wehub-resource-sync
128 lines
5.2 KiB
Python
128 lines
5.2 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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from QuantConnect.Logging import *
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from enum import Enum
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class RsiAlphaModel(AlphaModel):
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'''Uses Wilder's RSI to create insights.
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Using default settings, a cross over below 30 or above 70 will trigger a new insight.'''
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def __init__(self,
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period = 14,
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resolution = Resolution.DAILY):
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'''Initializes a new instance of the RsiAlphaModel class
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Args:
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period: The RSI indicator period'''
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self.period = period
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self.resolution = resolution
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self.insight_period = Time.multiply(Extensions.to_time_span(resolution), period)
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self.symbol_data_by_symbol ={}
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self.name = '{}({},{})'.format(self.__class__.__name__, period, resolution)
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def update(self, algorithm, data):
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'''Updates this alpha model with the latest data from the algorithm.
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This is called each time the algorithm receives data for subscribed securities
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Args:
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algorithm: The algorithm instance
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data: The new data available
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Returns:
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The new insights generated'''
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insights = []
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for symbol, symbol_data in self.symbol_data_by_symbol.items():
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rsi = symbol_data.rsi
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previous_state = symbol_data.state
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state = self.get_state(rsi, previous_state)
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if state != previous_state and rsi.is_ready:
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if state == State.TRIPPED_LOW:
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insights.append(Insight.price(symbol, self.insight_period, InsightDirection.UP))
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if state == State.TRIPPED_HIGH:
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insights.append(Insight.price(symbol, self.insight_period, InsightDirection.DOWN))
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symbol_data.state = state
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return insights
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def on_securities_changed(self, algorithm, changes):
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'''Cleans out old security data and initializes the RSI for any newly added securities.
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Event fired each time the we add/remove securities from the data feed
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Args:
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algorithm: The algorithm instance that experienced the change in securities
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changes: The security additions and removals from the algorithm'''
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# clean up data for removed securities
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for security in changes.removed_securities:
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symbol_data = self.symbol_data_by_symbol.pop(security.symbol, None)
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if symbol_data:
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symbol_data.dispose()
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# initialize data for added securities
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added_symbols = []
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for security in changes.added_securities:
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symbol = security.symbol
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if symbol not in self.symbol_data_by_symbol:
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symbol_data = SymbolData(algorithm, symbol, self.period, self.resolution)
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self.symbol_data_by_symbol[symbol] = symbol_data
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added_symbols.append(symbol)
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if added_symbols:
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history = algorithm.history[TradeBar](added_symbols, self.period, self.resolution)
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for trade_bars in history:
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for bar in trade_bars.values():
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self.symbol_data_by_symbol[bar.symbol].update(bar)
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def get_state(self, rsi, previous):
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''' Determines the new state. This is basically cross-over detection logic that
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includes considerations for bouncing using the configured bounce tolerance.'''
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if rsi.current.value > 70:
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return State.TRIPPED_HIGH
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if rsi.current.value < 30:
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return State.TRIPPED_LOW
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if previous == State.TRIPPED_LOW:
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if rsi.current.value > 35:
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return State.MIDDLE
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if previous == State.TRIPPED_HIGH:
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if rsi.current.value < 65:
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return State.MIDDLE
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return previous
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class SymbolData:
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'''Contains data specific to a symbol required by this model'''
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def __init__(self, algorithm, symbol, period, resolution):
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self.algorithm = algorithm
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self.symbol = symbol
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self.state = State.MIDDLE
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self.rsi = RelativeStrengthIndex(period, MovingAverageType.WILDERS)
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self.consolidator = algorithm.resolve_consolidator(symbol, resolution)
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algorithm.register_indicator(symbol, self.rsi, self.consolidator)
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def update(self, bar):
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self.consolidator.update(bar)
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def dispose(self):
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self.algorithm.subscription_manager.remove_consolidator(self.symbol, self.consolidator)
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class State(Enum):
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'''Defines the state. This is used to prevent signal spamming and aid in bounce detection.'''
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TRIPPED_LOW = 0
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MIDDLE = 1
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TRIPPED_HIGH = 2
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