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https://github.com/wassname/catalyst.git
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ENH: Bound trade amount with asset specific min trade size
This commit is contained in:
committed by
Victor Grau Serrat
parent
48143d3212
commit
e5a137f205
+7
-10
@@ -125,6 +125,7 @@ from catalyst.utils.factory import create_simulation_parameters
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from catalyst.utils.math_utils import (
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tolerant_equals,
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round_if_near_integer,
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round_nearest
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)
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from catalyst.utils.pandas_utils import clear_dataframe_indexer_caches
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from catalyst.utils.preprocess import preprocess
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@@ -1488,7 +1489,7 @@ class TradingAlgorithm(object):
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def _calculate_order(self, asset, amount,
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limit_price=None, stop_price=None, style=None):
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amount = self.round_order(amount)
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amount = self.round_order(amount, asset)
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# Raises a ZiplineError if invalid parameters are detected.
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self.validate_order_params(asset,
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@@ -1505,16 +1506,13 @@ class TradingAlgorithm(object):
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return amount, style
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@staticmethod
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def round_order(amount):
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def round_order(amount, asset):
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"""
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Convert number of shares to an integer.
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By default, truncates to the integer share count that's either within
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.0001 of amount or closer to zero.
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E.g. 3.9999 -> 4.0; 5.5 -> 5.0; -5.5 -> -5.0
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Converts the number of shares to the smallest tradable lot size for
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the asset being ordered.
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"""
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return int(round_if_near_integer(amount))
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return round_nearest(amount, asset.min_trade_size)
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def validate_order_params(self,
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asset,
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@@ -1550,7 +1548,6 @@ class TradingAlgorithm(object):
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self.updated_portfolio(),
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self.get_datetime(),
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self.trading_client.current_data)
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@staticmethod
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def __convert_order_params_for_blotter(limit_price, stop_price, style):
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"""
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@@ -59,6 +59,7 @@ cdef class Asset:
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cdef readonly object exchange
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cdef readonly object exchange_full
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cdef readonly object min_trade_size
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_kwargnames = frozenset({
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'sid',
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@@ -70,6 +71,7 @@ cdef class Asset:
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'auto_close_date',
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'exchange',
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'exchange_full',
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'min_trade_size',
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})
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def __init__(self,
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@@ -81,7 +83,8 @@ cdef class Asset:
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object end_date=None,
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object first_traded=None,
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object auto_close_date=None,
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object exchange_full=None):
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object exchange_full=None,
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object min_trade_size=None):
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self.sid = sid
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self.sid_hash = hash(sid)
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@@ -94,6 +97,7 @@ cdef class Asset:
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self.end_date = end_date
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self.first_traded = first_traded
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self.auto_close_date = auto_close_date
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self.min_trade_size = min_trade_size
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def __int__(self):
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return self.sid
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@@ -148,7 +152,8 @@ cdef class Asset:
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def __repr__(self):
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attrs = ('symbol', 'asset_name', 'exchange',
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'start_date', 'end_date', 'first_traded', 'auto_close_date')
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'start_date', 'end_date', 'first_traded', 'auto_close_date',
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'min_trade_size')
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tuples = ((attr, repr(getattr(self, attr, None)))
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for attr in attrs)
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strings = ('%s=%s' % (t[0], t[1]) for t in tuples)
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@@ -170,7 +175,8 @@ cdef class Asset:
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self.end_date,
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self.first_traded,
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self.auto_close_date,
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self.exchange_full))
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self.exchange_full,
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self.min_trade_size))
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cpdef to_dict(self):
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"""
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@@ -186,6 +192,7 @@ cdef class Asset:
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'auto_close_date': self.auto_close_date,
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'exchange': self.exchange,
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'exchange_full': self.exchange_full,
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'min_trade_size': self.min_trade_size
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}
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@classmethod
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@@ -234,7 +241,7 @@ cdef class Equity(Asset):
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def __repr__(self):
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attrs = ('symbol', 'asset_name', 'exchange',
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'start_date', 'end_date', 'first_traded', 'auto_close_date',
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'exchange_full')
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'exchange_full', 'min_trade_size')
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tuples = ((attr, repr(getattr(self, attr, None)))
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for attr in attrs)
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strings = ('%s=%s' % (t[0], t[1]) for t in tuples)
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@@ -39,7 +39,8 @@ equities = sa.Table(
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sa.Column('first_traded', sa.Integer),
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sa.Column('auto_close_date', sa.Integer),
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sa.Column('exchange', sa.Text),
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sa.Column('exchange_full', sa.Text)
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sa.Column('exchange_full', sa.Text),
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sa.Column('min_trade_size', sa.Float)
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)
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equity_symbol_mappings = sa.Table(
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@@ -73,6 +73,7 @@ _equities_defaults = {
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'exchange': None,
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# optional, something like "New York Stock Exchange"
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'exchange_full': None,
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'min_trade_size': None
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}
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# Default values for the futures DataFrame
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@@ -41,6 +41,7 @@ DEFAULT_EQUITY_VOLUME_SLIPPAGE_BAR_LIMIT = 0.025
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DEFAULT_FUTURE_VOLUME_SLIPPAGE_BAR_LIMIT = 0.05
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class LiquidityExceeded(Exception):
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pass
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@@ -205,12 +206,14 @@ class VolumeShareSlippage(SlippageModel):
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def process_order(self, data, order):
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volume = data.current(order.asset, "volume")
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min_trade_size = order.asset.min_trade_size
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max_volume = self.volume_limit * volume
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# price impact accounts for the total volume of transactions
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# created against the current minute bar
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remaining_volume = max_volume - self.volume_for_bar
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if remaining_volume < 1:
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if remaining_volume < min_trade_size:
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# we can't fill any more transactions
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raise LiquidityExceeded()
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@@ -218,7 +221,7 @@ class VolumeShareSlippage(SlippageModel):
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# volume available in the bar or the open amount.
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cur_volume = int(min(remaining_volume, abs(order.open_amount)))
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if cur_volume < 1:
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if cur_volume < min_trade_size:
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return None, None
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# tally the current amount into our total amount ordered.
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@@ -65,14 +65,10 @@ def create_transaction(order, dt, price, amount):
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# floor the amount to protect against non-whole number orders
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# TODO: Investigate whether we can add a robust check in blotter
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# and/or tradesimulation, as well.
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amount_magnitude = int(abs(amount))
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if amount_magnitude < 1:
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raise Exception("Transaction magnitude must be at least 1.")
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transaction = Transaction(
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asset=order.asset,
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amount=int(amount),
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amount=amounts,
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dt=dt,
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price=price,
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order_id=order.id
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@@ -17,6 +17,8 @@ import math
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from numpy import isnan
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def round_nearest(x, a):
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return round(round(x / a) * a, -int(math.floor(math.log10(a))))
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def tolerant_equals(a, b, atol=10e-7, rtol=10e-7, equal_nan=False):
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"""Check if a and b are equal with some tolerance.
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