def _calculate_old_pca_betas(x):
_d_comb = x
pr = _d_comb.retrieve('Close')
pca0_ = _d_comb.retrieve('OPCA0')
pca1_ = _d_comb.retrieve('OPCA1')
pca2_ = _d_comb.retrieve('OPCA2')
pca3_ = _d_comb.retrieve('OPCA3')
tc = pr.tick_cols()
#### no stock currently called PCA - but this can break!!
pca0_ = cruf.DataFrame.merge(pr, pca0_, on='Date')
pca1_ = cruf.DataFrame.merge(pr, pca1_, on='Date')
pca2_ = cruf.DataFrame.merge(pr, pca2_, on='Date')
pca3_ = cruf.DataFrame.merge(pr, pca3_, on='Date')
for i in range(60, 300, 60):
# i = 60
pca0 = pca0_.copy()
pca1 = pca1_.copy()
pca2 = pca2_.copy()
pca3 = pca3_.copy()
for j in tc:
pca0[j] = crtf.beta_cc(pca0[j].values, pca0['PCA'].values, i)
pca1[j] = crtf.beta_cc(pca1[j].values, pca1['PCA'].values, i)
pca2[j] = crtf.beta_cc(pca2[j].values, pca2['PCA'].values, i)
pca3[j] = crtf.beta_cc(pca3[j].values, pca3['PCA'].values, i)
del pca0['PCA']
del pca1['PCA']
del pca2['PCA']
del pca3['PCA']
i_ = int(i/20)
_d_comb.store('OPCA0_Beta_'+str(i_)+'m', pca0)
_d_comb.store('OPCA1_Beta_'+str(i_)+'m', pca1)
_d_comb.store('OPCA2_Beta_'+str(i_)+'m', pca2)
_d_comb.store('OPCA3_Beta_'+str(i_)+'m', pca3)
def _calculate_more_betas(x):
_d_comb = x
ret = _d_comb.retrieve('Returns')
lev = _d_comb.retrieve('Lev_CC_120D')
vol = _d_comb.retrieve('Vol_CC_120D')
univ = _d_comb.retrieve('Univ')
retl = ret.copy()
tc = ret.tick_cols()
for i in tc:
retl[i] = ret[i].values*lev[i].values
# calculate an equal weighted index
eq_idx = _dummy_df(retl)
retl_values = ret[tc].values # returns instead of retl
univ_values = univ[tc].values
retl_values[univ_values == 0] = np.nan
retl_cnt = np.sum(~np.isnan(retl_values), axis=1)
retl_values[np.isnan(retl_values)] = 0
retl_values = np.sum(retl_values, axis=1)
retl_values /= retl_cnt
eq_idx['Index'] = crup.conv_to_price(retl_values)
# crup.plot_ts(eq_idx['Date'].values, eq_idx['Index'].values)
# calculate the betas
pr = _d_comb.retrieve('Close')
eq_val = eq_idx['Index'].values
eq_beta = pr.copy()
for i in tc:
eq_beta[i] = crtf.beta_cc(pr[i].values, eq_val, 60)
_d_comb.store('EQIDX_Beta_3m', eq_beta)
eq_beta = pr.copy()
for i in tc:
eq_beta[i] = crtf.beta_cc(pr[i].values, eq_val, 120)
_d_comb.store('EQIDX_Beta_6m', eq_beta)
eq_beta = pr.copy()
for i in tc:
eq_beta[i] = crtf.beta_cc(pr[i].values, eq_val, 180)
_d_comb.store('EQIDX_Beta_9m', eq_beta)
eq_beta = pr.copy()
for i in tc:
eq_beta[i] = crtf.beta_cc(pr[i].values, eq_val, 240)
_d_comb.store('EQIDX_Beta_12m', eq_beta)
def _calculate_old_pca_betas2(x):
_d_opca_wgt, _d_comb = x
pca_pr = _d_opca_wgt.retrieve('Prices')
tick_pr = _d_comb.retrieve('Close')
pca_cols = [i for i in pca_pr.columns.tolist() if i != 'Date']
tick_cols = [i for i in tick_pr.columns.tolist() if i != 'Date']
for i in pca_cols:
pca_pr_i = pca_pr[['Date', i]]
tick_pr_i = cruf.DataFrame.merge(tick_pr, pca_pr_i, on='Date')
tick_pr_i_beta = tick_pr.copy()
for j in tick_cols:
tick_pr_i_beta[j] = crtf.beta_cc(tick_pr_i[j].values, tick_pr_i[i].values, 120)
_d_opca_wgt.store(i+'_Beta', tick_pr_i_beta)
return None
def _refresh_stats(x):
_d_comb, _d_sig = x
comb_prices = _d_comb.retrieve('Close')
spy_prices = d_pr_cl.retrieve('SPY')
# store the leverage
comb_vol = comb_prices.copy()
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.vol_cc(comb_prices[i].values, 30) # changed it back
comb_lev = comb_vol.copy()
for i in comb_lev.tick_cols():
comb_lev[i] = crtf.lrma(0.01/comb_vol[i].values, 30, lg=True)
_d_comb.store('Lev_CC_30D', comb_lev)
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.lrma(comb_vol[i].values, 30, lg=True)
_d_comb.store('Vol_CC_30D', comb_vol)
comb_vol = comb_prices.copy()
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.vol_cc(comb_prices[i].values, 60) # changed it back
comb_lev = comb_vol.copy()
for i in comb_lev.tick_cols():
comb_lev[i] = crtf.lrma(0.01/comb_vol[i].values, 30, lg=True)
_d_comb.store('Lev_CC_60D', comb_lev)
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.lrma(comb_vol[i].values, 30, lg=True)
_d_comb.store('Vol_CC_60D', comb_vol)
comb_vol = comb_prices.copy()
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.vol_cc(comb_prices[i].values, 120) # changed it back
comb_lev = comb_vol.copy()
for i in comb_lev.tick_cols():
comb_lev[i] = crtf.lrma(0.01/comb_vol[i].values, 30, lg=True)
_d_comb.store('Lev_CC_120D', comb_lev)
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.lrma(comb_vol[i].values, 30, lg=True)
_d_comb.store('Vol_CC_120D', comb_vol)
comb_vol = comb_prices.copy()
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.vol_cc(comb_prices[i].values, 240) # changed it back
comb_lev = comb_vol.copy()
for i in comb_lev.tick_cols():
comb_lev[i] = crtf.lrma(0.01/comb_vol[i].values, 30, lg=True)
_d_comb.store('Lev_CC_240D', comb_lev)
for i in comb_vol.tick_cols():
comb_vol[i] = crtf.lrma(comb_vol[i].values, 30, lg=True)
_d_comb.store('Vol_CC_240D', comb_vol)
# generate the signals
for j in range(1, 51):
comb_ret_qr = comb_prices.copy()
comb_ret_lr = comb_prices.copy()
for i in comb_ret_lr.tick_cols():
comb_ret_qr[i] = crtf.qrbeta(comb_ret_qr[i].values, j*10)
comb_ret_lr[i] = crtf.lrbeta(comb_ret_lr[i].values, j*10)
_d_sig.store('QrB_'+str(j*10)+'D', comb_ret_qr)
_d_sig.store('LrB_'+str(j*10)+'D', comb_ret_lr)
del comb_ret_lr
del comb_ret_qr
# generate 12-1 momentum, its score and factor returns
comb_mom = comb_prices.copy()
for i in comb_mom.tick_cols():
comb_mom[i] = crtf.lrma(crtf.ret(comb_mom[i].values, 250)-crtf.ret(comb_mom[i].values, 21), 20)
_d_comb.store('MOM_12m1v', comb_mom)
comb_mom1 = comb_mom.copy()
comb_mom1_tc = comb_mom.tick_cols()
comb_mom1_val = comb_mom[comb_mom1_tc].values
comb_mom1_val_st = np.sum(~np.isnan(comb_mom1_val), axis=1)
comb_mom1_idx = np.where(comb_mom1_val_st>30)[0][0]
dummy = np.empty(len(comb_mom1_tc)) * np.nan
for j in range(0, comb_mom1_idx):
comb_mom1_val[j, :] = dummy
for j in range(comb_mom1_idx, comb_mom1_val.shape[0]):
comb_mom1_val[j, :] = crup.full_norm_rankit(comb_mom1_val[j, :])
comb_mom1[:, comb_mom1_tc] = comb_mom1_val
_d_comb.store('MOM_12m1s', comb_mom1)
comb_mom1['Close'] = np.nan
comb_ret = _d_comb.retrieve('Returns')[comb_mom1_tc].values
comb_ret[np.isnan(comb_ret)] = 0
comb_mom1_val[np.isnan(comb_mom1_val)] = 0
comb_mom1['Close'] = 2*np.sum(comb_ret * comb_mom1_val, axis=1)/np.sum(abs(comb_mom1_val), axis=1)
comb_mom1 = comb_mom1[['Date', 'Close']]
comb_mom1['Close'] = crup.conv_to_price(comb_mom1['Close'].values)
_d_comb.store('MOMf', comb_mom1)
# calculate mom_beta
comb_mom_val = comb_mom1['Close'].values
comb_mom_beta = comb_prices.copy()
for i in comb_mom_beta.tick_cols():
comb_mom_beta[i] = crtf.beta_cc(comb_mom_beta[i].values, comb_mom_val, 120)
_d_comb.store('MOM_Beta_6m', comb_mom_beta)
comb_mom_beta = comb_prices.copy()
for i in comb_mom_beta.tick_cols():
comb_mom_beta[i] = crtf.beta_cc(comb_mom_beta[i].values, comb_mom_val, 60)
_d_comb.store('MOM_Beta_3m', comb_mom_beta)
comb_mom_beta = comb_prices.copy()
for i in comb_mom_beta.tick_cols():
comb_mom_beta[i] = crtf.beta_cc(comb_mom_beta[i].values, comb_mom_val, 180)
_d_comb.store('MOM_Beta_9m', comb_mom_beta)
comb_mom_beta = comb_prices.copy()
for i in comb_mom_beta.tick_cols():
comb_mom_beta[i] = crtf.beta_cc(comb_mom_beta[i].values, comb_mom_val, 240)
_d_comb.store('MOM_Beta_12m', comb_mom_beta)
# calculate low_vol_score
comb_lowv = comb_prices.copy()
for i in comb_lowv.tick_cols():
comb_lowv[i] = crtf.lrma(crtf.vol_cc(comb_prices[i].values, 32, zl=False), 20)
_d_comb.store('LVOL_32dv', comb_lowv)
comb_lowv1 = comb_lowv.copy()
comb_lowv1_tc = comb_lowv.tick_cols()
comb_lowv1_val = comb_lowv[comb_lowv1_tc].values
comb_lowv1_val_st = np.sum(~np.isnan(comb_lowv1_val), axis=1)
comb_lowv1_idx = np.where(comb_lowv1_val_st>30)[0][0]
dummy = np.empty(len(comb_lowv1_tc)) * np.nan
for j in range(0, comb_lowv1_idx):
comb_lowv1_val[j, :] = dummy
for j in range(comb_lowv1_idx, comb_lowv1_val.shape[0]):
comb_lowv1_val[j, :] = crup.full_norm_rankit(comb_lowv1_val[j, :])
comb_lowv1[:, comb_lowv1_tc] = comb_lowv1_val
_d_comb.store('LVOL_32ds', comb_lowv1)
comb_lowv1['Close'] = np.nan
comb_ret = _d_comb.retrieve('Returns')[comb_lowv1_tc].values
comb_ret[np.isnan(comb_ret)] = 0
comb_lowv1_val[np.isnan(comb_lowv1_val)] = 0
comb_lowv1['Close'] = 2*np.sum(comb_ret * comb_lowv1_val, axis=1)/np.sum(abs(comb_lowv1_val), axis=1)
comb_lowv1 = comb_lowv1[['Date', 'Close']]
comb_lowv1['Close'] = crup.conv_to_price(comb_lowv1['Close'].values)
_d_comb.store('LVOLf', comb_lowv1)
# calculate lvol_beta
comb_lowv_val = comb_lowv1['Close'].values
comb_lowv_beta = comb_prices.copy()
for i in comb_lowv_beta.tick_cols():
comb_lowv_beta[i] = crtf.beta_cc(comb_lowv_beta[i].values, comb_lowv_val, 120)
_d_comb.store('LVOL_Beta_6m', comb_lowv_beta)
comb_lowv_beta = comb_prices.copy()
for i in comb_lowv_beta.tick_cols():
comb_lowv_beta[i] = crtf.beta_cc(comb_lowv_beta[i].values, comb_lowv_val, 60)
_d_comb.store('LVOL_Beta_3m', comb_lowv_beta)
comb_lowv_beta = comb_prices.copy()
for i in comb_lowv_beta.tick_cols():
comb_lowv_beta[i] = crtf.beta_cc(comb_lowv_beta[i].values, comb_lowv_val, 180)
_d_comb.store('LVOL_Beta_9m', comb_lowv_beta)
comb_lowv_beta = comb_prices.copy()
for i in comb_lowv_beta.tick_cols():
comb_lowv_beta[i] = crtf.beta_cc(comb_lowv_beta[i].values, comb_lowv_val, 240)
_d_comb.store('LVOL_Beta_12m', comb_lowv_beta)
# correlation with SPY
comb_sp_beta = comb_prices.copy()
comb_sp_beta2 = comb_prices.copy()
comb_sp_beta3 = comb_prices.copy()
comb_sp_beta4 = comb_prices.copy()
for i in comb_sp_beta.tick_cols():
x_ = cruf.DataFrame.merge(comb_sp_beta[['Date', i]], spy_prices[['Date', 'Close']], how='left', on='Date')
x_.sort('Date')
x_['Close'] = crtf.fill(x_['Close'].values)
x_[i] = crtf.fill(x_[i].values)
comb_sp_beta[i] = crtf.beta_cc(x_[i].values, x_['Close'].values, 120)
comb_sp_beta2[i] = crtf.beta_cc(x_[i].values, x_['Close'].values, 60)
comb_sp_beta3[i] = crtf.beta_cc(x_[i].values, x_['Close'].values, 180)
comb_sp_beta4[i] = crtf.beta_cc(x_[i].values, x_['Close'].values, 240)
_d_comb.store('SP_Beta_6m', comb_sp_beta)
_d_comb.store('SP_Beta_3m', comb_sp_beta2)
_d_comb.store('SP_Beta_9m', comb_sp_beta3)
_d_comb.store('SP_Beta_12m', comb_sp_beta4)
return None
