Add custom indicator research template

project-templates/python/custom-indicator/main.py

@@ -9,7 +9,7 @@ def initialize(self) -> None:
         self.set_start_date(2024, 9, 1)
         self.set_end_date(2024, 12, 31)
         # Request daily SPY data to feed the indicators to generate trade signals and trade.
-        self._spy = self.add_equity("SPY", data_normalization_mode=DataNormalizationMode.RAW)
+        self._spy = self.add_equity("SPY")
         # Create a custom money flow index to generate a trade signal.
         self._custom_mfi = CustomMoneyFlowIndex(20)
         # Warm up for immediate usage of indicators.

project-templates/python/custom-indicator/research.ipynb

@@ -0,0 +1,199 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ci-logo",
+   "metadata": {},
+   "source": [
+    "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n",
+    "<hr>\n",
+    "\n",
+    "## Custom Indicator Research\n",
+    "\n",
+    "This notebook implements a custom Money Flow Index and builds value and signal series from daily SPY history."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ci-setup-md",
+   "metadata": {},
+   "source": [
+    "### Set Up QuantBook\n",
+    "\n",
+    "Create a daily SPY subscription for the custom indicator updates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ci-setup",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "qb = QuantBook()\n",
+    "qb.set_start_date(2024, 12, 31)\n",
+    "qb.settings.seed_initial_prices = True\n",
+    "equity = qb.add_equity(\"SPY\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ci-class-md",
+   "metadata": {},
+   "source": [
+    "### Define Indicator\n",
+    "\n",
+    "Implement a [custom Money Flow Index Indicator](https://www.quantconnect.com/docs/v2/writing-algorithms/indicators/custom-indicators)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ci-class",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class CustomMoneyFlowIndex(PythonIndicator):\n",
+    "\n",
+    "    def __init__(self, period: int) -> None:\n",
+    "        super().__init__()\n",
+    "        self.value = 0\n",
+    "        self._previous_typical_price = 0\n",
+    "        self._negative_money_flow: RollingWindow[float] = RollingWindow(period)\n",
+    "        self._positive_money_flow: RollingWindow[float] = RollingWindow(period)\n",
+    "\n",
+    "    def update(self, input: TradeBar) -> bool:\n",
+    "        # Estimate the money flow by averaging the price multiplied by volume.\n",
+    "        typical_price = (input.high + input.low + input.close) / 3\n",
+    "        money_flow = typical_price * input.volume\n",
+    "        # Classify the flow as positive or negative relative to the previous bar.\n",
+    "        self._negative_money_flow.add(money_flow if typical_price < self._previous_typical_price else 0)\n",
+    "        self._positive_money_flow.add(money_flow if typical_price > self._previous_typical_price else 0)\n",
+    "        self._previous_typical_price = typical_price\n",
+    "        positive_money_flow_sum = sum(self._positive_money_flow)\n",
+    "        total_money_flow = positive_money_flow_sum + sum(self._negative_money_flow)\n",
+    "        # Set the value to the positive money flow ratio.\n",
+    "        self.value = 100\n",
+    "        if total_money_flow != 0:\n",
+    "            self.value *= positive_money_flow_sum / total_money_flow\n",
+    "        return self._positive_money_flow.is_ready"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ci-build-md",
+   "metadata": {},
+   "source": [
+    "### Build Time Series\n",
+    "\n",
+    "Feed daily TradeBar history through the indicator and store its value for each bar."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ci-build",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2024-01-31 16:00:00    67.098719\n",
+       "2024-02-01 16:00:00    66.933356\n",
+       "2024-02-02 16:00:00    72.315045\n",
+       "2024-02-05 16:00:00    72.500965\n",
+       "2024-02-06 16:00:00    72.214645\n",
+       "                         ...    \n",
+       "2024-12-23 16:00:00    56.324222\n",
+       "2024-12-24 13:00:00    55.565956\n",
+       "2024-12-26 16:00:00    55.006566\n",
+       "2024-12-27 16:00:00    53.274876\n",
+       "2024-12-30 16:00:00    48.933252\n",
+       "Name: mfi, Length: 231, dtype: float64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mfi = CustomMoneyFlowIndex(20)\n",
+    "mfi_by_date = {\n",
+    "    bar.end_time: mfi.value\n",
+    "    for bar in qb.history[TradeBar](equity, 250, Resolution.DAILY)\n",
+    "    if mfi.update(bar)\n",
+    "}\n",
+    "\n",
+    "indicator_values = pd.Series(mfi_by_date, name=\"mfi\")\n",
+    "indicator_values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ci-signal-md",
+   "metadata": {},
+   "source": [
+    "### Signal Series\n",
+    "\n",
+    "Derive long and short signals based on the money flow indicator."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "ci-signal",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2024-01-31 16:00:00    1\n",
+       "2024-02-01 16:00:00    1\n",
+       "2024-02-02 16:00:00    1\n",
+       "2024-02-05 16:00:00    1\n",
+       "2024-02-06 16:00:00    1\n",
+       "                      ..\n",
+       "2024-12-23 16:00:00    1\n",
+       "2024-12-24 13:00:00    1\n",
+       "2024-12-26 16:00:00    1\n",
+       "2024-12-27 16:00:00    1\n",
+       "2024-12-30 16:00:00   -1\n",
+       "Name: signal, Length: 231, dtype: int64"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Go long when demand outweighs supply, otherwise go short.\n",
+    "signal = pd.Series(-1, index=indicator_values.index, name=\"signal\")\n",
+    "signal[indicator_values > 50] = 1\n",
+    "signal"
+   ]
+  }
+ ],
+ "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
+}