def grade_symbol(self, symbol: str, output: OUTPUT_TYPE) -> SymbolGrade:
"""Assigns a pass/fail grade depending on whether the model output is True/False."""
# Fail the symbol if it has no output
if output is None or not output:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
else:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.PASS)
def grade_symbol(self, symbol: str, output: OUTPUT_TYPE) -> SymbolGrade:
"""
Always assigns a passing grade.
"""
# Assign a passing grade if the symbol is to be ignored.
if output is LongShortFavor.NOT_APPLICABLE:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.PASS)
# TEMPORARY: Always assign a passing grade.
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.PASS)
def grade_symbol(self, symbol: str, output: OUTPUT_TYPE) -> SymbolGrade:
"""Returns a grade based on % of profit targets that yield profit in simulation."""
# Fail the symbol if it has no output
if output is None:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
# Fail the symbol if the median of median daily profits is negligible
if median(output.target_med_pct_profits) < 0.05:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
# Fail the symbol if the median of average daily profits is negligible
if median(output.target_avg_pct_profits) < 0.05:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
# Assign the symbol a higher grade for higher profits
profits = median(output.target_avg_pct_profits)
if profits < 0.07:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.RISKY)
elif profits < 0.09:
return SymbolGrade(symbol, self.model_type,
SymbolGradeValue.UNPROMISING)
elif profits < 0.12:
return SymbolGrade(symbol, self.model_type,
SymbolGradeValue.SATISFACTORY)
elif profits < 0.15:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.GOOD)
elif profits < 0.2:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.GREAT)
else:
return SymbolGrade(symbol, self.model_type,
SymbolGradeValue.EXCELLENT)
def grade_symbol(self, symbol: str, output: AbstractForgetfulModel.OUTPUT_TYPE) -> SymbolGrade:
# Fail the symbol if it has no output
if output is None:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
# Assign a good grade if strongest percent dip is not too little or too much
# Essentially the sweet spot is anywhere between 0.1% and 0.3%
if output < 0.025 or output > 0.5:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
elif output < 0.05 or output > 0.45:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.RISKY)
elif output < 0.075 or output > 0.4:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.UNPROMISING)
elif output < 0.125 or output > 0.35:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.GOOD)
elif output < 0.15 or output > 0.3:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.GREAT)
else:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.EXCELLENT)
def grade_symbol(self, symbol: str, output: OUTPUT_TYPE) -> SymbolGrade:
"""Assigns a good grade to a high momentum value."""
# Fail the symbol if it has no output
if output is None:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
# Fail the symbol if price is trending strongly downward
if output < -0.5:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
# Assign a bad grade if price is trending moderately downward
elif output < -0.2:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.RISKY)
# Assign a mediocre grade if price is trending somewhat downward
elif output < -0.09:
return SymbolGrade(symbol, self.model_type,
SymbolGradeValue.UNPROMISING)
# Assign a neutral grade if price trending flat or up & down
elif output < 0.09:
return SymbolGrade(symbol, self.model_type,
SymbolGradeValue.SATISFACTORY)
# Assign a good grade if price is trending somewhat upward
elif output < 0.15:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.GOOD)
# Assign a great grade if price is trending strongly upward
elif output < 0.5:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.GREAT)
# Assign a mediocre grade if price is trending strongly upward (because we likely won't catch a price dip)
else:
return SymbolGrade(symbol, self.model_type,
SymbolGradeValue.UNPROMISING)
def grade_symbol(self, symbol: str, output: any) -> SymbolGrade:
"""Passes the symbol if its average daily price spread is at least 0.8%. Fails otherwise."""
if output is None or output < 0.008:
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.PASS)
def grade_symbol(self, symbol: str, output: OUTPUT_TYPE) -> SymbolGrade:
"""Returns whether the symbol passed all Breakout1Model checks."""
return SymbolGrade(symbol, self.model_type, SymbolGradeValue.PASS) if output.get_val('status') == 'VIABLE' \
else SymbolGrade(symbol, self.model_type, SymbolGradeValue.FAIL)