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DOC Markdown fixes to release announcement.

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Thomas Wiecki
2015-02-13 13:51:59 +01:00
parent 1a51ff1ee9
commit bab3d9e731
1 changed files with 29 additions and 34 deletions
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docs/release-notes/zipline-0.7.1.md
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## Bug Fixes (BUG)
* Fix a bug where the reported returns could sharply dip for random periods of
time. [PR378](https://github.com/quantopian/zipline/pull/378)
### Fix a bug where the reported returns could sharply dip for random periods of time. [PR378](https://github.com/quantopian/zipline/pull/378)
## Enhancements (ENH)
* Account object: Adds an account object to conext to track information about
the trading account. [PR396](https://github.com/quantopian/zipline/pull/396)
### Account object: Adds an account object to conext to track information about the trading account. [PR396](https://github.com/quantopian/zipline/pull/396)
> Example:
@@ -19,8 +17,7 @@
> Returns the settled cash value that is stored on the account object. This
> value is updated accordingly as the algorithm is run.
* HistoryContainer can now grow
dynamically. [PR412](https://github.com/quantopian/zipline/pull/412)
### HistoryContainer can now grow dynamically. [PR412](https://github.com/quantopian/zipline/pull/412)
> Calls to `history` will now be able to increase the size or change the shape
> of the history container to be able to service the call. `add_history` now
@@ -28,8 +25,7 @@
> container. This change is backwards compatible with `history`, all existing
> algorithms should continue to work as intended.
* Simple transforms ported from quantopian and use history.
[PR429](https://github.com/quantopian/zipline/pull/429)
### Simple transforms ported from quantopian and use history. [PR429](https://github.com/quantopian/zipline/pull/429)
> SIDData now has methods for:
@@ -45,13 +41,12 @@
> return the daily returns of the given security.
> Example:
> ```
> # The standard deviation of the price in the last 3 days.
> data[security].stdev(3)
> ```
```python
# The standard deviation of the price in the last 3 days.
data[security].stdev(3)
```
* New fields in Performance Period
[PR464](https://github.com/quantopian/zipline/pull/464)
### New fields in Performance Period [PR464](https://github.com/quantopian/zipline/pull/464)
> Performance Period has new fields accessible in return value of to_dict:
@@ -62,29 +57,29 @@
> - shorts count
> - longs count
* Allow order_percent to work with various market values (by Jeremiah Lowin)
[PR477](https://github.com/quantopian/zipline/pull/477)
> Currently, `order_percent()` and `order_target_percent()` both operate as a percentage of `self.portfolio.portfolio_value`. This PR lets them operate as percentages of other important MVs.
### Allow order_percent to work with various market values (by Jeremiah Lowin) [PR477](https://github.com/quantopian/zipline/pull/477)
> Also adds `context.get_market_value()`, which enables this functionality.
> Currently, `order_percent()` and `order_target_percent()` both operate as a percentage of `self.portfolio.portfolio_value`. This PR lets them operate as percentages of other important MVs.
> For example:
> ```python
> # this is how it works today (and this still works)
> # put 50% of my portfolio in AAPL
> order_percent('AAPL', 0.5)
> # note that if this were a fully invested portfolio, it would become 150% levered.
> Also adds `context.get_market_value()`, which enables this functionality.
> # take half of my available cash and buy AAPL
> order_percent('AAPL', 0.5, percent_of='cash')
> For example:
```python
# this is how it works today (and this still works)
# put 50% of my portfolio in AAPL
order_percent('AAPL', 0.5)
# note that if this were a fully invested portfolio, it would become 150% levered.
> # rebalance my short position, as a percentage of my current short book
> order_target_percent('MSFT', 0.1, percent_of='shorts')
# take half of my available cash and buy AAPL
order_percent('AAPL', 0.5, percent_of='cash')
> # rebalance within a custom group of stocks
> tech_stocks = ('AAPL', 'MSFT', 'GOOGL')
> tech_filter = lambda p: p.sid in tech_stocks
> for stock in tech_stocks:
> order_target_percent(stock, 1/3, percent_of_fn=tech_filter)
> ```
# rebalance my short position, as a percentage of my current short book
order_target_percent('MSFT', 0.1, percent_of='shorts')
# rebalance within a custom group of stocks
tech_stocks = ('AAPL', 'MSFT', 'GOOGL')
tech_filter = lambda p: p.sid in tech_stocks
for stock in tech_stocks:
order_target_percent(stock, 1/3, percent_of_fn=tech_filter)
```