I recently came across the “An early Halloween for gold traders” article by Mark Hulbert. I have discussed this type of seasonality analysis in my presentation at R/Finance this year.

It is very easy to run the seasonality analysis using the Systematic Investor Toolbox.

###############################################################################
# Load Systematic Investor Toolbox (SIT)
# http://systematicinvestor.wordpress.com/systematic-investor-toolbox/
###############################################################################
setInternet2(TRUE)
con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))
    source(con)
close(con)

    #*****************************************************************
    # Load historical data
    #****************************************************************** 
    load.packages('quantmod')
    ticker = 'GLD'
    
    data = getSymbols(ticker, src = 'yahoo', from = '1970-01-01', auto.assign = F)
        data = adjustOHLC(data, use.Adjusted=T)
        
    #*****************************************************************
    # Look at the Month of the Year Seasonality
    #****************************************************************** 
    month.year.seasonality(data, ticker)

This confirms that October have been historically bad for Gold, but we used only 8 years of history because GLD only started traded in 2004.

To get a more complete picture, there is a long history of Gold prices at the Deutch Bank. I found this data source used at the Wikiposit.

I created a helper function deutch.bank.data.gold() function in data.r at github to download prices from the Deutch Bank site.

    #*****************************************************************
    # Load long series of gold prices from Deutch Bank
    #****************************************************************** 
    data = deutch.bank.data.gold()

    #*****************************************************************
    # Look at the Month of the Year Seasonality
    #****************************************************************** 
    month.year.seasonality(data, 'GOLD', lookback.len = nrow(data))

The October have been historically bad for Gold using longer time series as well.

Next I would recommend looking at the daily Gold’s performance in October to get a better picture. You might want to use the Seasonality Tool for this purpose. Please read the Historical Seasonality Analysis: What company in DOW 30 is likely to do well in January? post for a case study on how to use the Seasonality Tool.

To view the complete source code for this example, please have a look at the bt.october.gold.test() function in bt.test.r at github.