def write_hourly_volume_index_to_csv(print_components=0):
bitstamp, time_list_bitstampM, prices_bitstampM, volumes_bitstampM = di.get_list(exc="bitstampusd")
coinbase, time_list_coinbaseM, prices_coinbaseM, volumes_coinbaseM = di.get_list(exc="coinbaseusd")
korbit, time_list_korbitM, prices_korbitM, volumes_korbitM = di.get_list(exc="korbitkrw")
krak, time_list_krakM, prices_krakM, volumes_krakM = di.get_list(exc="krakeneur")
cc, time_list_ccM, prices_ccM, volumes_ccM = di.get_list(exc="coincheckjpy")
bitstamp_hour_list, prices, volumes_bitstampH = dis.convert_to_hour(time_list_bitstampM, prices_bitstampM,volumes_bitstampM)
coinbase_hour_list, prices, volumes_coinbaseH = dis.convert_to_hour(time_list_coinbaseM, prices_coinbaseM, volumes_coinbaseM)
korbit_hour_list, prices, volumes_korbitH = dis.convert_to_hour(time_list_korbitM, prices_korbitM, volumes_korbitM)
krak_hour_list, prices, volumes_krakH = dis.convert_to_hour(time_list_krakM, prices_krakM, volumes_krakM)
cc_hour_list, prices, volumes_ccH = dis.convert_to_hour(time_list_ccM, prices_ccM, volumes_ccM)
time_list_combined, volumes_combined = dis.add_two_series_w_different_times(coinbase_hour_list, volumes_coinbaseH, bitstamp_hour_list, volumes_bitstampH)
time_list_combined, volumes_combined = dis.add_two_series_w_different_times(time_list_combined, volumes_combined, korbit_hour_list, volumes_korbitH)
time_list_combined, volumes_combined = dis.add_two_series_w_different_times(time_list_combined, volumes_combined, krak_hour_list, volumes_krakH)
time_list_combined, volumes_combined = dis.add_two_series_w_different_times(cc_hour_list, volumes_ccH, time_list_combined, volumes_combined)
if print_components == 1:
total = sum(volumes_bitstampH) + sum(volumes_coinbaseH) + sum(volumes_korbitH) + sum(volumes_krakH) + sum(volumes_ccH)
# bitstamp_perc = 100 * float(sum(volumes_bitstampH) / total)
# coinbase_perc = 100 * float(sum(volumes_coinbaseH) / total)
# korbit_perc = 100 * float(sum(volumes_korbitH) / total)
# krak_perc = 100 * float(sum(volumes_krakH) / total)
# cc_perc = 100 * float(sum(volumes_ccH) / total)
#
# print("%s approximate share of the total volume")
location = "data/export_csv/"
file_name = location + "global_hourly_volume_index.csv"
with open(file_name, 'w', newline='') as csvfile:
writ = csv.writer(csvfile, delimiter=';', quotechar='|', quoting=csv.QUOTE_MINIMAL)
print("\033[0;32;0m Writing to file '%s'...\033[0;0;0m" % file_name)
header2 = ["Time"]
header2.append("Volume")
writ.writerow(header2)
for i in range(len(volumes_combined)):
rowdata = [time_list_combined[i]]
rowdata.append(volumes_combined[i])
writ.writerow(rowdata)
def write_daily_volume_index_to_csv():
bitstamp, time_list_bitstampM, prices_bitstampM, volumes_bitstampM = di.get_list(exc="bitstampusd")
coinbase, time_list_coinbaseM, prices_coinbaseM, volumes_coinbaseM = di.get_list(exc="coinbaseusd")
korbit, time_list_korbitM, prices_korbitM, volumes_korbitM = di.get_list(exc="korbitkrw")
krak, time_list_krakM, prices_krakM, volumes_krakM = di.get_list(exc="krakeneur")
cc, time_list_ccM, prices_ccM, volumes_ccM = di.get_list(exc="coincheckjpy")
bitstamp_day_list, prices, volumes_bitstampD = dis.convert_to_day(time_list_bitstampM, prices_bitstampM,volumes_bitstampM)
coinbase_day_list, prices, volumes_coinbaseD = dis.convert_to_day(time_list_coinbaseM, prices_coinbaseM,volumes_coinbaseM)
korbit_day_list, prices, volumes_korbitD = dis.convert_to_day(time_list_korbitM, prices_korbitM, volumes_korbitM)
krak_day_list, prices, volumes_krakD = dis.convert_to_day(time_list_krakM, prices_krakM, volumes_krakM)
cc_day_list, prices, volumes_ccD = dis.convert_to_day(time_list_ccM, prices_ccM, volumes_ccM)
#
# time_list_combined, volumes_combined = dis.add_two_series_w_different_times(coinbase_day_list, volumes_coinbaseD, bitstamp_day_list, volumes_bitstampD)
# time_list_combined, volumes_combined = dis.add_two_series_w_different_times(time_list_combined, volumes_combined, korbit_day_list, volumes_korbitD)
# time_list_combined, volumes_combined = dis.add_two_series_w_different_times(time_list_combined, volumes_combined, krak_day_list, volumes_krakD)
# time_list_combined, volumes_combined = dis.add_two_series_w_different_times(cc_day_list, volumes_ccD, time_list_combined, volumes_combined)
time_list_combined, volumes_combined = dis.fix_gv(bitstamp_day_list, volumes_bitstampD, coinbase_day_list, volumes_coinbaseD, korbit_day_list, volumes_korbitD, krak_day_list, volumes_krakD, cc_day_list, volumes_ccD)
location = "data/export_csv/"
file_name = location + "global_daily_volume_index.csv"
with open(file_name, 'w', newline='') as csvfile:
writ = csv.writer(csvfile, delimiter=';', quotechar='|', quoting=csv.QUOTE_MINIMAL)
print("\033[0;32;0m Writing to file '%s'...\033[0;0;0m" % file_name)
header2 = ["Time"]
header2.append("Volume")
writ.writerow(header2)
for i in range(len(volumes_combined)):
rowdata = [time_list_combined[i]]
rowdata.append(volumes_combined[i])
writ.writerow(rowdata)
import data_import as di
import plot
from Jacob import jacob_support as jake_supp
import data_import_support as dis
spec = "01012015_6"
intraday = 0
intraweek = 1
exch = [0] # 0=bitstamp, 1=coincheck
#exchanges, time_list_minutes, prices_minutes, volumes_minutes = di.get_lists_legacy(opening_hours="n", make_totals="n")
exchanges, time_list, prices, volume = di.get_list(0)
"""
for exc in exch:
exc_name = "_" + exchanges[exc] + "_TEST_" + spec
print()
print("SEASONALITY FOR", exchanges[exc].upper())
if intraday == 1:
# HOURS ----------------------------------------------------------------------------------------------------
print("------ INTRADAY ------")
time_list_hours, returns_hours, spread_hours, log_volumes_hours, illiq_hours, \
illiq_hours_time, log_illiq_hours, rvol_hours, log_rvol_hours = \
dis.clean_series_hour(time_list_minutes, prices_minutes, volumes_minutes, exc=exc, convert_time_zones=1)
# Finding average for every hour of the day
hour_of_day, avg_volumes_hour, low_volumes_hour, upper_volumes_hour = dis.cyclical_average(time_list_hours, log_volumes_hours, frequency="h")
hour_of_day, avg_spread_hour, low_spread_hour, upper_spread_hour = dis.cyclical_average(time_list_hours, spread_hours, frequency="h")
import regression_support
from Sondre import sondre_support_formulas as supp
import data_import_support as dis
import plot
exchanges = ["korbit"]
hours_in_window = [
1, 2, 4
] # La denne være en liste med de forskjellige vinduene analysen skal gjøres for
convert_coeffs_to_percentage = 1 # Convert coeffs and std.errs. of returnsH and spreadH to percentage
convert_logs = 0 # Convert coeffs and std.errs. of rvol and illiq to percentage, i.e. 100*exp(coeff) NB! Doesn't work
subtract_means = 1
log_illiqs = True
for exc in exchanges:
exc_name, time_listH, returnsH, spreadH, volumesH, log_volumesH, illiqH, log_illiqH, rvolH, log_rvolH = di.get_list(
exc=exc, freq=1, local_time=1)
hour = supp.fix_time_list(time_listH)[3]
print()
print("------------------------ INTRADAY REGRESSION FOR",
exc_name.upper()[0:-3], "-------------------------")
print()
print()
print(
" ------------------------------------------------Regression table for Intraday seasonality-----------------------------------------"
)
n = len(hour)
for h in hours_in_window: # Itererer over de forskjellige vinduene
import realized_volatility
import rolls
import ILLIQ
from Jacob import jacob_support as jake_supp
os.chdir("/Users/sondre/Documents/GitHub/krypto")
unedited = 0
transformed = 1
# Transformation
exch = ["bitstamp", "coinbase", "btcn", "korbit"]
for exc in exch:
exc_name, time_listD, returnsD, volumesD, log_volumesD, spreadD, illiqD, log_illiqD, rvolD, log_rvolD = di.get_list(
exc, freq="d", local_time=0)
exc_name, time_listM, pricesM, volumesM = di.get_list(exc, freq="m")
timeD, pricesD, volumes_rawD = dis.convert_to_day(time_listM, pricesM,
volumesM)
#
plot.time_series_single(timeD, pricesD, "price_" + exc_name)
plot.time_series_single(time_listD, volumesD, "volume_" + exc_name)
plot.time_series_single(time_listD,
illiqD,
"Log_ILLIQ_" + exc_name,
logy=1,
perc=1,
ndigits=3)
plot.time_series_single(time_listD,
rvolD,
os.chdir("/Users/Sondre/Documents/GitHub/krypto")
#local_time = 0
import_new_exchanges = False
global_volumes = False
global_volumes_experimental = True
spread_vs_global_volume_regression_daily = False
spread_vs_global_volume_regression_hourly= False
make_real_spread_csv = False
real_spread_vs_our_spread = False
if import_new_exchanges:
for exc in range(6):
exc_name, time_listM, pricesM, volumesM = di.get_list(exc)
time_listH, returnsH, spreadH, volumesH, log_volumesH, illiqH, log_illiqH, rvolH, log_rvolH = dis.clean_series_hour(time_listM, pricesM, volumesM, exc=exc, convert_time_zones=local_time, plot_for_extreme=0)
dis.write_clean_csv(exc_name, time_listH, returnsH, spreadH, volumesH, log_volumesH, illiqH, log_illiqH, rvolH, log_rvolH, freq="h", local_time=local_time)
time_listD, returnsD, spreadD, volumesD, log_volumesD, illiqD, log_illiqD, rvolD, log_rvolD = dis.clean_series_days(time_listM, pricesM, volumesM, exc=exc, convert_time_zones=1, plot_for_extreme=0)
dis.write_clean_csv(exc_name, time_listD, returnsD, spreadD, volumesD, log_volumesD, illiqD, log_illiqD, rvolD, log_rvolD, freq="d")
if global_volumes:
# gvi.write_hourly_volume_index_to_csv()
gvi.write_daily_volume_index_to_csv()
time_list_indexD, volume_indexD = gvi.get_global_daily_volume_index()
# time_list_indexH, volume_indexH = gvi.get_global_hourly_volume_index()
time_listD, volumes_actualD = di.get_global_volume_actual_daily()
plt.plot(volume_indexD)
from Sondre import sondre_support_formulas as supp
import data_import_support as dis
import rolls
exchanges = [3, 4] # select pair
remove_extremes = 1
remove_zero_volume = 1
remove_zero_bas = 1
print_cyclical = 1
print_results = 0
sum_volumes = 1
if sum_volumes == 1:
summed_volume = []
bitstamp, time_list_bitstampM, prices_bitstampM, volumes_bitstampM = di.get_list(
0)
coinbase, time_list_coinbaseM, prices_coinbaseM, volumes_coinbaseM = di.get_list(
3)
kraken, time_list_krakenM, prices_krakenM, volumes_krakenM = di.get_list(5)
bitstamp_hour_list, prices, volumes_bitstampH = dis.convert_to_hour(
time_list_bitstampM, prices_bitstampM, volumes_bitstampM)
coinbase_hour_list, prices, volumes_coinbaseH = dis.convert_to_hour(
time_list_coinbaseM, prices_coinbaseM, volumes_coinbaseM)
kraken_hour_list, prices, volumes_krakenH = dis.convert_to_hour(
time_list_krakenM, prices_krakenM, volumes_krakenM)
j = 0 #coinbase counter
t = 0 #kraken counter
partsum = 0
"""
korea = 1
regular = 0
cutoff = 0
if korea == 1:
time_list_tick, price_tick, volume_tick = dis.quick_import(4)
time_list_minute = dis.unix_to_timestamp(time_list_tick[cutoff:])
price_tick = price_tick[cutoff:]
volume_tick = volume_tick[cutoff:]
else:
exch, time_list_minute, price_tick, volume_tick = di.get_list(regular)
"""
gap = 0
equal = 0
volume_checker = volume_tick[0]
volume_checker_zero = 0
price_checker = price_tick[0]
price_checker_zero = 0
last_year, last_month, last_day, last_hour, last_minute = supp.fix_time_list(time_list_minute[0], single_time_stamp=1)
for i in range(0, len(time_list_minute)):
volume_checker += volume_tick[i]
price_checker += price_tick[i]
if volume_tick[i] <= 0:
volume_checker_zero += 1