jblitzar/github-python-corpus · Datasets at Hugging Face

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else:
xrate = get_exchange_rates([args.currency], data['default_currency'], data['dates'],
start=args.start, end=args.end)[args.currency][-num_days]
args.capital *= xrate

# Volatile specifics
num_stocks, num_records = logp.shape
order = 2
horizon = 5
t = num_records - num_days

# extract hierarchical info
info = extract_hierarchical_info(data['sectors'], data['industries'])
info['order_scale'] = np.linspace(1 / (order + 1), 1, order + 1)[::-1].astype('float32')[None, :]
info['tt'] = (np.linspace(1 / t, 1, t) ** np.arange(order + 1).reshape(-1, 1)).astype('float32')
tt_pred = ((1 + (np.arange(1 + horizon) / t)) ** np.arange(order + 1).reshape(-1, 1)).astype('float32')

# tournament participants
names = ["Adam", "Betty", "Chris", "Dany", "Eddy", "Flora"]
tournament = {name: globals()[name](args.capital) for name in names}

# initialize capitals
uninvested = np.zeros((len(names), num_days))
invested = np.zeros((len(names), num_days))
capitals = np.zeros((len(names), num_days))
risks = np.zeros((len(names), num_days))

str_format = "{:<11} {:<20} {:<20} {:<20} {:<60} {:<20}"
num_dashes = 143
separator = num_dashes * "-"

print("\n* LET'S THE BOT-TOURNAMENT BEGINS! *\n")
for j in range(num_days, 0, -1):
phi_m, psi_m, phi_s, psi_s, phi_i, psi_i, phi, psi = train_msis_mcs(logp[:, -t - j:-j], info)

logp_est, std_logp_est = estimate_logprice_statistics(phi.numpy(), psi.numpy(), info['tt'])
logp_pred, std_logp_pred = estimate_logprice_statistics(phi.numpy(), psi.numpy(), tt_pred)
logp_ind_est, std_logp_ind_est = estimate_logprice_statistics(phi_i.numpy(), psi_i.numpy(), info['tt'])
logp_sec_est, std_logp_sec_est = estimate_logprice_statistics(phi_s.numpy(), psi_s.numpy(), info['tt'])
logp_mkt_est, std_logp_mkt_est = estimate_logprice_statistics(phi_m.numpy(), psi_m.numpy(), info['tt'])

p_est, std_p_est = estimate_price_statistics(logp_est, std_logp_est)
p_ind_est, std_p_ind_est = estimate_price_statistics(logp_ind_est, std_logp_ind_est)
p_sec_est, std_p_sec_est = estimate_price_statistics(logp_sec_est, std_logp_sec_est)
p_mkt_est, std_p_mkt_est = estimate_price_statistics(logp_mkt_est, std_logp_mkt_est)

variances = {}
for i, ticker in enumerate(tickers):
variances[ticker] = {"stock": std_p_est[i, -1] ** 2,
"industry": std_p_ind_est[info['industries_id'][i], -1] ** 2,
"sector": std_p_sec_est[info['sectors_id'][i], -1] ** 2,
"market": std_p_mkt_est[0, -1] ** 2}

scores = (logp_pred[:, horizon] - logp[:, -j - 1]) / std_logp_pred.squeeze()
rates = rate(scores)
growth = np.dot(phi.numpy()[:, 1:], np.arange(1, order + 1))

bot_info = {tickers[i]: {"price": price[i, -j - 1], "rate": rates[i], "growth": growth[i], "scores": scores[i]} for i in range(num_stocks)}
next_price = {tickers[i]: price[i, -j] for i in range(num_stocks)}

print()
print("DATE:", data['dates'].date[-j].strftime("%Y-%m-%d"))
print(separator)
print(str_format.format("BOT", "CAPITAL", "UNINVESTED", "INVESTED", "OWNED", "RISK"))
print(separator)
for i, (name, bot) in enumerate(tournament.items()):
bot.trade(bot_info)
bot.compute_capital(next_price)

risks[i, num_days - j] = compute_risk(bot.portfolio, variances, data['sectors'], data['industries'])
capitals[i, num_days - j] = bot.capital / xrate

print(str_format.format(name,
"{} {}".format(np.round(bot.capital / xrate, 2), args.currency),
"{} {}".format(np.round(bot.uninvested / xrate, 2), args.currency),
"{} {}".format(np.round(bot.invested / xrate, 2), args.currency),
' '.join(map(str, list(bot.portfolio.keys())[:10])) + ("..." if len(bot.portfolio.keys()) > 10 else ""),
np.round(risks[i, num_days - j], 2)))

print(separator)
print(separator)

# plot capitals
fig = plt.figure(figsize=(15, 8))
plt.title("Capitals over time", fontsize=15)
plt.plot(data['dates'][-num_days:], capitals.T)
plt.legend(names, loc="upper left", fontsize=12)
plt.xticks(rotation=45)
plt.ylabel("capital in {}".format(args.currency))

if not os.path.exists('plots'):
os.mkdir('plots')
fig_name = 'plots/tournament_capitals.png'
fig.savefig(fig_name, dpi=fig.dpi)
print('Plot of capitals over time has been saved in {}/{}.'.format(os.getcwd(), fig_name))

fig = plt.figure(figsize=(15, 8))
plt.title("Portfolio risk over time", fontsize=15)
plt.plot(data['dates'][-num_days:], risks.T)
plt.legend(names, loc="upper left", fontsize=12)

else:

xrate = get_exchange_rates([args.currency], data['default_currency'], data['dates'],

start=args.start, end=args.end)[args.currency][-num_days]

args.capital *= xrate

# Volatile specifics

num_stocks, num_records = logp.shape

order = 2

horizon = 5

t = num_records - num_days

# extract hierarchical info

info = extract_hierarchical_info(data['sectors'], data['industries'])

info['order_scale'] = np.linspace(1 / (order + 1), 1, order + 1)[::-1].astype('float32')[None, :]

info['tt'] = (np.linspace(1 / t, 1, t) ** np.arange(order + 1).reshape(-1, 1)).astype('float32')

tt_pred = ((1 + (np.arange(1 + horizon) / t)) ** np.arange(order + 1).reshape(-1, 1)).astype('float32')

# tournament participants

names = ["Adam", "Betty", "Chris", "Dany", "Eddy", "Flora"]

tournament = {name: globals()[name](args.capital) for name in names}

# initialize capitals

uninvested = np.zeros((len(names), num_days))

invested = np.zeros((len(names), num_days))

capitals = np.zeros((len(names), num_days))

risks = np.zeros((len(names), num_days))

str_format = "{:<11} {:<20} {:<20} {:<20} {:<60} {:<20}"

num_dashes = 143

separator = num_dashes * "-"

print("\n*** LET'S THE BOT-TOURNAMENT BEGINS! ***\n")

for j in range(num_days, 0, -1):

phi_m, psi_m, phi_s, psi_s, phi_i, psi_i, phi, psi = train_msis_mcs(logp[:, -t - j:-j], info)

logp_est, std_logp_est = estimate_logprice_statistics(phi.numpy(), psi.numpy(), info['tt'])

logp_pred, std_logp_pred = estimate_logprice_statistics(phi.numpy(), psi.numpy(), tt_pred)

logp_ind_est, std_logp_ind_est = estimate_logprice_statistics(phi_i.numpy(), psi_i.numpy(), info['tt'])

logp_sec_est, std_logp_sec_est = estimate_logprice_statistics(phi_s.numpy(), psi_s.numpy(), info['tt'])

logp_mkt_est, std_logp_mkt_est = estimate_logprice_statistics(phi_m.numpy(), psi_m.numpy(), info['tt'])

p_est, std_p_est = estimate_price_statistics(logp_est, std_logp_est)

p_ind_est, std_p_ind_est = estimate_price_statistics(logp_ind_est, std_logp_ind_est)

p_sec_est, std_p_sec_est = estimate_price_statistics(logp_sec_est, std_logp_sec_est)

p_mkt_est, std_p_mkt_est = estimate_price_statistics(logp_mkt_est, std_logp_mkt_est)

variances = {}

for i, ticker in enumerate(tickers):

variances[ticker] = {"stock": std_p_est[i, -1] ** 2,

"industry": std_p_ind_est[info['industries_id'][i], -1] ** 2,

"sector": std_p_sec_est[info['sectors_id'][i], -1] ** 2,

"market": std_p_mkt_est[0, -1] ** 2}

scores = (logp_pred[:, horizon] - logp[:, -j - 1]) / std_logp_pred.squeeze()

rates = rate(scores)

growth = np.dot(phi.numpy()[:, 1:], np.arange(1, order + 1))

bot_info = {tickers[i]: {"price": price[i, -j - 1], "rate": rates[i], "growth": growth[i], "scores": scores[i]} for i in range(num_stocks)}

next_price = {tickers[i]: price[i, -j] for i in range(num_stocks)}

print()

print("DATE:", data['dates'].date[-j].strftime("%Y-%m-%d"))

print(separator)

print(str_format.format("BOT", "CAPITAL", "UNINVESTED", "INVESTED", "OWNED", "RISK"))

print(separator)

for i, (name, bot) in enumerate(tournament.items()):

bot.trade(bot_info)

bot.compute_capital(next_price)

risks[i, num_days - j] = compute_risk(bot.portfolio, variances, data['sectors'], data['industries'])

capitals[i, num_days - j] = bot.capital / xrate

print(str_format.format(name,

"{} {}".format(np.round(bot.capital / xrate, 2), args.currency),

"{} {}".format(np.round(bot.uninvested / xrate, 2), args.currency),

"{} {}".format(np.round(bot.invested / xrate, 2), args.currency),

' '.join(map(str, list(bot.portfolio.keys())[:10])) + ("..." if len(bot.portfolio.keys()) > 10 else ""),

np.round(risks[i, num_days - j], 2)))

print(separator)

# plot capitals

fig = plt.figure(figsize=(15, 8))

plt.title("Capitals over time", fontsize=15)

plt.plot(data['dates'][-num_days:], capitals.T)

plt.legend(names, loc="upper left", fontsize=12)

plt.xticks(rotation=45)

plt.ylabel("capital in {}".format(args.currency))

if not os.path.exists('plots'):

os.mkdir('plots')

fig_name = 'plots/tournament_capitals.png'

fig.savefig(fig_name, dpi=fig.dpi)

print('Plot of capitals over time has been saved in {}/{}.'.format(os.getcwd(), fig_name))

fig = plt.figure(figsize=(15, 8))

plt.title("Portfolio risk over time", fontsize=15)

plt.plot(data['dates'][-num_days:], risks.T)

plt.legend(names, loc="upper left", fontsize=12)