def passive_roll_child_order(
data: dataBlob,
trade: int,
instrument_order: instrumentOrder,
) -> list:
log = instrument_order.log_with_attributes(data.log)
diag_positions = diagPositions(data)
instrument_code = instrument_order.instrument_code
diag_contracts = diagContracts(data)
current_contract = diag_contracts.get_priced_contract_id(instrument_code)
next_contract = diag_contracts.get_forward_contract_id(instrument_code)
position_current_contract = (
diag_positions.get_position_for_instrument_and_contract_date(
instrument_code, current_contract))
# Break out because so darn complicated
if position_current_contract == 0:
# Passive roll and no position in the current contract, start trading
# the next contract
log.msg(
"Passive roll handling order %s, no position in current contract, entire trade in next contract %s"
% (str(instrument_order), next_contract))
return [contractIdAndTrade(next_contract, trade)]
# ok still have a position in the current contract
increasing_trade = sign(trade) == sign(position_current_contract)
if increasing_trade:
# Passive roll and increasing trade
# Do it all in next contract
log.msg(
"Passive roll handling order %s, increasing trade, entire trade in next contract %s"
% (str(instrument_order), next_contract))
return [contractIdAndTrade(next_contract, trade)]
# ok a reducing trade
new_position = position_current_contract + trade
sign_of_position_is_unchanged = sign(position_current_contract) == sign(
new_position)
if new_position == 0 or sign_of_position_is_unchanged:
# A reducing trade that we can do entirely in the current contract
log.msg(
"Passive roll handling order %s, reducing trade, entire trade in next contract %s"
% (str(instrument_order), next_contract))
return [contractIdAndTrade(current_contract, trade)]
# OKAY to recap: it's a passive roll, but the trade will be split between
# current and next
list_of_child_contract_dates_and_trades = \
passive_trade_split_over_two_contracts(trade=trade,
current_contract=current_contract,
next_contract=next_contract,
position_current_contract=position_current_contract)
log.msg(
"Passive roll handling order %s, reducing trade, split trade between contract %s and %s"
% (str(instrument_order), current_contract, next_contract))
return list_of_child_contract_dates_and_trades
def passive_roll_child_order(position_current_contract, current_contract, next_contract, trade, log, instrument_order):
# Break out because so darn complicated
if position_current_contract == 0:
# Passive roll and no position in the current contract, start trading the next
log.msg("Passive roll handling order %s, no position in current contract, entire trade in next contract %s" %
(str(instrument_order), next_contract))
return [(next_contract, trade)]
# ok still have a position in the current contract
increasing_trade = sign(trade) == sign(position_current_contract)
if increasing_trade:
# Passive roll and increasing trade
# Do it all in next contract
log.msg("Passive roll handling order %s, increasing trade, entire trade in next contract %s" %
(str(instrument_order), next_contract))
return [(next_contract, trade)]
# ok a reducing trade
new_position = position_current_contract + trade
sign_of_position_is_unchanged = sign(position_current_contract) == sign(new_position)
if new_position == 0 or sign_of_position_is_unchanged:
# A reducing trade that we can do entirely in the current contract
log.msg("Passive roll handling order %s, reducing trade, entire trade in next contract %s" %
(str(instrument_order), next_contract))
return [(current_contract, trade)]
## OKAY to recap: it's a passive roll, but the trade will be split between current and next
log.msg("Passive roll handling order %s, reducing trade, split trade between contract %s and %s" %
(str(instrument_order), current_contract, next_contract))
trade_in_current_contract = - position_current_contract
trade_in_next_contract = trade - trade_in_current_contract
return [(current_contract, trade_in_current_contract), (next_contract, trade_in_next_contract)]
def resolveBS_for_list(trade_list):
## result is always positive
trade = highest_common_factor_for_list(trade_list)
trade = sign(trade_list[0]) * trade
return resolveBS(trade)
def cut_down_proposed_instrument_trade_okay(self, instrument_trade):
strategy_name = instrument_trade.strategy_name
instrument_code = instrument_trade.instrument_code
proposed_trade = instrument_trade.trade.as_int()
## want to CUT DOWN rather than bool possible trades
## underneath should be using tradeQuantity and position objects
## these will handle abs cases plus legs if required in future
max_trade_ok_against_strategy_instrument = \
self.check_if_proposed_trade_okay_against_strategy_instrument_constraint(strategy_name,
instrument_code,
proposed_trade)
max_trade_ok_against_instrument = \
self.check_if_proposed_trade_okay_against_instrument_constraint(instrument_code,
proposed_trade)
mini_max_trade = sign(proposed_trade) * \
min([abs(max_trade_ok_against_instrument),
abs(max_trade_ok_against_strategy_instrument)])
instrument_trade = instrument_trade.replace_trade_only_use_for_unsubmitted_trades(
mini_max_trade)
return instrument_trade
def expiry_diff(carry_row, floor_date_diff=20):
"""
Given a pandas row containing CARRY_CONTRACT and PRICE_CONTRACT, both of
which represent dates
Return the annualised difference between the dates
:param carry_row: object with attributes CARRY_CONTRACT and PRICE_CONTRACT
:type carry_row: pandas row, or something that quacks like it
:param floor_date_diff: If date resolves to less than this, floor here (*default* 20)
:type carry_row: pandas row, or something that quacks like it
:returns: datetime.datetime or datetime.date
"""
if carry_row.PRICE_CONTRACT == "" or carry_row.CARRY_CONTRACT == "":
return np.nan
ans = float((expiry_date(carry_row.CARRY_CONTRACT) -
expiry_date(carry_row.PRICE_CONTRACT)).days)
if abs(ans) < floor_date_diff:
ans = sign(ans) * floor_date_diff
ans = ans / CALENDAR_DAYS_IN_YEAR
return ans
def cut_down_proposed_instrument_trade_okay(self, instrument_trade):
strategy_name = instrument_trade.strategy_name
instrument_code = instrument_trade.instrument_code
proposed_trade = instrument_trade.trade.as_int()
## want to CUT DOWN rather than bool possible trades
## FIXME:
## underneath should be using tradeQuantity and position objects
## these will handle abs cases plus legs if required in future
# :FIXME
instrument_strategy = instrumentStrategy(
strategy_name=strategy_name, instrument_code=instrument_code)
max_trade_ok_against_instrument_strategy = \
self.check_if_proposed_trade_okay_against_instrument_strategy_constraint(instrument_strategy,
proposed_trade)
max_trade_ok_against_instrument = \
self.check_if_proposed_trade_okay_against_instrument_constraint(instrument_code,
proposed_trade)
## FIXME THIS IS UGLY WOULD BE BETTER IF DONE INSIDE TRADE SIZE OBJECT
mini_max_trade = sign(proposed_trade) * \
min([abs(max_trade_ok_against_instrument),
abs(max_trade_ok_against_instrument_strategy)])
instrument_trade = instrument_trade.replace_trade_only_use_for_unsubmitted_trades(
mini_max_trade)
return instrument_trade
def map_forecast_value_scalar(x, threshold, capped_value, a_param, b_param):
"""
Non linear mapping of x value; replaces forecast capping; with defaults will map 1 for 1
We want to end up with a function like this, for raw forecast x and mapped forecast m,
capped_value c and threshold_value t:
if -t < x < +t: m=0
if abs(x)>c: m=sign(x)*c*a
if c < x < -t: (x+t)*b
if t < x < +c: (x-t)*b
:param x: value to map
:param threshold: value below which map to zero
:param capped_value: maximum value we want x to take (without non linear mapping)
:param a_param: slope
:param b_param:
:return: mapped x
"""
x = float(x)
if np.isnan(x):
return x
if abs(x) < threshold:
return 0.0
if x >= -capped_value and x <= -threshold:
return b_param * (x + threshold)
if x >= threshold and x <= capped_value:
return b_param * (x - threshold)
if abs(x) > capped_value:
return sign(x) * capped_value * a_param
raise Exception("This should cover all conditions!")
def _DEPRECATE_apply_floor_to_date_differential(
fraction_of_year_between_expiries: float, floor_date_diff: float):
if abs(fraction_of_year_between_expiries) < floor_date_diff:
fraction_of_year_between_expiries = \
sign(fraction_of_year_between_expiries) * floor_date_diff
return fraction_of_year_between_expiries
def expiry_diff(carry_row, floor_date_diff=20):
"""
Given a pandas row containing CARRY_CONTRACT and PRICE_CONTRACT, both of which represent dates
Return the annualised difference between the dates
:param carry_row: object with attributes CARRY_CONTRACT and PRICE_CONTRACT
:type carry_row: pandas row, or something that quacks like it
:param floor_date_diff: If date resolves to less than this, floor here (*default* 20)
:type carry_row: pandas row, or something that quacks like it
:returns: datetime.datetime or datetime.date
"""
if carry_row.PRICE_CONTRACT == "" or carry_row.CARRY_CONTRACT == "":
return np.nan
ans = float((expiry_date(carry_row.CARRY_CONTRACT) -
expiry_date(carry_row.PRICE_CONTRACT)).days)
if abs(ans) < floor_date_diff:
ans = sign(ans) * floor_date_diff
ans = ans / CALENDAR_DAYS_IN_YEAR
return ans
def what_trade_is_possible(self, proposed_trade: int):
abs_proposed_trade = abs(proposed_trade)
possible_abs_trade = self.what_abs_trade_is_possible(
abs_proposed_trade)
# convert to same sign as proposed
possible_trade = possible_abs_trade * sign(proposed_trade)
return possible_trade
def _apply_reduce_only(self, original_position_no_override,
proposed_trade):
desired_new_position = original_position_no_override + proposed_trade.trade
if sign(desired_new_position) != sign(original_position_no_override):
# Closing trade only; don't allow sign to change
new_trade_value = -original_position_no_override
elif abs(desired_new_position) > abs(original_position_no_override):
# Increasing trade not allowed
new_trade_value = 0
else:
# Reducing trade and sign not changing, we'll allow
new_trade_value = proposed_trade.trade
proposed_trade.replace_trade_only_use_for_unsubmitted_trades(
new_trade_value)
return proposed_trade
def _apply_reduce_only(original_position_no_override: int,
proposed_trade: Order) -> Order:
proposed_trade_value = proposed_trade.trade.as_single_trade_qty_or_error()
desired_new_position = original_position_no_override + proposed_trade_value
if sign(desired_new_position) != sign(original_position_no_override):
# Wants sign to change, we convert into a pure closing trade
new_trade_value = -original_position_no_override
elif abs(desired_new_position) > abs(original_position_no_override):
# Increasing trade not allowed, zero trade
new_trade_value = 0
else:
# Reducing trade and sign not changing, we'll allow
new_trade_value = proposed_trade_value
proposed_trade.replace_required_trade_size_only_use_for_unsubmitted_trades(
tradeQuantity(new_trade_value))
return proposed_trade
def apply_fixed_position(position):
"""
Turn a variable position into one that is held constant regardless of changes in volatility
:param position: Raw position series, without stoploss or entry / exit logic
:return: New position series
"""
# assume all lined up
current_position = 0.0
new_position = []
for iday in range(len(position)):
original_position_now = position[iday]
if current_position == 0.0:
# no position, check for signal
if np.isnan(original_position_now):
# no signal
new_position.append(0.0)
continue
if original_position_now > 0.0 or original_position_now < 0.0:
# go long or short
current_position = original_position_now
new_position.append(current_position)
continue
if sign(current_position) != sign(original_position_now):
# changed sign
current_position = original_position_now
new_position.append(current_position)
continue
# already holding a position of same sign
new_position.append(current_position)
new_position = pd.DataFrame(new_position, position.index)
return new_position
def calculate_direction(
optimum_weight: float,
minimum: float = -A_VERY_LARGE_NUMBER,
maximum: float = A_VERY_LARGE_NUMBER,
) -> float:
if minimum >= 0:
return 1
if maximum <= 0:
return -1
if np.isnan(optimum_weight):
return 1
return sign(optimum_weight)
def get_spread_price(self, list_of_prices):
assert len(self._trade_or_fill_qty) == len(list_of_prices)
if len(self._trade_or_fill_qty) == 1:
return list_of_prices[0]
# spread price won't make sense otherwise
assert sum(self._trade_or_fill_qty) == 0
sign_to_adjust = sign(self._trade_or_fill_qty[0])
multiplied_prices = [
x * y * sign_to_adjust
for x, y in zip(self._trade_or_fill_qty, list_of_prices)
]
return sum(multiplied_prices)
def fraction_of_year_between_price_and_carry_expiries(carry_row,
floor_date_diff: int = 1
) -> float:
"""
Given a pandas row containing CARRY_CONTRACT and PRICE_CONTRACT, both of
which represent dates
Return the difference between the dates as a fraction
Positive means PRICE BEFORE CARRY, negative means CARRY BEFORE PRICE
:param carry_row: object with attributes CARRY_CONTRACT and PRICE_CONTRACT
:type carry_row: pandas row, or something that quacks like it
:param floor_date_diff: If date resolves to less than this, floor here (*default* 20)
:type int
:returns: float
>>> import pandas as pd
>>> carry_df = pd.DataFrame(dict(PRICE_CONTRACT =["20200601", "20200601", "20200601"],\
CARRY_CONTRACT = ["20200303", "20200905", "20200603"]))
>>> fraction_of_year_between_price_and_carry_expiries(carry_df.iloc[0])
-0.2464065708418891
>>> fraction_of_year_between_price_and_carry_expiries(carry_df.iloc[1])
0.26283367556468173
>>> fraction_of_year_between_price_and_carry_expiries(carry_df.iloc[2], floor_date_diff= 50)
0.13689253935660506
"""
if carry_row.PRICE_CONTRACT == "" or carry_row.CARRY_CONTRACT == "":
return np.nan
period_between_expiries = get_datetime_from_datestring(carry_row.CARRY_CONTRACT) \
- get_datetime_from_datestring(carry_row.PRICE_CONTRACT)
days_between_expiries = period_between_expiries.days
if abs(days_between_expiries) < floor_date_diff:
days_between_expiries = sign(days_between_expiries) * floor_date_diff
## Annualise, ensuring float output
fraction_of_year_between_expiries = float(
days_between_expiries) / CALENDAR_DAYS_IN_YEAR
return fraction_of_year_between_expiries
def get_spread_price(self, list_of_prices):
if list_of_prices is None:
return None
if isinstance(list_of_prices, int) or isinstance(
list_of_prices, float):
list_of_prices = [list_of_prices]
assert len(self._trade_or_fill_qty) == len(list_of_prices)
if len(self._trade_or_fill_qty) == 1:
return list_of_prices[0]
# spread price won't make sense otherwise
assert sum(self._trade_or_fill_qty) == 0
sign_to_adjust = sign(self._trade_or_fill_qty[0])
multiplied_prices = [
x * y * sign_to_adjust
for x, y in zip(self._trade_or_fill_qty, list_of_prices)
]
return sum(multiplied_prices)
def what_trade_is_possible(self, trade: int) -> int:
if self.position_limit is NO_LIMIT:
return trade
position = self.position
new_position = position + trade
# position limit should be abs, but just in case...
abs_position_limit = abs(self.position_limit)
signed_position_limit = int(abs_position_limit * sign(new_position))
if abs(new_position) <= abs_position_limit:
possible_trade = trade
elif trade > 0 and new_position >= 0:
possible_trade = max(0, signed_position_limit - position)
elif trade < 0 and new_position < 0:
possible_trade = min(0, signed_position_limit - position)
else:
possible_trade = 0
return int(possible_trade)
def stoploss(price, vol, position, Xfactor=4):
"""
Apply trailing stoploss
:param price:
:param vol: eg system.rawdata.daily_returns_volatility("SP500")
:param position: Raw position series, without stoploss or entry / exit logic
:return: New position series
"""
# assume all lined up
current_position = 0.0
previous_position = 0.0
new_position = []
price_list_since_position_held = []
for iday in range(len(price)):
current_price = price[iday]
if current_position == 0.0:
# no position, check for signal
original_position_now = position[iday]
if np.isnan(original_position_now):
# no signal
new_position.append(0.0)
continue
if original_position_now > 0.0 or original_position_now < 0.0:
# potentially going long / short
# check last position to avoid whipsaw
if previous_position == 0.0 or sign(
original_position_now) != sign(previous_position):
# okay to do this - we don't want to enter a new position unless sign changed
# we set the position at the sized position at moment of inception
current_position = original_position_now
price_list_since_position_held.append(current_price)
new_position.append(current_position)
continue
# if we've made it this far then:
# no signal
new_position.append(0.0)
continue
# already holding a position
# calculate HWM
sign_position = sign(current_position)
price_list_since_position_held.append(current_price)
current_vol = vol[iday]
trailing_factor = current_vol * Xfactor
if sign_position == 1:
# long
hwm = np.nanmax(price_list_since_position_held)
threshold = hwm - trailing_factor
close_trade = current_price < threshold
else:
# short
hwm = np.nanmin(price_list_since_position_held)
threshold = hwm + trailing_factor
close_trade = current_price > threshold
if close_trade:
previous_position = copy(current_position)
current_position = 0.0
# note if we don't close the current position is maintained
price_list_since_position_held = []
new_position.append(current_position)
new_position = pd.DataFrame(new_position, price.index)
return new_position
def sign_equal(self, other):
return all([sign(x) == sign(y) for x, y in zip(self, other)])
def buy_or_sell(self) -> int:
# sign of trade quantity
return sign(self[0])
def resolveBS_for_calendar_spread(trade_list):
trade = highest_common_factor_for_list(trade_list)
trade = sign(trade_list[0]) * trade
return resolveBS(trade)
def apply_floor_to_date_differential(days_between_expiries: float,
floor_date_diff: float):
if abs(days_between_expiries) < floor_date_diff:
days_between_expiries = sign(days_between_expiries) * floor_date_diff
return days_between_expiries
def buy_or_sell(self):
return sign(self.qty[0])
def what_trade_is_possible_single_leg_trade(position: int, position_limit: int, proposed_trade: int)-> int:
"""
>>> what_trade_is_possible(1, 1, 0)
0
>>> what_trade_is_possible(5, 1, 0)
0
>>> what_trade_is_possible(0, 3, 1)
1
>>> what_trade_is_possible(0, 3, 2)
2
>>> what_trade_is_possible(0, 3, 3)
3
>>> what_trade_is_possible(0, 3, 4)
3
>>> what_trade_is_possible(0, 3, -1)
-1
>>> what_trade_is_possible(0, 3, -2)
-2
>>> what_trade_is_possible(0, 3, -3)
-3
>>> what_trade_is_possible(0, 3, -4)
-3
>>> what_trade_is_possible(2, 3, 1)
1
>>> what_trade_is_possible(2, 3, 2)
1
>>> what_trade_is_possible(2, 3, -2)
-2
>>> what_trade_is_possible(2, 3, -4)
-4
>>> what_trade_is_possible(2, 3, -5)
-5
>>> what_trade_is_possible(2, 3, -6)
-5
>>> what_trade_is_possible(5, 3, 2)
0
>>> what_trade_is_possible(5, 3, -1)
-1
>>> what_trade_is_possible(5, 3, -2)
-2
>>> what_trade_is_possible(5, 3, -9)
-8
>>> what_trade_is_possible(2, 3, -4)
-4
>>> what_trade_is_possible(2, 3, -5)
-5
>>> what_trade_is_possible(2, 3, -6)
-5
>>> what_trade_is_possible(0, 3, 1)
1
>>> what_trade_is_possible(0, 3, -4)
-3
>>> what_trade_is_possible(-2, 3, -1)
-1
>>> what_trade_is_possible(-2, 3, -2)
-1
>>> what_trade_is_possible(-5, 3, -2)
0
>>> what_trade_is_possible(-5, 3, 1)
1
>>> what_trade_is_possible(-5, 3, 2)
2
>>> what_trade_is_possible(-5, 3, 2)
2
>>> what_trade_is_possible(-5, 3, 7)
7
>>> what_trade_is_possible(-5, 3, 9)
8
>>> what_trade_is_possible(-3, 3, 7)
6
>>> what_trade_is_possible(3, 3, -7)
-6
"""
if proposed_trade==0:
return proposed_trade
new_position = position + proposed_trade
# position limit should be abs, but just in case...
abs_position_limit = abs(position_limit)
signed_position_limit = int(abs_position_limit * sign(new_position))
if abs(new_position)<=abs_position_limit:
## new position is within limits
return proposed_trade
if position>=0 and abs(position)<=abs_position_limit:
## Was okay, but won't be after trade
## We move to the limit, either long or short depending on what the trade wanted to do
possible_new_position = signed_position_limit
possible_trade = possible_new_position - position
return possible_trade
if position>=0 and abs(position)>abs_position_limit:
## Was already too big
if proposed_trade>=0:
# want to buy when already too big
return 0
if new_position>0:
## selling, but sell isn't big enough to get within limits
## we don't increase the size of a trade
return proposed_trade
else:
## selling and gone out the other side
possible_new_position = signed_position_limit
possible_trade = possible_new_position - position
return possible_trade
if position<0 and abs(position)<=abs_position_limit:
## Was okay, but won't be after trade
## We move to the limit, either long or short depending on what the trade wanted to do
possible_new_position = signed_position_limit
possible_trade = possible_new_position - position
return possible_trade
if position<0 and abs(position)>abs_position_limit:
## Was already too big
if proposed_trade<0:
# want to sell when already too big
return 0
if new_position<0:
## buying but not big enough to get within limits
## we don't increase the size of a trade
return proposed_trade
else:
# buying and gone out the other side
possible_new_position = signed_position_limit
possible_trade = possible_new_position - position
return possible_trade
raise Exception("Don't know how to handle original position %f proposed trade %f limit %f" % (position, proposed_trade, abs_position_limit))
