def __init__(self):
company = "GOOG"
startDate = (1992, 1, 1)
endDate = (2014, 10, 17)
# First chart data
quotes = quotes_historical_yahoo_ohlc(company, startDate, endDate)
if len(quotes) == 0:
raise SystemExit
# Second chart data
dates = ValuesParser.getValues(quotes, "date")
openValues = ValuesParser.getValues(quotes, "open")
closeValues = ValuesParser.getValues(quotes, "close")
highValues = ValuesParser.getValues(quotes, "high")
lowValues = ValuesParser.getValues(quotes, "low")
volumeValues = ValuesParser.getValues(quotes, "volume")
predictedOpenValues = AutoRegression.calculateEstimation(openValues, AutoRegression.calculateARCoefficients(openValues, 5))
predictedCloseValues = AutoRegression.calculateEstimation(openValues, AutoRegression.calculateARCoefficients(closeValues, 5))
predictedHighValues = AutoRegression.calculateEstimation(openValues, AutoRegression.calculateARCoefficients(highValues, 5))
predictedLowValues = AutoRegression.calculateEstimation(openValues, AutoRegression.calculateARCoefficients(lowValues, 5))
predictedVolumeValues = AutoRegression.calculateEstimation(openValues, AutoRegression.calculateARCoefficients(volumeValues, 5))
predictedQuotes = ValuesParser.getQuotes(dates, predictedOpenValues, predictedCloseValues, predictedHighValues, predictedLowValues, predictedVolumeValues)
""" L'algorithme utilisant les 5 premières valeurs pour en déduire les 5 suivantes,
les 5 premières valeurs des prévisions sont fatalement nulles. Pour ne pas avoir
le même résultat que le screenshot du mail, (l'échelle changeante à cause des valeurs nulles)
j'ai copié les premières valeurs pour avoir une meilleure lisibilité """
predictedQuotes[0:5] = quotes[0:5]
# Charts
CandleStickChart("Cotations", quotes)
CandleStickChart("Prévisions", predictedQuotes)
def candlestickGraph(start, end, stock):
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter('%b %y') # e.g., Jan 12016
dayFormatter = DateFormatter('%d')
quotes = quotes_historical_yahoo_ohlc(stock, start, end)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.1)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=.6, colorup='#77d879', colordown='#db3f3f', alpha=0.65)
ax.xaxis.set_major_locator(mticker.MaxNLocator(10))
for label in ax.xaxis.get_ticklabels():
label.set_rotation(45)
ax.xaxis_date()
plt.setp(plt.gca().get_xticklabels(), rotation=45)
plt.show()
def show_candlestick(ticker, startD, endD):
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc(ticker, startD, endD)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
#ax.xaxis.set_major_locator(mondays)
#ax.xaxis.set_minor_locator(alldays)
#ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
plt.show()
def spyBenchPlot(m1, d1, y1, m2, d2, y2):
"""
plot the s%p 500 index(ticker: spy) candlestick chart
:param m1: staring month
:param d1: starting day
:param y1: starting year
:param m2: ending month
:param d2: ending day
:param y2: ending year
:return:
"""
date1 = (y1, m1, d1)
date2 = (y2, m2, d2)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
quotes = quotes_historical_yahoo_ohlc('spy', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
plt.title('S&P 500 ETF')
plt.show()
def ret_f(ticker, begdate, enddate):
p = quotes_historical_yahoo_ohlc(ticker,
begdate,
enddate,
asobject=True,
adjusted=True)
return ((p.open[1:] - p.open[:-1]) / p.open[1:])
def show_candlestick(ticker, startD, endD):
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter("%b %d") # e.g., Jan 12
dayFormatter = DateFormatter("%d") # e.g., 12
quotes = quotes_historical_yahoo_ohlc(ticker, startD, endD)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
# ax.xaxis.set_major_locator(mondays)
# ax.xaxis.set_minor_locator(alldays)
# ax.xaxis.set_major_formatter(weekFormatter)
# ax.xaxis.set_minor_formatter(dayFormatter)
# plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment="right")
plt.show()
def plot_stock_date(symbol, start_date, end_date, tweet_volume):
# Get the quote data from the symbol and unpack it
quotes = pltf.quotes_historical_yahoo_ohlc(symbol, start_date, end_date)
ds, open, highs, lows,close, volumes = zip(*quotes)
# Scale the labels with the amount of quotes
if len(quotes) < 31:
locator = DayLocator()
weekFormatter = DateFormatter('%b %d')
elif len(quotes) >=31 and len(quotes) < 500:
locator = MonthLocator()
weekFormatter = DateFormatter('%y %b')
elif len(quotes) >= 500 and len(quotes) < 600:
locator = MonthLocator()
weekFormatter = DateFormatter('%b')
else:
locator = YearLocator()
weekFormatter = DateFormatter('%y')
alldays = WeekdayLocator()
# Create the figure, axis, and locators
fig = plt.figure(1)
ax = plt.subplot(311)
ax2 = plt.subplot(312)
ax3 = plt.subplot(313)
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
# Plot candlestick
pltf.candlestick_ohlc(ax, quotes, width=0.6, colorup='g')
# Set date and autoscale
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
ax2.xaxis_date()
ax2.autoscale_view()
ax3.xaxis_date()
ax3.autoscale_view()
# Extract the volume and calculate the color for each bar
vol = [v for v in volumes]
vol = np.asarray(vol)
dates = [d for d in ds]
op = [o for o in open]
cl = [c for c in close]
cols = []
for x in range(0, len(op)):
if op[x] - cl[x] < 0:
cols.append('g')
else:
cols.append('r')
# Plot volume as red and green bars
ax2.bar(dates, vol, width=1.0,align='center', color=cols)
# Plot tweet volume
tweet_volume = np.asarray(tweet_volume)
dates = []
for x in range(0, len(tweet_volume)):
dates.append(ds[0] + x)
ax3.bar(dates, tweet_volume, width=1.0, align='center')
# Show figure
plt.show()
def ret_annual(ticker,begtime,endtime):
x = quotes_historical_yahoo_ohlc(ticker,begtime,endtime,asobject=True,adjusted=True)
logret = np.log(x.aclose[1:]/x.aclose[:-1])
date = []
for i in np.arange(len(x)-1):
date.append(x.date[i+1].strftime("%Y")) #wrong: date=date.append()
ret = pd.DataFrame(logret,date,columns=[ticker])
return np.exp(ret.groupby(ret.index).sum())-1
def redraw(self):
self._axes.clear()
if self._instrument != None:
try:
fh = finance.quotes_historical_yahoo_ohlc(
self._instrument, self._startingTimestamp,
self._endTimestamp)
prices = fh
finance.candlestick_ohlc(self._axes, prices, width=0.6)
self._canvas.draw()
except Exception:
print("Couldn't find symbol")
def read(self, stock_name):
start = (2011, 12, 1)
end = (2016, 12, 1)
try:
quotes = quotes_historical_yahoo_ohlc(stock_name, start, end)
if len(quotes) == 0:
raise SystemExit
except:
quotes = []
for i in range(0, len(quotes)):
self.insert(quotes[i][0], quotes[i][1], quotes[i][2], quotes[i][3],
quotes[i][4], quotes[i][5])
def month_ret(ticker, begtime, endtime):
prices = quotes_historical_yahoo_ohlc(ticker,
begtime,
endtime,
asobject=True,
adjusted=True)
log_ret = np.log(prices.aclose[1:] / prices.aclose[:-1])
month_date = []
for i in np.arange(len(log_ret)):
month_date.append(prices.date[i + 1].strftime('%Y%m'))
log_ret_df = pd.DataFrame(data=log_ret, index=month_date, columns=[ticker])
return np.exp(log_ret_df.groupby(log_ret_df.index).sum()) - 1
def monthly_ret(ticker, begtime, endtime):
p = quotes_historical_yahoo_ohlc(ticker,
begtime,
endtime,
asobject=True,
adjusted=True)
date = []
for i in np.arange(len(p.date) - 1):
date.append(p.date[i + 1].strftime("%Y%m"))
logret = np.log(p.aclose[1:] / p.aclose[:-1])
ret = pd.DataFrame(logret, date, columns=[ticker])
return np.exp(ret.groupby(ret.index).sum()) - 1
def matplot_finance():
start = (2014, 5, 1)
end = (2014, 6, 30)
pdb.set_trace()
quotes = mpf.quotes_historical_yahoo_ohlc('DIA', start, end)
fig, ax = plt.subplots(figsize=(8, 5))
fig.subplots_adjust(bottom=0.2)
mpf.candlestick_ohlc(ax, quotes, width=0.6, colorup='b', colordown='r')
plt.grid(True)
ax.xaxis_date()
ax.autoscale_view()
# Rotate labels by 30 degrees
plt.setp(plt.gca().get_xticklabels(), rotation=30)
plt.savefig(PATH + 'candle.png', dpi=300)
plt.close()
fig, ax = plt.subplots(figsize=(8, 5))
mpf.plot_day_summary_ohlc(ax, quotes, colorup='b', colordown='r')
plt.grid(True)
ax.xaxis_date()
plt.title('DAX Index')
plt.ylabel('index level')
plt.setp(plt.gca().get_xticklabels(), rotation=30)
plt.savefig(PATH + 'plot_day_sum.png', dpi=300)
plt.close()
quotes = np.array(mpf.quotes_historical_yahoo_ohlc('YHOO', start, end))
fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(8, 6))
mpf.candlestick_ohlc(ax1, quotes, width=0.6, colorup='b', colordown='r')
ax1.set_title('Yahoo Inc.')
ax1.set_ylabel('Index Level')
ax1.grid(True)
ax1.xaxis_date()
plt.bar(quotes[:, 0] - 0.25, quotes[:, 5], width=0.5)
ax2.set_ylabel('volume')
ax2.grid(True)
ax2.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=30)
plt.savefig(PATH + 'candle2plot.png', dpi=300)
plt.close()
def LPSD(ticker,begtime,endtime):
p=quotes_historical_yahoo_ohlc(ticker,begtime,endtime,asobject=True,
adjusted=True)
ff=pd.read_pickle('ffDaily.pickle')
ret=(p.aclose[1:]-p.aclose[:-1])/p.aclose[1:]
print(ff)
print(ret)
print(p.date[1:])
x=pd.DataFrame(ret,p.date[1:],columns=['ret'])
print(x)
final=pd.merge(x,ff,left_index=True,right_index=True)
print(final)
k=final.ret-final.Rf
k1=k[k>0]
return np.std(k1)*np.sqrt(252)
def out_put(stock, str1, str2): data = quotes_historical_yahoo_ohlc(stock, str2date(str1), str2date(str2)) if len(data) == 0: raise SystemExit print len(data) output = list() for item in data: temp = str(num2date(item[0])) temp2 = temp[:-6] o = list() o.append(temp2) for i in range(1, len(item)-1): o.append(item[i]) output.append(o) return output
def pltPoly(symbol = 'DISH'):
today = date.today()
start = (today.year - 1, today.month, today.day)
month_formatter = DateFormatter("%b %Y")
alldays = DayLocator()
months = MonthLocator()
quotes = quotes_historical_yahoo_ohlc(symbol, start, today)
fig = plt.figure()
ax = fig.add_subplot(111)
ax = plt.subplot(111)
ax.xaxis.set_major_locator(months)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(month_formatter)
candlestick_ohlc(ax, quotes)
fig.autofmt_xdate()
plt.show()
def myplot_candlestick(ticker, weeks):
start = datetime.date.today() + datetime.timedelta(days=-weeks*7)
quotes = quotes_historical_yahoo_ohlc(ticker, start, datetime.date.today())
fig = plt.figure()
ax = plt.axes()
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y/%m'))
fig.autofmt_xdate()
ax.set_title(ticker)
sht = xw.Book.caller().sheets.active
sht.pictures.add(fig, name='52W', update=True, left=sht.range('B5').left, top=sht.range('B5').top)
return str(int(weeks))+'W Candlestick Plot'
def plotStockHist(stockCode, startDate, endDate):
# startDate, endDate required as tuples in format (Year, month, day) to work with quotes_historical_yahoo
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc(stockCode, startDate, endDate)
if len(quotes) != 0:
#do stuff
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
plt.ylabel('Stock Price')
startDateStr = str(startDate[2]) + "/" + str(startDate[1]) + "/" + str(
startDate[0])
endDateStr = str(endDate[2]) + "/" + str(endDate[1]) + "/" + str(
endDate[0])
plt.xlabel("period " + startDateStr + " to " + endDateStr)
plt.title("Stock Code:" + stockCode)
plt.savefig("candleStickChart.png")
#plt.show()
else:
#error, exit gracefully.
print("no history found, no chart plotted.")
def pandas_simple_candlestick_ohlc():
# 开始时间
start = datetime.datetime(2017, 1, 1)
# 结束时间
end = datetime.date.today()
# 沪市
ticker_ss = '600000.ss'
# 深市
ticker_sz = '000001.sz'
# 港股
ticker_hk = '0700.hk'
# 获取数据
quotes = quotes_historical_yahoo_ohlc(ticker_sz, start, end)
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
# 设置主要刻度的显示格式
weekFormatter = DateFormatter('%m-%d-%Y')
ax.xaxis.set_major_formatter(weekFormatter)
# 设置主要刻度Locator，将major ticks设在星期一
mondays = WeekdayLocator(MONDAY)
ax.xaxis.set_major_locator(mondays)
# 设置次要刻度Locator，将minor ticks设在每日
alldays = DayLocator()
ax.xaxis.set_minor_locator(alldays)
# 注意，ohlc代表o开盘价、h最高价、l最低价、c收盘价
candlestick_ohlc(ax, quotes, width=0.6, colorup='r', colordown='g')
ax.grid(True)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
plt.show()
from matplotlib.finance import quotes_historical_yahoo_ohlc
import sys
from datetime import date
import matplotlib.pyplot as plt
import numpy as np
# (1) 下载一年以来的数据：
today = date.today()
start = (today.year - 1, today.month, today.day)
symbol = 'DISH'
if len(sys.argv) == 2:
symbol = sys.argv[1]
quotes = quotes_historical_yahoo_ohlc(symbol, start, today)
# (2) 上一步得到的股价数据存储在Python列表中。将其转化为NumPy数组并提取出收盘价数据：
quotes = np.array(quotes)
close = quotes.T[4]
# (3) 指定合理数量的柱形，绘制分布直方图：
plt.hist(close, np.sqrt(len(close)))
plt.show()
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 11 22:04:18 2016
@author: Administrator
"""
from matplotlib.finance import quotes_historical_yahoo_ohlc
from datetime import date
import pandas as pd
today=date.today();
start=(today.year-1,today.month,today.day)
quotes=quotes_historical_yahoo_ohlc('AAPL',start,today)
df=pd.DataFrame(quotes)
print df
from matplotlib.colors import colorConverter
from matplotlib.lines import Line2D, TICKLEFT, TICKRIGHT
from matplotlib.patches import Rectangle
from matplotlib.transforms import Affine2D
if __name__ == '__main__':
starttime = dt.date(2015,1,1)
endtime = dt.date.today()
ticker = 'SPY'
fh = mpf.fetch_historical_yahoo(ticker, starttime, endtime)
r = mlab.csv2rec(fh);
fh.close()
r.sort()
df = pd.DataFrame.from_records(r)
quotes = mpf.quotes_historical_yahoo_ohlc(ticker, starttime, endtime)
fig, (ax1, ax2) = plt.subplots(2, sharex=True)
tdf = df.set_index('date')
cdf = tdf['close']
cdf.plot(label = "close price", ax=ax1)
pd.rolling_mean(cdf, window=30, min_periods=1).plot(label = "30-day moving averages", ax=ax1)
pd.rolling_mean(cdf, window=10, min_periods=1).plot(label = "10-day moving averages", ax=ax1)
ax1.set_xlabel(r'Date')
ax1.set_ylabel(r'Price')
ax1.grid(True)
props = font_manager.FontProperties(size=10)
leg = ax1.legend(loc='lower right', shadow=True, fancybox=True, prop=props)
leg.get_frame().set_alpha(0.5)
ax1.set_title('%s Daily' % ticker, fontsize=14)
mpf.candlestick_ohlc(ax2, quotes, width=0.6)
ax2.set_ylabel(r'Price')
label.set_rotation(45)
plt.setp(plt_sh.get_xticklabels(),visible = True)
fig.autofmt_xdate()
plt.title(u'sh000001')
plt.show()
## get data from yahoo
ticker = '600028' # 600028 是"中国石化"的股票代码
ticker += '.ss' # .ss 表示上证 .sz表示深证
date1 = (2015, 8, 1) # 起始日期，格式：(年，月，日)元组
date2 = (2016, 1, 1) # 结束日期，格式：(年，月，日)元组
quotes = mfinance.quotes_historical_yahoo_ohlc(ticker, date1, date2)
## 蜡烛图
def plot_K(tuples,name):
mondays = mdates.WeekdayLocator(mdates.MONDAY) # 主要刻度
alldays = mdates.DayLocator() # 次要刻度
#weekFormatter = DateFormatter(‘%b %d‘) # 如：Jan 12
mondayFormatter = mdates.DateFormatter('%m-%d-%Y') # 如：2-29-2015
dayFormatter = mdates.DateFormatter('%d') # 如：12
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
# ax.xaxis.set_major_locator(mondays)
# ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_locator(mdates.DayLocator(bymonthday=range(1,32), interval=30))
import numpy as np
import matplotlib.pylab as plt
import matplotlib.finance as mpf
import pandas
from sklearn.linear_model import LinearRegression
start = (2013, 1, 1)
end = (2016, 1, 1)
# ohcl = open, high, low, close
quotes = mpf.quotes_historical_yahoo_ohlc('GOOG', start, end)
tickerClose = [close[3] for close in quotes]
deltaClose = pandas.Series(np.gradient(tickerClose))
#googleDrift = np.polyfit(np.arange(len(tickerClose))/365., np.log10(tickerClose),1)
#print googleDrift
#plt.plot(np.arange(len(tickerClose)),np.log10(tickerClose))
print tickerClose[0], tickerClose[-1], sum(deltaClose)
plt.plot(pandas.rolling_mean(deltaClose, 90))
plt.plot(deltaClose)
plt.show()
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2004, 2, 1)
date2 = (2004, 4, 12)
stockCode = 'INTC'
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc(stockCode, date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.xticks(rotation=45)
plt.yticks()
plt.title("股票代码：601558两年K线图")
plt.xlabel("时间")
plt.ylabel("股价（元）")
mpf.candlestick_ohlc(ax,data_list,width=1.5,colorup='r',colordown='green')
plt.grid()
'''
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.finance as mpf
start = (2014, 5, 1)
end = (2014, 6, 30)
quotes = mpf.quotes_historical_yahoo_ohlc('^GDAXI', start, end)
#quotes = mpf.quotes_historical_yahoo(‘^GDAXI’, start, end)
quotes[:2]
fig, ax = plt.subplots(figsize=(8, 5))
fig.subplots_adjust(bottom=0.2)
print "Hello"
#use Line2d
#mpf.plot_day_summary_oclh(ax, quotes, ticksize=3, colorup=’k’, colordown=’r’)#
mpf.candlestick_ohlc(ax, quotes, width=0.6, colorup='b', colordown='r')
#mpf.candlestick(ax, quotes, width=0.6, colorup=’b’, colordown=’r’)
plt.grid(True)
ax.xaxis_date()
# dates on the x-axis
ax.autoscale_view()
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
pyplot.style.use('ggplot')
fig, ax = pyplot.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
finance.candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
pyplot.setp(pyplot.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
pyplot.show()
if __name__ == '__main__':
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = datetime(2004, 2, 1)
date2 = datetime(2004, 4, 12)
quotes = finance.quotes_historical_yahoo_ohlc('INTC', date1, date2)
if len(quotes) == 0:
raise SystemExit
plot_ohlc(quotes)
"""
Crear una gráfica de caja y bigotes para la cotización de un valor en bolsa
"""
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# Extraemos las cotizaciones para las fechas siguientes
fecha1 = (2014, 10, 13)
fecha2 = (2014, 11, 13)
# Vamos a la web y nos traemos la información de la cotización
valores = quotes_historical_yahoo_ohlc('AAPL', fecha1, fecha2)
if len(valores) == 0:
raise SystemExit
# Definimos el aspecto de la gráfica
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
# Ponemos marcas mayores para los lunes
lunes = WeekdayLocator(MONDAY)
ax.xaxis.set_major_locator(lunes)
# Ponemos marcas menores para el resto de días
resto_dias = DayLocator()
ax.xaxis.set_minor_locator(resto_dias)
# Damos formato a los días
formato_semana = DateFormatter('%b %d') # e.g., Ene 12
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2015, 2, 1)
date2 = (2015, 5, 22)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('600000.SS', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
import numpy as np
import matplotlib.colors as colors
import matplotlib.finance as finance
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
startdate = datetime.date(2016, 1, 1)
today = enddate = datetime.date.today()
ticker = '601231.SS'
fh = finance.fetch_historical_yahoo(ticker, startdate, enddate)
quotes = finance.quotes_historical_yahoo_ohlc(ticker, startdate, enddate)
# a numpy record array with fields: date, open, high, low, close, volume, adj_close)
r = mlab.csv2rec(fh)
print(quotes[0])
print(r[0])
fh.close()
r.sort()
def moving_average(x, n, type='simple'):
"""
compute an n period moving average.
for label in plt_sh.xaxis.get_ticklabels():
label.set_rotation(45)
plt.setp(plt_sh.get_xticklabels(), visible=True)
fig.autofmt_xdate()
plt.title(u"sh000001")
plt.show()
## get data from yahoo
ticker = "600028" # 600028 是"中国石化"的股票代码
ticker += ".ss" # .ss 表示上证 .sz表示深证
date1 = (2015, 8, 1) # 起始日期，格式：(年，月，日)元组
date2 = (2016, 1, 1) # 结束日期，格式：(年，月，日)元组
quotes = mfinance.quotes_historical_yahoo_ohlc(ticker, date1, date2)
## 蜡烛图
def plot_K(tuples, name):
mondays = mdates.WeekdayLocator(mdates.MONDAY) # 主要刻度
alldays = mdates.DayLocator() # 次要刻度
# weekFormatter = DateFormatter(‘%b %d‘) # 如：Jan 12
mondayFormatter = mdates.DateFormatter("%m-%d-%Y") # 如：2-29-2015
dayFormatter = mdates.DateFormatter("%d") # 如：12
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
# ax.xaxis.set_major_locator(mondays)
# ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_locator(mdates.DayLocator(bymonthday=range(1, 32), interval=30))
__author__ = 'harsshal'
from matplotlib.finance import quotes_historical_yahoo_ohlc
date1 = (2010, 12, 31)
date2 = (2015, 12, 31)
price = quotes_historical_yahoo_ohlc('MSFT', date1, date2)
print("hi")
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc, plot_day_summary_ohlc
%matplotlib inline
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2015, 2, 1)
date2 = (2015, 3, 1)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('GOOG', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary_ohlc(ax, quotes, ticksize=3, colorup=u'g', colordown=u'r')
#candlestick_ohlc(ax, quotes, width=0.2, colorup=u'k', colordown=u'r', alpha=1.0)
candlestick_ohlc(ax, quotes, width=0.6, colorup=u'g')
ax.xaxis_date()
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2016, 2, 1)
date2 = (2017, 1, 5)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('^KS11', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
#ax.xaxis.set_major_locator(mondays)
#ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6, colorup='red', colordown='blue')
ax.xaxis_date()
ax.autoscale_view()
"""
Create a candlestick chart for a stock
"""
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# Grab the stock data between these dates
date1 = (2014, 10, 13)
date2 = (2014, 11, 13)
# Go to the web and pull the stock info
quotes = quotes_historical_yahoo_ohlc('AAPL', date1, date2)
if len(quotes) == 0:
raise SystemExit
# Set up the graph
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
# Major ticks on Mondays
mondays = WeekdayLocator(MONDAY)
ax.xaxis.set_major_locator(mondays)
# Minor ticks on all days
alldays = DayLocator()
ax.xaxis.set_minor_locator(alldays)
# Format the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
def finance(data, parameters, output):
#data
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2016, 8, 1)
date2 = (2016, 9, 9)
sticker = ''
with open(data) as f:
f_csv = csv.reader(f)
headers = next(f_csv)
for row in f_csv:
sticker = row[0]
date1 = literal_eval(row[1])
date2 = literal_eval(row[2])
#parameters
param = ""
figsize = (8, 6)
param1 = ""
if 'figsize' in parameters.keys():
figsize = eval(parameters['figsize'])
fig, ax = plt.subplots(figsize=(11, 5))
if 'title' in parameters.keys():
ax.set_title(parameters['title'])
if 'witdth' in parameters.keys():
param = param + ",width=" + str(parameters['width'])
if 'colorup' in parameters.keys():
param = param + ",colorup='" + parameters['colorup'] + "'"
if 'colordown' in parameters.keys():
param = param + ",colordown='" + parameters['colordown'] + "'"
if 'rotation' in parameters.keys():
param1 = param1 + ",rotation=" + str(parameters['rotation'])
if 'horizontalalignment' in parameters.keys():
param1 = param1 + ",horizontalalignment='" + parameters[
'horizontalalignment'] + "'"
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc(sticker, date1, date2)
if len(quotes) == 0:
raise SystemExit
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
exec("candlestick_ohlc(ax, quotes, width=0.6" + param + ")")
ax.xaxis_date()
ax.autoscale_view()
exec("plt.setp(plt.gca().get_xticklabels()" + param1 + ")")
# adding horizontal grid lines
plt.grid(True, linestyle='--', linewidth=0.5)
savefig(output, format='svg')
line.set_data(x, y)
return line
anim=animation.FuncAnimation(fig, animate, init_func=init, frames=10000, interval=5000)
plt.show()
# 导入需要的库
import tushare as ts
import matplotlib.pyplot as plt
import matplotlib.finance as mpf
# 设置历史数据区间
date1 = (2014, 12, 1) # 起始日期，格式：(年，月，日)元组
date2 = (2016, 12, 1) # 结束日期，格式：(年，月，日)元组
# 从雅虎财经中获取股票代码601558的历史行情
quotes = mpf.quotes_historical_yahoo_ohlc('601558.ss', date1, date2)
# 创建一个子图
fig, ax = plt.subplots(facecolor=(0.5, 0.5, 0.5))
fig.subplots_adjust(bottom=0.2)
# 设置X轴刻度为日期时间
ax.xaxis_date()
# X轴刻度文字倾斜45度
plt.xticks(rotation=45)
plt.title("股票代码：601558两年K线图")
plt.xlabel("时间")
plt.ylabel("股价（元）")
mpf.candlestick_ohlc(ax, quotes, width=1.2, colorup='r', colordown='green')
plt.grid(True)
# Now we plot only the X last days
daysBack = 20
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
#ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#Another way of getting stock data.
quotes = quotes_historical_yahoo_ohlc(
tickers[ticIdx], startDate, today
) # output format is: [datenum, open,high,low,close,volume] one date per row.
candlestick_ohlc(ax, quotes[-daysBack:-1], width=0.5)
ax.plot(finData.index[-daysBack:-1],
finData.close[-daysBack:-1],
'b',
label='Close')
ax.plot(finData.index[-daysBack:-1],
ma50[-daysBack:-1],
'k',
label='50 day MA')
ax.set_title(tickers[ticIdx] + ' Last Date:' +
finData.index[-1].strftime('%Y-%m-%d'))
ax.legend(loc='best', fontsize=fs)
ax.grid('on')
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2004, 2, 1)
date2 = (2004, 4, 12)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('INTC', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
ticker = '600028' # 600028 是"中国石化"的股票代码
ticker += '.ss' # .ss 表示上证 .sz表示深证
date1 = (2015, 8, 1) # 起始日期，格式：(年，月，日)元组
date2 = (2016, 1, 1) # 结束日期，格式：(年，月，日)元组
mondays = WeekdayLocator(MONDAY) # 主要刻度
alldays = DayLocator() # 次要刻度
#weekFormatter = DateFormatter('%b %d') # 如：Jan 12
mondayFormatter = DateFormatter('%m-%d-%Y') # 如：2-29-2015
dayFormatter = DateFormatter('%d') # 如：12
quotes = quotes_historical_yahoo_ohlc(ticker, date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(mondayFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6, colorup='r', colordown='g')
ax.xaxis_date()
def getQuote(symbol, startDate=None, endDate=None):
if(startDate == None):
startDate = datetime(1900, 1, 1)
if(endDate == None):
endDate = datetime.today()
#endDate = datetime(2012,12,12)
try:
conn = sqlite3.connect("./db/" + symbol + ".db")
c = conn.cursor()
r = c.execute('''SELECT count(*) FROM sqlite_master
WHERE type=\'table\' AND name=\'prices\' ''')
tableExists = r.fetchone()[0] > 0
if tableExists:
# Calculate the start date for continuing the history data
result = c.execute("SELECT min(date), max(date) FROM prices")
if result:
firstDate, lastDate = result.fetchone()
if(firstDate != None and lastDate != None):
# print "Table exists, starting at " + date2str(firstDate) + \
# ", ending at " + date2str(lastDate)
startDateEpochs = lastDate + 1
dt = datetime.fromordinal(startDateEpochs-1721425)
startDate = datetime(dt.year, dt.month, dt.day, 00, 00)
else:
# No table existing => create one
c.execute('''CREATE TABLE prices(
date integer, o real, h real, l real, c real, v real
)''')
# print "startDate=" + str(startDate)
# print "endDate=" + str(endDate)
# print "difference=" + str(endDate-startDate)
difference = endDate - startDate
#print "startDate=" + str(startDate)
#print "endDate=" + str(endDate)
if difference.days > 0:
# print "=> " + str(difference.days) + " days"
try:
#print "mf.quotes_historical_yahoo(" + str(urllib.quote(symbol)) + \
#", " + str(startDate) + ", " + str(endDate) + ")"
quotes = mf.quotes_historical_yahoo_ohlc(symbol, startDate, endDate)
if quotes:
for q in quotes:
c.execute("INSERT INTO prices VALUES("
+ str(1721425 + q[0]) # date
+ ", " + str(q[1]) # open
+ ", " + str(q[2]) # high
+ ", " + str(q[3]) # low
+ ", " + str(q[4]) # close
+ ", " + str(q[5]) # volume
+ ")")
print "Added " + str(len(quotes)) + " items for " + symbol
else:
print "No new data available."
conn.commit()
except KeyboardInterrupt:
raise KeyboardInterrupt
except:
print "Error:", sys.exc_info()[0]
else:
print "=> nothing to do."
conn.close()
except KeyboardInterrupt:
raise KeyboardInterrupt
except:
print "Error:", sys.exc_info()[0]
import numpy as np
import matplotlib.finance as mpf
import matplotlib.pyplot as plt
import matplotlib
start = (2015, 4, 1)
end = (2016, 4, 28)
quotes = mpf.quotes_historical_yahoo_ohlc('INGN', start, end)
print quotes
import pandas as pd
import numpy as np
import statsmodels.api as sm
from matplotlib.finance import quotes_historical_yahoo_ohlc
ff = pd.read_csv(
'https://raw.githubusercontent.com/alexpetralia/fama_french/master/FF_monthly.CSV',
index_col='Date')
begtime = (2008, 10, 1)
endtime = (2013, 11, 30)
price = quotes_historical_yahoo_ohlc('IBM',
begtime,
endtime,
asobject=True,
adjusted=True)
logret = np.log(price.aclose[1:] / price.aclose[:-1])
month = []
for i in price.date:
month.append(int(i.strftime("%Y%m")))
ret = pd.DataFrame(data=logret, index=month[1:], columns=['ret'])
ret = np.exp(ret.groupby(ret.index).sum()) - 1
final = pd.merge(ff, ret, right_index=True, left_index=True)
y = final.ret
x = final[['Mkt-RF', 'SMB', 'HML']]
x = sm.add_constant(x)
results = sm.OLS(y, x).fit()
print(results.params)
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
print ts.__version__
date1 = (2004, 2, 1)
date2 = (2004, 4, 12)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter("%b %d") # e.g., Jan 12
dayFormatter = DateFormatter("%d") # e.g., 12
quotes = quotes_historical_yahoo_ohlc("MSFT", date1, date2)
if len(quotes) == 0:
raise SystemExit
print str(quotes)
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
# ax.xaxis.set_minor_formatter(dayFormatter)
# plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2004, 2, 1)
date2 = (2004, 4, 12)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('INTC', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
def load_data_yahoo(code, start_date, end_date ):
# http://blog.csdn.net/matrix_laboratory/article/details/50687910
# http://blog.csdn.net/mengwuyoulin/article/details/51165851
fh = finance.quotes_historical_yahoo_ohlc(code, start_date, end_date,adjusted=False)
# print type(fh)
return fh[0][4]
