diff --git a/COT_data_nasdaq_Silver.ipynb b/COT_data_nasdaq_Silver.ipynb
new file mode 100644
index 0000000..78fc3bc
--- /dev/null
+++ b/COT_data_nasdaq_Silver.ipynb
@@ -0,0 +1,3027 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "68e3c2ce-ed33-4c9d-851c-86184d9d3414",
+   "metadata": {},
+   "source": [
+    "# Load NASDAQ API key (Data Link API) - Silver\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "7629bec6-f9e7-4180-aa56-0c2e857d34cb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "import os\n",
+    "\n",
+    "# Load the environment variables from .env file\n",
+    "load_dotenv(\"api_keys\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "aa5b3443-449e-4f02-b231-1ffdef4d11ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loaded key\n"
+     ]
+    }
+   ],
+   "source": [
+    "nasdaq_api_key = os.getenv('NASDAQ_API_KEY')\n",
+    "if len(nasdaq_api_key) > 0:\n",
+    "    print(\"loaded key\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5fdcd717-d4a3-4e7e-b8b5-a4369bd1bc83",
+   "metadata": {},
+   "source": [
+    "## Retrieve 2 year of COT data (% shifts producers long / short)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "fc5d6a91-c107-443e-8b6e-84e10d945ca2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "            Open Interest  Producer/Merchant/Processor/User Longs  \\\n",
+      "Date                                                                \n",
+      "2023-11-28       139144.0                                  3472.0   \n",
+      "2023-12-05       139753.0                                  4714.0   \n",
+      "2023-12-12       134281.0                                  4311.0   \n",
+      "2023-12-19       127549.0                                  3701.0   \n",
+      "2023-12-26       131408.0                                  4063.0   \n",
+      "\n",
+      "            Producer/Merchant/Processor/User Shorts  Swap Dealer Longs  \\\n",
+      "Date                                                                     \n",
+      "2023-11-28                                  40323.0            33045.0   \n",
+      "2023-12-05                                  41340.0            33328.0   \n",
+      "2023-12-12                                  38849.0            30707.0   \n",
+      "2023-12-19                                  39714.0            30908.0   \n",
+      "2023-12-26                                  41011.0            29911.0   \n",
+      "\n",
+      "            Swap Dealer Shorts  Swap Dealer Spreads  Money Manager Longs  \\\n",
+      "Date                                                                       \n",
+      "2023-11-28             44049.0               3770.0              45604.0   \n",
+      "2023-12-05             48716.0               2932.0              43852.0   \n",
+      "2023-12-12             43665.0               2832.0              33472.0   \n",
+      "2023-12-19             43686.0               1911.0              34931.0   \n",
+      "2023-12-26             45585.0               2415.0              36546.0   \n",
+      "\n",
+      "            Money Manager Shorts  Money Manager Spreads  \\\n",
+      "Date                                                      \n",
+      "2023-11-28               21842.0                 6885.0   \n",
+      "2023-12-05               22322.0                 7544.0   \n",
+      "2023-12-12               24805.0                 8439.0   \n",
+      "2023-12-19               20060.0                 6662.0   \n",
+      "2023-12-26               19749.0                 6847.0   \n",
+      "\n",
+      "            Other Reportable Longs  Other Reportable Shorts  \\\n",
+      "Date                                                          \n",
+      "2023-11-28                 17276.0                   6758.0   \n",
+      "2023-12-05                 19389.0                   4616.0   \n",
+      "2023-12-12                 22212.0                   2421.0   \n",
+      "2023-12-19                 17700.0                   2820.0   \n",
+      "2023-12-26                 18013.0                   2947.0   \n",
+      "\n",
+      "            Other Reportable Spreads  Total Reportable Longs  \\\n",
+      "Date                                                           \n",
+      "2023-11-28                    2445.0                112497.0   \n",
+      "2023-12-05                    1607.0                113366.0   \n",
+      "2023-12-12                    1706.0                103679.0   \n",
+      "2023-12-19                    1577.0                 97390.0   \n",
+      "2023-12-26                    2137.0                 99932.0   \n",
+      "\n",
+      "            Total Reportable Shorts  Non Reportable Longs  \\\n",
+      "Date                                                        \n",
+      "2023-11-28                 126072.0               26647.0   \n",
+      "2023-12-05                 129077.0               26387.0   \n",
+      "2023-12-12                 122717.0               30602.0   \n",
+      "2023-12-19                 116430.0               30159.0   \n",
+      "2023-12-26                 120691.0               31476.0   \n",
+      "\n",
+      "            Non Reportable Shorts  \n",
+      "Date                               \n",
+      "2023-11-28                13072.0  \n",
+      "2023-12-05                10676.0  \n",
+      "2023-12-12                11564.0  \n",
+      "2023-12-19                11119.0  \n",
+      "2023-12-26                10717.0  \n"
+     ]
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "import pandas as pd\n",
+    "from datetime import datetime\n",
+    "import urllib.parse\n",
+    "\n",
+    "# API endpoint components\n",
+    "base_url = \"https://data.nasdaq.com/api/v3/datasets/\"\n",
+    "dataset = \"CFTC/084691_F_ALL\"\n",
+    "data_format = \".json\"\n",
+    "\n",
+    "# Parameters\n",
+    "params = {\n",
+    "    \"start_date\": \"2022-01-01\",\n",
+    "    \"end_date\": \"2024-01-01\",\n",
+    "    \"api_key\": nasdaq_api_key  # Make sure this variable is defined\n",
+    "}\n",
+    "\n",
+    "# Construct the full URL with parameters\n",
+    "param_string = urllib.parse.urlencode(params)\n",
+    "url = f\"{base_url}{dataset}{data_format}?{param_string}\"\n",
+    "\n",
+    "# Make the API request\n",
+    "response = requests.get(url)\n",
+    "\n",
+    "# Check if the request was successful\n",
+    "if response.status_code == 200:\n",
+    "    # Parse the JSON response\n",
+    "    data = response.json()\n",
+    "    \n",
+    "    # Extract the dataset from the response\n",
+    "    dataset = data['dataset']\n",
+    "    \n",
+    "    # Create a pandas DataFrame\n",
+    "    df = pd.DataFrame(dataset['data'], columns=dataset['column_names'])\n",
+    "    \n",
+    "    # Convert the date column to datetime\n",
+    "    df['Date'] = pd.to_datetime(df['Date'])\n",
+    "    \n",
+    "    # Set the date as the index\n",
+    "    df.set_index('Date', inplace=True)\n",
+    "    \n",
+    "    # Sort the DataFrame by date\n",
+    "    df.sort_index(inplace=True)\n",
+    "    \n",
+    "    # Display the first few rows of the DataFrame\n",
+    "    print(df.tail())\n",
+    "    \n",
+    "    # You can now use this DataFrame for further analysis or visualization\n",
+    "    \n",
+    "else:\n",
+    "    print(f\"Error fetching data: {response.status_code}\")\n",
+    "    print(response.text)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "a1ab3a82-5682-4701-ab9e-414d6d4ff115",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Open Interest', 'Producer/Merchant/Processor/User Longs',\n",
+       "       'Producer/Merchant/Processor/User Shorts', 'Swap Dealer Longs',\n",
+       "       'Swap Dealer Shorts', 'Swap Dealer Spreads', 'Money Manager Longs',\n",
+       "       'Money Manager Shorts', 'Money Manager Spreads',\n",
+       "       'Other Reportable Longs', 'Other Reportable Shorts',\n",
+       "       'Other Reportable Spreads', 'Total Reportable Longs',\n",
+       "       'Total Reportable Shorts', 'Non Reportable Longs',\n",
+       "       'Non Reportable Shorts'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "61ac72a5-b8f9-451f-ae0e-2c9b5ed7358a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Open Interest</th>\n",
+       "      <th>Producer/Merchant/Processor/User Longs</th>\n",
+       "      <th>Producer/Merchant/Processor/User Shorts</th>\n",
+       "      <th>Swap Dealer Longs</th>\n",
+       "      <th>Swap Dealer Shorts</th>\n",
+       "      <th>Swap Dealer Spreads</th>\n",
+       "      <th>Money Manager Longs</th>\n",
+       "      <th>Money Manager Shorts</th>\n",
+       "      <th>Money Manager Spreads</th>\n",
+       "      <th>Other Reportable Longs</th>\n",
+       "      <th>Other Reportable Shorts</th>\n",
+       "      <th>Other Reportable Spreads</th>\n",
+       "      <th>Total Reportable Longs</th>\n",
+       "      <th>Total Reportable Shorts</th>\n",
+       "      <th>Non Reportable Longs</th>\n",
+       "      <th>Non Reportable Shorts</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2023-11-28</th>\n",
+       "      <td>139144.0</td>\n",
+       "      <td>3472.0</td>\n",
+       "      <td>40323.0</td>\n",
+       "      <td>33045.0</td>\n",
+       "      <td>44049.0</td>\n",
+       "      <td>3770.0</td>\n",
+       "      <td>45604.0</td>\n",
+       "      <td>21842.0</td>\n",
+       "      <td>6885.0</td>\n",
+       "      <td>17276.0</td>\n",
+       "      <td>6758.0</td>\n",
+       "      <td>2445.0</td>\n",
+       "      <td>112497.0</td>\n",
+       "      <td>126072.0</td>\n",
+       "      <td>26647.0</td>\n",
+       "      <td>13072.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2023-12-05</th>\n",
+       "      <td>139753.0</td>\n",
+       "      <td>4714.0</td>\n",
+       "      <td>41340.0</td>\n",
+       "      <td>33328.0</td>\n",
+       "      <td>48716.0</td>\n",
+       "      <td>2932.0</td>\n",
+       "      <td>43852.0</td>\n",
+       "      <td>22322.0</td>\n",
+       "      <td>7544.0</td>\n",
+       "      <td>19389.0</td>\n",
+       "      <td>4616.0</td>\n",
+       "      <td>1607.0</td>\n",
+       "      <td>113366.0</td>\n",
+       "      <td>129077.0</td>\n",
+       "      <td>26387.0</td>\n",
+       "      <td>10676.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2023-12-12</th>\n",
+       "      <td>134281.0</td>\n",
+       "      <td>4311.0</td>\n",
+       "      <td>38849.0</td>\n",
+       "      <td>30707.0</td>\n",
+       "      <td>43665.0</td>\n",
+       "      <td>2832.0</td>\n",
+       "      <td>33472.0</td>\n",
+       "      <td>24805.0</td>\n",
+       "      <td>8439.0</td>\n",
+       "      <td>22212.0</td>\n",
+       "      <td>2421.0</td>\n",
+       "      <td>1706.0</td>\n",
+       "      <td>103679.0</td>\n",
+       "      <td>122717.0</td>\n",
+       "      <td>30602.0</td>\n",
+       "      <td>11564.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2023-12-19</th>\n",
+       "      <td>127549.0</td>\n",
+       "      <td>3701.0</td>\n",
+       "      <td>39714.0</td>\n",
+       "      <td>30908.0</td>\n",
+       "      <td>43686.0</td>\n",
+       "      <td>1911.0</td>\n",
+       "      <td>34931.0</td>\n",
+       "      <td>20060.0</td>\n",
+       "      <td>6662.0</td>\n",
+       "      <td>17700.0</td>\n",
+       "      <td>2820.0</td>\n",
+       "      <td>1577.0</td>\n",
+       "      <td>97390.0</td>\n",
+       "      <td>116430.0</td>\n",
+       "      <td>30159.0</td>\n",
+       "      <td>11119.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2023-12-26</th>\n",
+       "      <td>131408.0</td>\n",
+       "      <td>4063.0</td>\n",
+       "      <td>41011.0</td>\n",
+       "      <td>29911.0</td>\n",
+       "      <td>45585.0</td>\n",
+       "      <td>2415.0</td>\n",
+       "      <td>36546.0</td>\n",
+       "      <td>19749.0</td>\n",
+       "      <td>6847.0</td>\n",
+       "      <td>18013.0</td>\n",
+       "      <td>2947.0</td>\n",
+       "      <td>2137.0</td>\n",
+       "      <td>99932.0</td>\n",
+       "      <td>120691.0</td>\n",
+       "      <td>31476.0</td>\n",
+       "      <td>10717.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Open Interest  Producer/Merchant/Processor/User Longs  \\\n",
+       "Date                                                                \n",
+       "2023-11-28       139144.0                                  3472.0   \n",
+       "2023-12-05       139753.0                                  4714.0   \n",
+       "2023-12-12       134281.0                                  4311.0   \n",
+       "2023-12-19       127549.0                                  3701.0   \n",
+       "2023-12-26       131408.0                                  4063.0   \n",
+       "\n",
+       "            Producer/Merchant/Processor/User Shorts  Swap Dealer Longs  \\\n",
+       "Date                                                                     \n",
+       "2023-11-28                                  40323.0            33045.0   \n",
+       "2023-12-05                                  41340.0            33328.0   \n",
+       "2023-12-12                                  38849.0            30707.0   \n",
+       "2023-12-19                                  39714.0            30908.0   \n",
+       "2023-12-26                                  41011.0            29911.0   \n",
+       "\n",
+       "            Swap Dealer Shorts  Swap Dealer Spreads  Money Manager Longs  \\\n",
+       "Date                                                                       \n",
+       "2023-11-28             44049.0               3770.0              45604.0   \n",
+       "2023-12-05             48716.0               2932.0              43852.0   \n",
+       "2023-12-12             43665.0               2832.0              33472.0   \n",
+       "2023-12-19             43686.0               1911.0              34931.0   \n",
+       "2023-12-26             45585.0               2415.0              36546.0   \n",
+       "\n",
+       "            Money Manager Shorts  Money Manager Spreads  \\\n",
+       "Date                                                      \n",
+       "2023-11-28               21842.0                 6885.0   \n",
+       "2023-12-05               22322.0                 7544.0   \n",
+       "2023-12-12               24805.0                 8439.0   \n",
+       "2023-12-19               20060.0                 6662.0   \n",
+       "2023-12-26               19749.0                 6847.0   \n",
+       "\n",
+       "            Other Reportable Longs  Other Reportable Shorts  \\\n",
+       "Date                                                          \n",
+       "2023-11-28                 17276.0                   6758.0   \n",
+       "2023-12-05                 19389.0                   4616.0   \n",
+       "2023-12-12                 22212.0                   2421.0   \n",
+       "2023-12-19                 17700.0                   2820.0   \n",
+       "2023-12-26                 18013.0                   2947.0   \n",
+       "\n",
+       "            Other Reportable Spreads  Total Reportable Longs  \\\n",
+       "Date                                                           \n",
+       "2023-11-28                    2445.0                112497.0   \n",
+       "2023-12-05                    1607.0                113366.0   \n",
+       "2023-12-12                    1706.0                103679.0   \n",
+       "2023-12-19                    1577.0                 97390.0   \n",
+       "2023-12-26                    2137.0                 99932.0   \n",
+       "\n",
+       "            Total Reportable Shorts  Non Reportable Longs  \\\n",
+       "Date                                                        \n",
+       "2023-11-28                 126072.0               26647.0   \n",
+       "2023-12-05                 129077.0               26387.0   \n",
+       "2023-12-12                 122717.0               30602.0   \n",
+       "2023-12-19                 116430.0               30159.0   \n",
+       "2023-12-26                 120691.0               31476.0   \n",
+       "\n",
+       "            Non Reportable Shorts  \n",
+       "Date                               \n",
+       "2023-11-28                13072.0  \n",
+       "2023-12-05                10676.0  \n",
+       "2023-12-12                11564.0  \n",
+       "2023-12-19                11119.0  \n",
+       "2023-12-26                10717.0  "
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96e0f458-9969-41a5-a153-9229c441eee5",
+   "metadata": {},
+   "source": [
+    "## Plot the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "0babd084-6190-4681-a6a3-23a95b92a68c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "line": {
+          "color": "blue",
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "Producer/Merchant/Processor/User Longs",
+         "type": "scatter",
+         "x": [
+          "2022-01-04T00:00:00",
+          "2022-01-11T00:00:00",
+          "2022-01-18T00:00:00",
+          "2022-01-25T00:00:00",
+          "2022-02-01T00:00:00",
+          "2022-02-08T00:00:00",
+          "2022-02-15T00:00:00",
+          "2022-02-22T00:00:00",
+          "2022-03-01T00:00:00",
+          "2022-03-08T00:00:00",
+          "2022-03-15T00:00:00",
+          "2022-03-22T00:00:00",
+          "2022-03-29T00:00:00",
+          "2022-04-05T00:00:00",
+          "2022-04-12T00:00:00",
+          "2022-04-19T00:00:00",
+          "2022-04-26T00:00:00",
+          "2022-05-03T00:00:00",
+          "2022-05-10T00:00:00",
+          "2022-05-17T00:00:00",
+          "2022-05-24T00:00:00",
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+      ]
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Metrics for Producer/Merchant/Processor/User Longs:\n",
+      "Volatility (Standard Deviation): 1.36%\n",
+      "Average: 3.23%\n",
+      "Median: 3.00%\n",
+      "Minimum: 0.64%\n",
+      "Maximum: 7.14%\n",
+      "Typical Range: 2.37% to 3.78%\n",
+      "\n",
+      "Metrics for Producer/Merchant/Processor/User Shorts:\n",
+      "Volatility (Standard Deviation): 3.96%\n",
+      "Average: 25.57%\n",
+      "Median: 25.32%\n",
+      "Minimum: 18.08%\n",
+      "Maximum: 32.77%\n",
+      "Typical Range: 22.26% to 28.93%\n",
+      "\n",
+      "Correlation between Longs and Shorts: -0.22\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import plotly.graph_objects as go\n",
+    "import numpy as np\n",
+    "\n",
+    "# Assuming df is your DataFrame with the COT data\n",
+    "# If not, you'll need to load your data here\n",
+    "\n",
+    "# Calculate percentages for producers\n",
+    "categories = [\n",
+    "    'Producer/Merchant/Processor/User Longs',\n",
+    "    'Producer/Merchant/Processor/User Shorts'\n",
+    "]\n",
+    "\n",
+    "for category in categories:\n",
+    "    df[f'{category} %'] = df[category] / df['Open Interest'] * 100\n",
+    "\n",
+    "# Create the main figure\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "# Add traces for each category\n",
+    "colors = ['blue', 'red']\n",
+    "for i, category in enumerate(categories):\n",
+    "    fig.add_trace(go.Scatter(\n",
+    "        x=df.index, \n",
+    "        y=df[f'{category} %'], \n",
+    "        mode='lines',\n",
+    "        name=category,\n",
+    "        line=dict(width=2, color=colors[i])\n",
+    "    ))\n",
+    "\n",
+    "# Update layout\n",
+    "fig.update_layout(\n",
+    "    title='COT Data: Percentage of Open Interest for Producers',\n",
+    "    yaxis_title='Percentage of Open Interest',\n",
+    "    xaxis_title='Date',\n",
+    "    legend_title='Producer Categories',\n",
+    "    height=600,\n",
+    "    width=1200,\n",
+    "    hovermode='x unified'\n",
+    ")\n",
+    "\n",
+    "# Improve date labeling for better readability\n",
+    "fig.update_xaxes(\n",
+    "    tickformat=\"%d %b %Y\",\n",
+    "    tickangle=45,\n",
+    "    dtick=\"M1\",\n",
+    "    ticklabelmode=\"period\"\n",
+    ")\n",
+    "\n",
+    "# Set y-axis to percentage\n",
+    "fig.update_yaxes(ticksuffix='%')\n",
+    "\n",
+    "# Show the plot\n",
+    "fig.show()\n",
+    "\n",
+    "# Calculate and print metrics\n",
+    "for category in categories:\n",
+    "    print(f\"\\nMetrics for {category}:\")\n",
+    "    data = df[f'{category} %']\n",
+    "    \n",
+    "    print(f\"Volatility (Standard Deviation): {data.std():.2f}%\")\n",
+    "    print(f\"Average: {data.mean():.2f}%\")\n",
+    "    print(f\"Median: {data.median():.2f}%\")\n",
+    "    print(f\"Minimum: {data.min():.2f}%\")\n",
+    "    print(f\"Maximum: {data.max():.2f}%\")\n",
+    "    \n",
+    "    # Calculate typical range\n",
+    "    typical_low = np.percentile(data, 25)\n",
+    "    typical_high = np.percentile(data, 75)\n",
+    "    print(f\"Typical Range: {typical_low:.2f}% to {typical_high:.2f}%\")\n",
+    "\n",
+    "# Calculate and print the correlation between longs and shorts\n",
+    "correlation = df[f'{categories[0]} %'].corr(df[f'{categories[1]} %'])\n",
+    "print(f\"\\nCorrelation between Longs and Shorts: {correlation:.2f}\")"
+   ]
+  },
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+   "execution_count": 26,
+   "id": "a7f6c187-39dc-4950-9e3f-0a328825c443",
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",
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Data: Open Interest Over Time (Silver)\"},\"yaxis\":{\"title\":{\"text\":\"Open Interest\"}},\"xaxis\":{\"title\":{\"text\":\"Date\"},\"tickformat\":\"%d %b %Y\",\"tickangle\":45,\"dtick\":\"M1\",\"ticklabelmode\":\"period\"},\"height\":600,\"width\":800,\"hovermode\":\"x unified\"},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
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+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Metrics for Open Interest:\n",
+      "Volatility (Standard Deviation): 5894.28\n",
+      "Average: 131794.00\n",
+      "Median: 131408.00\n",
+      "Minimum: 123640.00\n",
+      "Maximum: 144138.00\n",
+      "Typical Range: 126377.50 to 135836.50\n",
+      "\n",
+      "Overall trend: Downward\n",
+      "\n",
+      "Significant points:\n",
+      "Peak on 2023-10-10 00:00:00: 126971.00\n",
+      "Peak on 2023-12-05 00:00:00: 139753.00\n",
+      "Trough on 2023-09-12 00:00:00: 125292.00\n",
+      "Trough on 2023-10-17 00:00:00: 123640.00\n",
+      "Trough on 2023-12-19 00:00:00: 127549.00\n",
+      "\n",
+      "Sudden changes (>5% day-to-day):\n",
+      "2023-12-19 00:00:00: -5.01% change\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import plotly.graph_objects as go\n",
+    "import numpy as np\n",
+    "from scipy import signal\n",
+    "\n",
+    "# Assuming df is your DataFrame with the COT data\n",
+    "# If not, you'll need to load your data here\n",
+    "\n",
+    "# Create the main figure\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "# Add trace for Open Interest\n",
+    "fig.add_trace(go.Scatter(\n",
+    "    x=df.index, \n",
+    "    y=df['Open Interest'], \n",
+    "    mode='lines',\n",
+    "    name='Open Interest',\n",
+    "    line=dict(width=2, color='blue')\n",
+    "))\n",
+    "\n",
+    "# Update layout\n",
+    "fig.update_layout(\n",
+    "    title='COT Data: Open Interest Over Time (Silver)',\n",
+    "    yaxis_title='Open Interest',\n",
+    "    xaxis_title='Date',\n",
+    "    height=600,\n",
+    "    width=800,\n",
+    "    hovermode='x unified'\n",
+    ")\n",
+    "\n",
+    "# Improve date labeling for better readability\n",
+    "fig.update_xaxes(\n",
+    "    tickformat=\"%d %b %Y\",\n",
+    "    tickangle=45,\n",
+    "    dtick=\"M1\",\n",
+    "    ticklabelmode=\"period\"\n",
+    ")\n",
+    "\n",
+    "# Show the plot\n",
+    "fig.show()\n",
+    "\n",
+    "# Calculate and print metrics\n",
+    "print(\"\\nMetrics for Open Interest:\")\n",
+    "data = df['Open Interest']\n",
+    "\n",
+    "print(f\"Volatility (Standard Deviation): {data.std():.2f}\")\n",
+    "print(f\"Average: {data.mean():.2f}\")\n",
+    "print(f\"Median: {data.median():.2f}\")\n",
+    "print(f\"Minimum: {data.min():.2f}\")\n",
+    "print(f\"Maximum: {data.max():.2f}\")\n",
+    "\n",
+    "# Calculate typical range\n",
+    "typical_low = np.percentile(data, 25)\n",
+    "typical_high = np.percentile(data, 75)\n",
+    "print(f\"Typical Range: {typical_low:.2f} to {typical_high:.2f}\")\n",
+    "\n",
+    "# Identify trends\n",
+    "def identify_trend(series):\n",
+    "    # Calculate the overall trend\n",
+    "    trend = np.polyfit(range(len(series)), series, 1)[0]\n",
+    "    if trend > 0:\n",
+    "        return \"Upward\"\n",
+    "    elif trend < 0:\n",
+    "        return \"Downward\"\n",
+    "    else:\n",
+    "        return \"Stable\"\n",
+    "\n",
+    "trend = identify_trend(data)\n",
+    "print(f\"\\nOverall trend: {trend}\")\n",
+    "\n",
+    "# Identify significant points\n",
+    "def find_peaks(series, prominence=1000):\n",
+    "    peaks, _ = signal.find_peaks(series, prominence=prominence)\n",
+    "    troughs, _ = signal.find_peaks(-series, prominence=prominence)\n",
+    "    return peaks, troughs\n",
+    "\n",
+    "peaks, troughs = find_peaks(data)\n",
+    "\n",
+    "print(\"\\nSignificant points:\")\n",
+    "for peak in peaks:\n",
+    "    print(f\"Peak on {df.index[peak]}: {data.iloc[peak]:.2f}\")\n",
+    "for trough in troughs:\n",
+    "    print(f\"Trough on {df.index[trough]}: {data.iloc[trough]:.2f}\")\n",
+    "\n",
+    "# Identify sudden changes\n",
+    "pct_change = data.pct_change()\n",
+    "sudden_changes = pct_change[abs(pct_change) > 0.05]  # 5% threshold\n",
+    "if not sudden_changes.empty:\n",
+    "    print(\"\\nSudden changes (>5% day-to-day):\")\n",
+    "    for date, change in sudden_changes.items():\n",
+    "        print(f\"{date}: {change*100:.2f}% change\")\n",
+    "else:\n",
+    "    print(\"\\nNo sudden changes above 5% threshold detected.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "10913a96-3d9a-4224-8984-6fb9abf31e72",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Silver_Fundamentals.ipynb b/Silver_Fundamentals.ipynb
new file mode 100644
index 0000000..9852abc
--- /dev/null
+++ b/Silver_Fundamentals.ipynb
@@ -0,0 +1,1849 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bf16a6eb-44a2-4dd7-8d4d-598e6f2c9b24",
+   "metadata": {},
+   "source": [
+    "# Silver "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4405f172-43b6-4245-bcd8-2c6e01fada3a",
+   "metadata": {},
+   "source": [
+    "We can download the data from the CFTC via Python.\n",
+    "\n",
+    "Many data APIs become commercial for recent prices. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f3704b41-1622-4596-ae99-3201b9bd8e14",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Selected: disaggregated_fut\n",
+      "Downloaded single year data from: 2020\n",
+      "Stored the file f_year.txt in the working directory.\n",
+      "Selected: disaggregated_fut\n",
+      "Downloaded single year data from: 2021\n",
+      "Stored the file f_year.txt in the working directory.\n",
+      "Selected: disaggregated_fut\n",
+      "Downloaded single year data from: 2022\n",
+      "Stored the file f_year.txt in the working directory.\n",
+      "Selected: disaggregated_fut\n",
+      "Downloaded single year data from: 2023\n",
+      "Stored the file f_year.txt in the working directory.\n",
+      "Selected: disaggregated_fut\n",
+      "Downloaded single year data from: 2024\n",
+      "Stored the file f_year.txt in the working directory.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import cot_reports as cot  # Ensure cot_reports is correctly imported and cot.cot_year() works as expected\n",
+    "\n",
+    "df = pd.DataFrame()\n",
+    "begin_year = 2020\n",
+    "end_year = 2024\n",
+    "\n",
+    "for i in range(begin_year, end_year + 1):\n",
+    "    # Assuming cot.cot_year returns a DataFrame\n",
+    "    single_year = pd.DataFrame(cot.cot_year(i, cot_report_type='disaggregated_fut'))\n",
+    "    single_year.to_csv(f'./COT_CFTC_{i}.csv', index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f4f90eb0-dca4-4589-a385-408c66c6e0a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['COT_CFTC_2022.csv', 'COT_CFTC_2023.csv', 'COT_CFTC_2021.csv', 'COT_CFTC_2020.csv', 'COT_CFTC_2024.csv']\n"
+     ]
+    }
+   ],
+   "source": [
+    "import glob\n",
+    "\n",
+    "# Adjust the path and pattern according to your CSV files location and naming convention\n",
+    "csv_files = glob.glob('COT_CFTC_20*.csv')\n",
+    "print(csv_files)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "414b7248-5acc-46a9-916a-cbed7228331f",
+   "metadata": {},
+   "source": [
+    "At this point, we have the CFTC Disaggregated Futures report from 2022 to 2024 (until today)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "084eb98b-1914-49e0-b57a-4e7717ea159c",
+   "metadata": {},
+   "source": [
+    "## Load the data, and prepare the dataset\n",
+    "\n",
+    "The CFTC report contains data on all futures, not just silver."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "cb167036-4f9b-4405-a942-71fae7d7aec7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_1629470/490941526.py:1: DtypeWarning: Columns (120,121,132,133,134,135,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  df = pd.read_csv('COT_CFTC_2024.csv')\n"
+     ]
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('COT_CFTC_2024.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2f554d5a-e6da-4a6c-a16e-f2b3294b4824",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8344, 191)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df[\"Report_Date_as_YYYY-MM-DD\"] = pd.to_datetime(df[\"Report_Date_as_YYYY-MM-DD\"], format='%Y-%m-%d')\n",
+    "df.set_index(\"Report_Date_as_YYYY-MM-DD\")\n",
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4bd367af-8385-406a-87ee-5aa68b3a8b7a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "8345\n"
+     ]
+    }
+   ],
+   "source": [
+    "!cat COT_CFTC_2024.csv | wc -l"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "fc275bed-93a3-4c66-87e0-7312aa712f6a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Market_and_Exchange_Names</th>\n",
+       "      <th>As_of_Date_In_Form_YYMMDD</th>\n",
+       "      <th>Report_Date_as_YYYY-MM-DD</th>\n",
+       "      <th>CFTC_Contract_Market_Code</th>\n",
+       "      <th>CFTC_Market_Code</th>\n",
+       "      <th>CFTC_Region_Code</th>\n",
+       "      <th>CFTC_Commodity_Code</th>\n",
+       "      <th>Open_Interest_All</th>\n",
+       "      <th>Prod_Merc_Positions_Long_All</th>\n",
+       "      <th>Prod_Merc_Positions_Short_All</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Conc_Net_LE_4_TDR_Long_Other</th>\n",
+       "      <th>Conc_Net_LE_4_TDR_Short_Other</th>\n",
+       "      <th>Conc_Net_LE_8_TDR_Long_Other</th>\n",
+       "      <th>Conc_Net_LE_8_TDR_Short_Other</th>\n",
+       "      <th>Contract_Units</th>\n",
+       "      <th>CFTC_Contract_Market_Code_Quotes</th>\n",
+       "      <th>CFTC_Market_Code_Quotes</th>\n",
+       "      <th>CFTC_Commodity_Code_Quotes</th>\n",
+       "      <th>CFTC_SubGroup_Code</th>\n",
+       "      <th>FutOnly_or_Combined</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>WHEAT-SRW - CHICAGO BOARD OF TRADE</td>\n",
+       "      <td>240813</td>\n",
+       "      <td>2024-08-13</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>401604</td>\n",
+       "      <td>68899</td>\n",
+       "      <td>85867</td>\n",
+       "      <td>...</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>31.7</td>\n",
+       "      <td>54.2</td>\n",
+       "      <td>42.6</td>\n",
+       "      <td>(CONTRACTS OF 5,000 BUSHELS)</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>1</td>\n",
+       "      <td>A10</td>\n",
+       "      <td>FutOnly</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>WHEAT-SRW - CHICAGO BOARD OF TRADE</td>\n",
+       "      <td>240806</td>\n",
+       "      <td>2024-08-06</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>431547</td>\n",
+       "      <td>73401</td>\n",
+       "      <td>85750</td>\n",
+       "      <td>...</td>\n",
+       "      <td>41.6</td>\n",
+       "      <td>32.3</td>\n",
+       "      <td>57.3</td>\n",
+       "      <td>41.7</td>\n",
+       "      <td>(CONTRACTS OF 5,000 BUSHELS)</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>1</td>\n",
+       "      <td>A10</td>\n",
+       "      <td>FutOnly</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>WHEAT-SRW - CHICAGO BOARD OF TRADE</td>\n",
+       "      <td>240730</td>\n",
+       "      <td>2024-07-30</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>432863</td>\n",
+       "      <td>73086</td>\n",
+       "      <td>83875</td>\n",
+       "      <td>...</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>28.5</td>\n",
+       "      <td>60.8</td>\n",
+       "      <td>38.4</td>\n",
+       "      <td>(CONTRACTS OF 5,000 BUSHELS)</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>1</td>\n",
+       "      <td>A10</td>\n",
+       "      <td>FutOnly</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WHEAT-SRW - CHICAGO BOARD OF TRADE</td>\n",
+       "      <td>240723</td>\n",
+       "      <td>2024-07-23</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>421227</td>\n",
+       "      <td>63636</td>\n",
+       "      <td>81374</td>\n",
+       "      <td>...</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>27.9</td>\n",
+       "      <td>63.5</td>\n",
+       "      <td>37.7</td>\n",
+       "      <td>(CONTRACTS OF 5,000 BUSHELS)</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>1</td>\n",
+       "      <td>A10</td>\n",
+       "      <td>FutOnly</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>WHEAT-SRW - CHICAGO BOARD OF TRADE</td>\n",
+       "      <td>240716</td>\n",
+       "      <td>2024-07-16</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>413885</td>\n",
+       "      <td>64297</td>\n",
+       "      <td>81558</td>\n",
+       "      <td>...</td>\n",
+       "      <td>50.4</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>65.9</td>\n",
+       "      <td>37.3</td>\n",
+       "      <td>(CONTRACTS OF 5,000 BUSHELS)</td>\n",
+       "      <td>001602</td>\n",
+       "      <td>CBT</td>\n",
+       "      <td>1</td>\n",
+       "      <td>A10</td>\n",
+       "      <td>FutOnly</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 191 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Market_and_Exchange_Names  As_of_Date_In_Form_YYMMDD  \\\n",
+       "0  WHEAT-SRW - CHICAGO BOARD OF TRADE                     240813   \n",
+       "1  WHEAT-SRW - CHICAGO BOARD OF TRADE                     240806   \n",
+       "2  WHEAT-SRW - CHICAGO BOARD OF TRADE                     240730   \n",
+       "3  WHEAT-SRW - CHICAGO BOARD OF TRADE                     240723   \n",
+       "4  WHEAT-SRW - CHICAGO BOARD OF TRADE                     240716   \n",
+       "\n",
+       "  Report_Date_as_YYYY-MM-DD CFTC_Contract_Market_Code CFTC_Market_Code  \\\n",
+       "0                2024-08-13                    001602             CBT    \n",
+       "1                2024-08-06                    001602             CBT    \n",
+       "2                2024-07-30                    001602             CBT    \n",
+       "3                2024-07-23                    001602             CBT    \n",
+       "4                2024-07-16                    001602             CBT    \n",
+       "\n",
+       "   CFTC_Region_Code  CFTC_Commodity_Code  Open_Interest_All  \\\n",
+       "0                 0                    1             401604   \n",
+       "1                 0                    1             431547   \n",
+       "2                 0                    1             432863   \n",
+       "3                 0                    1             421227   \n",
+       "4                 0                    1             413885   \n",
+       "\n",
+       "   Prod_Merc_Positions_Long_All  Prod_Merc_Positions_Short_All  ...  \\\n",
+       "0                         68899                          85867  ...   \n",
+       "1                         73401                          85750  ...   \n",
+       "2                         73086                          83875  ...   \n",
+       "3                         63636                          81374  ...   \n",
+       "4                         64297                          81558  ...   \n",
+       "\n",
+       "   Conc_Net_LE_4_TDR_Long_Other  Conc_Net_LE_4_TDR_Short_Other  \\\n",
+       "0                          39.0                           31.7   \n",
+       "1                          41.6                           32.3   \n",
+       "2                          46.0                           28.5   \n",
+       "3                          48.3                           27.9   \n",
+       "4                          50.4                           28.0   \n",
+       "\n",
+       "   Conc_Net_LE_8_TDR_Long_Other  Conc_Net_LE_8_TDR_Short_Other  \\\n",
+       "0                          54.2                           42.6   \n",
+       "1                          57.3                           41.7   \n",
+       "2                          60.8                           38.4   \n",
+       "3                          63.5                           37.7   \n",
+       "4                          65.9                           37.3   \n",
+       "\n",
+       "                 Contract_Units  CFTC_Contract_Market_Code_Quotes  \\\n",
+       "0  (CONTRACTS OF 5,000 BUSHELS)                            001602   \n",
+       "1  (CONTRACTS OF 5,000 BUSHELS)                            001602   \n",
+       "2  (CONTRACTS OF 5,000 BUSHELS)                            001602   \n",
+       "3  (CONTRACTS OF 5,000 BUSHELS)                            001602   \n",
+       "4  (CONTRACTS OF 5,000 BUSHELS)                            001602   \n",
+       "\n",
+       "   CFTC_Market_Code_Quotes  CFTC_Commodity_Code_Quotes  CFTC_SubGroup_Code  \\\n",
+       "0                     CBT                            1                 A10   \n",
+       "1                     CBT                            1                 A10   \n",
+       "2                     CBT                            1                 A10   \n",
+       "3                     CBT                            1                 A10   \n",
+       "4                     CBT                            1                 A10   \n",
+       "\n",
+       "   FutOnly_or_Combined  \n",
+       "0              FutOnly  \n",
+       "1              FutOnly  \n",
+       "2              FutOnly  \n",
+       "3              FutOnly  \n",
+       "4              FutOnly  \n",
+       "\n",
+       "[5 rows x 191 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "38311a58-d12d-49ae-9abb-a17bcc7f7a22",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Filter for rows where \"Market_and_Exchange_Names\" matches either of the specified values\n",
+    "silver_df = df[df[\"Market_and_Exchange_Names\"].isin([\"SILVER - COMMODITY EXCHANGE INC.\"])].copy()\n",
+    "\n",
+    "\n",
+    "# After filtering, you can standardize the \"Market_and_Exchange_Names\" if you want all of them to have the same name\n",
+    "# This is optional and based on your specific requirement to 'merge' under a unified label\n",
+    "silver_df[\"Market_and_Exchange_Names\"] = \"COPPER-GRADE #1 - COMMODITY EXCHANGE INC.\"\n",
+    "\n",
+    "silver_df[\"Report_Date_as_YYYY-MM-DD\"] = pd.to_datetime(df[\"Report_Date_as_YYYY-MM-DD\"], format='%Y-%m-%d')\n",
+    "silver_df = silver_df.set_index(\"Report_Date_as_YYYY-MM-DD\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "af7ce715-7958-48bd-bb4e-2dbb4ec50171",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(33, 190)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "silver_df.shape # we have calendar week 33"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "0c1b24aa-db20-4935-828b-c7ca9f4959e4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Market_and_Exchange_Names', 'As_of_Date_In_Form_YYMMDD', 'CFTC_Contract_Market_Code', 'CFTC_Market_Code', 'CFTC_Region_Code', 'CFTC_Commodity_Code', 'Open_Interest_All', 'Prod_Merc_Positions_Long_All', 'Prod_Merc_Positions_Short_All', 'Swap_Positions_Long_All', 'Swap__Positions_Short_All', 'Swap__Positions_Spread_All', 'M_Money_Positions_Long_All', 'M_Money_Positions_Short_All', 'M_Money_Positions_Spread_All', 'Other_Rept_Positions_Long_All', 'Other_Rept_Positions_Short_All', 'Other_Rept_Positions_Spread_All', 'Tot_Rept_Positions_Long_All', 'Tot_Rept_Positions_Short_All', 'NonRept_Positions_Long_All', 'NonRept_Positions_Short_All', 'Open_Interest_Old', 'Prod_Merc_Positions_Long_Old', 'Prod_Merc_Positions_Short_Old', 'Swap_Positions_Long_Old', 'Swap__Positions_Short_Old', 'Swap__Positions_Spread_Old', 'M_Money_Positions_Long_Old', 'M_Money_Positions_Short_Old', 'M_Money_Positions_Spread_Old', 'Other_Rept_Positions_Long_Old', 'Other_Rept_Positions_Short_Old', 'Other_Rept_Positions_Spread_Old', 'Tot_Rept_Positions_Long_Old', 'Tot_Rept_Positions_Short_Old', 'NonRept_Positions_Long_Old', 'NonRept_Positions_Short_Old', 'Open_Interest_Other', 'Prod_Merc_Positions_Long_Other', 'Prod_Merc_Positions_Short_Other', 'Swap_Positions_Long_Other', 'Swap__Positions_Short_Other', 'Swap__Positions_Spread_Other', 'M_Money_Positions_Long_Other', 'M_Money_Positions_Short_Other', 'M_Money_Positions_Spread_Other', 'Other_Rept_Positions_Long_Other', 'Other_Rept_Positions_Short_Other', 'Other_Rept_Positions_Spread_Other', 'Tot_Rept_Positions_Long_Other', 'Tot_Rept_Positions_Short_Other', 'NonRept_Positions_Long_Other', 'NonRept_Positions_Short_Other', 'Change_in_Open_Interest_All', 'Change_in_Prod_Merc_Long_All', 'Change_in_Prod_Merc_Short_All', 'Change_in_Swap_Long_All', 'Change_in_Swap_Short_All', 'Change_in_Swap_Spread_All', 'Change_in_M_Money_Long_All', 'Change_in_M_Money_Short_All', 'Change_in_M_Money_Spread_All', 'Change_in_Other_Rept_Long_All', 'Change_in_Other_Rept_Short_All', 'Change_in_Other_Rept_Spread_All', 'Change_in_Tot_Rept_Long_All', 'Change_in_Tot_Rept_Short_All', 'Change_in_NonRept_Long_All', 'Change_in_NonRept_Short_All', 'Pct_of_Open_Interest_All', 'Pct_of_OI_Prod_Merc_Long_All', 'Pct_of_OI_Prod_Merc_Short_All', 'Pct_of_OI_Swap_Long_All', 'Pct_of_OI_Swap_Short_All', 'Pct_of_OI_Swap_Spread_All', 'Pct_of_OI_M_Money_Long_All', 'Pct_of_OI_M_Money_Short_All', 'Pct_of_OI_M_Money_Spread_All', 'Pct_of_OI_Other_Rept_Long_All', 'Pct_of_OI_Other_Rept_Short_All', 'Pct_of_OI_Other_Rept_Spread_All', 'Pct_of_OI_Tot_Rept_Long_All', 'Pct_of_OI_Tot_Rept_Short_All', 'Pct_of_OI_NonRept_Long_All', 'Pct_of_OI_NonRept_Short_All', 'Pct_of_Open_Interest_Old', 'Pct_of_OI_Prod_Merc_Long_Old', 'Pct_of_OI_Prod_Merc_Short_Old', 'Pct_of_OI_Swap_Long_Old', 'Pct_of_OI_Swap_Short_Old', 'Pct_of_OI_Swap_Spread_Old', 'Pct_of_OI_M_Money_Long_Old', 'Pct_of_OI_M_Money_Short_Old', 'Pct_of_OI_M_Money_Spread_Old', 'Pct_of_OI_Other_Rept_Long_Old', 'Pct_of_OI_Other_Rept_Short_Old', 'Pct_of_OI_Other_Rept_Spread_Old', 'Pct_of_OI_Tot_Rept_Long_Old', 'Pct_of_OI_Tot_Rept_Short_Old', 'Pct_of_OI_NonRept_Long_Old', 'Pct_of_OI_NonRept_Short_Old', 'Pct_of_Open_Interest_Other', 'Pct_of_OI_Prod_Merc_Long_Other', 'Pct_of_OI_Prod_Merc_Short_Other', 'Pct_of_OI_Swap_Long_Other', 'Pct_of_OI_Swap_Short_Other', 'Pct_of_OI_Swap_Spread_Other', 'Pct_of_OI_M_Money_Long_Other', 'Pct_of_OI_M_Money_Short_Other', 'Pct_of_OI_M_Money_Spread_Other', 'Pct_of_OI_Other_Rept_Long_Other', 'Pct_of_OI_Other_Rept_Short_Other', 'Pct_of_OI_Other_Rept_Spread_Other', 'Pct_of_OI_Tot_Rept_Long_Other', 'Pct_of_OI_Tot_Rept_Short_Other', 'Pct_of_OI_NonRept_Long_Other', 'Pct_of_OI_NonRept_Short_Other', 'Traders_Tot_All', 'Traders_Prod_Merc_Long_All', 'Traders_Prod_Merc_Short_All', 'Traders_Swap_Long_All', 'Traders_Swap_Short_All', 'Traders_Swap_Spread_All', 'Traders_M_Money_Long_All', 'Traders_M_Money_Short_All', 'Traders_M_Money_Spread_All', 'Traders_Other_Rept_Long_All', 'Traders_Other_Rept_Short_All', 'Traders_Other_Rept_Spread_All', 'Traders_Tot_Rept_Long_All', 'Traders_Tot_Rept_Short_All', 'Traders_Tot_Old', 'Traders_Prod_Merc_Long_Old', 'Traders_Prod_Merc_Short_Old', 'Traders_Swap_Long_Old', 'Traders_Swap_Short_Old', 'Traders_Swap_Spread_Old', 'Traders_M_Money_Long_Old', 'Traders_M_Money_Short_Old', 'Traders_M_Money_Spread_Old', 'Traders_Other_Rept_Long_Old', 'Traders_Other_Rept_Short_Old', 'Traders_Other_Rept_Spread_Old', 'Traders_Tot_Rept_Long_Old', 'Traders_Tot_Rept_Short_Old', 'Traders_Tot_Other', 'Traders_Prod_Merc_Long_Other', 'Traders_Prod_Merc_Short_Other', 'Traders_Swap_Long_Other', 'Traders_Swap_Short_Other', 'Traders_Swap_Spread_Other', 'Traders_M_Money_Long_Other', 'Traders_M_Money_Short_Other', 'Traders_M_Money_Spread_Other', 'Traders_Other_Rept_Long_Other', 'Traders_Other_Rept_Short_Other', 'Traders_Other_Rept_Spread_Other', 'Traders_Tot_Rept_Long_Other', 'Traders_Tot_Rept_Short_Other', 'Conc_Gross_LE_4_TDR_Long_All', 'Conc_Gross_LE_4_TDR_Short_All', 'Conc_Gross_LE_8_TDR_Long_All', 'Conc_Gross_LE_8_TDR_Short_All', 'Conc_Net_LE_4_TDR_Long_All', 'Conc_Net_LE_4_TDR_Short_All', 'Conc_Net_LE_8_TDR_Long_All', 'Conc_Net_LE_8_TDR_Short_All', 'Conc_Gross_LE_4_TDR_Long_Old', 'Conc_Gross_LE_4_TDR_Short_Old', 'Conc_Gross_LE_8_TDR_Long_Old', 'Conc_Gross_LE_8_TDR_Short_Old', 'Conc_Net_LE_4_TDR_Long_Old', 'Conc_Net_LE_4_TDR_Short_Old', 'Conc_Net_LE_8_TDR_Long_Old', 'Conc_Net_LE_8_TDR_Short_Old', 'Conc_Gross_LE_4_TDR_Long_Other', 'Conc_Gross_LE_4_TDR_Short_Other', 'Conc_Gross_LE_8_TDR_Long_Other', 'Conc_Gross_LE_8_TDR_Short_Other', 'Conc_Net_LE_4_TDR_Long_Other', 'Conc_Net_LE_4_TDR_Short_Other', 'Conc_Net_LE_8_TDR_Long_Other', 'Conc_Net_LE_8_TDR_Short_Other', 'Contract_Units', 'CFTC_Contract_Market_Code_Quotes', 'CFTC_Market_Code_Quotes', 'CFTC_Commodity_Code_Quotes', 'CFTC_SubGroup_Code', 'FutOnly_or_Combined']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(list(silver_df.columns))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "b30a8b94-6388-4476-a008-8e69959cfbb9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Pct_of_Open_Interest_Old',\n",
+       " 'Pct_of_OI_Prod_Merc_Long_Old',\n",
+       " 'Pct_of_OI_Prod_Merc_Short_Old',\n",
+       " 'Pct_of_OI_Swap_Long_Old',\n",
+       " 'Pct_of_OI_Swap_Short_Old',\n",
+       " 'Pct_of_OI_Swap_Spread_Old',\n",
+       " 'Pct_of_OI_M_Money_Long_Old',\n",
+       " 'Pct_of_OI_M_Money_Short_Old',\n",
+       " 'Pct_of_OI_M_Money_Spread_Old',\n",
+       " 'Pct_of_OI_Other_Rept_Long_Old',\n",
+       " 'Pct_of_OI_Other_Rept_Short_Old',\n",
+       " 'Pct_of_OI_Other_Rept_Spread_Old',\n",
+       " 'Pct_of_OI_Tot_Rept_Long_Old',\n",
+       " 'Pct_of_OI_Tot_Rept_Short_Old',\n",
+       " 'Pct_of_OI_NonRept_Long_Old',\n",
+       " 'Pct_of_OI_NonRept_Short_Old']"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "open_interest_pct_old_columns = [col for col in df.columns if 'pct' in col.lower() and col.endswith('_Old')]\n",
+    "open_interest_pct_old_columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7f04ca58-7f5b-4cef-9941-620067cd8751",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "needed_columns = [\"Open_Interest_All\", \"Pct_of_OI_Prod_Merc_Long_Old\", \"Pct_of_OI_Prod_Merc_Short_Old\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "a862cbe7-49c8-43b1-ba34-a87f37b40daa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Open_Interest_All</th>\n",
+       "      <th>Pct_of_OI_Prod_Merc_Long_Old</th>\n",
+       "      <th>Pct_of_OI_Prod_Merc_Short_Old</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Report_Date_as_YYYY-MM-DD</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2024-08-13</th>\n",
+       "      <td>147859</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>25.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2024-08-06</th>\n",
+       "      <td>147537</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>25.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2024-07-30</th>\n",
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+       "      <td>2.7</td>\n",
+       "      <td>25.4</td>\n",
+       "    </tr>\n",
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+       "      <th>2024-07-23</th>\n",
+       "      <td>157106</td>\n",
+       "      <td>2.2</td>\n",
+       "      <td>25.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2024-07-16</th>\n",
+       "      <td>166641</td>\n",
+       "      <td>1.7</td>\n",
+       "      <td>26.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           Open_Interest_All  Pct_of_OI_Prod_Merc_Long_Old  \\\n",
+       "Report_Date_as_YYYY-MM-DD                                                    \n",
+       "2024-08-13                            147859                           3.1   \n",
+       "2024-08-06                            147537                           3.0   \n",
+       "2024-07-30                            151437                           2.7   \n",
+       "2024-07-23                            157106                           2.2   \n",
+       "2024-07-16                            166641                           1.7   \n",
+       "\n",
+       "                           Pct_of_OI_Prod_Merc_Short_Old  \n",
+       "Report_Date_as_YYYY-MM-DD                                 \n",
+       "2024-08-13                                          25.3  \n",
+       "2024-08-06                                          25.4  \n",
+       "2024-07-30                                          25.4  \n",
+       "2024-07-23                                          25.8  \n",
+       "2024-07-16                                          26.0  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "filtered_silver_df = silver_df[needed_columns].copy()\n",
+    "filtered_silver_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "106e2cd2-8c1a-407e-9c1d-94301b3261e7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac29c5fd-e220-4c6c-9366-ce3349a71385",
+   "metadata": {},
+   "source": [
+    "## Open Interest (COT) CFTC"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "6c517b33-fae5-44f2-be07-00b7e9a65cac",
+   "metadata": {},
+   "outputs": [
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Data: Open Interest Over Time (Silver)\"},\"yaxis\":{\"title\":{\"text\":\"Open Interest\"}},\"xaxis\":{\"title\":{\"text\":\"Date\"},\"tickformat\":\"%d %b %Y\",\"tickangle\":45,\"dtick\":\"M1\",\"ticklabelmode\":\"period\"},\"height\":600,\"width\":800,\"hovermode\":\"x unified\"},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
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+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Metrics for Open Interest:\n",
+      "Volatility (Standard Deviation): 15889.35\n",
+      "Average: 158040.03\n",
+      "Median: 157106.00\n",
+      "Minimum: 131956.00\n",
+      "Maximum: 186945.00\n",
+      "Typical Range: 146584.00 to 171371.00\n",
+      "\n",
+      "Overall trend: Downward\n",
+      "\n",
+      "Significant points:\n",
+      "Peak on 4: 166641.00\n",
+      "Peak on 12: 186945.00\n",
+      "Peak on 17: 175784.00\n",
+      "Peak on 26: 152544.00\n",
+      "Peak on 29: 138617.00\n",
+      "Trough on 6: 154724.00\n",
+      "Trough on 14: 161868.00\n",
+      "Trough on 23: 141026.00\n",
+      "Trough on 28: 136544.00\n",
+      "Trough on 30: 131956.00\n",
+      "\n",
+      "Sudden changes (>5% day-to-day):\n",
+      "2024-07-16 00:00:00: 6.07% change\n",
+      "2024-07-02 00:00:00: -5.22% change\n",
+      "2024-06-25 00:00:00: 7.59% change\n",
+      "2024-06-18 00:00:00: 6.09% change\n",
+      "2024-05-14 00:00:00: -8.33% change\n",
+      "2024-05-07 00:00:00: -5.55% change\n",
+      "2024-04-23 00:00:00: 5.67% change\n",
+      "2024-03-12 00:00:00: -5.63% change\n",
+      "2024-01-30 00:00:00: -7.32% change\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import plotly.graph_objects as go\n",
+    "import numpy as np\n",
+    "from scipy import signal\n",
+    "\n",
+    "# Assuming df is your DataFrame with the COT data\n",
+    "# If not, you'll need to load your data here\n",
+    "\n",
+    "# Create the main figure\n",
+    "fig = go.Figure()\n",
+    "\n",
+    "# Add trace for Open Interest\n",
+    "fig.add_trace(go.Scatter(\n",
+    "    x=filtered_silver_df.index, \n",
+    "    y=filtered_silver_df['Open_Interest_All'], \n",
+    "    mode='lines',\n",
+    "    name='Open Interest',\n",
+    "    line=dict(width=2, color='blue')\n",
+    "))\n",
+    "\n",
+    "# Update layout\n",
+    "fig.update_layout(\n",
+    "    title='COT Data: Open Interest Over Time (Silver)',\n",
+    "    yaxis_title='Open Interest',\n",
+    "    xaxis_title='Date',\n",
+    "    height=600,\n",
+    "    width=800,\n",
+    "    hovermode='x unified'\n",
+    ")\n",
+    "\n",
+    "# Improve date labeling for better readability\n",
+    "fig.update_xaxes(\n",
+    "    tickformat=\"%d %b %Y\",\n",
+    "    tickangle=45,\n",
+    "    dtick=\"M1\",\n",
+    "    ticklabelmode=\"period\"\n",
+    ")\n",
+    "\n",
+    "# Show the plot\n",
+    "fig.show()\n",
+    "\n",
+    "# Calculate and print metrics\n",
+    "print(\"\\nMetrics for Open Interest:\")\n",
+    "data = filtered_silver_df['Open_Interest_All']\n",
+    "\n",
+    "print(f\"Volatility (Standard Deviation): {data.std():.2f}\")\n",
+    "print(f\"Average: {data.mean():.2f}\")\n",
+    "print(f\"Median: {data.median():.2f}\")\n",
+    "print(f\"Minimum: {data.min():.2f}\")\n",
+    "print(f\"Maximum: {data.max():.2f}\")\n",
+    "\n",
+    "# Calculate typical range\n",
+    "typical_low = np.percentile(data, 25)\n",
+    "typical_high = np.percentile(data, 75)\n",
+    "print(f\"Typical Range: {typical_low:.2f} to {typical_high:.2f}\")\n",
+    "\n",
+    "# Identify trends\n",
+    "def identify_trend(series):\n",
+    "    # Calculate the overall trend\n",
+    "    trend = np.polyfit(range(len(series)), series, 1)[0]\n",
+    "    if trend > 0:\n",
+    "        return \"Upward\"\n",
+    "    elif trend < 0:\n",
+    "        return \"Downward\"\n",
+    "    else:\n",
+    "        return \"Stable\"\n",
+    "\n",
+    "trend = identify_trend(data)\n",
+    "print(f\"\\nOverall trend: {trend}\")\n",
+    "\n",
+    "# Identify significant points\n",
+    "def find_peaks(series, prominence=1000):\n",
+    "    peaks, _ = signal.find_peaks(series, prominence=prominence)\n",
+    "    troughs, _ = signal.find_peaks(-series, prominence=prominence)\n",
+    "    return peaks, troughs\n",
+    "\n",
+    "peaks, troughs = find_peaks(data)\n",
+    "\n",
+    "print(\"\\nSignificant points:\")\n",
+    "for peak in peaks:\n",
+    "    print(f\"Peak on {df.index[peak]}: {data.iloc[peak]:.2f}\")\n",
+    "for trough in troughs:\n",
+    "    print(f\"Trough on {df.index[trough]}: {data.iloc[trough]:.2f}\")\n",
+    "\n",
+    "# Identify sudden changes\n",
+    "pct_change = data.pct_change()\n",
+    "sudden_changes = pct_change[abs(pct_change) > 0.05]  # 5% threshold\n",
+    "if not sudden_changes.empty:\n",
+    "    print(\"\\nSudden changes (>5% day-to-day):\")\n",
+    "    for date, change in sudden_changes.items():\n",
+    "        print(f\"{date}: {change*100:.2f}% change\")\n",
+    "else:\n",
+    "    print(\"\\nNo sudden changes above 5% threshold detected.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce80decc-23b4-4ae5-b112-1e433440a05f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ede29b5a-eb59-448c-a7d6-bba51d6dee84",
+   "metadata": {},
+   "source": [
+    "## Data Export for AmiBroker\n",
+    "\n",
+    "(You have to tick the box \"No quotation data\" in the Import wizard and select the fields according to the CSV header)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "d7d3aae5-7043-409e-b5ae-0aed4a3b4de4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data exported to silver_data_for_amibroker.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "def export_to_amibroker_csv(df, output_file='amibroker_data.csv'):\n",
+    "    # Create a copy of the DataFrame to avoid modifying the original\n",
+    "    export_df = df.copy()\n",
+    "    \n",
+    "    # Reset the index to make the date a column\n",
+    "    export_df = export_df.reset_index()\n",
+    "    \n",
+    "    # Rename columns to match AmiBroker format\n",
+    "    export_df['Date'] = pd.to_datetime(export_df['Report_Date_as_YYYY-MM-DD'])\n",
+    "    export_df['Close'] = export_df['Open_Interest_All']\n",
+    "    export_df['Volume'] = export_df['Pct_of_OI_Prod_Merc_Long_Old']\n",
+    "    \n",
+    "    # Create Open, High, Low columns with the same value as Close\n",
+    "    export_df['Open'] = export_df['Close']\n",
+    "    export_df['High'] = export_df['Close']\n",
+    "    export_df['Low'] = export_df['Close']\n",
+    "    \n",
+    "    # Select and order columns for AmiBroker\n",
+    "    amibroker_df = export_df[['Date', 'Open', 'High', 'Low', 'Close', 'Volume']]\n",
+    "    \n",
+    "    # Sort by date in descending order (most recent first)\n",
+    "    amibroker_df = amibroker_df.sort_values('Date', ascending=False)\n",
+    "    \n",
+    "    # Export to CSV\n",
+    "    amibroker_df.to_csv(output_file, index=False, date_format='%Y-%m-%d')\n",
+    "    print(f\"Data exported to {output_file}\")\n",
+    "\n",
+    "# Usage\n",
+    "export_to_amibroker_csv(filtered_silver_df, 'silver_data_for_amibroker.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2044602a-9024-4522-bc15-ef8903c28758",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
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+   "file_extension": ".py",
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+   "name": "python",
+   "nbconvert_exporter": "python",
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+ "nbformat": 4,
+ "nbformat_minor": 5
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