update notebooks

Author: AnilSorathiya

notebooks/code_samples/capital_markets/quickstart_option_pricing_models.ipynb

@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 4,
    "id": "86a8da01",
    "metadata": {},
    "outputs": [],
@@ -324,7 +324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 6,
    "id": "b27d7fc3",
    "metadata": {},
    "outputs": [],
@@ -374,7 +374,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 7,
    "id": "f29f07ef",
    "metadata": {},
    "outputs": [],
@@ -417,13 +417,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 8,
    "id": "0e129f19",
    "metadata": {},
    "outputs": [],
    "source": [
     "ticker = \"MSFT\"\n",
-    "expiration_date =  \"2024-11-15\" # Example expiration date in 'YYYY-MM-DD' form\n",
+    "expiration_date =  \"2024-12-06\" # Example expiration date in 'YYYY-MM-DD' form\n",
     "\n",
     "market_data = get_market_data(ticker=ticker, expiration_date_str=expiration_date)"
    ]
@@ -440,7 +440,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 9,
    "id": "d28df598",
    "metadata": {},
    "outputs": [],
@@ -459,7 +459,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 10,
    "id": "dc070da8",
    "metadata": {},
    "outputs": [],
@@ -589,7 +589,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "calculation_date = ql.Date(4, 11, 2024)\n",
+    "calculation_date = ql.Date(26, 11, 2024)\n",
     "# Convert expiration date string to QuantLib.Date\n",
     "expiry_date_parts = list(map(int, expiration_date.split('-')))\n",
     "maturity_date = ql.Date(expiry_date_parts[2], expiry_date_parts[1], expiry_date_parts[0])\n",
@@ -637,7 +637,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 12,
    "id": "810cf887",
    "metadata": {},
    "outputs": [],
@@ -686,7 +686,6 @@
     "\n",
     "    }\n",
     "    df1 = pd.DataFrame(data)\n",
-    "\n",
     "    return {\"strikes variation benchmarking\": df1}"
    ]
   },
@@ -725,7 +724,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 14,
    "id": "80492c82",
    "metadata": {},
    "outputs": [],
@@ -784,7 +783,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 15,
    "id": "4862005d",
    "metadata": {},
    "outputs": [],
@@ -811,7 +810,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 16,
    "id": "b2115371",
    "metadata": {},
    "outputs": [],
@@ -854,10 +853,10 @@
     "result.log()\n",
     "# Visualize how option prices change with different strike prices\n",
     "plot_results(\n",
-    "    pd.DataFrame(result.metric.summary.results[0].data),\n",
+    "    pd.DataFrame(result.tables[0].data),\n",
     "    params={\n",
     "        \"x\": \"strike_price\",\n",
-    "        \"y\":\"value\",\n",
+    "        \"y\":\"Value\",\n",
     "        \"label\":\"Strike price\",\n",
     "        \"xlabel\":\"Strike price\",\n",
     "        \"ylabel\":\"option price\",\n",
@@ -878,7 +877,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 18,
    "id": "b977f2e3",
    "metadata": {},
    "outputs": [],
@@ -1151,7 +1150,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.10.14"
   }
  },
  "nbformat": 4,