Alphapy

This release connects models with systems for **MarketFlow**, i.e., you can now use the probabilities generated by a classifier as trading signals. For example:

~~~~
system:
name : alpha
holdperiod : 0
longentry : phigh_0.6
longexit :
shortentry :
shortexit :
scale : False
~~~~

The variables **phigh** and **plow** are variables defined by *AlphaPy*. For example, if the probability associated with a time series prediction is greater than or equal to 0.6, then the system would go long. Likewise, a short entry might have a value of *plow_0.4*, meaning the probability is less than or equal to 0.4.

This release also fixes a bug with **'.'** in variable names, such as the examples shown above.

The **market** section of the *market.yml* has been changed to add the fields **create_model** and **data_fractal** (**resample_data** has been removed). If **fractal** is different than the **data_fractal**, then the data are resampled to the *fractal* value. Set **create_model** to *False* if you wish to test different systems after creating your initial model, or if your systems are free-standing and don't use the output of a model.

~~~~
market:
create_model : True
data_fractal : 1min
data_history : 100
forecast_period : 1
fractal : 20min
lag_period : 1
leaders : []
predict_history : 50
schema : data
subject : crypto
target_group : btc
~~~~

Finally, there is now one general system for both daily and intraday systems. Intraday signals are automatically closed at the end of the day. All systems follow the format shown above, and you can mix model-based signals with technical signals.

Support has been added for **Quandl** data (15) using the pandas Web data reader, e.g., you can now specify *quandl_wiki* in the schema field. Note that WIKI is a source of free end-of-day stock data from Quandl, but its data history is limited. Regarding the state of Google and Yahoo stock data, AlphaPy can still get intraday data from Google, but end-of-day data is no longer available from Google. Getting end-of-day stock data from Yahoo is sporadic, so we recommend a paid provider for consistency.

You can now drop files into the *data* directory: intraday data, daily data, or any other regular time series. Intraday data must have a separate *date* and *time* column, along with the OHLCV columns. Daily data and higher requires only the *date* column. To use local data, specify *schema: data* in the *market.yml* file. The file names must conform to the convention: *symbol_subject_schema_fractal.csv*, e.g., aapl_stock_data_1d.csv.

We added a new *crypto* subject to test out AlphaPy on cryptocurrency data. We will contribute another tutorial shortly for testing an open range breakout system on *btc_crypto_data_1min.csv*. Note that fractals now conform to Pandas series offsets if the user chooses to resample from the original data (16).

This release contains the following features:

1. Sequence-to-Sequence Input and Output (Issue 9)
2. Date-Stamped Train and Test Files (Issue 10)
3. Expanded Logging for Data Feeds

Bug release version for fixing daily data access. Yahoo is no longer providing daily quotes, so we switched to Google Finance.

First release of AlphaPy