def trend_least_square(self, prices, diff_vals, cutoff, mult):
diff = self.find_matches(diff_vals, cutoff, mult)
temp_prices = self.match_indexes(diff, prices)
inter, slope = Helper.least_square(temp_prices)
return Straight(inter, slope, 0, self.sim_vars.analysisRange), diff
def run_algo(self, stock):
finished_trades = []
print "Running SR: %s" % (stock,)
splits = []
data = Helper.read_data_file(self.data_file_loc + stock + self.data_file_ext)
# Not all stocks have split data
try:
splits = Helper.read_split_file(self.split_file_loc + stock + self.split_file_ext)
except:
None
trades = []
short_buffer_zone = False
long_buffer_zone = False
for i in range(0, len(data) - self.sim_vars.analysisRange, self.sim_vars.stepSize):
prices = data[i: i+self.sim_vars.analysisRange]
for j in range(0, len(prices)):
prices[j].index = j
close = prices[-1].close
cur_split = Split(1.0, 0)
for split in splits:
if split.timestamp < prices[-1].timestamp < (split.timestamp + 86400):
cur_split = split
# Check if we can exit trade
finished_trades.extend(self.check_exit(trades, prices[-1], cur_split))
# Find least square line of all prices
inter, slope = Helper.least_square(prices)
mean_least_square = Straight(inter, slope, 0, self.sim_vars.analysisRange)
y_vals = mean_least_square.y_vals
diff_vals = [prices[z].close - y_vals[z] for z in range(0, len(prices))]
# Generate least square trend lines
(res_least_square, res_diff) = self.trend_least_square(prices, diff_vals, self.sim_vars.resCutoff, 1)
(sup_least_square, sup_diff) = self.trend_least_square(prices, diff_vals, self.sim_vars.supCutoff, -1)
res_val = res_least_square.y_vals[-1]
sup_val = sup_least_square.y_vals[-1]
# Generate range to enter trade
max_long_buy_point = sup_val + (res_val-sup_val)*self.sim_vars.resMaxBuyPer/100
min_long_buy_point = sup_val + (res_val-sup_val)*self.sim_vars.resMinBuyPer/100
max_short_sell_point = res_val - (res_val-sup_val)*self.sim_vars.supMinBuyPer/100
min_short_sell_point = res_val - (res_val-sup_val)*self.sim_vars.supMaxBuyPer/100
if long_buffer_zone or short_buffer_zone:
# Find sections of line that have matches
pos_matches = [False, False, False]
neg_matches = [False, False, False]
for k in range(0, 3):
for diff in res_diff:
if (k+1)*(len(prices))//3 > diff.index > k*(len(prices))//3:
pos_matches[k] = True
for diff in sup_diff:
if (k+1)*(len(prices))//3 > diff.index > k*(len(prices))//3:
neg_matches[k] = True
buy_point, sell_point, pot_buy, actual_type = Helper.trendType(res_least_square.slope,
sup_least_square.slope, res_least_square.intercept,
sup_least_square.intercept,
self.sim_vars.analysisRange, self.sim_vars.supMinBuyPer/100.0,
self.sim_vars.resMinBuyPer/100.0, close,
self.sim_vars.analysisRange-1, self.sim_vars.analysisRange-1)
#only consider buying when support matches in middle and at least one side
long_pot_buy = pot_buy and (neg_matches[1] and (neg_matches[0] or neg_matches[2])) \
and (pos_matches[1] and (pos_matches[0] and pos_matches[2]))
short_pot_buy = long_pot_buy
if self.sim_vars.longStocks and long_buffer_zone and sell_point > close*(1.0 + self.sim_vars.minimumPercent/100.0) and long_pot_buy:
if min_long_buy_point <= close <= max_long_buy_point:
long_buffer_zone = False
t = PlotTrade("long", prices[-1].timestamp, None, close, None, None, None, sell_point,
close - close*self.sim_vars.stopLossPerc/100.0, prices, sup_least_square, res_least_square, stock)
t.mean_line = mean_least_square
trades.append(t)
elif self.sim_vars.shortStocks and short_buffer_zone and buy_point < close/(1.0 + self.sim_vars.minimumPercent/100.0) and short_pot_buy:
if min_short_sell_point <= close <= max_short_sell_point:
short_buffer_zone = False
t = PlotTrade("short", prices[-1].timestamp, None, close, None, None, None, buy_point,
close + close*self.sim_vars.stopLossPerc/100, prices, sup_least_square, res_least_square, stock)
t.mean_line = mean_least_square
trades.append(t)
# We only want to allow trades if we go below a buffer zone
# Check if within buffer zone
if sup_val + (res_val-sup_val)*(self.sim_vars.bufferPercent/100.0) >= close:
long_buffer_zone = True
elif close < min_long_buy_point and long_buffer_zone:
long_buffer_zone = True
else:
long_buffer_zone = False
if res_val - (res_val-sup_val)*(self.sim_vars.bufferPercent/100.0) <= close:
short_buffer_zone = True
elif close > max_short_sell_point and short_buffer_zone:
short_buffer_zone = True
else:
short_buffer_zone = False
return finished_trades
