wassname/catalyst
1
0
Fork 0
mirror of https://github.com/wassname/catalyst.git synced 2026-07-12 14:56:21 +08:00
Code Issues Packages Projects Releases Wiki Activity

PERF: Remove repeated member lookup for cumulative metrics.

Browse Source 
The metrics DataFrame is referred to several times, so remove the extra
attribute lookups.
This commit is contained in:
Eddie Hebert
2015-07-01 10:50:57 -04:00
parent 7a1a6ddb37
commit 62ab540fa2
1 changed files with 17 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files
zipline/finance/risk/cumulative.py
+17 -15
View File
@@ -290,9 +290,10 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
raise Exception(message)
self.update_current_max()
self.metrics.benchmark_volatility.iloc[dt_loc] = \
metrics = self.metrics
metrics.benchmark_volatility.iloc[dt_loc] = \
self.calculate_volatility(self.benchmark_returns)
self.metrics.algorithm_volatility.iloc[dt_loc] = \
metrics.algorithm_volatility.iloc[dt_loc] = \
self.calculate_volatility(self.algorithm_returns)
# caching the treasury rates for the minutely case is a
@@ -311,13 +312,13 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
self.excess_returns[dt_loc] = (
self.algorithm_cumulative_returns[dt_loc] -
self.treasury_period_return)
self.metrics.beta.iloc[dt_loc] = self.calculate_beta()
self.metrics.alpha.iloc[dt_loc] = self.calculate_alpha()
self.metrics.sharpe.iloc[dt_loc] = self.calculate_sharpe()
self.metrics.downside_risk.iloc[dt_loc] = \
metrics.beta.iloc[dt_loc] = self.calculate_beta()
metrics.alpha.iloc[dt_loc] = self.calculate_alpha()
metrics.sharpe.iloc[dt_loc] = self.calculate_sharpe()
metrics.downside_risk.iloc[dt_loc] = \
self.calculate_downside_risk()
self.metrics.sortino.iloc[dt_loc] = self.calculate_sortino()
self.metrics.information.iloc[dt_loc] = self.calculate_information()
metrics.sortino.iloc[dt_loc] = self.calculate_sortino()
metrics.information.iloc[dt_loc] = self.calculate_information()
self.max_drawdown = self.calculate_max_drawdown()
self.max_drawdowns[dt_loc] = self.max_drawdown
self.max_leverage = self.calculate_max_leverage()
@@ -331,12 +332,13 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
dt = self.latest_dt
dt_loc = self.latest_dt_loc
period_label = dt.strftime("%Y-%m")
metrics = self.metrics
rval = {
'trading_days': self.num_trading_days,
'benchmark_volatility':
self.metrics.benchmark_volatility.iloc[dt_loc],
metrics.benchmark_volatility.iloc[dt_loc],
'algo_volatility':
self.metrics.algorithm_volatility.iloc[dt_loc],
metrics.algorithm_volatility.iloc[dt_loc],
'treasury_period_return': self.treasury_period_return,
# Though the two following keys say period return,
# they would be more accurately called the cumulative return.
@@ -346,11 +348,11 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
self.algorithm_cumulative_returns[dt_loc],
'benchmark_period_return':
self.benchmark_cumulative_returns[dt_loc],
'beta': self.metrics.beta.iloc[dt_loc],
'alpha': self.metrics.alpha.iloc[dt_loc],
'sharpe': self.metrics.sharpe.iloc[dt_loc],
'sortino': self.metrics.sortino.iloc[dt_loc],
'information': self.metrics.information.iloc[dt_loc],
'beta': metrics.beta.iloc[dt_loc],
'alpha': metrics.alpha.iloc[dt_loc],
'sharpe': metrics.sharpe.iloc[dt_loc],
'sortino': metrics.sortino.iloc[dt_loc],
'information': metrics.information.iloc[dt_loc],
'excess_return': self.excess_returns[dt_loc],
'max_drawdown': self.max_drawdown,
'max_leverage': self.max_leverage,