560 lines
81 KiB
Plaintext
560 lines
81 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Load Packages"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"printyellow (generic function with 1 method)"
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"using Printf, Dates, Statistics, CSV, DataFrames\n",
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"include(\"jlFiles/printmat.jl\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Loading Some Data with CSV.jl"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The first 4 lines of Data/Options_prices_US_Canada.csv:\n",
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"\n",
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"symbol,exchange,date,adjusted close,option symbol,expiration,strike,call/put,style,ask,bid,volume,open interest,unadjusted\n",
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"SPX,CBOE,03/30/17,2368.06,SPXW 170331C00300000,03/31/17,300,C,E,2073.9,2062.9,0,0,2368.927\n",
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"SPX,CBOE,03/30/17,2368.06,SPXW 170331P00300000,03/31/17,300,P,E,0.1,0,0,0,2368.927\n",
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"SPX,CBOE,03/30/17,2368.06,SPXW 170331C00400000,03/31/17,400,C,E,1974.1,1962.7,0,0,2368.927\n",
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"\n"
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]
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}
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],
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"source": [
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"DataFile = \"Data/Options_prices_US_Canada.csv\"\n",
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"\n",
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"println(\"The first 4 lines of $(DataFile):\\n\")\n",
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"txt = readlines(DataFile)\n",
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"printmat(txt[1:4])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Use `normalizenames` to get names that can be used in Julia as variables names and specify the `dateformat` used in the csv file (to convert to proper Julia dates). The dates in the file are given as `03/30/17` which CSV/DataFrames interpret as 30 March year 17 (AD). We add `Dates.Year(2000)` to get year 2017."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[1m13952×10 DataFrame\u001b[0m\n",
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"\u001b[1m Row \u001b[0m│\u001b[1m symbol \u001b[0m\u001b[1m date \u001b[0m\u001b[1m close \u001b[0m\u001b[1m expiration \u001b[0m\u001b[1m strike \u001b[0m\u001b[1m call_put \u001b[0m\u001b[1m ask \u001b[0m\u001b[1m\u001b[0m ⋯\n",
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"\u001b[1m \u001b[0m│\u001b[90m String3 \u001b[0m\u001b[90m Date \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Date \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m String1 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m\u001b[0m ⋯\n",
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"───────┼────────────────────────────────────────────────────────────────────────\n",
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" 1 │ SPX 2017-03-30 2368.06 2017-03-31 300.0 C 2073.9 ⋯\n",
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" 2 │ SPX 2017-03-30 2368.06 2017-03-31 300.0 P 0.1\n",
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" 3 │ SPX 2017-03-30 2368.06 2017-03-31 400.0 C 1974.1\n",
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" 4 │ SPX 2017-03-30 2368.06 2017-03-31 400.0 P 0.05\n",
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" 5 │ SPX 2017-03-30 2368.06 2017-03-31 500.0 C 1874.1 ⋯\n",
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" 6 │ SPX 2017-03-30 2368.06 2017-03-31 500.0 P 0.05\n",
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" 7 │ SPX 2017-03-30 2368.06 2017-03-31 600.0 C 1774.1\n",
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" 8 │ SPX 2017-03-30 2368.06 2017-03-31 600.0 P 0.05\n",
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" 9 │ SPX 2017-03-30 2368.06 2017-03-31 700.0 C 1673.9 ⋯\n",
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" 10 │ SPX 2017-03-30 2368.06 2017-03-31 700.0 P 0.05\n",
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" 11 │ SPX 2017-03-30 2368.06 2017-03-31 750.0 C 1624.1\n",
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" ⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱\n",
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" 13943 │ XIU 2017-03-30 23.06 2019-03-15 21.0 C 3.21\n",
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" 13944 │ XIU 2017-03-30 23.06 2019-03-15 21.0 P 1.71 ⋯\n",
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" 13945 │ XIU 2017-03-30 23.06 2019-03-15 22.0 C 2.53\n",
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" 13946 │ XIU 2017-03-30 23.06 2019-03-15 22.0 P 2.03\n",
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" 13947 │ XIU 2017-03-30 23.06 2019-03-15 23.0 C 1.97\n",
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" 13948 │ XIU 2017-03-30 23.06 2019-03-15 23.0 P 2.51 ⋯\n",
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" 13949 │ XIU 2017-03-30 23.06 2019-03-15 24.0 C 1.5\n",
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" 13950 │ XIU 2017-03-30 23.06 2019-03-15 24.0 P 3.12\n",
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" 13951 │ XIU 2017-03-30 23.06 2019-03-15 25.0 C 1.13\n",
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" 13952 │ XIU 2017-03-30 23.06 2019-03-15 25.0 P 3.64 ⋯\n",
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"\u001b[36m 3 columns and 13931 rows omitted\u001b[0m"
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]
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}
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],
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"source": [
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"df1 = CSV.read(DataFile,DataFrame,normalizenames=true,dateformat=\"mm/dd/yy\")\n",
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"\n",
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"df1.date .+= Dates.Year(2000) #03/30/17 to 03/30/2017\n",
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"df1.expiration .+= Dates.Year(2000)\n",
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"\n",
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"select!(df1,Not([:exchange,:option_symbol,:style,:unadjusted])) #deleting some columns\n",
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"rename!(df1,:adjusted_close => :close) #renaming a column\n",
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"\n",
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"show(df1)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Task 1\n",
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"\n",
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"Create a new DataFrame that contains only the data for SPX and those option contracts that were traded (volume > 0). Hint: `df1[vv, :]` picks out the rows of the data frame for which `vv` is `true`. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[1m2359×10 DataFrame\u001b[0m\n",
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"\u001b[1m Row \u001b[0m│\u001b[1m symbol \u001b[0m\u001b[1m date \u001b[0m\u001b[1m close \u001b[0m\u001b[1m expiration \u001b[0m\u001b[1m strike \u001b[0m\u001b[1m call_put \u001b[0m\u001b[1m ask \u001b[0m\u001b[1m \u001b[0m ⋯\n",
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"\u001b[1m \u001b[0m│\u001b[90m String3 \u001b[0m\u001b[90m Date \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Date \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m String1 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m \u001b[0m ⋯\n",
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"──────┼─────────────────────────────────────────────────────────────────────────\n",
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" 1 │ SPX 2017-03-30 2368.06 2017-03-31 1600.0 C 774.0 ⋯\n",
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" 2 │ SPX 2017-03-30 2368.06 2017-03-31 1600.0 P 0.05\n",
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" 3 │ SPX 2017-03-30 2368.06 2017-03-31 2040.0 P 0.05\n",
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" 4 │ SPX 2017-03-30 2368.06 2017-03-31 2050.0 P 0.05\n",
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" 5 │ SPX 2017-03-30 2368.06 2017-03-31 2100.0 P 0.05 ⋯\n",
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" 6 │ SPX 2017-03-30 2368.06 2017-03-31 2110.0 C 264.5\n",
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" 7 │ SPX 2017-03-30 2368.06 2017-03-31 2120.0 P 0.05\n",
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" 8 │ SPX 2017-03-30 2368.06 2017-03-31 2150.0 P 0.05\n",
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" 9 │ SPX 2017-03-30 2368.06 2017-03-31 2175.0 C 199.5 ⋯\n",
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" 10 │ SPX 2017-03-30 2368.06 2017-03-31 2175.0 P 0.05\n",
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" 11 │ SPX 2017-03-30 2368.06 2017-03-31 2180.0 C 194.5\n",
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" ⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱\n",
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" 2350 │ SPX 2017-03-30 2368.06 2019-12-20 1900.0 P 111.4\n",
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" 2351 │ SPX 2017-03-30 2368.06 2019-12-20 2000.0 P 136.0 ⋯\n",
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" 2352 │ SPX 2017-03-30 2368.06 2019-12-20 2200.0 C 345.7\n",
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" 2353 │ SPX 2017-03-30 2368.06 2019-12-20 2300.0 C 287.0\n",
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" 2354 │ SPX 2017-03-30 2368.06 2019-12-20 2350.0 C 259.7\n",
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" 2355 │ SPX 2017-03-30 2368.06 2019-12-20 2375.0 P 264.3 ⋯\n",
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" 2356 │ SPX 2017-03-30 2368.06 2019-12-20 2400.0 C 230.7\n",
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" 2357 │ SPX 2017-03-30 2368.06 2019-12-20 2400.0 P 275.3\n",
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" 2358 │ SPX 2017-03-30 2368.06 2019-12-20 2800.0 C 74.9\n",
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" 2359 │ SPX 2017-03-30 2368.06 2019-12-20 3000.0 C 37.5 ⋯\n",
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"\u001b[36m 3 columns and 2338 rows omitted\u001b[0m"
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]
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}
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],
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"source": [
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"vv = (df1.symbol .== \"SPX\") .& (df1.volume .> 0) #rows with SPX, and trade\n",
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"\n",
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"df2 = df1[vv, :] #create new df, only some rows\n",
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"\n",
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"show(df2)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Task 2\n",
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"\n",
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"Create a *group* for each expiration date. These groups can be referred to as `dataG2[key]`.\n",
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"\n",
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"Hints: `groupby()`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"dataG2 = groupby(df2,:expiration); #grouped by expiration date"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Task 3\n",
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"\n",
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"Print the number of contracts (`nrow`) and the sum of the open interest `:open_interest=>sum` for each of the expiration dates.\n",
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"\n",
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"Hint: `combine()`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div class=\"data-frame\"><p>34 rows × 3 columns</p><table class=\"data-frame\"><thead><tr><th></th><th>expiration</th><th>nrow</th><th>open_interest_sum</th></tr><tr><th></th><th title=\"Date\">Date</th><th title=\"Int64\">Int64</th><th title=\"Int64\">Int64</th></tr></thead><tbody><tr><th>1</th><td>2017-03-31</td><td>100</td><td>1010183</td></tr><tr><th>2</th><td>2017-04-03</td><td>94</td><td>109345</td></tr><tr><th>3</th><td>2017-04-05</td><td>84</td><td>102022</td></tr><tr><th>4</th><td>2017-04-07</td><td>140</td><td>467105</td></tr><tr><th>5</th><td>2017-04-10</td><td>73</td><td>51755</td></tr><tr><th>6</th><td>2017-04-12</td><td>67</td><td>56228</td></tr><tr><th>7</th><td>2017-04-13</td><td>109</td><td>303944</td></tr><tr><th>8</th><td>2017-04-17</td><td>70</td><td>40855</td></tr><tr><th>9</th><td>2017-04-19</td><td>57</td><td>25690</td></tr><tr><th>10</th><td>2017-04-21</td><td>166</td><td>1775684</td></tr><tr><th>11</th><td>2017-04-24</td><td>69</td><td>15085</td></tr><tr><th>12</th><td>2017-04-26</td><td>56</td><td>6560</td></tr><tr><th>13</th><td>2017-04-28</td><td>124</td><td>467161</td></tr><tr><th>14</th><td>2017-05-05</td><td>129</td><td>169530</td></tr><tr><th>15</th><td>2017-05-12</td><td>121</td><td>225600</td></tr><tr><th>16</th><td>2017-05-19</td><td>158</td><td>937452</td></tr><tr><th>17</th><td>2017-05-26</td><td>95</td><td>12914</td></tr><tr><th>18</th><td>2017-05-31</td><td>105</td><td>120944</td></tr><tr><th>19</th><td>2017-06-02</td><td>34</td><td>0</td></tr><tr><th>20</th><td>2017-06-16</td><td>126</td><td>1956193</td></tr><tr><th>21</th><td>2017-06-30</td><td>72</td><td>136661</td></tr><tr><th>22</th><td>2017-07-21</td><td>39</td><td>51058</td></tr><tr><th>23</th><td>2017-07-31</td><td>27</td><td>56511</td></tr><tr><th>24</th><td>2017-08-31</td><td>14</td><td>15578</td></tr><tr><th>25</th><td>2017-09-15</td><td>45</td><td>524556</td></tr><tr><th>26</th><td>2017-09-29</td><td>17</td><td>45842</td></tr><tr><th>27</th><td>2017-12-15</td><td>46</td><td>759858</td></tr><tr><th>28</th><td>2017-12-29</td><td>22</td><td>35398</td></tr><tr><th>29</th><td>2018-01-19</td><td>18</td><td>78967</td></tr><tr><th>30</th><td>2018-03-16</td><td>16</td><td>15051</td></tr><tr><th>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td></tr></tbody></table></div>"
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],
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"text/latex": [
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"\\begin{tabular}{r|ccc}\n",
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"\t& expiration & nrow & open\\_interest\\_sum\\\\\n",
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"\t\\hline\n",
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"\t& Date & Int64 & Int64\\\\\n",
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"\t\\hline\n",
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"\t1 & 2017-03-31 & 100 & 1010183 \\\\\n",
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"\t2 & 2017-04-03 & 94 & 109345 \\\\\n",
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"\t3 & 2017-04-05 & 84 & 102022 \\\\\n",
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"\t4 & 2017-04-07 & 140 & 467105 \\\\\n",
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"\t5 & 2017-04-10 & 73 & 51755 \\\\\n",
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|
|
"\t6 & 2017-04-12 & 67 & 56228 \\\\\n",
|
|||
|
|
"\t7 & 2017-04-13 & 109 & 303944 \\\\\n",
|
|||
|
|
"\t8 & 2017-04-17 & 70 & 40855 \\\\\n",
|
|||
|
|
"\t9 & 2017-04-19 & 57 & 25690 \\\\\n",
|
|||
|
|
"\t10 & 2017-04-21 & 166 & 1775684 \\\\\n",
|
|||
|
|
"\t11 & 2017-04-24 & 69 & 15085 \\\\\n",
|
|||
|
|
"\t12 & 2017-04-26 & 56 & 6560 \\\\\n",
|
|||
|
|
"\t13 & 2017-04-28 & 124 & 467161 \\\\\n",
|
|||
|
|
"\t14 & 2017-05-05 & 129 & 169530 \\\\\n",
|
|||
|
|
"\t15 & 2017-05-12 & 121 & 225600 \\\\\n",
|
|||
|
|
"\t16 & 2017-05-19 & 158 & 937452 \\\\\n",
|
|||
|
|
"\t17 & 2017-05-26 & 95 & 12914 \\\\\n",
|
|||
|
|
"\t18 & 2017-05-31 & 105 & 120944 \\\\\n",
|
|||
|
|
"\t19 & 2017-06-02 & 34 & 0 \\\\\n",
|
|||
|
|
"\t20 & 2017-06-16 & 126 & 1956193 \\\\\n",
|
|||
|
|
"\t21 & 2017-06-30 & 72 & 136661 \\\\\n",
|
|||
|
|
"\t22 & 2017-07-21 & 39 & 51058 \\\\\n",
|
|||
|
|
"\t23 & 2017-07-31 & 27 & 56511 \\\\\n",
|
|||
|
|
"\t24 & 2017-08-31 & 14 & 15578 \\\\\n",
|
|||
|
|
"\t25 & 2017-09-15 & 45 & 524556 \\\\\n",
|
|||
|
|
"\t26 & 2017-09-29 & 17 & 45842 \\\\\n",
|
|||
|
|
"\t27 & 2017-12-15 & 46 & 759858 \\\\\n",
|
|||
|
|
"\t28 & 2017-12-29 & 22 & 35398 \\\\\n",
|
|||
|
|
"\t29 & 2018-01-19 & 18 & 78967 \\\\\n",
|
|||
|
|
"\t30 & 2018-03-16 & 16 & 15051 \\\\\n",
|
|||
|
|
"\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
|
|||
|
|
"\\end{tabular}\n"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"\u001b[1m34×3 DataFrame\u001b[0m\n",
|
|||
|
|
"\u001b[1m Row \u001b[0m│\u001b[1m expiration \u001b[0m\u001b[1m nrow \u001b[0m\u001b[1m open_interest_sum \u001b[0m\n",
|
|||
|
|
"\u001b[1m \u001b[0m│\u001b[90m Date \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Int64 \u001b[0m\n",
|
|||
|
|
"─────┼──────────────────────────────────────\n",
|
|||
|
|
" 1 │ 2017-03-31 100 1010183\n",
|
|||
|
|
" 2 │ 2017-04-03 94 109345\n",
|
|||
|
|
" 3 │ 2017-04-05 84 102022\n",
|
|||
|
|
" 4 │ 2017-04-07 140 467105\n",
|
|||
|
|
" 5 │ 2017-04-10 73 51755\n",
|
|||
|
|
" 6 │ 2017-04-12 67 56228\n",
|
|||
|
|
" 7 │ 2017-04-13 109 303944\n",
|
|||
|
|
" 8 │ 2017-04-17 70 40855\n",
|
|||
|
|
" 9 │ 2017-04-19 57 25690\n",
|
|||
|
|
" 10 │ 2017-04-21 166 1775684\n",
|
|||
|
|
" 11 │ 2017-04-24 69 15085\n",
|
|||
|
|
" ⋮ │ ⋮ ⋮ ⋮\n",
|
|||
|
|
" 25 │ 2017-09-15 45 524556\n",
|
|||
|
|
" 26 │ 2017-09-29 17 45842\n",
|
|||
|
|
" 27 │ 2017-12-15 46 759858\n",
|
|||
|
|
" 28 │ 2017-12-29 22 35398\n",
|
|||
|
|
" 29 │ 2018-01-19 18 78967\n",
|
|||
|
|
" 30 │ 2018-03-16 16 15051\n",
|
|||
|
|
" 31 │ 2018-03-29 9 153\n",
|
|||
|
|
" 32 │ 2018-06-15 17 69132\n",
|
|||
|
|
" 33 │ 2018-12-21 27 179774\n",
|
|||
|
|
" 34 │ 2019-12-20 13 9213\n",
|
|||
|
|
"\u001b[36m 13 rows omitted\u001b[0m"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 6,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"combine(dataG2,nrow,:open_interest=>sum) #same information as above, uncomment to se"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"# Task 4 \n",
|
|||
|
|
"Creating two new DataFrames: for expiration date 2017-04-21 and another for 2017-06-16.\n",
|
|||
|
|
"\n",
|
|||
|
|
"Hint: `dataG2[(expiration = Date(\"2017-04-21\"),)]`"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 7,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"\n"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"#creating two new DataFrames: for two different expiration days\n",
|
|||
|
|
"\n",
|
|||
|
|
"df_20170421 = dataG2[(expiration = Date(\"2017-04-21\"),)]\n",
|
|||
|
|
"df_20170616 = dataG2[(expiration = Date(\"2017-06-16\"),)]\n",
|
|||
|
|
"\n",
|
|||
|
|
"println()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"# Task 5\n",
|
|||
|
|
"\n",
|
|||
|
|
"For the expiration date 2017-04-21, calculate the mid price as the average of the `.ask` and `.bid`. \n",
|
|||
|
|
"\n",
|
|||
|
|
"Plot the mid price as a function of the strike price `.strike` for put options. Add a curve another curve for the call options."
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 8,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"using Plots #this loads the Plots package\n",
|
|||
|
|
"\n",
|
|||
|
|
"#pyplot(size=(600,400)) #choice of plotting backend\n",
|
|||
|
|
"gr(size=(480,320))\n",
|
|||
|
|
"default(fmt = :svg) "
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 9,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
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|
|
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
|
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],
|
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"source": [
|
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|
|
"vv_P = df_20170421.call_put .== \"P\" #put options\n",
|
|||
|
|
"vv_C = df_20170421.call_put .== \"C\" #call options\n",
|
|||
|
|
"\n",
|
|||
|
|
"midPrice = (df_20170421.ask + df_20170421.bid)/2 #creates a traditional vector\n",
|
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|
|
"\n",
|
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|
|
"p1 = plot( df_20170421.strike[vv_P],midPrice[vv_P],label=\"puts\",\n",
|
|||
|
|
" linecolor = :red,\n",
|
|||
|
|
" linestyle = :solid,\n",
|
|||
|
|
" linewidth = 1,\n",
|
|||
|
|
" title = \"Option prices $(df_20170421.date[1])\",\n",
|
|||
|
|
" xlabel = \"strike prices\" )\n",
|
|||
|
|
"plot!( df_20170421.strike[vv_C],midPrice[vv_C],label=\"calls\",\n",
|
|||
|
|
" linecolor = :blue,\n",
|
|||
|
|
" linestyle = :dot,\n",
|
|||
|
|
" linewidth = 2 )\n",
|
|||
|
|
"vline!([df_20170421.close[1]],linecolor=:black,line=(:dash,2),label=\"SPX level\")\n",
|
|||
|
|
"display(p1)"
|
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|
|
]
|
|||
|
|
},
|
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|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
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|
|
}
|
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|
|
],
|
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|
|
"metadata": {
|
|||
|
|
"@webio": {
|
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|
|
"lastCommId": null,
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|
"lastKernelId": null
|
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},
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|
|
"anaconda-cloud": {},
|
|||
|
|
"kernelspec": {
|
|||
|
|
"display_name": "Julia 1.7.0",
|
|||
|
|
"language": "julia",
|
|||
|
|
"name": "julia-1.7"
|
|||
|
|
},
|
|||
|
|
"language_info": {
|
|||
|
|
"file_extension": ".jl",
|
|||
|
|
"mimetype": "application/julia",
|
|||
|
|
"name": "julia",
|
|||
|
|
"version": "1.7.0"
|
|||
|
|
},
|
|||
|
|
"nteract": {
|
|||
|
|
"version": "0.23.1"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 4
|
|||
|
|
}
|