advanced-algorithmic-trading

437
)
# Create the lookback and lookforward shifts
for i in range(0, lookback_minutes):
ts["Lookback%s" % str(i+1)] = ts["Close"].shift(i+1)
for i in range(0, lookforward_minutes):
ts["Lookforward%s" % str(i+1)] = ts["Close"].shift(-(i+1))
ts.dropna(inplace=True)
# Adjust all of these values to be percentage returns
ts["Lookback0"] = ts["Close"].pct_change()*100.0
for i in range(0, lookback_minutes):
ts["Lookback%s" % str(i+1)] = ts[
"Lookback%s" % str(i+1)
].pct_change()*100.0
for i in range(0, lookforward_minutes):
ts["Lookforward%s" % str(i+1)] = ts[
"Lookforward%s" % str(i+1)
].pct_change()*100.0
ts.dropna(inplace=True)
# Determine if the stock has gone up at least by
# ’up_down_factor’ x ’percent_factor’ and down no more
# then ’percent_factor’
up = up_down_factor*percent_factor
down = percent_factor
# Create the list of True/False entries for each date
# as to whether the up/down logic is true
down_cols = [
ts["Lookforward%s" % str(i+1)] > -down
for i in range(0, lookforward_minutes)
]
up_cols = [
ts["Lookforward%s" % str(i+1)] > up
for i in range(0, lookforward_minutes)
]
# Carry out the bitwise and, as well as bitwise or
# for the down and up logic
down_tot = down_cols[0]
for c in down_cols[1:]:
down_tot = down_tot & c
up_tot = up_cols[0]
for c in up_cols[1:]:
up_tot = up_tot | c