Merge pull request #411 from quantopian/fix_nbs

Fix example notebooks

Author: twiecki

pyfolio/examples/Fama-French Benchmark.ipynb

@@ -4,18 +4,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Bayesian performance analysis example in pyfolio"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "There are also a few more advanced (and still experimental) analysis methods in pyfolio based on Bayesian statistics. \n",
+    "# Bayesian performance analysis example in pyfolio\n",
+    "\n",
+    "There are a few advanced analysis methods in pyfolio based on Bayesian statistics. \n",
     "\n",
-    "The main benefit of these methods is **uncertainty quantification**. All the values you saw above, like the Sharpe ratio, are just single numbers. These estimates are noisy because they have been computed over a limited number of data points. So how much can you trust these numbers? You don't know because there is no sense of uncertainty. That is where Bayesian statistics helps as instead of single values, we are dealing with probability distributions that assign degrees of belief to all possible parameter values.\n",
+    "The main benefit of these methods is **uncertainty quantification**. All the traditional measures of performance, like the Sharpe ratio, are just single numbers. These estimates are noisy because they have been computed over a limited number of data points. So how much can you trust these numbers? You don't know because there is no sense of uncertainty. That is where Bayesian statistics helps as instead of single values, we are dealing with probability distributions that assign degrees of belief to all possible parameter values.\n",
     "\n",
-    "Lets create the Bayesian tear sheet. Under the hood this is running MCMC sampling in [`PyMC3`](http://pymc-devs.github.io/pymc3/) to estimate the posteriors which can take quite a while (that's the reason why we don't generate this by default in `create_full_tear_sheet()`)."
+    "Lets create the Bayesian tear sheet. Under the hood this is running MCMC sampling in [PyMC3](http://pymc-devs.github.io/pymc3/) to estimate the posteriors which can take quite a while (that's the reason why we don't generate this by default in `create_full_tear_sheet`)."
    ]
   },
   {
@@ -181,7 +176,7 @@
    "source": [
     "## Running models directly\n",
     "\n",
-    "You can also run individual models. All models can be found in `pyfolio.bayesian` and run via the `run_model()` function."
+    "You can also run individual models. All models can be found in `pyfolio.bayesian` and run via the `run_model` function."
    ]
   },
   {
@@ -335,27 +330,27 @@
     "* [A blog post about the Bayesian models with Sepideh Sadeghi](http://blog.quantopian.com/bayesian-cone/)\n",
     "* [My personal blog on Bayesian modeling](http://twiecki.github.io/)\n",
     "* A talk I gave in Singapore on [Probabilistic Programming in Quantitative Finance]( http://blog.quantopian.com/probabilistic-programming-for-non-statisticians/)\n",
-    "* The IPython NB book [Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)."
+    "* A series of IPython notebooks on [Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)."
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "python3"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3
+    "version": 2
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "pygments_lexer": "ipython2",
+   "version": "2.7.13"
   }
  },
  "nbformat": 4,

pyfolio/examples/bayesian.ipynb

@@ -1,5 +1,14 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Full Tear Sheet Example\n",
+    "\n",
+    "_**Note:**_ Please run this notebook in [Quantopian Research](https://www.quantopian.com/notebooks)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -169,9 +178,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.10"
+   "version": "2.7.13"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}