

In [1]:

    
using PyPlot
using Dates
using YahooFinanceAPI









    



INFO: Loading help data...



In [30]:

    
startDate = Date(2000,1,1)
sym = "^GSPC";
data = fetchHistoricalData("$sym", startDate);



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#compute the N-day trailing average
lag = 50;
ma = zeros(length(data.adjusted_close)-lag)
for i = lag+1:length(data.adjusted_close)
    sum = 0
    for j = 1:lag
        sum += data.adjusted_close[i-j]
    end
    ma[i-lag] = sum/lag;
end

Basic Plotting



In [32]:

    
plot(data.dates,data.adjusted_close,"b-")
plot(data.dates[lag+1:end], ma, "r-")
legend(["$sym", "$sym MA$(lag)"])









    












    Out[32]:





PyObject <matplotlib.legend.Legend object at 0x7ff897e38d50>

Comparing S&P 500 and VIX



In [33]:

    
vixdat = fetchHistoricalData("^VIX",startDate);



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subplot(2,1,1)
plot(data.dates, data.adjusted_close)
legend([sym],"best")
subplot(2,1,2)
plot(vixdat.dates, vixdat.adjusted_close)
legend(["^VIX"],"best")









    












    Out[34]:





PyObject <matplotlib.legend.Legend object at 0x7ff897c8fbd0>



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