def Update(self, algorithm, changes):
''' Creates an insight for each security based on the alphabetical
value of its symbol
Returns:
The new insights generated'''
algorithm.Debug('update: ' + str(changes))
insights = []
for security in self.securities:
first_letter = str(security.Symbol)[0]
second_letter = str(security.Symbol)[1]
# insight parameters based on symbol letters
direction = InsightDirection.Up if ord(first_letter) > ord('M') else InsightDirection.Down
magnitude = float(ord(first_letter)) / float(ord('Z'))
confidence = float(ord(second_letter)) / float(ord('Z'))
insight = Insight(
security.Symbol,
timedelta(minutes=10),
InsightType.Price,
direction,
magnitude,
confidence,
)
#self.EmitInsights(insight)
insights.append(insight)
return insights
def Update(self, algorithm, data):
''' Creates a constant insight for each security as specified via the constructor
Args:
algorithm: The algorithm instance
data: The new data available
Returns:
The new insights generated'''
for security in self.securities:
if self.ShouldEmitInsight(algorithm.UtcTime, security.Symbol):
yield Insight(security.Symbol, self.period, self.type,
self.direction, self.magnitude, self.confidence)
def Update(self, algorithm, data):
insights = [] # list to store the new insights to be created
# loop through securities and generate insights
for security in self.securities:
# check if there's new data for the security or we're already invested
# if there's no new data but we're invested, we keep updating the insight since we don't really need to place orders
if data.ContainsKey(security.Symbol) or algorithm.Portfolio[security.Symbol].Invested:
# append the insights list with the prediction for each symbol
insights.append(Insight.Price(security.Symbol, self.insightExpiry, self.insightDirection))
else:
algorithm.Log('(Alpha) excluding this security due to missing data: ' + str(security.Symbol.Value))
return insights
def Update(self, algorithm, data):
''' Creates a constant insight for each security as specified via the constructor
Args:
algorithm: The algorithm instance
data: The new data available
Returns:
The new insights generated'''
insights = []
for security in self.securities:
# security price could be zero until we get the first data point. e.g. this could happen
# when adding both forex and equities, we will first get a forex data point
if security.Price != 0 and self.ShouldEmitInsight(
algorithm.UtcTime, security.Symbol):
insights.append(
Insight(security.Symbol, self.period, self.type,
self.direction, self.magnitude, self.confidence))
return insights