[SC 7521] Move capital markets notebooks from code sharing to code samples

notebooks/code_sharing/capital_markets/quickstart_option_pricing_models.ipynb → notebooks/code_samples/capital_markets/quickstart_option_pricing_models.ipynb

@@ -33,7 +33,6 @@
     "- [Initialize the ValidMind Library](#toc3_)    \n",
     "- [Initialize the Python environment](#toc4_)    \n",
     "  - [Preview the documentation template](#toc4_1_)    \n",
-    "- [Data preparation](#toc5_)    \n",
     "- [Model development](#toc6_)   \n",
     "  - [Synthetic data generation](#toc6_1_)\n",
     "  - [Model Calibration](#toc6_2_)    \n",
@@ -189,7 +188,7 @@
     "    # api_key=\"...\",\n",
     "    # api_secret=\"...\",\n",
     "    # model=\"...\",\n",
-    ")"
+    ")\n"
    ]
   },
   {
@@ -206,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "29d2c1a0",
    "metadata": {},
    "outputs": [],
@@ -244,31 +243,6 @@
     "vm.preview_template()"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "0d22f562",
-   "metadata": {},
-   "source": [
-    "<a id='toc5_'></a>\n",
-    "## Data Preparation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b0267993",
-   "metadata": {},
-   "source": [
-    "### Market Data Sources"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7f0cd4bc",
-   "metadata": {},
-   "source": [
-    "### Market Data Quality and Availability"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "6d6a8447",
@@ -280,7 +254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "c3f5b0b9",
    "metadata": {},
    "outputs": [],
@@ -301,7 +275,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "d3748656",
    "metadata": {},
    "outputs": [],
@@ -432,7 +406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "42cb9070",
    "metadata": {},
    "outputs": [],
@@ -448,13 +422,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "c81282bd",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Parameters for synthetic data\n",
-    "# Common\n",
     "S0 = 100\n",
     "K = 100\n",
     "T = 1\n",
@@ -495,7 +468,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "5e709e0e",
    "metadata": {},
    "outputs": [],
@@ -593,15 +566,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "id": "ac733262",
    "metadata": {},
    "outputs": [],
    "source": [
     "@vm.test(\"my_custom_tests.BenchmarkTest\")\n",
     "def benchmark_test(bs_model, sv_model, strikes, maturities):\n",
     "    \"\"\"\n",
-    "    Compaparison between blacksholes and stoachastic volatility model\n",
+    "    Comparison between Black Scholes and stochastic volatility model\n",
     "\n",
     "    \"\"\"\n",
     "    bs_model_type = type(bs_model).__name__\n",
@@ -674,7 +647,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "id": "80492c82",
    "metadata": {},
    "outputs": [],
@@ -705,12 +678,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "id": "b2115371",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Example usage:\n",
     "S0 = 100\n",
     "T = 1\n",
     "r = 0.05\n",
@@ -730,7 +702,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "id": "f6c98fbe",
    "metadata": {},
    "outputs": [],
@@ -743,7 +715,7 @@
     "        plt.title(params[\"title\"])\n",
     "        plt.legend()\n",
     "        plt.grid(True)\n",
-    "        plt.show()  # close the plot to avoid displaying it"
+    "        plt.show() "
    ]
   },
   {
@@ -783,7 +755,7 @@
     ")\n",
     "result.log()\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"strike\",\n",
     "        \"y\":\"Option price\",\n",
@@ -795,6 +767,16 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b30e1b5a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "fe2c8f65",
@@ -831,7 +813,7 @@
     ")\n",
     "result.log()\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"barrier\",\n",
     "        \"y\":\"Option price\",\n",
@@ -854,7 +836,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 18,
    "id": "7bdd02ed",
    "metadata": {},
    "outputs": [],
@@ -1035,7 +1017,7 @@
     ")\n",
     "result.log()\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"kappa\",\n",
     "        \"y\":\"Option price\",\n",
@@ -1083,7 +1065,7 @@
     ")\n",
     "result.log()\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"theta\",\n",
     "        \"y\":\"Option price\",\n",
@@ -1131,7 +1113,7 @@
     ")\n",
     "result.log()\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"xi\",\n",
     "        \"y\":\"Option price\",\n",
@@ -1179,7 +1161,7 @@
     ")\n",
     "result.log()\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"rho\",\n",
     "        \"y\":\"Option price\",\n",