331 lines
7.6 KiB
Plaintext
331 lines
7.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "f0b34223",
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"metadata": {},
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"source": [
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"<div style=\"background-color:#000;\"><img src=\"pqn.png\"></img></div>"
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]
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},
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{
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"cell_type": "markdown",
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"id": "faa221b8",
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"metadata": {},
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"source": [
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"This code retrieves stock and options data for the ETF \"SPY\" and futures data for the symbol \"ES\". It uses the OpenBB Terminal SDK to load the data, including historical prices and options chains. The retrieved data is then stored in HDF5 files for easy access and persistence. This is useful for financial analysis and modeling, enabling efficient data storage and manipulation. The code concludes by reading the stored data and printing it for verification."
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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": null,
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"id": "1e4509d9",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from openbb_terminal.sdk import openbb"
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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": null,
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"id": "0d2e2e11",
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"metadata": {},
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"outputs": [],
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"source": [
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"STOCKS_DATA_STORE = \"stocks.h5\"\n",
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"FUTURES_DATA_STORE = \"futures.h5\""
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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": null,
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"id": "2fe2335b",
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"metadata": {},
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"outputs": [],
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"source": [
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"ticker = \"SPY\"\n",
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"root = \"ES\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "24c85387",
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"metadata": {},
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"source": [
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"Retrieve stock price data for the ticker \"SPY\""
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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": null,
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"id": "b650ad85",
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"metadata": {},
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"outputs": [],
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"source": [
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"spy_equity = openbb.stocks.load(ticker)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8e1952ce",
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"metadata": {},
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"source": [
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"Retrieve options expiration dates for the ticker \"SPY\""
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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": null,
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"id": "3f1867fa",
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"metadata": {},
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"outputs": [],
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"source": [
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"spy_expirations = openbb.stocks.options.expirations(ticker)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "473c96d9",
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"metadata": {},
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"source": [
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"Retrieve historical options data for a specific expiration date"
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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": null,
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"id": "88dd5dff",
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"metadata": {},
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"outputs": [],
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"source": [
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"spy_historic = openbb.stocks.options.hist(\n",
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" ticker, \n",
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" spy_expirations[1], \n",
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" 440\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a15b5e11",
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"metadata": {},
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"source": [
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"Retrieve options chains for the ticker \"SPY\""
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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": null,
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"id": "22932258",
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"metadata": {},
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"outputs": [],
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"source": [
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"spy_chains = openbb.stocks.options.chains(ticker)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2b653927",
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"metadata": {},
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"source": [
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"Store the retrieved stock and options data in an HDF5 file"
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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": null,
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"id": "87844c25",
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"metadata": {},
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"outputs": [],
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"source": [
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"with pd.HDFStore(STOCKS_DATA_STORE) as store:\n",
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" store.put(\"equities/spy/stock_prices\", spy_equity)\n",
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" store.put(\"equities/spy/options_prices\", spy_historic)\n",
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" store.put(\"equities/spy/chains\", spy_chains)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f19a14bb",
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"metadata": {},
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"source": [
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"Retrieve and store futures data for the symbol \"ES\" for specific expiration dates"
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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": null,
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"id": "a3596058",
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"metadata": {},
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"outputs": [],
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"source": [
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"with pd.HDFStore(FUTURES_DATA_STORE) as store:\n",
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" for i in range(23, 31):\n",
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" expiry = f\"20{i}-12\"\n",
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" df = openbb.futures.historical(\n",
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" symbols=[root],\n",
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" expiry=expiry,\n",
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" start_date=\"2020-01-01\",\n",
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" end_date=\"2022-12-31\"\n",
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" )\n",
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" df.rename(\n",
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" columns={\n",
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" \"Adj Close\": expiry\n",
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" },\n",
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" inplace=True\n",
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" )\n",
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" prices = df[expiry]\n",
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" store.put(f'futures/{root}/{expiry}', prices)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e2d26e16",
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"metadata": {},
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"source": [
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"Load stored stock prices, options prices, and options chains from the HDF5 file"
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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": null,
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"id": "1f6f38e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"with pd.HDFStore(STOCKS_DATA_STORE) as store:\n",
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" spy_prices = store[\"equities/spy/stock_prices\"]\n",
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" spy_options = store[\"equities/spy/options_prices\"]\n",
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" spy_chains = store[\"equities/spy/chains\"]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "eaef333c",
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"metadata": {},
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"source": [
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"Load stored futures prices for a specific expiration date from the HDF5 file"
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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": null,
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"id": "718f2b5e",
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"metadata": {},
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"outputs": [],
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"source": [
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"with pd.HDFStore(FUTURES_DATA_STORE) as store:\n",
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" es_prices = store[f\"futures/{root}/2023-12\"]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6e8de69d",
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"metadata": {},
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"source": [
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"Print the loaded stock prices for verification"
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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": null,
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"id": "be69f51a",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(spy_prices)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "738952d1",
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"metadata": {},
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"source": [
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"Print the loaded options prices for verification"
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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": null,
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"id": "a6ce0462",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(spy_options)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "36b43858",
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"metadata": {},
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"source": [
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"Print the loaded options prices for verification"
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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": null,
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"id": "d23ab3b5",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(spy_options)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5b9da3de",
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"metadata": {},
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"source": [
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"Print the loaded futures prices for verification"
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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": null,
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"id": "c3afda92",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(es_prices)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3c427529",
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"metadata": {},
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"source": [
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"<a href=\"https://pyquantnews.com/\">PyQuant News</a> is where finance practitioners level up with Python for quant finance, algorithmic trading, and market data analysis. Looking to get started? Check out the fastest growing, top-selling course to <a href=\"https://gettingstartedwithpythonforquantfinance.com/\">get started with Python for quant finance</a>. For educational purposes. Not investment advise. Use at your own risk."
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]
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}
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],
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"metadata": {
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"jupytext": {
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"cell_metadata_filter": "-all",
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"main_language": "python",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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