Fortune/putSpread.py at main · Austin-Src/Fortune · GitHub

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import ameritrade as am
import requests

# Calculate when spread return is zero
def getZeroProfit(stockPrice, sellStrike, buyStrike, sellPrice, buyPrice):
	hitZero = 0

	# Check that return is positive
	data = calculateProfits(0, stockPrice,
		sellStrike, buyStrike, sellPrice, buyPrice, 0)

	if data is not None:
		if data[6]>= 0:
			spreadCost = data[5]
			hitZero = (((buyStrike - spreadCost) / stockPrice) - 1) * 100
	return hitZero

# Calculate max spread return
def calculateProfits(change, stockPrice, sellStrike, buyStrike, sellPrice,
	buyPrice, hitsZero):

	stock_Price = stockPrice * change
	buyValue = stock_Price - buyStrike
	sellValue = sellStrike - stock_Price


	spreadValue = buyValue + sellValue
	spreadCost = buyPrice - sellPrice

	if buyPrice == 0:
		spreadCost = 0.0
	if sellPrice == 0:
		spreadCost = 0.0
	spreadProfit = spreadCost - spreadValue * -1.0

	if spreadCost == 0:
		percentReturn = 0.0
	else:
		percentReturn = spreadProfit / spreadCost * -1.0


	return [stockPrice, buyStrike, sellStrike, buyPrice, sellPrice,
		spreadCost, spreadProfit * -1, percentReturn * 100, hitsZero]

# Wrapper function returns Zero Profit and Expected Return
def getProfits(stock_Price, sell_Strike, buy_Strike, sell_Price, buy_Price):
	outputs = []

	hitsZero = getZeroProfit(stock_Price, sell_Strike, buy_Strike,
		sell_Price, buy_Price)
	outputs.append(calculateProfits(1.1, stock_Price,
			sell_Strike, buy_Strike, sell_Price,
			buy_Price, hitsZero))
	return outputs

# Pulls all relevant put spreads for a given stock
def putSpread(stock, expiration, protection, spreadReturn, spreadCost, openInterest, priceSpread):
	data = am.callAPI('PUT', stock)
	expDate = 'putExpDateMap'
	selections = am.getDates(data, expDate)
	x = expiration
	outputs = []


	# Check that Call has an Options Chain for Selected Date
	try:
		z = data[expDate][x]
	except:
		return

	for y in data[expDate][x]:

		bid = data[expDate][x][y][0]['bid']
		ask = data[expDate][x][y][0]['ask']
		underlyingPrice = data['underlyingPrice']
		strikePrice = data[expDate][x][y][0]['strikePrice']

		yPrice = (bid+ask)/2

		if yPrice == 0.0:
			continue

		if strikePrice <= underlyingPrice:
			continue

		for s in data[expDate][x]:
			# Only compare when sellstrike is higher
			if s >= y:
				continue

			# Only use in the money calls
			if data[expDate][x][s][0]['inTheMoney'] == 'false':
				continue

			bid = data[expDate][x][s][0]['bid']
			ask = data[expDate][x][s][0]['ask']
			sPrice = (bid+ask) / 2
			if sPrice == 0.0:
				continue

			if data[expDate][x][s][0]['strikePrice'] <= data['underlyingPrice']:
				continue

			#print(data[expDate][x][s][0]['description'])
			if data[expDate][x][s][0]['strikePrice'] < data[expDate][x][y][0]['strikePrice']:
				test = getProfits(data['underlyingPrice'],
					data[expDate][x][s][0]['strikePrice'],
					data[expDate][x][y][0]['strikePrice'],
					sPrice, yPrice)

				minProtection = protection
				minPercentReturn = spreadReturn
				minSpreadCost = spreadCost
				naturalPrice = data[expDate][x][y][0]['ask'] - data[expDate][x][s][0]['bid']
				midPrice = test[0][5]

				# Refine program outputs
				if test[0][8] is not None:
					if test[0][8] > float(minProtection):
						if test[0][7] >= float(minPercentReturn):
							if test[0][5] >= float(minSpreadCost):
								if data[expDate][x][y][0]['nonStandard'] == False:
									if data[expDate][x][s][0]['openInterest'] >= int(openInterest):
										if data[expDate][x][y][0]['openInterest'] >= int(openInterest):
											if naturalPrice - midPrice <= float(priceSpread):
												test[0][0] = str(data[expDate][x][s][0]['description'].split(" ")[0]) + " @ " + str(round(test[0][0], 2))
												test[0][1] = str(test[0][1]) + " : " + str(data[expDate][x][y][0]['openInterest'])
												test[0][2] = str(test[0][2]) + " : " + str(data[expDate][x][s][0]['openInterest'])
												outputs.append(test)


	flat_list = []
	for sublist in outputs:
	    for item in sublist:
                flat_list.append(item)

	return am.Sort(flat_list)