def clear(self, startcash=0):
'''
(Re-)Initialise the equity table in memory.
'''
self.startcash = startcash
self.cash = StockPrice([], [])
self.stocks = StockPrice([], [])
self.total = StockPrice([], [])
def load(self, system_id):
'''
Read all equity of <system> from the database.
'''
equity = Equity.objects.filter(system=system_id).order_by('date')
dates = []
cash = []
stocks = []
totals = []
for row in equity:
dates.append(row.date)
cash.append(row.cash)
stocks.append(row.positions)
totals.append(row.cash + row.positions)
self.cash = StockPrice(cash, dates)
self.stocks = StockPrice(stocks, dates)
self.total = StockPrice(totals, dates)
class EquityHistory(object):
'''
This class maintains the history of equity.
Equity is a DatedList of cash, stock and total value of the positions.
These lists are kept in memory.
The associated database table holds the equity position for each trading day.
Total equity = cash + positions value on each date.
'''
def __init__(self, startcash=None, system_id=None):
if startcash:
self.clear(startcash)
if system_id:
self.load(system_id)
def clear(self, startcash=0):
'''
(Re-)Initialise the equity table in memory.
'''
self.startcash = startcash
self.cash = StockPrice([], [])
self.stocks = StockPrice([], [])
self.total = StockPrice([], [])
def percentage(self):
'''
Return total equity, scaled so that the starting capital is 100.
'''
factor = 100 / self.total[0]
percentages = [t * factor for t in self.total]
return StockPrice(percentages, self.total.dates)
def update(self, date, cashflow, positions_value):
'''
Store the equity position on <date> in the DatedLists.
'''
try:
lastcash = self.cash[-1]
except IndexError:
lastcash = self.startcash
cash = lastcash + cashflow
self.cash.append((date, cash))
self.stocks.append((date, positions_value))
self.total.append((date, cash + positions_value))
def exists(self):
'''
Returns True if any equity exists in this instance, False otherwise.
'''
return bool(self.total)
def get(self, period='month'):
'''
Returns a list of the equity position on each <period>. Where <period>
may be one of the following: 'day', 'week', 'month' or 'year'.
'''
data = zip(self.stocks.dates, self.stocks.as_list(), self.cash, self.total)
start_equity = self.total[0]
period_start = start_equity
maxlen = len(self.stocks) - 1
equity = []
for i, (date, stocks, cash, total) in enumerate(data):
total = float(total)
if (period == 'day') or (i == maxlen) or (i == 0) or (
period == 'year' and
date.year != self.stocks.dates[i+1].year) or (
period == 'month' and
date.month != self.stocks.dates[i+1].month) or (
period == 'week' and date.isocalendar()[1] !=
self.stocks.dates[i+1].isocalendar()[1]):
period_equity = {
'date': date,
'cash': cash,
'stocks': stocks,
'total': total,
'gain':100.*(total/start_equity-1)}
if period != 'day':
period_equity['period_gain'] = 100.*(total/period_start-1)
equity.append(period_equity)
period_start = total
return equity
def calc_results(self):
'''
Returns a dict with:
* max_dd: The maximum drawdown over a 1 year period.
* min_dd_ratio: The lowest ratio of gain/max_dd in any one year period.
* min_month: The lowest gain in any calender month (or highest loss)
* max_month: The highest gain in any calender month (or lowest loss)
* neg_month: the average number of negative months per year
* sum_neg_months: the annualised sum of the losses during those months
* ann_gain: annualised profit in %
* min_year: The lowest gain in any 1 year period
* max_year: The highest gain in any 1 year period
'''
year = 252 # avg no of trading days in a year
data = {'max_dd':0, 'min_dd_ratio': 999.99}
year_gains = self.total.roc(year)[year-1:]
if len(year_gains):
data['min_year'] = min(year_gains)
data['max_year'] = max(year_gains)
else:
data['min_year'] = 0
data['max_year'] = 0
year_drawdowns = self.total.drawdown(year)
for year_dd, year_gain in zip(year_drawdowns, year_gains)[year-1:]:
dd_ratio = div(year_gain, year_dd) # in %/%
data['max_dd'] = max(data['max_dd'], year_dd)
if dd_ratio is not None:
data['min_dd_ratio'] = min(data['min_dd_ratio'], dd_ratio)
total_gain = max(0, self.total[-1] / self.total[0])
dt = self.total.dates[-1] - self.total.dates[0]
data['ann_profit'] = 100 * (total_gain ** (365./dt.days) - 1)
months = self.get('month')
data['min_month'] = min([x['period_gain'] for x in months])
data['max_month'] = max([x['period_gain'] for x in months])
neg_months = [x['period_gain'] for x in months if x['period_gain'] < 0]
data['n_neg_month'] = 12. * len(neg_months) / len(months)
data['sum_neg_mths'] = 12. * sum(neg_months) / len(months)
# sanitise results:
data['max_dd'] = min (data['max_dd'], 99)
for key in ('ann_profit', 'sum_neg_mths', 'min_year', 'max_year',
'min_month', 'max_month', 'min_dd_ratio'):
data[key] = min(max(data[key], -999), 999)
return data
def save(self, system):
'''
Writes the equity history from the lists to the Equity database table.
'''
with transaction.commit_on_success(): # for inserting in bulk (quicker)
for date, cash, stocks in zip(self.cash.dates, self.cash, self.stocks):
equity = {'system': system, 'date': date,
'cash':cash, 'positions': stocks}
Equity.objects.create(**equity)
def load(self, system_id):
'''
Read all equity of <system> from the database.
'''
equity = Equity.objects.filter(system=system_id).order_by('date')
dates = []
cash = []
stocks = []
totals = []
for row in equity:
dates.append(row.date)
cash.append(row.cash)
stocks.append(row.positions)
totals.append(row.cash + row.positions)
self.cash = StockPrice(cash, dates)
self.stocks = StockPrice(stocks, dates)
self.total = StockPrice(totals, dates)
def write_thumbnail_to_db(self, system, width=100, height=32):
'''
Calculate and store the y coordinates for generating a thumbnail image.
'''
totals = self.total.as_list()
Thumbnail.write_to_db(totals, system, width, height)
