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SILVER SEASONALITY (Trading As the Perth Mint) ABN 98 838 298 431 Ed Steer Recently Featured a Chart of Silver’S Seasonality

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SILVER SEASONALITY (Trading As the Perth Mint) ABN 98 838 298 431 Ed Steer Recently Featured a Chart of Silver’S Seasonality Gold Corporation SILVER SEASONALITY (trading as The Perth Mint) ABN 98 838 298 431 Ed Steer recently featured a chart of silver’s seasonality 310 Hay Street, East Perth, from SeasonalCharts.com. The fact that the chart just Western Australia, 6004, shows averages, without any indication of the reliability of Australia those averages, made me cautious. Below I’ll investigate seasonality in the silver market and its dependability. A statutory authority under the Gold Corporation Act (1987) of Western Australia The chart below uses London Fix data from 1982 through to 2011, the time period of the chart in Ed Steer’s post. 1982 is not a bad starting point as this excludes silver’s Founded in 1899, the Perth Mint is dramatic run up and crash which, due to the actions of the an integrated precious metal operation refining circa 10% of Hunts and the regulatory response, is arguably not an world gold production; servicing example of normal market behaviour. investors with legal tender bullion coins and bars and the Perth Mint Depository custodial facility; The method used is to first fill in any blank days with the providing collectors with innovative previous day’s prices to get a continuous data series. and high quality numismatic coins; Then each day’s price for each year is indexed so that the supplying mints with precious metal nd blanks; and operating a leading 2 of January equals 100. That way each year can be Perth tourist attraction. compared directly with each other, effectively converting each year’s dollar prices into percentage movements. Finally, the each day’s indexed price is averaged. For example, find the average of the 14 March 1982, 14 March 1983, etc up to the 14 March 2011. It is worth noting that this approach means we are only working with 30 points of data for each day of the year. This is not a large sample and can mean that the average can be influenced by a one significantly large data point. From this chart, it would 109 Average Indexed Daily Silver Prices from 1982 to 2011 seem that one good 108 strategy would be to sell in 107 April/May and buyback in July. However, the 106 average hides the 105 variability in price trends 104 between years. 103 102 As Adam Hamilton notes in this article on gold’s 101 seasonality, “averaging 10 100 and 90 or 45 and 55 both 99 yield 50, but as a 06 Jul 17 Jul 28 Jul 24 Oct 02 Oct 13 Oct 09 Apr 20 Apr 01 Jan 12 Jan 23 Jan 03 Jun 03 Feb 14 Feb 25 Feb 14 Jun 25 Jun 07 Mar 18 Mar 29 Mar 10 Sep 21 Sep 07 Dec 18 Dec 29 Dec 04 Nov 15 Nov 26 Nov 08 Aug 19 Aug 30 Aug 12 May 23 May speculator I have much 01 May more confidence the tighter second group will have better odds of being relevant to my trades.” Adam uses standard deviations to work out how confident he is in seasonality charts. This is statistically robust (although he only uses one standard deviation, which is only 68.2% of “confidence”) but another way of looking at variability is charting each year’s indexed prices (see below) that went into calculating the average in the chart on the previous page. I have smoothed the data out using a seven day moving average to make it (slightly) more readable. 180 1982 Indexed Daily Silver Prices (7 day moving average) 1983 I think it should be obvious 1984 1985 when looking at this chart 160 1986 1987 that the data underlying 1988 1989 the first chart is highly 1990 140 1991 variable, without any clear 1992 1993 seasonality or recurring 1994 120 1995 pattern. 1996 1997 1998 100 1999 2000 Earlier I mentioned the 2001 2002 potential for a small 80 2003 2004 sample to be skewed by 2005 2006 significant numbers. 2007 60 2008 Consider the three years 2009 2010 1987, 2006 and 2011 09 Jul 23 Jul 15 Oct 01 Oct 29 Oct 02 Apr 16 Apr 30 Apr 08 Jan 22 Jan 05 Feb 19 Feb 05 Mar 19 Mar 11 Jun 25 Jun 03 Sep 17 Sep 10 Dec 24 Dec 12 Nov 26 Nov 06 Aug 20 Aug 28 May 14 May 2011 around April/May (circled in red in the chart above). It looks like these three years are probably skewing that “sell in April/May, buy in July” rule by pushing up the daily averages during April and May. So what happens if we take out these three “abnormal” years and recalculate the averages? The chart below is the result. The removal of just three 109 Average Indexed Daily Silver Prices from 1982 to 2011 (excluding 1987, 2006 & 2011) years out of thirty has not 108 just changed the April and May averages, but 107 completely changed the 106 whole pattern of price 105 movements compared to 104 the original chart. Now it is 103 a case of sell in February, 102 buy in August. If seasonality “rules” are so 101 heavily affected by 100 removal of a few bits of 99 data, it isn’t looking like a 06 Jul 17 Jul 28 Jul 24 Oct 02 Oct 13 Oct 09 Apr 20 Apr 01 Jan 12 Jan 23 Jan 03 Jun 03 Feb 14 Feb 25 Feb 14 Jun 25 Jun 07 Mar 18 Mar 29 Mar 10 Sep 21 Sep 07 Dec 18 Dec 29 Dec 04 Nov 15 Nov 26 Nov 08 Aug 19 Aug 30 Aug 12 May 23 May reliable method. 01 May In this article on silver seasonality, Adam Hamilton suggests that using 30 year time frames for seasonal analysis “encompass bulls and bears alike, and prices behave very differently in bulls and bears”. He therefore prefers to look at silver’s bull market from 2000 to 2009 (the date of the article) and comes out in favour of some seasonality for silver, particularly in respect of a US “summer doldrum” period. I think he underplays the variability in the data, and thus overplays the confidence in relying on this seasonal indicator, but let us have a look at seasonality just for the recent bull market. Below is a silver seasonal chart for the time period 2001 (start of silver’s bull market in my opinion) through to 2011. This chart is not materially different to Adam’s 2000-2009 chart and shows silver trending sideways from April through to October. 124 Average Indexed Daily Silver Prices from 2001 to 2011 Again, the question is: what is the variability or 119 reliability of this average? To be statistically robust, 114 let’s add and subtract one standard deviation (SD) to 109 the average in the chart at right, as Adam has done in his analysis. See below for 104 this chart (the red line is the same data in both 99 charts). 06 Jul 17 Jul 28 Jul 24 Oct 02 Oct 13 Oct 09 Apr 20 Apr 01 Jan 12 Jan 23 Jan 03 Jun 03 Feb 14 Feb 25 Feb 14 Jun 25 Jun 07 Mar 18 Mar 29 Mar 10 Sep 21 Sep 07 Dec 18 Dec 29 Dec 04 Nov 15 Nov 26 Nov 08 Aug 19 Aug 30 Aug 12 May 23 May 01 May To give an example of how 160 Average Indexed Daily Silver Prices from 2001 to 2011 to interpret this chart, consider the 29th of 150 Average plus one SD December. The chart says Average 2001 - 2011 140 Average minus one SD that, on average, silver will end the year at 120, or up 130 20%. However, the green 120 line says that the average could end up at 91 (or 110 down 9%). The gold line 100 says that the average could also end at 150 (or 90 up 50%). 80 Since the green and gold 06 Jul 17 Jul 28 Jul 24 Oct 02 Oct 13 Oct 09 Apr 20 Apr 01 Jan 12 Jan 23 Jan 03 Jun 03 Feb 14 Feb 25 Feb 14 Jun 25 Jun 07 Mar 18 Mar 29 Mar 10 Sep 21 Sep 07 Dec 18 Dec 29 Dec 04 Nov 15 Nov 26 Nov 08 Aug 19 Aug 30 Aug 12 May 23 May 01 May lines are one standard deviation away from the average, it means that while this seasonality chart indicates silver will be up 20% by the end of a year on average, there is a 68.2% chance it will be between -9% or +50%. The rest of the 31.8% of the time it might end up further way from the average than -9% or +50%. Does that sound like a very reliable prediction? Another way of looking at the chart above is that 68.2% of the time the red line could be anywhere between the green and gold lines. No matter what different time periods or combinations (eg 1971-1980 bull and 2000-2011 bull) I tried, I have not been able to come up with a seasonal chart that doesn’t have this amount of variability. The conclusion is that silver does not demonstrate any real seasonality. The reason for this is that silver is a global market in which supply and demand are not driven by seasonal factors. Silver supply is not affected by weather – recycling, for example, is driven by high prices. Silver demand may have some seasonal drivers but being a global market, these are dispersed all through the year: Chinese new year; Hindu Akshaya Tritiya and Dhanteras in April and November respectively; Western Christmas jewellery sales; End of tax year selling (and refund cheques), which differs in each country; New year dated bullion coin releases – for US Mint this is in January but Perth Mint does this in late Q3 to early Q4.
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