Python matplotlib.finance.quotes_historical_yahoo_ochl() Examples

The following are 16 code examples of matplotlib.finance.quotes_historical_yahoo_ochl(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module matplotlib.finance , or try the search function .
Example #1
Source File: c7_16_def_sharpe_ratio.py    From Python-for-Finance-Second-Edition with MIT License 6 votes vote down vote up 
def sharpeRatio(ticker,begdate=(2012,1,1),enddate=(2016,12,31)):
    """Objective: estimate Sharpe ratio for stock
        ticker  : stock symbol 
        begdate : beginning date
        enddate : ending date
        
       Example #1: sharpeRatio("ibm")
                     0.0068655583807256159
        
       Example #2: date1=(1990,1,1)
                   date2=(2015,12,23)
                   sharpeRatio("ibm",date1,date2)
                     0.027831010497755326
    """
    import scipy as sp
    from matplotlib.finance import quotes_historical_yahoo_ochl as getData
    p = getData(ticker,begdate, enddate,asobject=True,adjusted=True)
    ret=p.aclose[1:]/p.aclose[:-1]-1
    return sp.mean(ret)/sp.std(ret)
Example #2
Source File: c6_08_dailyReturn_4_annual.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker,begdate, enddate):
    p = quotes_historical_yahoo_ochl(ticker, begdate,    
    enddate,asobject=True,adjusted=True)
    return((p.aclose[1:] - p.aclose[:-1])/p.aclose[:-1])
#
Example #3
Source File: c6_27_get_beta_good.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def dailyReturn(ticker,begdate,enddate):
     p = aa(ticker, begdate,enddate,asobject=True,adjusted=True)
     return p.aclose[1:]/p.aclose[:-1]-1
#
Example #4
Source File: c4_16_ttest_2stocks.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker,begdate,enddate):
     p = getData(ticker,begdate, enddate,asobject=True,adjusted=True)
     ret=p.aclose[1:]
     ret=p.aclose[1:]/p.aclose[:-1]-1
     return(ret)
Example #5
Source File: c9_32_mean_and_var.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker,begdate,enddte):
    x=getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    ret =x.aclose[1:]/x.aclose[:-1]-1
    return ret
Example #6
Source File: c9_44_impact_of_correlation_2stock_portfolio.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_annual(ticker,begdate,enddte):
    x=getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    logret =sp.log(x.aclose[1:]/x.aclose[:-1])
    date=[]
    d0=x.date
    for i in range(0,sp.size(logret)):
        date.append(d0[i].strftime("%Y"))
    y=pd.DataFrame(logret,date,columns=[ticker])
    return sp.exp(y.groupby(y.index).sum())-1
Example #7
Source File: c9_50_efficient_frontier.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_monthly(ticker):  #	function 1
    x = getData(ticker,(begYear,1,1),(endYear,12,31),asobject=True,adjusted=True)
    logret=np.log(x.aclose[1:]/x.aclose[:-1]) 
    date=[]
    d0=x.date
    for i in range(0,np.size(logret)): 
        date.append(''.join([d0[i].strftime("%Y"),d0[i].strftime("%m")]))
    y=pd.DataFrame(logret,date,columns=[ticker]) 
    return y.groupby(y.index).sum()

# function 2: objective function
Example #8
Source File: c9_77_Modigliani_m2_performance_measure.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker):  #	function 1
    x = getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    ret=x.aclose[1:]/x.aclose[:-1]-1 
    ddate=x['date'][1:]
    y=pd.DataFrame(ret,columns=[ticker],index=ddate) 
    return y.groupby(y.index).sum()
Example #9
Source File: c9_18_sharpe_ratio.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_annual(ticker,begdate,enddte):
    x=getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    logret =sp.log(x.aclose[1:]/x.aclose[:-1])
    date=[]
    d0=x.date
    for i in range(0,sp.size(logret)):
        date.append(d0[i].strftime("%Y"))
    y=pd.DataFrame(logret,date,columns=[ticker])
    return sp.exp(y.groupby(y.index).sum())-1
# function 2: estimate portfolio variance
Example #10
Source File: c9_21_optimal_portfolio_based_on_Sortino_ratio.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_annual(ticker,begdate,enddte):
    x=getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    logret =sp.log(x.aclose[1:]/x.aclose[:-1])
    date=[]
    d0=x.date
    for i in range(0,sp.size(logret)):
        date.append(d0[i].strftime("%Y"))
    y=pd.DataFrame(logret,date,columns=[ticker])
    return sp.exp(y.groupby(y.index).sum())-1
# function 2: estimate portfolio beta
Example #11
Source File: c9_23_efficient_based_on_sortino_ratio.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_annual(ticker,begdate,enddte):
    x=getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    logret =sp.log(x.aclose[1:]/x.aclose[:-1])
    date=[]
    d0=x.date
    for i in range(0,sp.size(logret)):
        date.append(d0[i].strftime("%Y"))
    y=pd.DataFrame(logret,date,columns=[ticker])
    return sp.exp(y.groupby(y.index).sum())-1

# function 2: estimate LPSD
Example #12
Source File: c9_52_impact_of_correlation_on_efficient_frontier_notWorking.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_monthly(ticker):  #	function 1
    x = getData(ticker,(begYear,1,1),(endYear,12,31),asobject=True,adjusted=True)
    logret=np.log(x.aclose[1:]/x.aclose[:-1]) 
    date=[]
    d0=x.date
    for i in range(0,np.size(logret)): 
        date.append(''.join([d0[i].strftime("%Y"),d0[i].strftime("%m")]))
    y=pd.DataFrame(logret,date,columns=[ticker]) 
    return y.groupby(y.index).sum()
Example #13
Source File: c8_34_Durbin_Watson_test_CAPM_IBM_residual.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def dailyRet(ticker,begdate,enddate):
    p =getData(ticker, begdate, enddate,asobject=True,adjusted=True)
    return p.aclose[1:]/p.aclose[:-1]-1
Example #14
Source File: c8_27_test_equal_variances.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker,begdate,enddate): 
    p = getData(ticker,begdate, enddate,asobject=True,adjusted=True) 
    return p.aclose[1:]/p.aclose[:-1]-1
Example #15
Source File: c15_07_equal_vol_2periods.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker,begdate,enddate):
    p =getData(ticker, begdate, enddate,asobject=True, adjusted=True)
    ret = p.aclose[1:]/p.aclose[:-1]-1 
    date_=p.date
    return pd.DataFrame(data=ret,index=date_[1:],columns=['ret'])
#
# call the above function twice
Example #16
Source File: c11_19_portfolio_VaR.py    From Python-for-Finance-Second-Edition with MIT License 5 votes vote down vote up 
def ret_f(ticker,begdate,enddte):
    x=getData(ticker,begdate,enddate,asobject=True,adjusted=True)
    ret=x.aclose[1:]/x.aclose[:-1]-1
    d0=x.date[1:]
    return pd.DataFrame(ret,index=d0,columns=[ticker])
# Step 3