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re-arranged fields so that history includes daily snapshots for cumulative measures.

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fawce
2012-04-19 23:27:35 -04:00
parent ddb1c51569
commit 08a5bd5a0d
3 changed files with 79 additions and 48 deletions
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zipline/finance/performance.py
+69 -42
View File
@@ -20,12 +20,6 @@ Performance Tracking
+-----------------+----------------------------------------------------+
| started_at | datetime in utc marking the start of this test |
+-----------------+----------------------------------------------------+
| cumulative_capti| The net capital used (positive is spent) through |
| al_used | the course of all the events sent to this tracker |
+-----------------+----------------------------------------------------+
| max_capital_used| The maximum amount of capital deployed through the |
| | course of all the events sent to this tracker |
+-----------------+----------------------------------------------------+
| last_close | The most recent close of the market. datetime in |
| | pytz.utc timezone. Will always be 23:59 on the |
| | date in UTC. The fact that the time may be on the |
@@ -106,6 +100,14 @@ Performance Period
| returns | percentage returns for the entire portfolio over the |
| | period |
+---------------+------------------------------------------------------+
| cumulative_ | The net capital used (positive is spent) during |
| capital_used | the period |
+---------------+------------------------------------------------------+
| max_capital_ | The maximum amount of capital deployed during the |
| used | period. |
+---------------+------------------------------------------------------+
| max_leverage | The maximum leverage used during the period. |
+---------------+------------------------------------------------------+
"""
@@ -136,10 +138,10 @@ class PerformanceTracker():
def __init__(self, trading_environment):
self.trading_environment = trading_environment
self.trading_day = datetime.timedelta(hours = 6, minutes = 30)
self.calendar_day = datetime.timedelta(hours = 24)
self.started_at = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
self.trading_environment = trading_environment
self.trading_day = datetime.timedelta(hours = 6, minutes = 30)
self.calendar_day = datetime.timedelta(hours = 24)
self.started_at = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
self.period_start = self.trading_environment.period_start
self.period_end = self.trading_environment.period_end
@@ -164,7 +166,10 @@ class PerformanceTracker():
# initial portfolio positions have zero value
0,
# initial cash is your capital base.
starting_cash = self.capital_base
self.capital_base,
# the cumulative period will be calculated over the entire test.
self.period_start,
self.period_end
)
# this performance period will span just the current market day
@@ -174,7 +179,10 @@ class PerformanceTracker():
# initial portfolio positions have zero value
0,
# initial cash is your capital base.
starting_cash = self.capital_base,
self.capital_base,
# the daily period will be calculated for the market day
self.market_open,
self.market_close,
# save the transactions for the daily periods
keep_transactions = True
)
@@ -206,10 +214,6 @@ class PerformanceTracker():
'period_start' : self.period_start,
'period_end' : self.period_end,
'progress' : self.progress,
'cumulative_capital_used' : self.cumulative_performance.cumulative_capital_used,
'max_capital_used' : self.cumulative_performance.max_capital_used,
'last_close' : self.market_close,
'last_open' : self.market_open,
'capital_base' : self.capital_base,
'cumulative_perf' : self.cumulative_performance.to_dict(),
'daily_perf' : self.todays_performance.to_dict(),
@@ -283,6 +287,8 @@ class PerformanceTracker():
self.todays_performance.positions,
self.todays_performance.ending_value,
self.todays_performance.ending_cash,
self.market_open,
self.market_close,
keep_transactions = True
)
@@ -369,20 +375,32 @@ class Position():
class PerformancePeriod():
def __init__(self, initial_positions, starting_value, starting_cash, keep_transactions=False):
self.ending_value = 0.0
self.period_capital_used = 0.0
self.pnl = 0.0
def __init__(
self,
initial_positions,
starting_value,
starting_cash,
period_open,
period_close,
keep_transactions=False):
self.period_open = period_open
self.period_close = period_close
self.ending_value = 0.0
self.period_capital_used = 0.0
self.pnl = 0.0
#sid => position object
self.positions = initial_positions
self.starting_value = starting_value
self.positions = initial_positions
self.starting_value = starting_value
#cash balance at start of period
self.starting_cash = starting_cash
self.ending_cash = starting_cash
self.keep_transactions = keep_transactions
self.processed_transactions = []
self.starting_cash = starting_cash
self.ending_cash = starting_cash
self.keep_transactions = keep_transactions
self.processed_transactions = []
self.cumulative_capital_used = 0.0
self.max_capital_used = 0.0
self.max_leverage = 0.0
self.calculate_performance()
@@ -457,16 +475,21 @@ class PerformancePeriod():
transactions = [x.as_dict() for x in self.processed_transactions]
return {
'ending_value' : self.ending_value,
'capital_used' : self.period_capital_used,
'starting_value' : self.starting_value,
'starting_cash' : self.starting_cash,
'ending_cash' : self.ending_cash,
'portfolio_value': self.ending_cash + self.ending_value,
'positions' : positions,
'pnl' : self.pnl,
'returns' : self.returns,
'transactions' : transactions,
'ending_value' : self.ending_value,
'capital_used' : self.period_capital_used,
'starting_value' : self.starting_value,
'starting_cash' : self.starting_cash,
'ending_cash' : self.ending_cash,
'portfolio_value' : self.ending_cash + self.ending_value,
'cumulative_capital_used' : self.cumulative_capital_used,
'max_capital_used' : self.max_capital_used,
'max_leverage' : self.max_leverage,
'positions' : positions,
'pnl' : self.pnl,
'returns' : self.returns,
'transactions' : transactions,
'period_open' : self.period_open,
'period_close' : self.period_close
}
def to_namedict(self):
@@ -481,12 +504,16 @@ class PerformancePeriod():
positions = zp.namedict(positions)
return zp.namedict({
'ending_value' : self.ending_value,
'capital_used' : self.period_capital_used,
'starting_value' : self.starting_value,
'starting_cash' : self.starting_cash,
'ending_cash' : self.ending_cash,
'positions' : positions
'ending_value' : self.ending_value,
'capital_used' : self.period_capital_used,
'starting_value' : self.starting_value,
'starting_cash' : self.starting_cash,
'ending_cash' : self.ending_cash,
'cumulative_capital_used' : self.cumulative_capital_used,
'max_capital_used' : self.max_capital_used,
'max_leverage' : self.max_leverage,
'positions' : positions,
'transactions' : self.processed_transactions
})
def get_positions(self, namedicted=False):
zipline/finance/risk.py
+1 -1
View File
@@ -194,7 +194,7 @@ class RiskMetrics():
http://en.wikipedia.org/wiki/Sharpe_ratio
"""
if self.algorithm_volatility == 0:
return None
return 0.0
return ( (self.algorithm_period_returns - self.treasury_period_return) /
self.algorithm_volatility )
zipline/protocol.py
+9 -5
View File
@@ -628,8 +628,6 @@ def PERF_FRAME(perf):
assert isinstance(perf['started_at'], datetime.datetime)
assert isinstance(perf['period_start'], datetime.datetime)
assert isinstance(perf['period_end'], datetime.datetime)
assert isinstance(perf['last_close'], datetime.datetime)
assert isinstance(perf['last_open'], datetime.datetime)
assert isinstance(perf['daily_perf'], dict)
assert isinstance(perf['cumulative_perf'], dict)
@@ -641,16 +639,22 @@ def PERF_FRAME(perf):
assert isinstance(cp['transactions'], list)
assert isinstance(tp['positions'], list)
assert isinstance(cp['positions'], list)
assert isinstance(tp['period_close'], datetime.datetime)
assert isinstance(tp['period_open'], datetime.datetime)
assert isinstance(cp['period_close'], datetime.datetime)
assert isinstance(cp['period_open'], datetime.datetime)
perf['started_at'] = EPOCH(perf['started_at'])
perf['period_start'] = EPOCH(perf['period_start'])
perf['period_end'] = EPOCH(perf['period_end'])
perf['last_close'] = EPOCH(perf['last_close'])
perf['last_open'] = EPOCH(perf['last_open'])
tp['period_close'] = EPOCH(tp['period_close'])
tp['period_open'] = EPOCH(tp['period_open'])
cp['period_close'] = EPOCH(cp['period_close'])
cp['period_open'] = EPOCH(cp['period_open'])
tp['transactions'] = convert_transactions(tp['transactions'])
cp['transactions'] = convert_transactions(cp['transactions'])
return BT_UPDATE_FRAME('PERF', perf)
def convert_transactions(transactions):