88 lines
4.5 KiB
Python
88 lines
4.5 KiB
Python
from datetime import datetime
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from pandas import DataFrame
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from strategies import advances
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from strategies import cumulative_rsi
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from strategies import declines
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from strategies import double_5s
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from strategies import down_days_in_a_row
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from strategies import end_of_month
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from strategies import high_volume_days
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from strategies import hilo_index_lows
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from strategies import ibs_rsi
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from strategies import internal_bar_strength
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from strategies import internal_bar_strength_band
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from strategies import large_moves_down
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from strategies import lower_lows
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from strategies import put_call_ratio_highs
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from strategies import rsi_25_75
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from strategies import rsi_power_zones
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from strategies import short_term_lows
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from strategies import tps
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from strategies import trin
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from strategies import trin_thrusts
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from strategies import turnaround
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from strategies import two_period_rsi
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from strategies import vix_above_moving_average
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from strategies import vix_reversal_1
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from strategies import vix_reversal_2
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from strategies import vix_reversal_3
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from strategies import vix_rsi
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from daily_data import get_daily_data
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def calculate_signals(data: DataFrame, days: int = 12) -> DataFrame:
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start_date = data['Date'].min()
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end_date = data['Date'].max()
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advances_data = get_daily_data(symbol = 'IINA.Z', start_date = start_date, end_date = end_date)
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declines_data = get_daily_data(symbol = 'IIND.Z', start_date = start_date, end_date = end_date)
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new_highs_data = get_daily_data(symbol = 'FINH.Z', start_date = start_date, end_date = end_date)
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new_lows_data = get_daily_data(symbol = 'FINL.Z', start_date = start_date, end_date = end_date)
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put_volume_data = get_daily_data(symbol = 'VPOT.Z', start_date = start_date, end_date = end_date)
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call_volume_data = get_daily_data(symbol = 'VCOT.Z', start_date = start_date, end_date = end_date)
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trin_data = get_daily_data(symbol = 'RINT.Z', start_date = start_date, end_date = end_date)
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vix_data = get_daily_data(symbol = 'VIX.XO', start_date = start_date, end_date = end_date)
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strategy_signals = [
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{'strategy': '2-Period RSI', 'signals': two_period_rsi(data)},
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{'strategy': 'Advances', 'signals': advances(data, advances_data, declines_data)},
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{'strategy': 'Cumulative RSI', 'signals': cumulative_rsi(data)},
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{'strategy': 'Declines', 'signals': declines(data, declines_data, advances_data)},
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{'strategy': 'Double 5\'s', 'signals': double_5s(data)},
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{'strategy': 'Down Days in a Row', 'signals': down_days_in_a_row(data)},
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{'strategy': 'End of Month', 'signals': end_of_month(data)},
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{'strategy': 'High Volume Days', 'signals': high_volume_days(data)},
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{'strategy': 'HILO Index Lows', 'signals': hilo_index_lows(data, new_highs_data, new_lows_data)},
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{'strategy': 'IBS + RSI', 'signals': ibs_rsi(data)},
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{'strategy': 'Internal Bar Strength', 'signals': internal_bar_strength(data)},
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{'strategy': 'Internal Bar Strength Band', 'signals': internal_bar_strength_band(data)},
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{'strategy': 'Large Moves Down', 'signals': large_moves_down(data)},
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{'strategy': 'Lower Lows', 'signals': lower_lows(data)},
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{'strategy': 'Put / Call Ratio Highs', 'signals': put_call_ratio_highs(data, put_volume_data, call_volume_data)},
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{'strategy': 'RSI 25 / 75', 'signals': rsi_25_75(data)},
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{'strategy': 'RSI PowerZones', 'signals': rsi_power_zones(data)},
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{'strategy': 'Short-Term Lows', 'signals': short_term_lows(data)},
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{'strategy': 'TPS', 'signals': tps(data)},
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{'strategy': 'TRIN', 'signals': trin(data, trin_data)},
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{'strategy': 'TRIN Thrusts', 'signals': trin_thrusts(data, trin_data)},
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{'strategy': 'Turnaround', 'signals': turnaround(data)},
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{'strategy': 'VIX Above Moving Average', 'signals': vix_above_moving_average(data, vix_data)},
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{'strategy': 'VIX Reversal 1', 'signals': vix_reversal_1(data, vix_data)},
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{'strategy': 'VIX Reversal 2', 'signals': vix_reversal_2(data, vix_data)},
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{'strategy': 'VIX Reversal 3', 'signals': vix_reversal_3(data, vix_data)},
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{'strategy': 'VIX RSI', 'signals': vix_rsi(data, vix_data)}
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]
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signal_data = []
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for signal_info in strategy_signals:
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signal_dict = {'Strategy': signal_info['strategy']}
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signals = signal_info['signals'].tail(days)
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dates = [datetime.strptime(str(date), '%Y-%m-%d').strftime('%m/%d') for date in data.tail(days)['Date']]
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for date, signal in zip(dates, signals):
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signal_dict[date] = signal
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signal_data.append(signal_dict)
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return DataFrame(signal_data) |