rets = []
pred_rets = []
equals = []
Returns = list(dff['Returns'])
Prediction = list(dff['Predictions'])
for i in range(len(dff)):
if Returns[i] > 0.03:
rets.append("Higher")
elif 0.03 >= Returns[i] >= -0.03:
rets.append("Neutral")
elif -0.03 > Returns[i]:
rets.append("Lower")
if Prediction[i] > 0.03:
pred_rets.append("Higher")
elif 0.03 >= Prediction[i] >= -0.03:
pred_rets.append("Neutral")
elif -0.03 > Prediction[i]:
pred_rets.append("Lower")

for i in range(len(dff)):
if rets[i] == pred_rets[i]:
equals.append(1)
else:
equals.append(0)

print "% Total Correct:", np.average(equals) * 100