", " 0.0,\n", " T,\n", " color='r',\n", " linestyle ='solid',\n", " lw = 1,\n", " label=r'$R_{+\\infty}$')\n", "\n", " ### generated from NDlib\n", " s_nd = np.array(trends_list[x][0]['trends']['node_count'][0])/population\n", " i_nd = np.array(trends_list[x][0]['trends']['node_count'][1])/population\n", " r_nd = np.array(trends_list[x][0]['trends']['node_count'][2])/population\n", " axs[x].plot(times,s_nd,\n", " '--',\n", " lw=lw,\n", " label=r'$S_t$')\n", " axs[x].plot(times,i_nd,\n", " '-.',\n", " lw=lw,\n", " label=r'$I_t$ ')\n", " axs[x].plot(times,r_nd,\n", " '-',\n", " lw=lw,\n", " label=r'$R_t$ ')\n", " \n", " ### generated from SIR\n", " #axs[x].plot(times,s,'-',lw=lw,label='S')\n", " #axs[x].plot(times,i,'--',lw=lw,label='I')\n", " #axs[x].plot(times,r,'-.',lw=lw,label='R')\n", " \n", " axs[x].set_xlim(0.0,T)\n", " axs[0].legend(loc=0,\n", " prop={'size': 22})\n", " axs[x].tick_params(axis='x', labelsize=lbsize)\n", " axs[x].tick_params(axis='y', labelsize=lbsize)\n", "\n", "plt.savefig(\"./draft/chapter/figures/sir_simulate.png\",format=\"PNG\")" ] }, { "cell_type": "markdown", "id": "51082468", "metadata": {}, "source": [ "### Appendix. The limiting size \n", "\n", "An analytical formula for the limiting size of the compartment $R$ exists under following assumptions. (See the [Wikipedia Page](https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology))\n", "\n", " - the basic reproductive ratio $\\frac{\\beta}{\\gamma}$ is strictly greater than 1\n", " - the initial fraction of the compartment $S_0/N$ is close to 1 \n", "\n", "To obtain the result, we use lower case letter $s_t$, $i_t$, and $r_t$ to represent the fractions of each compartment.\n", "\n", "\\begin{equation}\n", "\\begin{split}\n", "& s_{t+1} - s_{t} = - \\beta s_t i_t \\\\\n", "& i_{t+1}- i_{t} = \\beta s_t i_t - \\gamma i_t \\\\\n", "& r_{t+1} - r_t = \\gamma i_t \n", "\\end{split}\n", "\\end{equation}\n", "\n", "Divide the first equation above by $s_t$ into both sides and further rearrange it. \n", "\n", "\\begin{equation}\n", "\\begin{split}\n", "&\\Delta ln(s_{t+1}) \\equiv \\frac{s_{t+1} - s_{t}}{s_t} = - \\beta i_t \\\\ \n", "& \\rightarrow i_t = -\\frac{\\Delta ln(s_{t+1})}{\\beta}\n", "\\end{split}\n", "\\end{equation}\n", "\n", "Plug it in the third equation above, we get \n", "\n", "\\begin{equation}\n", "\\begin{split}\n", "&r_{t+1}- r_t = - \\frac{\\gamma}{\\beta} (ln(s_{t+1})-ln(s_{t})) \\\\ \n", "\\end{split}\n", "\\end{equation}\n", "\n", "The equation above holds for any choice of $t$ and $t+\\Delta t$, hence we have \n", "\n", "\\begin{equation}\n", "\\begin{split}\n", "&r_{t+\\Delta t}- r_t = - \\frac{\\gamma}{\\beta} (ln(s_{t+\\Delta t})-ln(s_{t})) \\\\ \n", "\\end{split}\n", "\\end{equation}\n", "\n", "Assuming the initial size of $i_0$ to be infinitely small, hence, $s_0=1$. Plug these $t=0$ values $s_0=1$ and $r_0 =0$, we obtain \n", "\n", "\\begin{equation}\n", "\\begin{split}\n", "&r_{\\Delta t} = \\frac{\\gamma}{\\beta} ln(s_{\\Delta t}) \\\\ \n", "\\end{split}\n", "\\end{equation}\n", "\n", "Taking the limit of the $\\Delta t$ to $+ \\infty$, and using the fact that in long run the fraction of the infection $i_{+\\infty}=0$, and $1+s_{+\\infty}=r_{+\\infty}$, we arrive at the folowing equation. \n", "\n", "\\begin{equation}\n", "\\begin{split}\n", "&r_{+\\infty} = - \\frac{\\gamma}{\\beta} ln(1-r_{+\\infty}) \\\\ \n", "&\\leftrightarrow e^{-\\frac{\\beta}{\\gamma} r_{+\\infty}} = 1-r_{+\\infty}\n", "\\end{split}\n", "\\end{equation}\n", "\n", "$r_{+\\infty}$ and $s_{+\\infty}$ can be solved. \n", "\n", "Notice that the limiting size does not depend on the specific values of $\\beta$ and $\\gamma$ but its ratio. \n" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "ExecuteTime,-autoscroll,collapsed", "notebook_metadata_filter": "all,-widgets,-varInspector" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "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" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false } }, "nbformat": 4, "nbformat_minor": 5 }