Fama-French alpha beta #182
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Posterior PDF for log(sigma) and log(nu). Also plots the stochastic volatility on top of the returns.
Explain the 8th and 9th rows in the Bayesian ipython notebook demonstrating the tear sheet. Also, a few grammatical edits to the rest of the Bayesian notebook. Reset spy.csv
Add a line to gitignore so that new notebook checkpoints are ignored.
Time to complete each model and plot is printed as each task is completed.
Stochastic volatility model takes as much time to run as rest of models combined, so turn it off by default.
Use only the most recent 400 days of returns.
I wasn’t quite finished running the Bayesian IPython notebook when I last pushed, apparently.
df_train is unchanged if the user wants to run the stochastic volatility model.
Linear regression to obtain initial guesses for alpha and beta is failing due to NaNs present in the benchmark data.
I think this generalization of alpha_beta to regress on multiple betas should work, but I haven’t tested it at all yet. Will do so in a few hours.
Getting a TypeError when executing start = pm.find_MAP(fmin=sp.optimize.fmin_powell).
alpha beta plot uses S&P500 by default, but users can specify benchmark_rets=“Fama-French” to show alpha and betas for Fama-French risk factors instead.
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Fama-French model can be used as a benchmark for alpha beta plots in the Bayesian tear sheet. I think this code is ready to be implemented on quantopian:master. |
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| These are new features and improvements of note in each release. | |||
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| ## v0.3 (TBA) | |||
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Still some problems with this branch not being up-to-date. Maybe redo this PR off of a clean master, or try rebasing.
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Looks great @sbussmann (but see minor comments). The main issue are the git problems so you might have to start from a fresh master with this. |
Linear regression to obtain initial guesses for alpha and beta is failing due to NaNs present in the benchmark data.
I think this generalization of alpha_beta to regress on multiple betas should work, but I haven’t tested it at all yet. Will do so in a few hours.
Getting a TypeError when executing start = pm.find_MAP(fmin=sp.optimize.fmin_powell).
alpha beta plot uses S&P500 by default, but users can specify benchmark_rets=“Fama-French” to show alpha and betas for Fama-French risk factors instead.
…a-french-alpha-beta Conflicts: pyfolio/bayesian.py pyfolio/examples/bayesian.ipynb pyfolio/tears.py
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I brought this branch up to date with quantopian:master and addressed the minor comments. Hope it's in good shape now! |
| elif benchmark_rets == 'Fama-French': | ||
| fama_french = True | ||
| rolling_window = utils.APPROX_BDAYS_PER_MONTH * 6 | ||
| benchmark_rets = timeseries.rolling_fama_french( |
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Merged
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Closing in favor of #200. |
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Adds Fama-French benchmark to alpha and beta plots in Bayesian tear sheet.
Not currently functional. Line 106:
start = pm.find_MAP(fmin=sp.optimize.fmin_powell)
fails with the following TypeError:
TypeError: Ambiguous name: beta - please check the names of the inputs of your function for duplicates.
I might need some help to debug this one.