L'analyse technique des graphiques boursiers est basée sur l'hypothèse de l'existence de modèles répétitifs, des modèles qui peuvent apporter des bénéfices. Nous avons vu deux bougies noires et trois bougies blanches dans un certain ordre - ouvrir et obtenir de l'argent. Mais pour une raison quelconque, il y a peu d'informations (ou elles sont totalement absentes) sur la preuve de cette hypothèse et comment et sur la base de ce qu'elle a été généralement formée. Ceux. combien de fois sur les données historiques tel ou tel chiffre a fonctionné comme il se doit. Où et qui a décidé qu'il y avait un triangle en chute, des tunnels, une tête et des épaules, etc. Qui a vérifié leur rentabilité sur les cotations accumulées pendant toute l'existence de l'échange? Pourquoi pas deux droites parallèles et un parallélépipède ou un cercle avec un ovale? Nous parlerons de cette preuve dans cet article, i.e. exécutez le script python pour trouver des modèles,nous obtenons des données historiques en copiant des graphiques de la salle.
Commençons par l'un des modèles les plus populaires - la tête et les épaules sur des graphiques de 6 heures pour 10 paires de devises.
Il faut amener les statistiques sous forme de DataFrame au format (il s'agit d'un extrait de la fin, les données sur 10 paires de devises à 6 heures en moyenne depuis 2005 prendront environ 160 mille lignes)
|
|
TEMPS |
OUVERT |
HAUTE |
FAIBLE |
FERMER |
TITRE |
|---|---|---|---|---|---|
16/09/19 06:00:00 |
1,3213 |
1,3234 |
1,3211 |
1,3232 |
USD_CAD_6H |
16/09/19 12:00:00 |
1,3230 |
1,3265 |
1.3228 |
1,3257 |
USD_CAD_6H |
16/09/19 18:00:00 |
1,3255 |
1,3270 |
1,3231 |
1,3247 |
USD_CAD_6H |
17/09/19 00:00:00 |
1,3248 |
1,3249 |
1,3232 |
1,3239 |
USD_CAD_6H |
17/09/19 06:00:00 |
1,3238 |
1,3253 |
1.3237 |
1,3247 |
USD_CAD_6H |
17/09/19 12:00:00 |
1,3249 |
1,3259 |
1,3240 |
1,3255 |
USD_CAD_6H |
17/09/19 18:00:00 |
1,3256 |
1,3298 |
1,3231 |
1,3247 |
USD_CAD_6H |
18/09/19 00:00:00 |
1,3245 |
1,3252 |
1.3237 |
1,3239 |
USD_CAD_6H |
18/09/19 06:00:00 |
1,3240 |
1,3258 |
1,3238 |
1,3254 |
USD_CAD_6H |
18/09/19 12:00:00 |
1,3252 |
1,3270 |
1,3249 |
1,3250 |
USD_CAD_6H |
18/09/19 18:00:00 |
1,3252 |
1,3285 |
1,3238 |
1,3273 |
USD_CAD_6H |
19/09/19 00:00:00 |
1,3277 |
1,3308 |
1,3267 |
1,3295 |
USD_CAD_6H |
19/09/19 06:00:00 |
1,3297 |
1,3305 |
1,3279 |
1,3282 |
USD_CAD_6H |
19/09/19 12:00:00 |
1.3281 |
1,3292 |
1,3272 |
1,3273 |
USD_CAD_6H |
19/09/19 18:00:00 |
1,3274 |
1,3279 |
1,3238 |
1,3243 |
USD_CAD_6H |
20/09/19 00:00:00 |
1,3244 |
1,3268 |
1,3242 |
1,3257 |
USD_CAD_6H |
20/09/19 06:00:00 |
1.3259 |
1.3271 |
1.3256 |
1.3266 |
USD_CAD_6H |
20/09/19 12:00:00 |
1.3265 |
1.3275 |
1.3256 |
1.3264 |
USD_CAD_6H |
20/09/19 18:00:00 |
1.3262 |
1.3299 |
1.3254 |
1.3255 |
USD_CAD_6H |
21/09/19 00:00:00 |
1.3253 |
1.3278 |
1.3251 |
1.3261 |
USD_CAD_6H |
. , , .. , , .. , , , , , .. , . , , , , - … , "" , .. . . , , ( ). , , .. , , - H&S ( ).
#,
list_H_AND_S=[]
# ( , , )
list_NOT_H_AND_S=[]
for i in range(600,len(df_ALL['CLOSE'])-600):
# , ..
if max(df_ALL['HIGH'][i-30:i+15])==df_ALL['HIGH'][i]:
# 15,
for z in range (15,200,15):
left_shoulder=max(df_ALL['HIGH'][i-30:i+15])
#
left_shoulder_index=df_ALL['HIGH'][i-30:i+15].idxmax()
# ,
if max(df_ALL['HIGH'][df_ALL['LOW'][left_shoulder_index:left_shoulder_index+z+1].idxmin():left_shoulder_index+z+1])>left_shoulder and\
(left_shoulder-min(df_ALL['LOW'][left_shoulder_index:left_shoulder_index+z+1]))/((max(df_ALL['HIGH'][df_ALL['LOW'][left_shoulder_index:left_shoulder_index+z+1].idxmin():left_shoulder_index+z+1])-min(df_ALL['LOW'][left_shoulder_index:left_shoulder_index+z+1])))>=0.6:
head=max(df_ALL['HIGH'][df_ALL['LOW'][left_shoulder_index:left_shoulder_index+z+1].idxmin():left_shoulder_index+z+1])
#
head_index=df_ALL['HIGH'][df_ALL['LOW'][left_shoulder_index:left_shoulder_index+z+1].idxmin():left_shoulder_index+z+1].idxmax()
for b in range (15,200,15):
# , ..
first_bottom= min(df_ALL['LOW'][left_shoulder_index:head_index+1])
# 1-
first_bottom_index=df_ALL['LOW'][left_shoulder_index:head_index+1].idxmin()
#
if min(df_ALL['LOW'][head_index:head_index+b])<first_bottom and \
(head-first_bottom)/(head-min(df_ALL['LOW'][head_index:head_index+b]))>=0.5:
second_bottom= min(df_ALL['LOW'][head_index:head_index+b])
# 2-
second_bottom_index=df_ALL['LOW'][head_index:head_index+b].idxmin()
for o in range(2,300):
# max(df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1]) -
if max(df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1])>=left_shoulder and \
max(df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1])<head and \
second_bottom_index+o-df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1].idxmax()>0 and \
(second_bottom_index+o+1)-df_ALL['LOW'][df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1].idxmax()]>2 and \
min(df_ALL['LOW'][df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1].idxmax():second_bottom_index+o+1])==df_ALL['LOW'][second_bottom_index+o] and \
min(df_ALL['LOW'][df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1].idxmax():second_bottom_index+o])>second_bottom and \
df_ALL['CLOSE'][second_bottom_index+o]<second_bottom and \
min(df_ALL['LOW'][second_bottom_index:df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1].idxmax()+1])==second_bottom and \
min(df_ALL['LOW'][left_shoulder_index:head_index])==first_bottom and \
max(df_ALL['HIGH'][first_bottom_index:second_bottom_index+1])==head and \
df_ALL['CLOSE'][second_bottom_index+o]-df_ALL['OPEN'][second_bottom_index+o]<=0:
# , H$S
for x in range (2,300):
# ,
# , (- )*2. ,
# -
if max(df_ALL['HIGH'][second_bottom_index+o:second_bottom_index+o+x+1])<=max(df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1]) and \
min(df_ALL['LOW'][second_bottom_index+o:second_bottom_index+o+x+1])<=second_bottom-(head-second_bottom)*2:
if (df_ALL['TIME'][left_shoulder_index]+' '+ df_ALL['TIME'][head_index]+' '+df_ALL['TIME'][second_bottom_index]+' '+df_ALL['TIME'][second_bottom_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_bottom_index+o]+' '+str(df_ALL['CLOSE'][o+second_bottom_index]-df_ALL['OPEN'][o+second_bottom_index])) not in list_H_AND_S:
list_H_AND_S.append(df_ALL['TIME'][left_shoulder_index]+' '+ df_ALL['TIME'][head_index]+' '+df_ALL['TIME'][second_bottom_index]+' '+df_ALL['TIME'][second_bottom_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_bottom_index+o]+' '+str(df_ALL['CLOSE'][o+second_bottom_index]-df_ALL['OPEN'][o+second_bottom_index]))
elif max(df_ALL['HIGH'][second_bottom_index+o:second_bottom_index+o+x+1])>max(df_ALL['HIGH'][second_bottom_index:second_bottom_index+o+1]) and \
min(df_ALL['LOW'][second_bottom_index+o:second_bottom_index+o+x+1])>first_bottom-(head-second_bottom):
if (df_ALL['TIME'][left_shoulder_index]+' '+ df_ALL['TIME'][head_index]+' '+df_ALL['TIME'][second_bottom_index]+' '+df_ALL['TIME'][second_bottom_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_bottom_index+o]+' '+str(df_ALL['CLOSE'][o+second_bottom_index]-df_ALL['OPEN'][o+second_bottom_index])) not in list_NOT_H_AND_S and \
(df_ALL['TIME'][left_shoulder_index]+' '+ df_ALL['TIME'][head_index]+' '+df_ALL['TIME'][second_bottom_index]+' '+df_ALL['TIME'][second_bottom_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_bottom_index+o]+' '+str(df_ALL['CLOSE'][o+second_bottom_index]-df_ALL['OPEN'][o+second_bottom_index])) not in list_H_AND_S:
list_NOT_H_AND_S.append(df_ALL['TIME'][left_shoulder_index]+' '+ df_ALL['TIME'][head_index]+' '+df_ALL['TIME'][second_bottom_index]+' '+df_ALL['TIME'][second_bottom_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_bottom_index+o]+' '+str(df_ALL['CLOSE'][o+second_bottom_index]-df_ALL['OPEN'][o+second_bottom_index]))
len(list_H_AND_S),len(list_NOT_H_AND_S)
1/6 ( ), ( -) , . . , , , - H&S , …
(/)
, , . 1 10, . ,
#
list_vimpel=[]
#
list_NOT_vimpel=[]
for i in range(600,len(df_ALL['CLOSE'])-1000):
if max(df_ALL['HIGH'][i-15:i+15])==df_ALL['HIGH'][i]:
for z in range (15,300,15):
#
first_max=max(df_ALL['HIGH'][i-15:i+15])
# 1-
first_max_index=df_ALL['HIGH'][i-15:i+15].idxmax()
if (first_max-min(df_ALL['LOW'][first_max_index:first_max_index+z+1]))>0 and \
max(df_ALL['HIGH'][df_ALL['LOW'][first_max_index:first_max_index+z+1].idxmin():first_max_index+z+1])>first_max and \
(max(df_ALL['HIGH'][df_ALL['LOW'][first_max_index:first_max_index+z+1].idxmin():first_max_index+z+1])-min(df_ALL['LOW'][first_max_index:first_max_index+z+1]))/(first_max-min(df_ALL['LOW'][first_max_index:first_max_index+z+1]))<=2.2 and \
(max(df_ALL['HIGH'][df_ALL['LOW'][first_max_index:first_max_index+z+1].idxmin():first_max_index+z+1])-min(df_ALL['LOW'][first_max_index:first_max_index+z+1]))/(first_max-min(df_ALL['LOW'][first_max_index:first_max_index+z+1]))>=1.3:
second_max=max(df_ALL['HIGH'][df_ALL['LOW'][first_max_index:first_max_index+z+1].idxmin():first_max_index+z+1])
second_max_index=df_ALL['HIGH'][df_ALL['LOW'][first_max_index:first_max_index+z+1].idxmin():first_max_index+z+1].idxmax()
# ,
first_min= min(df_ALL['LOW'][first_max_index:second_max_index+1])
# 1-
first_min_index=df_ALL['LOW'][first_max_index:second_max_index+1].idxmin()
for o in range(2,300):
if (second_max_index-first_min_index)>=25 and \
min(df_ALL['LOW'][second_max_index:second_max_index+o+1])==df_ALL['LOW'][o+second_max_index] and \
df_ALL['LOW'][o+second_max_index]>first_min and \
df_ALL['HIGH'][o+second_max_index]<second_max and \
(second_max_index-first_min_index)>=25 and \
max(df_ALL['HIGH'][first_min_index:o+second_max_index+1])==second_max and \
min(df_ALL['LOW'][first_min_index:second_max_index+1])==df_ALL['LOW'][first_min_index] and \
max(df_ALL['HIGH'][first_max_index:first_min_index+1])==first_max and \
(o+second_max_index)-second_max_index>=16 and \
df_ALL['LOW'][o+second_max_index]<=(first_min+((second_max-first_max)*(((o+second_max_index)-first_min_index)/(second_max_index-first_max_index)))) and \
df_ALL['CLOSE'][o+second_max_index]>=(first_min+((second_max-first_max)*(((o+second_max_index)-first_min_index)/(second_max_index-first_max_index)))):
for x in range (2,300):
if min(df_ALL['LOW'][o+second_max_index:o+second_max_index+x+1])==df_ALL['LOW'][o+second_max_index] and \
max(df_ALL['HIGH'][o+second_max_index:o+second_max_index+x+1])>=second_max:
if (df_ALL['TIME'][first_max_index]+' '+ df_ALL['TIME'][second_max_index]+' '+df_ALL['TIME'][second_max_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_max_index+o]+' '+str(df_ALL['CLOSE'][o+second_max_index]-df_ALL['OPEN'][o+second_max_index])+' '+str((second_max-first_min)/(first_max-first_min))+' '+str((second_max_index-first_min_index)/(first_min_index-first_max_index))+' '+str(((second_max-first_min)/(first_max-first_min))/((second_max-df_ALL['LOW'][o+second_max_index])/(second_max-first_min)))+' '+str(df_ALL['WeekDay'][o+second_max_index])+' '+str((second_max_index-first_max_index)/((o+second_max_index)-second_max_index))) not in list_vimpel:
list_vimpel.append(df_ALL['TIME'][first_max_index]+' '+ df_ALL['TIME'][second_max_index]+' '+df_ALL['TIME'][second_max_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_max_index+o]+' '+str(df_ALL['CLOSE'][o+second_max_index]-df_ALL['OPEN'][o+second_max_index])+' '+str((second_max-first_min)/(first_max-first_min))+' '+str((second_max_index-first_min_index)/(first_min_index-first_max_index))+' '+str(((second_max-first_min)/(first_max-first_min))/((second_max-df_ALL['LOW'][o+second_max_index])/(second_max-first_min)))+' '+str(df_ALL['WeekDay'][o+second_max_index])+' '+str((second_max_index-first_max_index)/((o+second_max_index)-second_max_index)))
elif min(df_ALL['LOW'][o+second_max_index:o+second_max_index+x+1])<df_ALL['LOW'][o+second_max_index] and \
max(df_ALL['HIGH'][o+second_max_index:o+second_max_index+x+1])<second_max:
if (df_ALL['TIME'][first_max_index]+' '+ df_ALL['TIME'][second_max_index]+' '+df_ALL['TIME'][second_max_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_max_index+o]+' '+str(df_ALL['CLOSE'][o+second_max_index]-df_ALL['OPEN'][o+second_max_index])+' '+str((second_max-first_min)/(first_max-first_min))+' '+str((second_max_index-first_min_index)/(first_min_index-first_max_index))+' '+str(((second_max-first_min)/(first_max-first_min))/((second_max-df_ALL['LOW'][o+second_max_index])/(second_max-first_min)))+' '+str(df_ALL['WeekDay'][o+second_max_index])+' '+str((second_max_index-first_max_index)/((o+second_max_index)-second_max_index))) not in list_NOT_vimpel and \
(df_ALL['TIME'][first_max_index]+' '+ df_ALL['TIME'][second_max_index]+' '+df_ALL['TIME'][second_max_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_max_index+o]+' '+str(df_ALL['CLOSE'][o+second_max_index]-df_ALL['OPEN'][o+second_max_index])+' '+str((second_max-first_min)/(first_max-first_min))+' '+str((second_max_index-first_min_index)/(first_min_index-first_max_index))+' '+str(((second_max-first_min)/(first_max-first_min))/((second_max-df_ALL['LOW'][o+second_max_index])/(second_max-first_min)))+' '+str(df_ALL['WeekDay'][o+second_max_index])+' '+str((second_max_index-first_max_index)/((o+second_max_index)-second_max_index))) not in list_vimpel:
list_NOT_vimpel.append(df_ALL['TIME'][first_max_index]+' '+ df_ALL['TIME'][second_max_index]+' '+df_ALL['TIME'][second_max_index+o]+' '+df_ALL['TITLE'][i]+' '+df_ALL['TITLE'][second_max_index+o]+' '+str(df_ALL['CLOSE'][o+second_max_index]-df_ALL['OPEN'][o+second_max_index])+' '+str((second_max-first_min)/(first_max-first_min))+' '+str((second_max_index-first_min_index)/(first_min_index-first_max_index))+' '+str(((second_max-first_min)/(first_max-first_min))/((second_max-df_ALL['LOW'][o+second_max_index])/(second_max-first_min)))+' '+str(df_ALL['WeekDay'][o+second_max_index])+' '+str((second_max_index-first_max_index)/((o+second_max_index)-second_max_index)))
len(list_vimpel),len(list_NOT_vimpel)
Le but de cet article n'est pas de réduire l'analyse technique à des pseudo-théories, mais plutôt de montrer la nature non scientifique de nombreux articles et manuels qui prétendent que les modèles populaires fonctionnent en raison de l'absence de réponse à la question principale - pourquoi cette combinaison de bougies fonctionne-t-elle? D'où venait cette information? Sur la base de l'expérience personnelle, comment la croyance en un créateur est-elle prouvée en Scientologie en tant que science? Peut-être que quelqu'un a découvert (non sans preuve, bien sûr) un modèle qui apporte au moins un certain profit, comme on dit, écrit dans les commentaires. L'avis des représentants de la sphère d'échange est particulièrement bienvenu. Merci pour l'attention!
PS L'auteur comprend que le code peut ne pas être écrit parfaitement, pas optimisé, etc.