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-rw-r--r--python/notebooks/Realized Vol.ipynb165
1 files changed, 10 insertions, 155 deletions
diff --git a/python/notebooks/Realized Vol.ipynb b/python/notebooks/Realized Vol.ipynb
index 464b14d6..cfa46012 100644
--- a/python/notebooks/Realized Vol.ipynb
+++ b/python/notebooks/Realized Vol.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -18,24 +18,9 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "b7808ffade83485bba8f589bedb10f68",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Dropdown(description='Index:', options=('IG', 'HY'), value='IG')"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"w = widgets.Dropdown(\n",
" options=['IG', 'HY'],\n",
@@ -48,7 +33,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -59,157 +44,27 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "4dfbcdf09a294dc781ad1a5b4c382c96",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "<matplotlib.axes._subplots.AxesSubplot at 0x7fe3eb2ad390>"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"onTR.plot()"
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<caption>Constant Mean - GARCH Model Results</caption>\n",
- "<tr>\n",
- " <th>Dep. Variable:</th> <td>spread_return</td> <th> R-squared: </th> <td> -0.001</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Mean Model:</th> <td>Constant Mean</td> <th> Adj. R-squared: </th> <td> -0.001</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Vol Model:</th> <td>GARCH</td> <th> Log-Likelihood: </th> <td> 94.1921</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Distribution:</th> <td>Normal</td> <th> AIC: </th> <td> -180.384</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Method:</th> <td>Maximum Likelihood</td> <th> BIC: </th> <td> -161.947</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th></th> <td></td> <th> No. Observations: </th> <td>742</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Date:</th> <td>Wed, Sep 11 2019</td> <th> Df Residuals: </th> <td>738</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Time:</th> <td>10:44:17</td> <th> Df Model: </th> <td>4</td> \n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<caption>Mean Model</caption>\n",
- "<tr>\n",
- " <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>95.0% Conf. Int.</th> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>mu</th> <td> -0.0178</td> <td>7.408e-03</td> <td> -2.400</td> <td>1.641e-02</td> <td>[-3.230e-02,-3.258e-03]</td>\n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<caption>Volatility Model</caption>\n",
- "<tr>\n",
- " <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>95.0% Conf. Int.</th> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>omega</th> <td>3.6040e-03</td> <td>1.414e-03</td> <td> 2.548</td> <td>1.082e-02</td> <td>[8.322e-04,6.376e-03]</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>alpha[1]</th> <td> 0.1348</td> <td>4.345e-02</td> <td> 3.103</td> <td>1.914e-03</td> <td>[4.968e-02, 0.220]</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>beta[1]</th> <td> 0.7960</td> <td>5.441e-02</td> <td> 14.631</td> <td>1.774e-48</td> <td>[ 0.689, 0.903]</td> \n",
- "</tr>\n",
- "</table><br/><br/>Covariance estimator: robust"
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.summary.Summary'>\n",
- "\"\"\"\n",
- " Constant Mean - GARCH Model Results \n",
- "==============================================================================\n",
- "Dep. Variable: spread_return R-squared: -0.001\n",
- "Mean Model: Constant Mean Adj. R-squared: -0.001\n",
- "Vol Model: GARCH Log-Likelihood: 94.1921\n",
- "Distribution: Normal AIC: -180.384\n",
- "Method: Maximum Likelihood BIC: -161.947\n",
- " No. Observations: 742\n",
- "Date: Wed, Sep 11 2019 Df Residuals: 738\n",
- "Time: 10:44:17 Df Model: 4\n",
- " Mean Model \n",
- "==============================================================================\n",
- " coef std err t P>|t| 95.0% Conf. Int.\n",
- "------------------------------------------------------------------------------\n",
- "mu -0.0178 7.408e-03 -2.400 1.641e-02 [-3.230e-02,-3.258e-03]\n",
- " Volatility Model \n",
- "============================================================================\n",
- " coef std err t P>|t| 95.0% Conf. Int.\n",
- "----------------------------------------------------------------------------\n",
- "omega 3.6040e-03 1.414e-03 2.548 1.082e-02 [8.322e-04,6.376e-03]\n",
- "alpha[1] 0.1348 4.345e-02 3.103 1.914e-03 [4.968e-02, 0.220]\n",
- "beta[1] 0.7960 5.441e-02 14.631 1.774e-48 [ 0.689, 0.903]\n",
- "============================================================================\n",
- "\n",
- "Covariance estimator: robust\n",
- "\"\"\""
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.summary()"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "ename": "NameError",
- "evalue": "name 'df' is not defined",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m-----------------------------------------------------------\u001b[0m",
- "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m<ipython-input-6-bc681e92175e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#compute lo and hi percentiles of atm volatility daily change (vol of vol)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mrvol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvol_var\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[0;32m~/projects/code/python/exploration/option_trades.py\u001b[0m in \u001b[0;36mvol_var\u001b[0;34m(percentile, index, start_date)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mwe\u001b[0m \u001b[0mshould\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0mit\u001b[0m \u001b[0mby\u001b[0m \u001b[0mseries\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 112\u001b[0m \"\"\"\n\u001b[0;32m--> 113\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0matm_vol\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstart_date\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 114\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrolling_vol\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mterm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 115\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;32m~/projects/code/python/exploration/option_trades.py\u001b[0m in \u001b[0;36matm_vol\u001b[0;34m(index, date, series, moneyness)\u001b[0m\n\u001b[1;32m 87\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0matm_vol\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mseries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmoneyness\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 89\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0matm_vol_calc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmoneyness\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 90\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 91\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrolling_vol\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'atm_vol'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mterm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mNameError\u001b[0m: name 'df' is not defined"
- ]
- }
- ],
+ "outputs": [],
"source": [
"#compute lo and hi percentiles of atm volatility daily change (vol of vol)\n",
"rvol.vol_var()"
generated by cgit v1.2.3-70-g09d2 (git 2.52.0) at 2025-12-21 22:48:31 +0000