# Stock Investors Financial Math
# https://www.fmlabs.com/reference/default.htm?url=SimpleMA.htm

# Alpha Vantage
# https://www.alphavantage.co/documentation/

# Pandas
# https://pandas.pydata.org/pandas-docs/stable/index.html

# Knowledge
# https://www.investopedia.com/articles/technical/02/050602.asp
# https://ntguardian.wordpress.com/2016/09/19/introduction-stock-market-data-python-1

do_plot = 1

if do_plot:
	import matplotlib.pyplot as plt
	import matplotlib as mpl
	mpl.rc('figure', max_open_warning = 0)

from stock import Stock

params = {
	'show_range_days' : 10,
	'btfd' : {'thresh_max' : -7, 'thresh_min' : 1, 'cand_window' : 5},
	'k_euro' : 1 / 1.11,
	'ema_alpha' : 0.75,
	'sma_days' : 10,
	'q_days' : 10,
	'fetch_on_outdated' : True
}

show_symbols = ['OHB.DE', 'ITMPF', 'PLUG', 'MOR.DE', 'CSCO', 'ERCA.DE', 'AVGO', 'DIS', 'UBSFF', 'DHER.DE', 'AIR']
show_symbols = ['CSCO']
#show_symbols = ['PCELF']
#show_symbols = ['OHB.DE']
#show_symbols = ['UBSFF']
#show_symbols = ['DHER.DE']
#show_symbols = ['WDI.DE']
#show_symbols = ['EVT.DE']
show_symbols = []

symbols = {
        'KEP' : {'name' : 'Korea Electric Power Corporation', 'currency' : '$'},
        'MRK.DE' : {'name' : 'Merck', 'currency' : '€'},
        'TOM.F' : {'name' : 'Toyota Motor Corporation', 'currency' : '€'},
	'SSHPF' : {'name' : 'Scanship Holding ASA', 'currency' : '$'},
	'RIG' : {'name' : 'Transocean Ltd.', 'currency' : '$'},
	'BBIO' : {'name' : 'BridgeBio Pharma, Inc.', 'currency' : '$'},
	'APA' : {'name' : 'Apache Corporation', 'currency' : '$'},
	'CBB-PB' : {'name' : 'Cincinnati Bell Inc.', 'currency' : '$'},
	'NMHLY' : {'name' : 'NMC Health Plc', 'currency' : '$'},
	'PINS' : {'name' : 'Pinterest', 'currency' : '$'},
	'TSLA' : {'name' : 'Tesla Inc.', 'currency' : '$'},
	'ACB' : {'name' : 'Aurora Cannabis Inc.', 'currency' : '$'},
	'ITCI' : {'name' : 'Intra-Cellular Therapies', 'currency' : '$'},
	'WDI.DE' : {'name' : 'WireCard', 'currency' : '€'},
	'AAPL' : {'name' : 'Apple', 'currency' : '$'},
	'XLNX' : {'name' : 'Xilinx', 'currency' : '$'},
	'QCOM' : {'name' : 'Qualcomm', 'currency' : '$'},
	'DPW.DE' : {'name' : 'Deutsche Post', 'currency' : '€'},
	'CSCO' : {'name' : 'Cisco', 'currency' : '$'},
	'AIR' : {'name' : 'Airbus', 'currency' : '$'},
	'BA' : {'name' : 'Boeing', 'currency' : '$'},
	'NVDA' : {'name' : 'Nvidia', 'currency' : '$'},
	'MSFT' : {'name' : 'Microsoft', 'currency' : '$'},
	'DIS' : {'name' : 'Disney', 'currency' : '$'},
	'NFLX' : {'name' : 'Netflix', 'currency' : '$'},
	'OHB.DE' : {'name' : 'OHB', 'currency' : '€'},
	'ERCA.DE' : {'name' : 'Ericsson', 'currency' : '€'},
	'VAR1.DE' : {'name' : 'Varta', 'currency' : '€'},
	'HD' : {'name' : 'Home Depot', 'currency' : '$'},
	'AMZN' : {'name' : 'Amazon', 'currency' : '$'},
	'GOOGL' : {'name' : 'Google', 'currency' : '$'},
	'FB2A.DE' : {'name': 'Facebook Inc.', 'currency' : '€'},
	'ZIL2.DE' : {'name': 'ElringKlinger', 'currency' : '€'},
	'SIS.DE' : {'name': 'First Sensor', 'currency' : '€'},
	'SIE.DE' : {'name': 'Siemens', 'currency' : '€'},
	'GFT.DE' : {'name': 'GFT Technologies', 'currency' : '€'},
	'AMD.DE' : {'name': 'Advanced Micro Devices', 'currency' : '€'},
	'CAP.DE' : {'name': 'Encavis', 'currency' : '€'},
	'ADBE' : {'name': 'Adobe', 'currency' : '$'},
	'PANW' : {'name': 'Palo Alto Networks', 'currency' : '$'},
	'AMAT' : {'name': 'Applied Materials', 'currency' : '$'},
	'RIB.DE' : {'name': 'RIB Software', 'currency' : '€'},
	'WAF.DE' : {'name': 'Siltronic', 'currency' : '€'},
	'EVT.DE' : {'name': 'Evotec', 'currency' : '€'},
	'VOW.DE' : {'name': 'Volkswagen', 'currency' : '€'},
	'BMW.DE' : {'name': 'BMW', 'currency' : '€'},
	'NSU.DE' : {'name': 'Audi', 'currency' : '€'},
	'DAI.DE' : {'name': 'Daimler', 'currency' : '€'},
	'SHA.DE' : {'name': 'Schaeffler', 'currency' : '€'},
	'CON.DE' : {'name': 'Continental', 'currency' : '€'},
	'DHER.DE' : {'name': 'Delivery Hero', 'currency' : '€'},
	'BSL.DE' : {'name': 'Basler', 'currency' : '€'},
	'D6H.DE' : {'name': 'DATAGROUP', 'currency' : '€'},
	'TC1.DE' : {'name': 'Tele Columbus', 'currency' : '€'},
	'VODI.DE' : {'name': 'Vodaphone Group', 'currency' : '€'},
	'ATVI' : {'name': 'Activision Blizzard', 'currency' : '$'},
	'GME' : {'name': 'GameStop', 'currency' : '$'},
	'NTO.F' : {'name': 'Nintendo', 'currency' : '$'},
	'UBSFF' : {'name': 'UBI Soft', 'currency' : '$'},
	'NXPRF' : {'name': 'Nexans', 'currency' : '$'},
#	'IMPUF' : {'name': 'Impala Platinum Holdings', 'currency' : '$'},
	'NMPNF' : {'name': 'Northam Platinum', 'currency' : '$'},
	'ALSMY' : {'name': 'Alstom', 'currency' : '$'},
	'ARRD.F' : {'name': 'Arcelor Mittal', 'currency' : '$'},
	'PHG' : {'name': 'Philips', 'currency' : '$'},
	'KEYS' : {'name': 'KeySight', 'currency' : '$'},
	'ORCL' : {'name': 'Oracle', 'currency' : '$'},
	'UBER' : {'name': 'Uber', 'currency' : '$'},
	'VMW' : {'name': 'VMWare', 'currency' : '$'},
	'AVGO' : {'name' : 'Avago', 'currency' : '$'},
	'CY' : {'name': 'Cypress Semiconductor', 'currency' : '$'},
	'QABSY' : {'name': 'Qanta Airways', 'currency' : '$'},
	'BLDP' : {'name': 'Ballard Power', 'currency' : '$'},
	'D7G.F' : {'name': 'Nel ASA', 'currency' : '$'},
	'ITMPF' : {'name': 'ITM Power', 'currency' : '$'},
	'PLUG' : {'name': 'PlugPower', 'currency' : '$'},
	'PCELF' : {'name': 'PowerCell', 'currency' : '$'},
	'SU.PA' : {'name': 'Schneider Electric', 'currency' : '$'},
#	'SON1.DE' : {'name': '', 'currency' : '€'},
	'STM.DE' : {'name': 'STM Micro', 'currency' : '€'},
	'BC8.DE' : {'name': 'Bechtle', 'currency' : '€'},
	'MOR.DE' : {'name' : 'Morphosys', 'currency' : '€'},
	'BAYN.DE' : {'name' : 'Bayer', 'currency' : '€'},
	'BEI.DE' : {'name' : 'Beiersdorf', 'currency' : '€'},
	'EUZ.DE' : {'name': 'Eckert & Ziegler', 'currency' : '€'},
	'SLAB' : {'name': 'Silicon Laboratories', 'currency' : '$'},
	'SPLK' : {'name' : 'Splunk', 'currency' : '$'},
	'IAG' : {'name' : 'IAG', 'currency' : '$'},
	'INTC' : {'name' : 'Intel Corporation', 'currency' : '$'},
	'I' : {'name': 'IntelSat', 'currency' : '$'}}

buy_list = {}
def buy_callback(data):
	name = data['name']
	item = data['item']
	if name not in buy_list:
		buy_list[name] = {'items': [item]}
	else:
		buy_list[name]['items'].append(item)

	print(data)

figNum = 1
if len(show_symbols) > 0:
	for symbol in show_symbols:
		if symbol in symbols:
			title = Stock(params, symbol, symbols[symbol])
			title.fetch()
			title.statistics()
			try:
				ind = title.analyze(buy_callback, range_days=params['show_range_days'])
				if do_plot:
					title.show(ind, figNum=figNum)
				figNum += 1
			except:
				print ("Exception occurred for {}".format(symbol))

else:
	for symbol in symbols:
		title = Stock(params, symbol, symbols[symbol])
		title.fetch()
		title.statistics()
		try:
			ind = title.analyze(buy_callback, range_days=params['show_range_days'])
			if Stock.has_candidate(ind, 'BTFD'):
				print('-----------------------------------------------')
				if do_plot:
					title.show(ind, figNum=figNum)
				figNum += 1
		except:
			print ("Exception occurred for {}".format(symbol))
gain_accum = 0
num_stocks = 0
for symbol in buy_list:
	items = buy_list[symbol]['items']
	title = Stock(params, symbol, symbols[symbol])
	title.fetch()
	title.statistics()
	gain = title.get_latest('close_n') - items[0]['value']
	gain_accum += gain
	num_stocks += 1
	print ('{}: Gain = {} %'.format(symbol, gain))

if num_stocks > 0:
	print ('Gain total = {} %'.format(gain_accum/num_stocks))

if do_plot:
	plt.show()