Add custom data ticker mapping research notebook

project-templates/python/custom-data-ticker-mapping/research.ipynb

@@ -0,0 +1,163 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "cdt-logo",
+   "metadata": {},
+   "source": [
+    "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n",
+    "<hr>\n",
+    "\n",
+    "## Custom Data with Ticker Mapping Research\n",
+    "\n",
+    "This notebook loads the mapped trade data from the Object Store and shows how the FB ticker resolves to the current META symbol."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cdt-setup-md",
+   "metadata": {},
+   "source": [
+    "### Set Up QuantBook\n",
+    "\n",
+    "Save the selected-trades file to the Object Store for the custom data reader."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cdt-content",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "SELECTED_TRADES_FILE = \"selected_trades.csv\"\n",
+    "\n",
+    "CONTENT = \"\"\"\n",
+    "2020-01-20,FB,100\n",
+    "2020-01-20,MSFT,200\n",
+    "2020-01-20,NVDA,300\n",
+    "2024-09-03,META,-100\n",
+    "2024-09-03,MSFT,-200\n",
+    "2024-09-03,NVDA,-300\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cdt-setup",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "qb = QuantBook()\n",
+    "qb.set_start_date(2024, 12, 31)\n",
+    "qb.object_store.save(SELECTED_TRADES_FILE, CONTENT)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cdt-class-md",
+   "metadata": {},
+   "source": [
+    "### Define the Custom Data Type\n",
+    "\n",
+    "Define a [custom securities](https://www.quantconnect.com/docs/v2/writing-algorithms/importing-data/streaming-data/custom-securities) reader that maps each point-in-time ticker to a Symbol."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cdt-class",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class SelectedTrades(PythonData):\n",
+    "\n",
+    "    def get_source(self, config: SubscriptionDataConfig, date: datetime, is_live_mode: bool) -> SubscriptionDataSource:\n",
+    "        return SubscriptionDataSource(SELECTED_TRADES_FILE, SubscriptionTransportMedium.OBJECT_STORE)\n",
+    "\n",
+    "    def reader(self, config: SubscriptionDataConfig, line: str, date: datetime, is_live_mode: bool) -> BaseData:\n",
+    "        if not line.strip():\n",
+    "            return None\n",
+    "        data = [x.strip() for x in line.split(',')]\n",
+    "        ticker = data[1]\n",
+    "        time = datetime.strptime(data[0], \"%Y-%m-%d\")\n",
+    "        # Resolve the point-in-time SecurityIdentifier so FB maps to today's META symbol.\n",
+    "        security_id = SecurityIdentifier.generate_equity(ticker, Market.USA, mapping_resolve_date=time)\n",
+    "        if security_id.date.year < 1998:\n",
+    "            return None\n",
+    "        trade = SelectedTrades()\n",
+    "        trade.symbol = Symbol(security_id, ticker)\n",
+    "        trade.end_time = time\n",
+    "        trade.time = time - timedelta(1)\n",
+    "        trade.quantity = float(data[2])\n",
+    "        return trade"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cdt-add",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trades = qb.add_data(SelectedTrades, \"X\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cdt-build-md",
+   "metadata": {},
+   "source": [
+    "### Build Time Series\n",
+    "\n",
+    "Request the full history of the mapped trade data and inspect the resolved symbols and quantities."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5f02b270",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "history = qb.history(SelectedTrades, trades.symbol, datetime(2020, 1, 1), datetime(2024, 12, 31))\n",
+    "history"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cdt-asset-history",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Extract the unique asset Symbols from the custom data history.\n",
+    "asset_symbols = list(history.index.levels[0])\n",
+    "# Request daily history for the assets referenced by the custom data.\n",
+    "asset_history = qb.history(asset_symbols, datetime(2020, 1, 1), datetime(2024, 12, 31), Resolution.DAILY)\n",
+    "asset_history"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Foundation-Py-Default",
+   "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": "3.11.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}