def main():
# read data
key_word = 'rare earths'
debt_data = pd.read_csv('../Data/%s_google_trend.csv' %key_word,header = 1)
nasdaq = pd.read_csv('../Data/nasdaq_historical_quotes.csv',header = 0)[['Date','Open','Close']]
# preprocess data
preprocess_raw_data = m.preprocessData(debt_data, key_word, nasdaq)
# strategy excution
trade_data = m.excuteStrategy(preprocess_raw_data,key_word, excute_random_strategy = False)
#print trade_data.describe()
# process trade result data
trade_data = processTradingData(trade_data)
# hmm model analyze
hmmtest(trade_data, trade_data[['Nasdaq_Close_RDP_5','Strategy_Gross_Return_RDP_5']])
columnName = []
period = [1,2,5,15,30]
column = ['Nasdaq_Close','Strategy_Gross_Return','Strategy_Cumulative_Return_R']
for col in column:
for i in period:
col_name = str('%s_RDP_%s' % (col, str(i)))
columnName.append(col_name)
def hmmAnalyze(key_word, result_csv):
# Acquiring data
fileName = ('../Data/%s_google_trend.csv'%key_word)
key_word_data = pd.read_csv(fileName,header = 1)
nasdaq = pd.read_csv('../Data/nasdaq_historical_quotes.csv',header = 0)[['Date','Open','Close']]
# Processing data
preprocess_raw_data = ma.preprocessData(key_word_data,key_word, nasdaq)
# add indicator into data for trading strategy
trade_data = ma.excuteStrategy(preprocess_raw_data, key_word)
# preprocess data
trade_data = hmm.processTradingData(trade_data)
# hmm model analyze
print ('%s is under test' %key_word)
result_model = hmm.hmmtest(trade_data, trade_data[['Nasdaq_Close_RDP_5','Strategy_Gross_Return_RDP_5']])
columnName = []
period = [1,2,5,15,30]
column = ['Nasdaq_Close','Strategy_Gross_Return','Strategy_Cumulative_Return_R']
for col in column:
for i in period:
col_name = str('%s_RDP_%s' % (col, str(i)))
columnName.append(col_name)
outputResult(key_word,result_model, result_csv,trade_data)
print('-------------------------')