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Lunar seasonality in precious metal returns?
Brian M. Luceya
a
International Integration Studies, Sutherland Center and School of Business, Trinity College Dublin,
Dublin 2, Ireland
First published on: 30 March 2009
To cite this Article Lucey, Brian M.(2010) 'Lunar seasonality in precious metal returns?', Applied Economics Letters, 17: 9,
835 — 838, First published on: 30 March 2009 (iFirst)
To link to this Article: DOI: 10.1080/17446540802516188
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Applied Economics Letters, 2010, 17, 835–838
Lunar seasonality in precious metal
returns?
Brian M. Lucey
Downloaded By: [Trinity College Dublin] At: 14:01 5 May 2011
International Integration Studies, Sutherland Center and School of Business,
Trinity College Dublin, Dublin 2, Ireland
E-mail: [email protected]
We demonstrate for the first time the existence of a lunar cycle on precious
metal returns. This appears to be more pronounced in silver than gold, with
very little evidence for an effect in platinum.
I. Introduction
Much research has been devoted to the issue of how,
and indeed if, phases of the moon affect human activity. Articles have analysed such diverse issues as the
linkage between lunar cycles and admissions to psychiatric hospitals (Campbell and Beets, 1978), medical
consultations (Neal and Colledge, 2000), criminality
(Tasso and Miller, 1976; Lieber, 1978), psychiatric
disturbances (Hicks-Caskey and Potter, 1991) and
absenteeism (Sands and Miller, 1991). The broad consensus of research across a variety of fields is that
actions associated with mood show slight but measurable variation across phases of the moon.
A further body of research has shown that investors
moods, whether they are aware of these or not, can
influence their economic actions. A detailed study in
the work of Lucey and Dowling (2005) notes a comprehensive set of findings based on the works of
Slovic, Loewenstein and others (Slovic 1987;
Loewenstein et al., 1999; Loewenstein, 2000;
MacGregor et al., 2000; Loewenstein et al., 2001)
which provide a linkage between emotion (or mood)
and economic outcomes. The key element of this line
of research is that investors may not be aware of the
effect that mood has on their decision making; even if
they are aware it is extraordinarily difficult to adjust
decision making effected by mood.
In finance research, there is a growing body of
literature that indicates the role of external moodsetting events on asset pricing. Research has indicated
the importance of weather, in particular, sunshine
(Hirshleifer and Shumway, 2003), the Seasonal
Affective Disorder (SAD) phenomena (Kamstra
et al., 2003), temporal adjustment because of daylight
savings (Kamstra et al., 2000) and a wide variety of
other weather and geophysical phenomena (Saunders,
1993; Chang et al., 2008) on cloud cover, on local
weather phenomena (Loughran and Schultz, 2004),
on temperature (Cao and Wei, 2005), on rain and
other measures (Keef and Roush, 2005) and on geomagnetic storms and temperature (Dowling and
Lucey, 2008). Remarkably little countervailing
research has been published, with the exception of
the work of Jacobsen and Marquering (2008).
Research has also noted the effect of sporting events
as mood-setting phenomena (Boyle and Walter, 2003;
Edmans et al., 2007).
More recently, there has emerged a body of work on
the putative role of lunar cycles on asset prices.
Drawing on the literature cited above, this article
finds again slight but measurable variation in asset
returns around lunar events. Yuan et al. (2006) noted
that this line of research goes back at least to Rotton
and Kelly (1985). Yuan et al. (2006), along with Dichev
and Janes (2003) found results consistent with
Hirshleifer and Shumway (2003)’s assertion that good
mood leads to good (positive) returns. In the present
context this has the implication that asset returns
should peak at the new moon and reach a trough at
the full moon. They found evidence that this was so in
the work of Dichev and Janes (2003) in the USA and in
the work of Yuan et al. (2006) in over 48 countries. The
mechanism for such an effect is the demonstrated linkage between the lunar cycle and deep physiological
rhythms (the circatrigintan rhythm; see, e.g. De
Applied Economics Letters ISSN 1350–4851 print/ISSN 1466–4291 online 2010 Taylor & Francis
http://www.informaworld.com
DOI: 10.1080/17446540802516188
835
B. M. Lucey
836
Downloaded By: [Trinity College Dublin] At: 14:01 5 May 2011
Castro and Pearcey, 1995; Bhattacharjee et al., 2000;
Sok et al., 2001, De León et al., 2003; Vandebosch et al.,
2006 as examples of many amongst studies that show
the existence of this rhythm).
Finally, we note the existence of research that suggests that precious metals, gold in particular, are subject to significant psychological and mood influences.
Aggarwal and Lucey (2007) showed evidence of significant anchoring and ‘magic number’ phenomena in
gold returns, Cavaletti et al. (2004) discussed the
importance of psychological issues in gold pricing
and trading. In addition, precious metals have been
shown (Davidson et al., 2003; Daly, 2005; Baur and
Lucey, 2006; Hillier et al., 2006) to be a valuable
addition to (mainly equity) portfolios. All these factors suggest that it is opportune and important to
undertake an examination of the role, if any, that
lunar cycles play in these assets.
II. Data
We analyse PM fixing prices in London for bullion
gold, silver and platinum, all of which are quoted in
US$ terms, for the period January 1998 to midSeptember 2007. In total, this gives us 2530 daily
observations, which we convert to returns for analysis
purposes. Data on lunar phases were collected from
the website of the Munich Astronomical Archive
(www.maa.mhn.de/home.html). Table 1 shows the
basic descriptive statistics of the data. From the
lunar data we created two dummy variable series,
each taking the value of 1 for the 7 days preceding,
including after a full or a new moon. We call these as
fullperiod and newperiod. Following Yuan et al. (2006)
and Dowling and Lucey (2008), we also created a sinusoidal variable defined as (Cos (2Dt))/29.53, where Dt
being the number of days elapsed since the previous full
Table 1. Descriptive statistics
Mean
Median
Max.
Min.
SD
Skewness
Kurtosis
Jarque-Bera
Probability
Gold
Silver
Platinum
0.035371
0.000000
7.005954
-6.247384
0.009588
0.174343
8.970131
3769.00
0.00
0.004727
0.000000
7.005954
-6.247384
0.006644
-0.291415
17.621363
7063.00
0.00
0.025240
0.000000
6.471021
-5.404057
0.006953
0.810279
17.776521
25646.00
0.00
Notes: The four moments and other descriptive statistics of
the daily returns *100 to the three precious metals, as well as
a J–B test for normality are shown.
moon captures the continuous nature of lunar effects
versus the discrete effects of the fullperiod and newperiod variables.
III. Analyses
We conducted a number of analyses, designed to examine the existence of a lunar effect, whether this might be
cyclical, the extent to which this effect if any manifests
itself in variance, and whether any findings are dependent on parametric assumptions of these tests.
We test means and variances across the new and full
moon periods, the existence or otherwise of cyclicality in
the returns attributable to lunar cyclicality, and whether
any observed cyclicality is a manifestation of purported
monthly or daily seasonality in returns. Table 2 shows
descriptive statistics when we split the returns into those
that occur in the newmoon and fullmoon periods defined
above. There is clear evidence that significant differences in returns exist as between both full and new
moon periods and between these periods and the overall
returns. For gold, returns around the full moon are no
less than five times smaller than the returns around the
new moon. This decline is seen also in silver and in
platinum; platinum returns being three times greater in
new moon periods when compared with full moon periods and silver four times; silver returns in new moon
periods being positive while those in full moon periods
being negative. Full moons are bad news, it appears, for
precious metal returns. We note, however, that statistically we cannot reject the null that the two periods
returns are equal for any of the metals investigated,
which is interesting given the differential between them.
We further investigate the cyclicality of returns by
means of a regression of the returns on the sinusoidal
variable. These results, in Table 3, indicate clearly that
for the case of silver at least there appears to be evidence of lunar seasonality. This is consistent with the
results found in the works of Dichev and Janes (2003)
and Yuan et al. (2006). However, there is no evidence
of such seasonality for gold or for platinum.
IV. Conclusion
We demonstrate for the first time the existence of a
lunar cycle on precious metal returns. This appears to
be more pronounced in silver than gold, with very little
evidence for an effect in platinum. Despite significant
apparent differences in the mean returns across the
lunar cycle, we do not seem to see a strong cycle in
evidence. Perhaps these markets are more efficient
than might have been considered a priori.
Lunar seasonality in precious metal returns?
837
Table 2. Full versus new moon returns
Gold
Silver
Overall
Full moon New moon
period
period
Overall
Mean
0.035371 0.004727
Median
0.000000 0.000000
Max.
7.005954 7.005954
Min.
-6.247384 -6.247384
SD
0.009588 0.006644
Skewness 0.174343 -0.291415
Kurtosis
8.970131 17.621363
Stat.
-1.07
-1.07
Downloaded By: [Trinity College Dublin] At: 14:01 5 May 2011
T-test
S-W
t-test*
Levene
test
0.025240
0.000000
6.471021
-5.404057
0.006953
0.810279
17.776521
Full moon New moon
period
period
Overall
Full moon New moon
period
period
0.029325 -0.004537
0.021045
0.049865
0.014400
0.049900
0.000000
0.000000
0.000000
0.000000
0.000000
0.000000
10.320766
9.907613 10.320766
8.427776
7.976500
8.427800
-16.075291 -12.004463 -16.075291 -17.277319 -11.256100 -17.277300
0.017166
0.012101
0.012289
0.013499
0.009376
0.013499
-0.753348 -0.827765 -1.046522 -0.741242 -0.344443 -0.741242
11.047464 18.647688 25.694403 18.530126 18.684400 18.530130
Stat.
-0.75
-0.75
p-value
0.28
0.28
1.95
Platinum
0.16
0.82
p-value
0.46
0.46
Stat.
-1.08
-1.08
p-value
0.28
0.28
0.37
305.52
0.00
Notes: The four moments and other descriptive statistics of the daily returns *100 to the three precious metals split according to
whether the returns occur in the newperiod or fullperiod defined as the 7 days before and after a new or full moon event are
shown. T-test is a standard t-test for equality of means as between these two periods, while S–W t-test is a t-test incorporating a
Satterthwaite–Welch correction for unequal sample size and variances. Levene test is a test or equality of variance. In all cases
the p-value is of a H0 that the mean (variance) are equal across the two samples.
Table 3. Lunar seasonality
p-value
Cosine
coeff.
p-value
0.29
1.26
0.30
0.01
-0.29
-1.26
0.29
0.01
-0.05
0.89
0.05
0.89
Constant
Gold return
Silver
return
Platinum
return
Notes: The results of a regression
ðCosð2Dt ÞÞ
þe
Ri ¼ þ 29:53
are shown.
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