def get_stgyLatest(minute_pnl,minute_hist,pky=['evening_star','morning_star','bearish_MACD','MACD'],debugTF=False):
from _alan_calc import chk_sign
from _alan_date import delta2dates
from lsi_minute import generate_comment_ohlc
qstr="sig==1 & lsc!='combo' & name in {}".format(pky)
temp_pnl = minute_pnl.query(qstr).sort_values(['pbdate'],ascending=[False]).iloc[:1]
if temp_pnl.shape[0]<1:
return {}
stgyName, stgyDate = temp_pnl[['name','pbdate']].iloc[0]
temp_hist = minute_hist.query("pbdate>={}".format(stgyDate)).sort_values(['pbdate'], ascending=False)
if 'MACD' in stgyName:
temp_hist['curr_trend'] = temp_hist['signal_value_macd']
else:
temp_hist['curr_trend'] = temp_hist['dxma5']
if len(temp_hist)>1:
curr_deriv = chk_sign(temp_hist['curr_trend'].iloc[1],temp_hist['curr_trend'].iloc[0])
else:
curr_deriv = -1
if temp_hist.shape[0]>0:
dstgy = temp_hist[['pbdate','price','ticker','curr_trend']].iloc[0].to_dict()
else:
dstgy = {}
dstgy.update(curr_deriv=curr_deriv)
dstgy['curr_date'] = dstgy.pop('pbdate')
if debugTF is True:
print >> sys.stderr, dstgy
dstgy.update(temp_pnl.iloc[0].to_dict())
e,s = minute_hist['epochs'][[-1,0]].values
dstgy['pnl_prd'] = delta2dates(e,s,fq='HOUR')
#return pd.Series(dstgy)
return dstgy
def getdb_ohlc_daily(ticker, startYmd, endYmd, sector, label, pgDB):
""" get info from ohlc_hist and ohlc_pnl for ohlc strategy info
"""
sq1 = "SELECT * FROM ohlc_latest_macd WHERE ticker = {0!r} order by pbdate DESC"
sq2 = "SELECT * FROM ohlc_ls_signal WHERE ticker = {0!r} order by pbdate DESC"
#sq1="SELECT ticker,pbdate,price,ma5,ma20,price-ma5 as ma5trend,signal_value_macd,signal_buysell_macd FROM ohlc_hist WHERE ticker = {0!r} and pbdate >= (SELECT max(pbdate) FROM ohlc_hist WHERE ticker = {0!r} and signal_buysell_macd <> 0 ) order by pbdate DESC"
#sq2="select distinct * from ohlc_pnl where ticker={0!r} and sig=1 and lsc<>'combo' and name similar to '%%(star|harami|MACD)' order by name,lsc,pbdate DESC"
g1 = pd.read_sql(sq1.format(ticker), pgDB)
g2 = pd.read_sql(sq2.format(ticker), pgDB).loc[:, [
"ticker", "name", "pbdate", "price", "lsc", "amount", "cum_amounts",
"sig", "tsig", "ttr_hold", "trr"
]]
pnl_prd = delta2dates(endYmd, startYmd, fq="M")
pbdate = endYmd
try:
m1 = g2.loc[~g2['name'].str.contains("MACD")].reset_index(
drop=True).sort_values(by=['pbdate'], ascending=False).iloc[0]
m1['curr_trend'] = m1['curr_deriv'] = 0
if len(g1) > 0:
m1['curr_trend'] = g1['ma5trend'][0]
if len(g1) > 1:
m1['curr_deriv'] = 1 if abs(g1['ma5trend'][0]) >= abs(
g1['ma5trend'][1]) else -1
m1['curr_date'] = pbdate
m1['pnl_prd'] = pnl_prd
m1['sector'] = sector
m1['label'] = label
except:
m1 = None
try:
m2 = g2.loc[g2['name'].str.contains("MACD")].reset_index(
drop=True).sort_values(by=['pbdate'], ascending=False).iloc[0]
m2['curr_trend'] = m2['curr_deriv'] = 0
if len(g1) > 0:
m2['curr_trend'] = g1['signal_value_macd'][0]
if len(g1) > 1:
m2['curr_deriv'] = 1 if abs(g1['signal_value_macd'][0]) >= abs(
g1['signal_value_macd'][1]) else -1
m2['curr_date'] = pbdate
m2['pnl_prd'] = pnl_prd
m2['sector'] = sector
m2['label'] = label
except:
m2 = None
return (pbdate, m1, m2)
def generate_comment_pppscf(f,
dotSign='.',
prcn=0,
usdSign='$ ',
udfLst=None,
lang="en",
ts=None):
""" stock past performance comment
"""
if ts is None:
ts = assign_ts_pppscf(lang=lang)
fp = f.iloc[-1].to_dict()
for ky, va in fp.items():
exec("{}=va".format(ky))
unitStr = fq2unit_str(freq, lang)
past_udf = udfStr(act_chg_zscore, udf=None, zs=0.0001, lang=lang)
past_difday = difday
past_act_chg_pct = roundPct(act_chg,
n=0,
pct=100,
dotSign=dotSign,
lang=lang)
past_range = str(
delta2dates(int(f.iloc[-1]['pbdate']),
int(f.iloc[0]['pbdate']),
fq='M')) + ("-month" if lang == "en" else "月")
fp = f.query("sig_act_chg==1").iloc[0].to_dict()
for ky, va in fp.items():
exec("{}=va".format(ky))
latest_startYM = ymd2md(xdate, ymd='%Y-%m-%d', ym="%B %Y", lang=lang)
latest_endYM = ymd2md(pdate, ymd='%Y-%m-%d', ym="%B %Y", lang=lang)
latest_udf = udfStr(act_chg_zscore, udf=None, zs=0.0001, lang=lang)
latest_act_chg_pct = roundPct(act_chg,
n=0,
pct=100,
dotSign=dotSign,
lang=lang)
dux = locals()
ret = jj_fmt(ts, dux)
global gData
gData = dux.copy()
del gData['fp']
return ret
def generate_daily_comment(f,
ts=None,
dotSign='.',
prcn=0,
usdSign='$',
udfLst=None,
lang="en"):
""" stock ohlc strategy comment for each strategy
essential f keys: ticker,name,price,trr,tsig,pbdate,curr_date,lsc,curr_trend,curr_deriv
"""
if ts is None:
return ''
try:
enhanceClause = f['enhanceClause']
except:
enhanceClause = ""
if 'enhanceName' in f: # For "enhance" case ONLY
enhanceName = pattern_cn(f['enhanceName'], lang=lang)
ynCode = f['ynCode']
else:
enhanceName = None
ynCode = 1
xnDay = delta2dates(f['curr_date'],
f['pbdate']) # to calc days of previous stragety
bsFlg = True if f['lsc'] == "long" else False
currFlg = True if f['curr_trend'] * f[
'amount'] >= 0 else False # check if current situation still persists
currChg = True if f[
'curr_deriv'] >= 0 else False # if situation persists, is it enhancing or diminishing
pastAdv = ""
trrAdv = ""
trrAddClause = ""
if lang == "cn":
currDateWd = ymd2md(str(f['curr_date']), lang=lang)
buySellVerb = "買入" if bsFlg else "賣出"
prepositionWd = rdWord("另外|同時|不但如此") if ynCode == 1 else rdWord(
"然而|但是|不過|可是")
pastTrendWd = "跌" if bsFlg else "漲" # reverse of long/short for beforeward harami/star signal
comingLookoutWd = rdWord("看漲|看多") if bsFlg else rdWord("看跌|看空")
comingTrendWd = rdWord("上昇|看多|向上提升") if bsFlg else rdWord("下降|看空|下滑")
continueTrendWd = rdWord(
"還在持續中並未改變|依然持續|仍在持續中") if currFlg else rdWord("並沒有持續|並未持續")
if currFlg is True:
upWd = rdWord("增强|升高|上升|向上提升")
dnWd = rdWord("減弱|下降|滑落|下滑")
continueStatusClause = "，還在" + upWd if currChg else "，但已逐漸" + dnWd
else:
continueStatusClause = ""
if xnDay < 1:
pastDayWd = "昨日"
elif xnDay < 2:
pastDayWd = "前一天".format(xnDay)
else:
pastDayWd = "{}天前".format(xnDay)
pastAdv = "曾經"
monthWd = "{}個月".format(f['pnl_prd'])
negWd = "而" if f['trr'] > -0.005 else rdWord("只是|但是|可惜|可是")
trrAdv = "" if f['trr'] > -0.005 else rdWord("只是|但是|可惜|可是")
trrAddClause = "" if f['trr'] > -0.005 else rdWord("，並非有效策略|，策略有待商榷")
else:
prepositionWd = rdWord(
"In the mean time|In addition") if ynCode == 1 else rdWord(
"However|Yet|Nevertheless")
currDateWd = ymd2md(f['curr_date'], lang=lang)
buySellVerb = "buy" if bsFlg else "sell"
pastTrendWd = "downtrend" if bsFlg else "uptrend" # reverse of long/short for beforeward harami/star signal
comingTrendWd = "uptrend" if bsFlg else "downtrend"
continueTrendWd = "still persists" if currFlg else "starts to reverse"
continueStatusClause = "continues to increase" if currChg else "starts to reduce"
if xnDay < 1:
pastDayWd = "just"
elif xnDay < 2:
pastDayWd = "yesterday".format(xnDay)
else:
pastDayWd = "{} days ago".format(xnDay)
monthWd = "{}-month".format(f['pnl_prd'])
negWd = "" if f['trr'] > -0.005 else "however"
label = f['label'] if 'label' in f else ''
ticker = f['ticker']
if label is None or str(label) == '':
label = ticker
price = roundUSD(f['price'], 1)
strategyName = f['name']
strategyName = pattern_cn(strategyName, lang=lang)
countWd = f['tsig']
trrPct = roundPct(f['trr'], 0, pct=1)
if trrPct == '0%' or trrPct == '-0%':
trrPct = "持平而已" if lang == "cn" else "flat"
pricingComm = ""
dux = locals()
ret = jj_fmt(ts, dux)
#ret=ts.format(**dux)
return (ret)
def recordHiLo(dx,
endDT=None,
ticker='',
colx='pchg',
colLst=['close', 'pchg'],
debugTF=False,
mthLst=[]):
'''
find hi/lo out of a range past months: 'mthLst':[-1,-3,-6,-12,-36,-60,-120]
based on time series DataFrame 'dx' that contains column 'colx' with DatetimeIndex
return dict object with keys:
fqWd, name, tags, days, months, years, endDT, mnxTF, hilo, startDT and 'colLst'
'''
if endDT is None:
endDT = dx.index[-1] # next_date()
if len(mthLst) < 1:
mthLst = [-1, -3, -6, -12, -36, -60, -120]
pbdate = int(endDT.strftime('%Y%m%d'))
kyLst = [
"fqWd", "name", "tags", "days", "months", "years", "endDT", "hilo",
"startDT"
]
if debugTF:
sys.stderr.write("{}\n".format(dx))
da = db = {}
jobj = dict(ticker=ticker, pbdate=pbdate, YTD={})
for months in mthLst:
#for months in [-6,-12,-36,-60,-120]:
mnxTF, hilo, idxmnx, startDT, startAT = is_record_hl(dx,
colx=colx,
months=months)
ndays = (endDT - startAT).days
nmonths = delta2dates(endDT, startAT, fq='M', rounding=1)
nyears = int(nmonths / 12) # only integer year
startYmd = int(startAT.strftime('%Y%m%d'))
if delta2dates(
startAT,
startDT) > 5: # STOP if act-delta-months less than months
break
name = "{}_MoSinceStart".format(nmonths)
else:
#name = "{}_Mo2Date".format(-months)
name = "YrToDate" if nyears > 0 else "LastMoToDate"
if (mnxTF is True):
colVa = dx.loc[idxmnx, colx]
hlWd = '最高' if hilo == 'HIGH' else '最低' if colVa >= 0 else '最差'
colWd = '價格' if colx in ['price', 'close', 'value'] else '變化'
if nyears < 1:
tags = "{} month {} {}".format(-months, colx, hilo)
fqWd = "{} 個月以來 {} {}".format(-months, hlWd, colWd)
else:
tags = "{} year {} {}".format(nyears, colx, hilo)
fqWd = "{} 年以來 {} {}".format(nyears, hlWd, colWd)
vaLst = [
fqWd, name, tags, ndays, nmonths, nyears, pbdate, hilo,
startYmd
]
db = dict(zip(kyLst, vaLst))
db.update(dx.loc[idxmnx, colLst].to_dict())
jobj.update(YTD=db)
if delta2dates(
startAT, startDT
) > 5: #- No longer used since longer delta months is not applicable
sys.stderr.write("===Act:{}, Start:{}, Months:{}\n".format(
startAT, startDT, months))
break
return jobj
