def __init__(self, api, secret, saved=None, n=26): self.account = account(api, secret) self.balances = np.array([self.account.balances[c] if c in self.account.balances else 0.0 for c in [RISKLESS] + QUOTES + CURRENCIES]) if saved is not None: try: with open(saved, 'rb') as file: loaded = pickle.load(file) self.manager = loaded.manager self.prices = loaded.prices self.returns = loaded.returns self.update_times = loaded.update_times self.portfolio = np.array(loaded.portfolio) return except FileNotFoundError: pass #get the portfolio... self.manager = MAMRPortfolioManager(len(CURRENCIES) + len(QUOTES) + 1, 4.105, 9.5, 1000, 0.0, n) from data.get_candles_spot import main as get_candles get_candles() price_changes = [] times = [] self.prices = [] for candle in candleLoader(DATABASE): #consider markets trading against BTC, so we need to invert the USDT price self.prices.append(np.array([1] + [candle[currency + 'USDT_OPEN'] for currency in QUOTES + CURRENCIES])) if len(self.prices) == 1: continue else: price_changes.append(self.prices[-1] / self.prices[-2]) times.append(candle['open_time']) for change, time in zip(price_changes[-n:], times[-n:]): self.manager.update(time, change) self.returns = price_changes self.update_times = times self.portfolio = self.account.get_portfolio_weighted(['USDT'] + QUOTES + CURRENCIES) self.manager.portfolio = np.array(self.portfolio) self.prices.append(np.array([1.05 ** (0.5 / 365)] + [np.mean(market.prices([a + 'USDT' for a in QUOTES + CURRENCIES])[b + 'USDT']) for b in QUOTES + CURRENCIES]))
def main():
#get all the candles and calculate the price changes
price_changes = []
prices = []
times = []
for candle in candleLoader(DATABASE):
#consider markets trading against BTC, so we need to invert the USDT price
prices.append(np.array([1] + [candle[currency + 'USDT_OPEN'] for currency in CURRENCIES]))
if len(prices) == 1:
continue
else:
price_changes.append(prices[-1] / prices[-2])
price_changes[-1][0] = 1.05 ** (0.5 / 365)
times.append(candle['open_time'])
#manager = MAMRPortfolioManager(len(CURRENCIES) + 1, 11.75, 371, 995, 0.001, 23)
#manager = MAMRPortfolioManager(len(CURRENCIES) + 1, 4.105, 9.5, 1000, 0.00075, 26)
manager = MAMRPortfolioManager(len(CURRENCIES) + 1, 4.105, 9.5, 1000, 0.000, 26)
#manager = MAMRPortfolioManager(len(CURRENCIES) + 1, 50, 50, 60, 0.000, 26)
for change, time in zip(price_changes, times):
manager.update(time, change)
print(manager.value)
plt.figure(0)
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times], np.array(manager.values[1:]), label='MAMR Portfolio Value')
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times], [p[1]/prices[0][1] for p in prices[1:]], label='BTC Return')
plt.yscale('log')
plt.ylabel('Return')
plt.title('MAMR 12 hour updates, 0.001 Transaction Fee')
plt.legend()
plt.figure(1)
for i, currency in enumerate(['USDT'] + CURRENCIES):
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times], [p[i] for p in manager.portfolios[1:]], label=currency)
plt.legend()
plt.show()
def main():
#get all the candles and calculate the price changes
price_changes = []
prices = []
times = []
funding_rates = []
for candle in candleLoader(DATABASE):
funding_rates.append([
candle[currency + 'USDT_funding_rate'] for currency in CURRENCIES
])
prices.append(
np.array(
[candle[currency + 'USDT_open'] for currency in CURRENCIES]))
if len(prices) == 1:
continue
else:
price_changes.append(prices[-1] / prices[-2])
times.append(candle['open_time'])
manager = PAMRPortfolioManager(len(CURRENCIES), 0, 200, 0.0000, 1)
for i, (change, time,
funding_rate) in enumerate(zip(price_changes, times,
funding_rates)):
print((times[-1] - time) / (1000 * 60 * 30))
if i % 16 == 0:
manager.update(time, change, np.array(funding_rate))
#manager.update(time, change, np.zeros(len(CURRENCIES)))
else:
manager.update(time, change, np.zeros(len(CURRENCIES)))
plt.figure(0)
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times],
manager.values[1:])
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times],
[p[1] / prices[0][1] for p in prices[1:]])
plt.yscale('log')
plt.figure(1)
for i, currency in enumerate(CURRENCIES):
plt.plot([p[i] for p in manager.portfolios], label=currency)
plt.legend()
plt.show()
def main():
#get all the candles and calculate the price changes
price_changes = []
prices = []
times = []
for candle in candleLoader(DATABASE):
#consider markets trading against BTC, so we need to invert the USDT price
prices.append(np.array([1 / candle['BTCUSDT_OPEN'], 1] + [candle[currency + 'BTC_OPEN'] for currency in CURRENCIES]))
if len(prices) == 1:
continue
else:
price_changes.append(prices[-1] / prices[-2])
times.append(candle['open_time'])
manager = PAMRPortfolioManager(len(CURRENCIES) + 2, 0.99, 4, 0.001)
for i, (change, time) in enumerate(zip(price_changes, times)):
print((times[-1] - time) / (1000 * 60 * 30))
manager.update(time, change)
plt.figure(0)
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times], np.array(manager.values[1:]) / np.array([p[0]/prices[0][0] for p in prices[1:]]), label='PAMR Portfolio Value')
plt.plot([datetime.datetime.fromtimestamp(time / 1000) for time in times], [prices[0][0]/p[0] for p in prices[1:]], label='BTC Return')
plt.yscale('log')
plt.ylabel('Return')
plt.title('PAMR Daily Updates, 0.001 Transaction Fee')
plt.legend()
plt.figure(1)
for i, currency in enumerate(['USDT', 'BTC'] + CURRENCIES):
print(currency)
plt.plot([p[i] for p in manager.portfolios], label=currency)
plt.legend()
plt.show()