def generate_final_tl():
clus_wgt = np.array([0.15, 0.075, 0.21, 0.075, 0.15, 0.06, 0.14, 0.14])
# calculate the latest
last_dt = d_bt_fw[0].listdir()
last_dt = last_dt[-5:]
for i in last_dt:
# i = last_dt[1]
tic = None
wgt = None
shr = None
for k in range(0, 8):
# k = 0
last_dt_pos = d_bt_fw[k].load(i)
tic_ = last_dt_pos["arr_0"]
wgt_ = last_dt_pos["arr_1"]
wgt_ = wgt_ * clus_wgt[k]
cl_ = d_comb[k].retrieve("Close")
cl_ = cl_[["Date"] + list(tic_)]
cl_idx = [ii for ii, jj in enumerate(crup.pd_dt_to_str(cl_["Date", list])) if jj == i][0]
cl_ = cl_[cl_idx, list(tic_)].values.astype("float64")
sh_ = wgt_ * cap * 1000 / cl_
if k == 0:
tic = tic_
wgt = wgt_
shr = sh_
else:
tic = np.concatenate((tic, tic_))
wgt = np.concatenate((wgt, wgt_))
shr = np.concatenate((shr, sh_))
wgt_chk = np.sum(np.abs(wgt))
print(wgt_chk)
if wgt_chk > 8:
wgt = wgt * 8 / wgt_chk
shr = shr * 8 / wgt_chk
if wgt_chk < 1:
wgt = wgt * 1 / wgt_chk
shr = shr * 1 / wgt_chk
shr = np.round(shr).astype("int64")
# remove zero shr values
shr_not_zero = np.where(shr != 0)[0]
if shr_not_zero.shape[0] > 0:
tic = tic[shr_not_zero]
wgt = wgt[shr_not_zero]
shr = shr[shr_not_zero]
tl = cruf.DataFrame({"Tick": tic, "Shares": shr, "Weight": wgt})
tl.sort("Weight")
del tl["Weight"]
tl = tl[["Tick", "Shares"]]
if i > last_dt[0]:
tl_comb = cruf.DataFrame.merge(tl, tl_old, on="Tick", how="outer")
tl_comb["Shares_x"] = crtf.fill1(tl_comb["Shares_x"].values, 0)
tl_comb["Shares_y"] = crtf.fill1(tl_comb["Shares_y"].values, 0)
tl_comb["Trade"] = tl_comb["Shares_x"] - tl_comb["Shares_y"]
tl_comb = tl_comb[["Tick", "Trade"]]
tl_comb.to_csv(crsf.cr_tl.name + "\\Tradelist_" + i + ".csv", index_label=None, index=False)
if i < last_dt[-1]:
tl_old = tl
tl.to_csv(crsf.cr_tl.name + "\\Portfolio_" + i + ".csv", index_label=None, index=False)
def _create_combined_data(x):
_clus, _d_comb = x
tick_sym_all = d_un.retrieve(_clus)['Ticker'].values.astype('str')
for i in tick_sym_all:
if i == tick_sym_all[0]:
comb_data_hor = d_cl.retrieve(i)
comb_data_hor = comb_data_hor[comb_data_hor['Date'] >= dt.datetime(1999, 12, 31), :]
comb_data_op = comb_data_hor[['Date', 'Open']]
comb_data_hi = comb_data_hor[['Date', 'High']]
comb_data_lo = comb_data_hor[['Date', 'Low']]
comb_data_cl = comb_data_hor[['Date', 'Close']]
comb_data_vl = comb_data_hor[['Date', 'Volume']]
comb_data_tr = comb_data_hor[['Date', 'Turnover']]
comb_data_op.rename({'Open': i})
comb_data_hi.rename({'High': i})
comb_data_lo.rename({'Low': i})
comb_data_cl.rename({'Close': i})
comb_data_vl.rename({'Volume': i})
comb_data_tr.rename({'Turnover': i})
else:
comb_data_hor_new = d_cl.retrieve(i)
comb_data_hor_new = comb_data_hor_new[comb_data_hor_new['Date'] >= dt.datetime(1999, 12, 31), :]
comb_data_op_new = comb_data_hor_new[['Date', 'Open']]
comb_data_hi_new = comb_data_hor_new[['Date', 'High']]
comb_data_lo_new = comb_data_hor_new[['Date', 'Low']]
comb_data_cl_new = comb_data_hor_new[['Date', 'Close']]
comb_data_vl_new = comb_data_hor_new[['Date', 'Volume']]
comb_data_tr_new = comb_data_hor_new[['Date', 'Turnover']]
comb_data_op_new.rename({'Open': i})
comb_data_hi_new.rename({'High': i})
comb_data_lo_new.rename({'Low': i})
comb_data_cl_new.rename({'Close': i})
comb_data_vl_new.rename({'Volume': i})
comb_data_tr_new.rename({'Turnover': i})
# merge them
comb_data_op = cruf.DataFrame.merge(comb_data_op, comb_data_op_new, on='Date')
comb_data_hi = cruf.DataFrame.merge(comb_data_hi, comb_data_hi_new, on='Date')
comb_data_lo = cruf.DataFrame.merge(comb_data_lo, comb_data_lo_new, on='Date')
comb_data_cl = cruf.DataFrame.merge(comb_data_cl, comb_data_cl_new, on='Date')
comb_data_vl = cruf.DataFrame.merge(comb_data_vl, comb_data_vl_new, on='Date')
comb_data_tr = cruf.DataFrame.merge(comb_data_tr, comb_data_tr_new, on='Date')
comb_data_op.sort('Date')
comb_data_hi.sort('Date')
comb_data_lo.sort('Date')
comb_data_cl.sort('Date')
comb_data_vl.sort('Date')
comb_data_tr.sort('Date')
tick_cols = comb_data_cl.tick_cols()
for i in tick_cols:
comb_data_cl[i] = crtf.fill(comb_data_cl[i].values)
comb_data_op[i] = crtf.fill2(comb_data_op[i].values, comb_data_cl[i].values)
comb_data_hi[i] = crtf.fill2(comb_data_hi[i].values, comb_data_cl[i].values)
comb_data_lo[i] = crtf.fill2(comb_data_lo[i].values, comb_data_cl[i].values)
comb_data_vl[i] = crtf.fill1(comb_data_vl[i].values, 0)
comb_data_tr[i] = crtf.fill1(comb_data_tr[i].values, 0)
# save the data
_d_comb.store('Open', comb_data_op)
_d_comb.store('High', comb_data_hi)
_d_comb.store('Low', comb_data_lo)
_d_comb.store('Close', comb_data_cl)
_d_comb.store('Volume', comb_data_vl)
_d_comb.store('Turnover', comb_data_tr)
return None
