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Revisions of international firms’ energy reserves and the reaction of the stock market
Energy 36 (2011) 3541e3546
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Energy journal homepage: www.elsevier.com/locate/energy
Revisions of international firms’ energy reserves and the reaction of the stock market Bert Scholtens*, Robert Wagenaar University of Groningen, Energy and Sustainability Centre, PO Box 800, 9700 AV Groningen, The Netherlands
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 December 2010 Received in revised form 21 March 2011 Accepted 22 March 2011 Available online 19 April 2011
Energy companies can adjust the estimation of their reserves. We investigate how these revisions impact on the value of these firms. We analyze 100 revisions in seventeen countries for the period 2000-2010. We use an event study and find that the revisions of energy reserves significantly impact on the market value of the firm. We also discover an asymmetry in this response as the market’s reaction to downward revisions is much larger than that to upward revisions. Furthermore, the response to revisions in Australia, Canada, UK and US is smaller than that in the other 13 countries and the response is smaller in the years with turmoil on the energy markets. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Energy companies Reserve revisions Event study
1. Introduction How do revisions of estimated energy reserves impact on the market value of equity of the revising firm? To find out, we focus on technical revisions of proven reserves. That is, reserves that are claimed to have reasonable certainty (at least 90% confidence) of being recoverable under the existing technical, economic and political conditions. This usually is referred to as P90 or 1P [1]. Reserves are relevant for the valuation of energy companies as they are a source of future earnings [2]. Therefore, the revisions of reserves can affect the value of these firms too. So far, most attention regarding the energy reserves and revisions thereof is directed at an aggregate level, see e.g. the discussion about peak oil [3,4], the analysis of oil transition [5] and the analysis of energy resources and use [6e8]. Alternatively, several studies concern the role of reserves in the operational management of firms and fields [9e13]. But, as far as we are aware of, the impact of reserve revisions on firm’s financial value has not been investigated. In this paper, we investigate the effect of P90 reserve revisions on the market value of the equity of international energy firms in the period 2000e2010. Since the beginning of the 1980s, analysts and experts worry about the quality of the information about the reserves energy companies report [2,14]. This worry results from the fact that
* Corresponding author. Tel.: þ31 503637064; fax: þ31 503638252. E-mail address: [email protected] (B. Scholtens). 0360-5442/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.energy.2011.03.060
estimating reserves is quite complicated and is subject to various choices that must be made [15]. Firms and governments may use different methodologies, definitions and classifications to arrive at reserve estimations. And there can be incentives for firms and governments to overstate the reserves [16]. Spear [17] examines the changes in the proven reserves reported by US oil and gas producers in annual reports of 1984e1988. He finds that revisions only have a modest influence on security returns. In this paper, we want to investigate whether and how the stock market responds to unexpected revisions of P90 energy reserves. We analyze 100 revisions for energy firms located in 17 countries in the period 2000e2010. We employ the event study methodology to find out about the stock market response [18e21]. We investigate upward and downward revisions and assess the symmetry in the market response to these revisions [22]. We think this asymmetry is interesting as several papers have found that there is a greater impact on economic activity of oil price increases than of oil price decreases [23e28]. This literature suggests two possible explanations for the asymmetric impact of positive and negative oil price shocks. It first suggests that it is the magnitude of relative price changes that matters. Second, the literature stresses there is an option value associated with waiting to invest. The rationale for these two explanations is usually based on adjustment costs, financial stress, sentiment, monetary policy responses and investment under uncertainty [26,27]. Furthermore, we check the robustness of our model to arrive at expected returns and go into the sensitivity of our findings by focusing on the response to reserve changes with various subsamples.
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In the remainder of the paper, we first introduce the data and the methodology. Then we report and discuss the results. The last section holds the conclusion. 2. Method and data 2.1. Method We use the event study methodology to investigate whether P90 revisions significantly impact on the market value of equity of the firm that revises the P90 reserves. The event study is a wellestablished approach in the finance and economics literature [18]. In essence, it relies on the assumption that stock market participants are forward looking. It is based on the capital asset pricing model which holds that prices will only move when new information becomes available [19,20]. New information is information that is unexpected for the market participants. Expectations already are integrated in stock price modeling and, therefore, in the stock price [21]. There are various ways to conduct an event study, but we rely on an approach that is validated by many studies and that can be regarded as the standard methodology [18]. This approach uses the so-called market and risk adjusted model. This model accounts for the price (return) development on the stock market where the firm is listed that is involved in the unexpected news (in our case, the firm that reports the reserve revision). Furthermore, it accounts for the specific risk of the firm’s stock. Then, expected returns are compared with actual returns during an event. Statistical tests are required to show whether any differences are significant. If so, the event is said to have abnormal returns [18,19,21]. The return of the firm i’s stock on day t (Ri,t) is defined as the log of the stock price on day t minus the log of the stock price of firm i on day (t-1). The market and risk adjusted returns model calculates the beta of the stock which reflects the volatility of the stock’s return vis-à-vis a benchmark, usually the domestic stock market index. This beta is calculated by relating the covariance of the stock return and the market return to the variance of the market return. The specific or individual risk (the so-called alpha) of the firm is defined as the stock’s return minus the beta times this return. To arrive at the abnormal return of firm i on day t, we subtract the alpha and beta times the stock market return from the individual stock’s return. As such, this approach is in line with the suggestion of Brown and Warner [21], see also MacKinlay [18]. We first calculate the return of the firm’s stock in the so-called estimation window, which is a period of time that predates the event. The event in our case is the reserve revision. These returns are the normal or expected returns. In the so-called event window, which is a period of time surrounding the event date (day 0; the day at which the new information becomes available), we take the difference between the actual returns and the expected returns. These return differences are the abnormal returns. We average these returns for all events and this average is the average abnormal return (AAR) for that particular day in the event window. We test whether or not the average abnormal returns are significantly different from zero. If so, we conclude that the event can be associated with a significant stock market response. We will use both parametric and non-parametric tests to find out whether there are significant abnormal returns in the event window. As the parametric test, we use the well-established Student t-test [29]. For the non-parametric test, we use the Wilcoxon Signed Rank test [29]. This test does account for the sign of the difference as well as for the size of the differences between pairs. For the pairs, the test investigates the difference in the medians. As the event day (day 0) we define that day on which the news about the P90 revision becomes available to the market. We use an
Table 1 Characteristics of the data sample (100 revisions). Country
#
Year
#
Canada US UK Australia Russia Norway South-Korea Netherlands Brazil, France, Italy Austria, Malaysia, New-Zealand, Portugal, Spain, Switzerland
19 18 16 10 7 6 5 4 3
2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000
9 10 14 12 15 13 20 5 1 0 1
Upward revisions Downward revisions
72 28
1
estimation window of 195 trading days to estimate the normal or expected returns: [200; 6]; the event window investigates the returns from day [-5] to day [þ5] [18]. So, the event window is [5; 5]. Apart from investigating average abnormal returns of our events, i.e. the reserve revisions, we also investigate the cumulative average abnormal return (CAAR). This CAAR calculates for a particular multiday period the response of the stock market. The CAAR of period [t-x, t] is the sum of the average abnormal returns from day [t-x] up to and including day t [21]. We will test the hypothesis that a revision of the reserves does significantly impact on the stock market return of the firm that announces this revision. The null hypothesis is that there is no significant impact. 2.2. Data We rely on LexisNexis for news items about changes in the estimations of the reserves of energy firms. We require that the firms have a listing on the stock exchange, that the stock is traded, that there are no cofounding effects (that is, at or around the same time of the revision, no other material news regarding the firm arrives at the market), and that the revision is in the period 2000e2010. As such, we end up with 100 revisions (see Appendix E for an overview of the events). Table 1 gives the key characteristics of our sample. It appears that there were 40 revisions in the period 2000e2005 and 60 in the period 2006e2010. Furthermore, 63 revisions were with energy firms from four countries (Australia, Canada, the US, and the UK). There were 72 upward revisions and 28 downward revisions. We use Datastream for information about stock prices and domestic market indices. Table 2 gives the descriptive statistics of the returns in the estimation window according to the market and risk adjusted returns model. The average return of the firm’s stock in the estimation window is .01% and this return is not significantly different from zero.
Table 2 Descriptive statistics of the returns. Mean
0.0001
Median Standard deviation Minimum Maximum Skewness Kurtosis Jarque-Bera
0.0001 0.0310 0.0818 0.1351 0.35 3.56 4.17
B. Scholtens, R. Wagenaar / Energy 36 (2011) 3541e3546
3. Results
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Table 4 Cumulative average abnormal returns in the event window.
In this section, we report the results. We first give the main results and then go into the robustness and sensitivity analysis. With respect to robustness, we will estimate the returns on the basis of alternative models. As to the sensitivity of our findings, we will compare upward and downward revisions, country origin, time period, and small and large revisions. Table 3 gives the average abnormal returns in the event window. It shows that on the event day (day 0) the average abnormal returns for the sample as a whole is 0.84% and statistically significant. The AAR of positive revisions is 1.60% and that of negative revisions is 1.53%. The AAR with positive revisions is marginally positive and significant in the parametric test for significance for day 1, but turns into the negative afterwards. The AARs with negative revisions are highly significant on day 1 and day 2 according to the parametric test, but not with the non-parametric test. During the event window, the abnormal returns remain negative. Table 4 provides the cumulated average abnormal returns (CAARs) for several subsets in the event window. For the sample as a whole, there is a significant and negative response in the full event window and for the period since the event. The CAAR of upward revisions is positive for most windows; the CAAR of downward revisions is negative and statistically significant for most windows. On the basis of Tables 3 and 4, we must reject the null hypothesis of no significant impact of reserve revisions on firm value. Therefore, we can conclude that revisions of P1 reserves have a significant impact on the return of the energy firm. This conclusion is in line with Spear [17] who investigated changes in proven reserves with US firms in the mid 1980s. We test the robustness of our model by investigating the AARs and CAARs with other types of models as well, namely the mean and the market adjusted returns model [19,21]. With the mean returns model, the estimated return is the simple mean return of all returns in the estimation window (so both the alpha and the beta are 0). With the market adjusted model, the alpha is set at 0 and the beta is 1. For brevity sake, we only provide the conclusions, the results are available upon request with the contacting author. We find that the results of this test do not differ from those of the main model: the AARs and CAARs are of the same order of magnitude and we also find that on the event day the positive revisions yield a significant positive AAR and the negative revisions yield a significant negative AAR. Furthermore, it appears that the negative response to downward revisions lasts for at least four days with the other two models as well and this response is significant for days 0, 1 and 2 with all models used. Therefore, we conclude that our results are robust to the choice of the model that is used to arrive at the expected returns.
Period
All revisions (N ¼ 100)
Upward revisions (N ¼ 72)
Downward revisions (N ¼ 28)
CAAR
p-value
CAAR
p-value
CAAR
p-value
[-5,5] [-5;1] [-5,0] [0,5] [1,5]
.0143 .0022 .0063 .0121 .0205
.0000 .4869 .0462 .0002 .0000
.0074 .0006 .0166 .0068 .0092
.0857 .8952 .0002 .1120 .0325
.0760 .0128 .0281 .0632 .0479
.0000 .0000 .0000 .0000 .0000
For sensitivity purposes, we did several tests regarding subgroups in our sample. First, we compared the responses regarding positive revisions (upward revisions) with those on negative (downward) revisions (see Appendix A). The reason for this particular analysis is that several studies [23e28] have established that ‘bad news’ in energy markets has much more impact than ‘good news’. Kahneman and Tversky [22] provide the theoretical foundations for this asymmetry. As to upward and downward reserve revisions, it turns out that the differences between the two responses were significantly different on day 0, 1 and 2 at the 1% confidence level (see Table A.1). Furthermore, it appears that the CAARs between upward and downward revisions are significantly different (see Table A.2). This confirms and strengthens the previous findings. These results are consistent with those reported by Lee et al. [23], Ferderer [24] and Sadorsky [25], who find that oil price and oil price volatility shocks exhibit asymmetric effects on production. Thus, our results suggest that the asymmetry in the response to ‘good’ and ‘bad’ news is applicable to upward and downward energy reserve revisions as well. Second, we look into countries as we are interested whether there are international differences regarding the response to reserve revisions. To this extent, we combined the events in Australia, Canada, the UK and the US and relate them to the events elsewhere (see Appendix B). We find that the response in these four countries significantly differs from that elsewhere on the event day. After the event the stock market’s response in the four countries to an upward revision is significantly different from that elsewhere until day 4. In case of downward revisions it is not significant on day 2 and significantly different for the other days (see Table B.1). For the cumulated returns, we find that the response to downward revisions is significantly different after the event in the four countries. More specifically, in Australia, Canada, the UK and the US, the market response is less pronounced than elsewhere (see Table B.2 Appendix). This finding might be related to the international differences in legal system and market development [30,31].
Table 3 Average abnormal returns in the event window. Day
5 4 3 2 1 0 1 2 3 4 5
All revisions (N ¼ 100)
Upward revisions (N ¼ 72)
Downward revisions (N ¼ 28)
AAR
p-value (par)
p-value (non par)
AAR
p-value (par)
p-value (non par)
AAR
p-value (par)
p-value (non par)
.0061 .0099 .0060 .0024 .0025 .0084 .0093 .0014 .0087 .0056 .0044
.0519 .0018 .0546 .4378 .4295 .0078 .0035 .6540 .0064 .0762 .1620
.2550 .1830 .7670 .3860 .8660 .0450 .0850 .3660 .3770 .2940 .3960
.0021 .0116 .0099 .0017 .0027 .0160 .0033 .0010 .0100 .0031 .0061
.3103 .0037 .0108 .3442 .2643 .0001 .2209 .4032 .0101 .2363 .0766
.4320 .5330 .3840 .5480 .9110 .0000 .9280 .7750 .4940 .0310 .7750
.0188 .0051 .0015 .0026 .0019 .0153 .0234 .0170 .0040 .0056 .0020
.0000 .1147 .3579 .2693 .3246 .0002 .0000 .0001 .1745 .0964 .3165
.0720 .3390 .8020 .4390 .8380 .0760 .2190 .1010 .3990 .6690 .9460
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La Porta et al. [30] argue that especially in common law countries, the legal system protects investors and offers an incentive to firms to provide accurate and reliable information. Then, market participants will have less uncertainty regarding news from firms. As a result, the response to unexpected news may be smaller in common law countries. Third is that we investigate the response in different sub periods (see Appendix C). In many cases, it appears that the response in the period 2000e2005 is significantly stronger than that in the period 2006e2010. This can best be seen by looking into the cumulated abnormal returns (Table C.2). We have the impression that this result can be related to the recent turmoil in the energy markets (see also [8]). Fourth and last is that we compare the 40% largest reserve revisions with the 40% smallest ones (see Appendix D). We do not compare the top-50 with the bottom-50 (ranking on the basis of size) as the difference between revisions around the mean is relatively small. Instead, we skip the median 20% revisions. The result is that we lose 20% of the observations. As expected, we find that in particular for negative revisions, there is a significant difference between small and large revisions (see Table D.1). In the case of cumulated abnormal returns, we find that the difference between small and large revisions is very clear for both positive and negative revisions (see Table D.2). This result can be related to the difference in the materiality between large and small reserve revisions.
4. Conclusion We investigate the stock market response regarding news about 100 P90 reserve revisions for international energy companies during 2000e2010. We find that upward revisions result in an average increase of about 1.60% of the energy firm’s market value of equity on the event day. Over a period of six days, the increase is 0.68% and not statistically significant. Downward revisions result in a decrease of about 1.53%. Here, over a period of six days, the change is 4.79% and highly significant. The negative response with respect to downward revisions persists for about a week. The differential between the valuation of positive and negative revisions appears to be statistically significant. This finding is in line with the literature on asymmetries regarding the response to ‘good’ and ‘bad’ news. We also find significant differences between the market valuation of reserve revisions in Australia, Canada, the UK and the US vis-à-vis those elsewhere; those in the former countries appear to be significantly smaller. This may be related to the differences in legal systems among the countries in the sample. In the common law countries, unexpected news is usually accompanied by less uncertainty and, therefore, will result in a less pronounced response. Furthermore, the response to revisions in the period 2000e2005 is stronger than that to reserve revisions in the period 2006e2010. We assume that this is the result of the turmoil in the (energy) markets in the latter period. The response to large revisions is much stronger than that to small revisions. This straightforward result can be related to the materiality of large versus small revisions. Our findings are robust to the modeling of expected stock market returns. Our findings show that technical revisions of proven reserves do impact on the valuation of energy firms. These reserves are a basis for future earnings and, hence, reserve revisions impact on the value of these earnings. We establish that there is an asymmetric response between upward and downward revisions. Especially in the case of downward revisions, the market value of the firm significantly drops. Therefore, it is of the utmost importance for the energy firms to provide accurate and robust estimations of their energy reserves.
Appendix A. Upward versus downward revisions
Table A.1 Day
5 4 3 2 1 0 1 2 3 4 5
Upward revisions (N ¼ 72)
Downward revisions (N ¼ 28)
Differential (upward downward)
AAR
p-value
AAR
p-value
differential
p-value
.0021 .0116 .0099 .0017 .0027 .0160 .0033 .0010 .0100 .0031 .0061
.3103 .0037 .0108 .3442 .2643 .0001 .2209 .4032 .0101 .2363 .0766
.0188 .0051 .0015 .0026 .0019 .0153 .0234 .0170 .0040 .0056 .0020
.0000 .1147 .3579 .2693 .3246 .0002 .0000 .0001 .1745 .0964 .3165
.0167 .0065 .0114 .0009 .0008 .0313 .0201 .0180 .0060 .0025 .0081
.0002 .1283 .0084 .8323 .8507 .0000 .0000 .0000 .1600 .5566 .0589
Table A.2 Day
[-5;5] [-5;-1] [-5;0] [0;5] [1;5]
Upward revisions
Downward revisions
Differential (upward downward)
CAAR
p-value
CAAR
p-value
differential
p- value
.0074 .0006 .0166 .0068 .0092
.0857 .8952 .0002 .1120 .0325
.0760 .0128 .0281 .0632 .0479
.0000 .0000 .0000 .0000 .0000
.0834 .0134 .0447 .0700 .0387
.0000 .0002 .0000 .0000 .0000
Appendix B. International differences Table B.1 Day
2 1 0 1 2 3 4 5
Australia, Canada, UK & US
Rest of the world
Australia, Canada, UK & US vs. Rest of the world
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
AAR
AAR
AAR
AAR
Positive (p-value)
Negative (p-value)
.0043 .0031 .0209 .0087 .0079 .0080 .0025 .0034
.0006 .0059 .0136 .0281 .0165 .0018 .0014 .0109
.0078 .0025 .0156 .0131 .0092 .0111 .0007 .0029
.0105 .0078 .0196 .0123 .0178 .0093 .0225 .0202
.0000 .3998 .0075 .0000 .0000 .0761 .0734 .4186
.0001 .0000 .0172 .0000 .3270 .0043 .0000 .0000
Table B.2 Period
[-5; 5] [-5;-1] [-5; 0] [0; 5] [1; 5]
Australia, Canada, UK & US
Rest of the world
Australia, Canada, UK & US vs. Rest of the world
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
CAAR
CAAR
CAAR
CAAR
Positive (p-value)
Negative (p-value)
.0034 .0031 .0209 .0130 .0079
.0109 .0059 .0136 .0479 .0343
.0029 .0025 .0156 .0118 .0037
.0202 .0078 .0196 .1016 .0821
.4186 .3998 .0075 .2973 .0275
.0000 .0000 .0172 .0000 .0000
B. Scholtens, R. Wagenaar / Energy 36 (2011) 3541e3546
Appendix C. 2000e2005 versus 2006e2010
3545
Appendix E. Overview of the reserve revisions (events)
Table C.1 Day
2 1 0 1 2 3 4 5
2000e2005
2006e2010
2000e2005 vs. 2006 e2010
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
AAR
AAR
AAR
AAR
Positive (p-value)
Negative (p-value)
.0048 .0030 .0163 .0063 .0007 .0207 .0009 .0036
.0033 .0016 .0182 .0275 .0199 .0062 .0092 .0047
.0056 .0049 .0159 .0002 .0015 .0044 .0041 .0040
.0047 .0038 .0023 .0220 .0082 .0065 .0155 .0097
.0000 .0000 .3634 .0000 .2590 .0000 .0000 .3730
.3665 .3066 .0002 .1016 .0000 .4712 .0724 .0006
Table C.2 Period
2000e2005
[-5; 5] [-5;-1] [-5; 0] [0; 5] [1; 5]
2006e2010
2000e2005 vs. 2006 e2010
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
CAAR
CAAR
CAAR
CAAR
Positive (p-value)
Negative (p-value)
.0036 .0030 .0163 .0054 .0217
.0047 .0016 .0182 .0857 .0675
.0040 .0049 .0159 .0132 .0028
.0097 .0038 .0023 .0284 .0260
.3730 .0000 .3634 .0000 .0000
.0006 .3066 .0002 .0000 .0000
Appendix D. Large versus small revisions
Table D.1 Day
2 1 0 1 2 3 4 5
Small revisions (N ¼ smallest 40%)
Large revisions (N ¼ largest 40%)
Large versus Small
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
AAR
AAR
AAR
AAR
Positive (p-value)
Negative (p-value)
.0129 .0011 .0149 .0113 .0048 .0067 .0035 .0074
.0066 .0009 .0093 .0180 .0039 .0059 .0016 .0117
.0177 .0012 .0169 .0108 .0043 .0027 .0110 .0057
.0009 .0037 .0202 .0233 .0281 .0076 .0300 .0098
.0001 .4932 .3977 .0029 .4773 .3057 .1709 .4154
.0000 .0084 .0000 .0000 .0000 .0704 .0000 .0000
Table D.2 Period
[-5; 5] [-5;-1] [-5; 0] [0; 5] [1; 5]
Small revisions (N ¼ smallest 40%)
Large revisions (N ¼ largest 40%)
Large versus Small
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
CAAR
CAAR
CAAR
CAAR
Positive (p-value)
Negative (p-value)
.0219 .0275 .0126 .0056 .0093
.0019 .0012 .0081 .0007 .0100
.0387 .0146 .0316 .0241 .0071
.1230 .0041 .0243 .1190 .0988
.0000 .0000 .0000 .0099 .0188
.0000 .0070 .0000 .0000 .0000
#
Event date
Firm
Country
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
26-12-2000 9-10-2001 26-11-2002 26-2-2003 26-2-2003 8-7-2003 14-7-2003 9-1-2004 16-1-2004 28-1-2004 2-2-2004 5-2-2004 10-2-2004 17-2-2004 20-2-2004 18-3-2004 18-3-2004 15-4-2004 19-4-2004 18-5-2004 19-5-2004 19-5-2004 29-6-2004 29-6-2004 27-7-2004 17-9-2004 17-11-2004 7-1-2005 17-1-2005 3-2-2005 16-2-2005 31-3-2005 18-7-2005 17-8-2005 20-9-2005 2-10-2005 13-10-2005 1-11-2005 23-11-2005 6-12-2005 26-1-2006 29-1-2006 21-2-2006 5-5-2006 14-5-2006 5-6-2006 5-6-2006 5-6-2006 5-6-2006 5-6-2006 23-8-2006 19-10-2006 16-11-2006 16-11-2006 24-11-2006 5-3-2007 31-5-2007 31-5-2007 31-5-2007 31-5-2007 31-5-2007 31-5-2007 12-6-2007 27-9-2007 22-11-2007 22-11-2007 18-12-2007 1-1-2008 26-1-2008 5-2-2008 7-2-2008
Petroz oil Statoil Murphy Oil Marathon Oil Corp. Hardman Resources Ltd BP Beach petroleum Ltd. Shell Petrobras Redwood Energy Ltd. Nexen Murphy Oil American Forest El Paso Vintage Petroleum Inc. Norsk Hydro BP Yukos Nelson Resources Ltd Cairn Energy Petro Canada Baytex Energy Trust BP Norsk Hydro Arena Resources Inc. Yukos Yukos ConocoPhillip Find Energy Ltd. Shell Santos ltd. Toreador Resources Cairn Energy Cano Petroleum Cairn Energy Canada Southern Petroleum Ltd. Chevron Eni Group Apex Resources Group Inc Devon Energy Repsol Petro- Canada ConocoPhillips Australian Worldwide Exploration Ltd. Cairn Energy Exxon Mobile Corp. Petro- Canada Chevron Murphy Oil Norsk Hydro ROC Oil Co Ltd. Canada Southern Petroleum Ltd. Husky Energy Woodside Petroleum AED oil Lukoil Rosneft Kumho Petrochemical Hyundai Corp. Daewoo GS Caltex Korea Gas Corp BP Toreador Resources Australian Worldwide Exploration Ltd. New-Zealand Oil and Gas DNO ASA Cairn Energy ROC Oil Co Ltd. Transglobe Energy Corp. Petrobras
Malaysia Norway USA Canada Australia UK Australia Netherlands Brazil Canada Canada USA USA USA USA Norway UK Russia Canada UK Canada Canada UK Norway USA Russia Russia USA Canada Netherlands Australia France UK USA UK Canada USA Italy USA UK Spain Canada USA Australia UK USA Canada USA USA Norway UK Canada Canada Australia Australia Russia Russia Korea Korea Korea Korea Korea UK France Australia New-Zealand Norway UK UK USA Brazil
(continued on next page)
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B. Scholtens, R. Wagenaar / Energy 36 (2011) 3541e3546
(continued ) #
Event date
Firm
Country
72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
7-2-2008 7-2-2008 7-2-2008 3-3-2008 1-4-2008 14-4-2008 27-6-2008 17-7-2008 7-8-2008 7-8-2008 7-10-2008 18-11-2008 30-12-2008 16-2-2009 25-2-2009 8-3-2009 12-3-2009 1-6-2009 29-8-2009 2-9-2009 8-10-2009 26-10-2009 13-12-2009 14-1-2010 29-1-2010 1-2-2010 9-2-2010 10-2-2010 17-2-2010
BG Group Galp Energia West Siberian Resources Ltd Pacific Rubiales Eni Group Gastar Explorations Ltd. Shell Dejour Enterprises Ltd Shell OMV BP Manas Petroleum BPZ Resources Bankers Petroleum Pan-Orient Energy Corp. Austral Pacific Energy Ltd. 3D Oil Stuart Petroleum Ltd. Gulf Keystone Petroleum OGX Nordic Oil and Gas Ltd BPZ Resources Statoil Gulf Keystone Petroleum Transglobe Energy Corp. Toreador Resources Alliance Oil Company Ltd Mediterranean Oil & Gas Plc Marathon Oil Corp.
UK Portugal Russia Canada Italy Canada Netherlands Canada Netherlands Austria UK Switzerland USA Canada Canada Australia Australia Australia UK Brazil Canada USA Norway UK USA France Russia Italy Canada
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[8] Lior N. Sustainable energy development: the present (2009) situation and possible paths to the future. Energy 2010;35:3976e94. [9] Page WP. Horizontal divestiture of energy companies: regional market evidence on coal production and reserve ownership concentration ratios. Energy 1980;5:1245e55. [10] Hirst E, Kirby B. Operating reserves and bulk-power reliability. Energy 1998; 23:949e59. [11] Kretzschmar GL, Sharifzyanova L. Limits to international diversification in oil & gas e domestic vs foreign asset control. Energy 2010;35:466e77. [12] Najafi M, Ehsan M, Fotuhi-Firuzabad M, Akhavein A, Afshar K. Optimal reserve capacity allocation with consideration of customer reliability. Energy 2010; 35:3883e90. [13] Tang X, Zhang B, Höök M, Feng L. Forecast of oil reserves and production in Daqing oilfield of China. Energy 2010;35:3097e102. [14] Bowden G. Estimating U.S. crude oil resources: organizational interests, political economy, and historical change. The Pacific Sociological Review 1982;25:419e48. [15] Haider GM. World oil reserves: problems in definition and estimation. OPEC Review 2000;24:305e27. [16] Balaban O, Tsatskin A. The paradox of oil reserve forecasts: the political implications of predicting oil reserves and oil consumption. Energy Policy 2010;38:1340e4. [17] Spear NA. The stock market reaction to the reserve quantity disclosures of U.S. oil and gas producers. Contemporary Accounting Research 1994;11:381e404. [18] MacKinlay AC. Event studies in economics and finance. Journal of Economic Literature 1997;35:13e39. [19] Brown SJ, Warner JB. Measuring security price performance. Journal of Financial Economics 1980;8:205e58. [20] Hillier D, Grinblatt M, Titman S. Financial markets and corporate strategy. Maidenhead: McGraw-Hill; 2008. [21] Brown SJ, Warner JB. Using daily stock returns. Journal of Financial Economics 1985;14:3e31. [22] Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science 1974;185:1124e31. [23] Lee K, Ni S, Ratti RA. Oil shocks and the macroeconomy: the role of price variability. Energy Journal 1995;1995(16):39e56. [24] Ferderer J. Oil price volatility and the macroeconomy. Journal of Macroeconomics 1996;18:1e26. [25] Sadorsky P. Oil price shocks and stock market activity. Energy Economics 1999;21:449e69. [26] Balke NS, Brown SPA, Yucel MK. Oil price shocks and the US economy: where does the asymmetry originate? Energy Journal 2002;23:27e52. [27] Jones DW, Leiby PN, Paik IK. Oil price shocks and the macroeconomy: what has been learned since 1986. Energy Journal 2004;25:1e32. [28] Sadorsky P. Assessing the impact of oil prices on firms of different sizes: its tough being in the middle. Energy Policy 2008;36:3854e61. [29] Newbold P, Carlson WL, Thorne B. Statistics for business and economics. Upper Saddle River, New Jersey: Pearson; 2007. [30] La Porta R, Lopez-De-Silanes F, Shleifer A. The economic consequences of legal origins. Journal of Economic Literature 2008;46:285e332. [31] Beck T, Demirgüç-Kunt A, Levine R. Law and finance: why does legal origin matter? Journal of Comparative Economics 2003;31:653e75.
Contents lists available at ScienceDirect
Energy journal homepage: www.elsevier.com/locate/energy
Revisions of international firms’ energy reserves and the reaction of the stock market Bert Scholtens*, Robert Wagenaar University of Groningen, Energy and Sustainability Centre, PO Box 800, 9700 AV Groningen, The Netherlands
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 December 2010 Received in revised form 21 March 2011 Accepted 22 March 2011 Available online 19 April 2011
Energy companies can adjust the estimation of their reserves. We investigate how these revisions impact on the value of these firms. We analyze 100 revisions in seventeen countries for the period 2000-2010. We use an event study and find that the revisions of energy reserves significantly impact on the market value of the firm. We also discover an asymmetry in this response as the market’s reaction to downward revisions is much larger than that to upward revisions. Furthermore, the response to revisions in Australia, Canada, UK and US is smaller than that in the other 13 countries and the response is smaller in the years with turmoil on the energy markets. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Energy companies Reserve revisions Event study
1. Introduction How do revisions of estimated energy reserves impact on the market value of equity of the revising firm? To find out, we focus on technical revisions of proven reserves. That is, reserves that are claimed to have reasonable certainty (at least 90% confidence) of being recoverable under the existing technical, economic and political conditions. This usually is referred to as P90 or 1P [1]. Reserves are relevant for the valuation of energy companies as they are a source of future earnings [2]. Therefore, the revisions of reserves can affect the value of these firms too. So far, most attention regarding the energy reserves and revisions thereof is directed at an aggregate level, see e.g. the discussion about peak oil [3,4], the analysis of oil transition [5] and the analysis of energy resources and use [6e8]. Alternatively, several studies concern the role of reserves in the operational management of firms and fields [9e13]. But, as far as we are aware of, the impact of reserve revisions on firm’s financial value has not been investigated. In this paper, we investigate the effect of P90 reserve revisions on the market value of the equity of international energy firms in the period 2000e2010. Since the beginning of the 1980s, analysts and experts worry about the quality of the information about the reserves energy companies report [2,14]. This worry results from the fact that
* Corresponding author. Tel.: þ31 503637064; fax: þ31 503638252. E-mail address: [email protected] (B. Scholtens). 0360-5442/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.energy.2011.03.060
estimating reserves is quite complicated and is subject to various choices that must be made [15]. Firms and governments may use different methodologies, definitions and classifications to arrive at reserve estimations. And there can be incentives for firms and governments to overstate the reserves [16]. Spear [17] examines the changes in the proven reserves reported by US oil and gas producers in annual reports of 1984e1988. He finds that revisions only have a modest influence on security returns. In this paper, we want to investigate whether and how the stock market responds to unexpected revisions of P90 energy reserves. We analyze 100 revisions for energy firms located in 17 countries in the period 2000e2010. We employ the event study methodology to find out about the stock market response [18e21]. We investigate upward and downward revisions and assess the symmetry in the market response to these revisions [22]. We think this asymmetry is interesting as several papers have found that there is a greater impact on economic activity of oil price increases than of oil price decreases [23e28]. This literature suggests two possible explanations for the asymmetric impact of positive and negative oil price shocks. It first suggests that it is the magnitude of relative price changes that matters. Second, the literature stresses there is an option value associated with waiting to invest. The rationale for these two explanations is usually based on adjustment costs, financial stress, sentiment, monetary policy responses and investment under uncertainty [26,27]. Furthermore, we check the robustness of our model to arrive at expected returns and go into the sensitivity of our findings by focusing on the response to reserve changes with various subsamples.
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In the remainder of the paper, we first introduce the data and the methodology. Then we report and discuss the results. The last section holds the conclusion. 2. Method and data 2.1. Method We use the event study methodology to investigate whether P90 revisions significantly impact on the market value of equity of the firm that revises the P90 reserves. The event study is a wellestablished approach in the finance and economics literature [18]. In essence, it relies on the assumption that stock market participants are forward looking. It is based on the capital asset pricing model which holds that prices will only move when new information becomes available [19,20]. New information is information that is unexpected for the market participants. Expectations already are integrated in stock price modeling and, therefore, in the stock price [21]. There are various ways to conduct an event study, but we rely on an approach that is validated by many studies and that can be regarded as the standard methodology [18]. This approach uses the so-called market and risk adjusted model. This model accounts for the price (return) development on the stock market where the firm is listed that is involved in the unexpected news (in our case, the firm that reports the reserve revision). Furthermore, it accounts for the specific risk of the firm’s stock. Then, expected returns are compared with actual returns during an event. Statistical tests are required to show whether any differences are significant. If so, the event is said to have abnormal returns [18,19,21]. The return of the firm i’s stock on day t (Ri,t) is defined as the log of the stock price on day t minus the log of the stock price of firm i on day (t-1). The market and risk adjusted returns model calculates the beta of the stock which reflects the volatility of the stock’s return vis-à-vis a benchmark, usually the domestic stock market index. This beta is calculated by relating the covariance of the stock return and the market return to the variance of the market return. The specific or individual risk (the so-called alpha) of the firm is defined as the stock’s return minus the beta times this return. To arrive at the abnormal return of firm i on day t, we subtract the alpha and beta times the stock market return from the individual stock’s return. As such, this approach is in line with the suggestion of Brown and Warner [21], see also MacKinlay [18]. We first calculate the return of the firm’s stock in the so-called estimation window, which is a period of time that predates the event. The event in our case is the reserve revision. These returns are the normal or expected returns. In the so-called event window, which is a period of time surrounding the event date (day 0; the day at which the new information becomes available), we take the difference between the actual returns and the expected returns. These return differences are the abnormal returns. We average these returns for all events and this average is the average abnormal return (AAR) for that particular day in the event window. We test whether or not the average abnormal returns are significantly different from zero. If so, we conclude that the event can be associated with a significant stock market response. We will use both parametric and non-parametric tests to find out whether there are significant abnormal returns in the event window. As the parametric test, we use the well-established Student t-test [29]. For the non-parametric test, we use the Wilcoxon Signed Rank test [29]. This test does account for the sign of the difference as well as for the size of the differences between pairs. For the pairs, the test investigates the difference in the medians. As the event day (day 0) we define that day on which the news about the P90 revision becomes available to the market. We use an
Table 1 Characteristics of the data sample (100 revisions). Country
#
Year
#
Canada US UK Australia Russia Norway South-Korea Netherlands Brazil, France, Italy Austria, Malaysia, New-Zealand, Portugal, Spain, Switzerland
19 18 16 10 7 6 5 4 3
2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000
9 10 14 12 15 13 20 5 1 0 1
Upward revisions Downward revisions
72 28
1
estimation window of 195 trading days to estimate the normal or expected returns: [200; 6]; the event window investigates the returns from day [-5] to day [þ5] [18]. So, the event window is [5; 5]. Apart from investigating average abnormal returns of our events, i.e. the reserve revisions, we also investigate the cumulative average abnormal return (CAAR). This CAAR calculates for a particular multiday period the response of the stock market. The CAAR of period [t-x, t] is the sum of the average abnormal returns from day [t-x] up to and including day t [21]. We will test the hypothesis that a revision of the reserves does significantly impact on the stock market return of the firm that announces this revision. The null hypothesis is that there is no significant impact. 2.2. Data We rely on LexisNexis for news items about changes in the estimations of the reserves of energy firms. We require that the firms have a listing on the stock exchange, that the stock is traded, that there are no cofounding effects (that is, at or around the same time of the revision, no other material news regarding the firm arrives at the market), and that the revision is in the period 2000e2010. As such, we end up with 100 revisions (see Appendix E for an overview of the events). Table 1 gives the key characteristics of our sample. It appears that there were 40 revisions in the period 2000e2005 and 60 in the period 2006e2010. Furthermore, 63 revisions were with energy firms from four countries (Australia, Canada, the US, and the UK). There were 72 upward revisions and 28 downward revisions. We use Datastream for information about stock prices and domestic market indices. Table 2 gives the descriptive statistics of the returns in the estimation window according to the market and risk adjusted returns model. The average return of the firm’s stock in the estimation window is .01% and this return is not significantly different from zero.
Table 2 Descriptive statistics of the returns. Mean
0.0001
Median Standard deviation Minimum Maximum Skewness Kurtosis Jarque-Bera
0.0001 0.0310 0.0818 0.1351 0.35 3.56 4.17
B. Scholtens, R. Wagenaar / Energy 36 (2011) 3541e3546
3. Results
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Table 4 Cumulative average abnormal returns in the event window.
In this section, we report the results. We first give the main results and then go into the robustness and sensitivity analysis. With respect to robustness, we will estimate the returns on the basis of alternative models. As to the sensitivity of our findings, we will compare upward and downward revisions, country origin, time period, and small and large revisions. Table 3 gives the average abnormal returns in the event window. It shows that on the event day (day 0) the average abnormal returns for the sample as a whole is 0.84% and statistically significant. The AAR of positive revisions is 1.60% and that of negative revisions is 1.53%. The AAR with positive revisions is marginally positive and significant in the parametric test for significance for day 1, but turns into the negative afterwards. The AARs with negative revisions are highly significant on day 1 and day 2 according to the parametric test, but not with the non-parametric test. During the event window, the abnormal returns remain negative. Table 4 provides the cumulated average abnormal returns (CAARs) for several subsets in the event window. For the sample as a whole, there is a significant and negative response in the full event window and for the period since the event. The CAAR of upward revisions is positive for most windows; the CAAR of downward revisions is negative and statistically significant for most windows. On the basis of Tables 3 and 4, we must reject the null hypothesis of no significant impact of reserve revisions on firm value. Therefore, we can conclude that revisions of P1 reserves have a significant impact on the return of the energy firm. This conclusion is in line with Spear [17] who investigated changes in proven reserves with US firms in the mid 1980s. We test the robustness of our model by investigating the AARs and CAARs with other types of models as well, namely the mean and the market adjusted returns model [19,21]. With the mean returns model, the estimated return is the simple mean return of all returns in the estimation window (so both the alpha and the beta are 0). With the market adjusted model, the alpha is set at 0 and the beta is 1. For brevity sake, we only provide the conclusions, the results are available upon request with the contacting author. We find that the results of this test do not differ from those of the main model: the AARs and CAARs are of the same order of magnitude and we also find that on the event day the positive revisions yield a significant positive AAR and the negative revisions yield a significant negative AAR. Furthermore, it appears that the negative response to downward revisions lasts for at least four days with the other two models as well and this response is significant for days 0, 1 and 2 with all models used. Therefore, we conclude that our results are robust to the choice of the model that is used to arrive at the expected returns.
Period
All revisions (N ¼ 100)
Upward revisions (N ¼ 72)
Downward revisions (N ¼ 28)
CAAR
p-value
CAAR
p-value
CAAR
p-value
[-5,5] [-5;1] [-5,0] [0,5] [1,5]
.0143 .0022 .0063 .0121 .0205
.0000 .4869 .0462 .0002 .0000
.0074 .0006 .0166 .0068 .0092
.0857 .8952 .0002 .1120 .0325
.0760 .0128 .0281 .0632 .0479
.0000 .0000 .0000 .0000 .0000
For sensitivity purposes, we did several tests regarding subgroups in our sample. First, we compared the responses regarding positive revisions (upward revisions) with those on negative (downward) revisions (see Appendix A). The reason for this particular analysis is that several studies [23e28] have established that ‘bad news’ in energy markets has much more impact than ‘good news’. Kahneman and Tversky [22] provide the theoretical foundations for this asymmetry. As to upward and downward reserve revisions, it turns out that the differences between the two responses were significantly different on day 0, 1 and 2 at the 1% confidence level (see Table A.1). Furthermore, it appears that the CAARs between upward and downward revisions are significantly different (see Table A.2). This confirms and strengthens the previous findings. These results are consistent with those reported by Lee et al. [23], Ferderer [24] and Sadorsky [25], who find that oil price and oil price volatility shocks exhibit asymmetric effects on production. Thus, our results suggest that the asymmetry in the response to ‘good’ and ‘bad’ news is applicable to upward and downward energy reserve revisions as well. Second, we look into countries as we are interested whether there are international differences regarding the response to reserve revisions. To this extent, we combined the events in Australia, Canada, the UK and the US and relate them to the events elsewhere (see Appendix B). We find that the response in these four countries significantly differs from that elsewhere on the event day. After the event the stock market’s response in the four countries to an upward revision is significantly different from that elsewhere until day 4. In case of downward revisions it is not significant on day 2 and significantly different for the other days (see Table B.1). For the cumulated returns, we find that the response to downward revisions is significantly different after the event in the four countries. More specifically, in Australia, Canada, the UK and the US, the market response is less pronounced than elsewhere (see Table B.2 Appendix). This finding might be related to the international differences in legal system and market development [30,31].
Table 3 Average abnormal returns in the event window. Day
5 4 3 2 1 0 1 2 3 4 5
All revisions (N ¼ 100)
Upward revisions (N ¼ 72)
Downward revisions (N ¼ 28)
AAR
p-value (par)
p-value (non par)
AAR
p-value (par)
p-value (non par)
AAR
p-value (par)
p-value (non par)
.0061 .0099 .0060 .0024 .0025 .0084 .0093 .0014 .0087 .0056 .0044
.0519 .0018 .0546 .4378 .4295 .0078 .0035 .6540 .0064 .0762 .1620
.2550 .1830 .7670 .3860 .8660 .0450 .0850 .3660 .3770 .2940 .3960
.0021 .0116 .0099 .0017 .0027 .0160 .0033 .0010 .0100 .0031 .0061
.3103 .0037 .0108 .3442 .2643 .0001 .2209 .4032 .0101 .2363 .0766
.4320 .5330 .3840 .5480 .9110 .0000 .9280 .7750 .4940 .0310 .7750
.0188 .0051 .0015 .0026 .0019 .0153 .0234 .0170 .0040 .0056 .0020
.0000 .1147 .3579 .2693 .3246 .0002 .0000 .0001 .1745 .0964 .3165
.0720 .3390 .8020 .4390 .8380 .0760 .2190 .1010 .3990 .6690 .9460
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La Porta et al. [30] argue that especially in common law countries, the legal system protects investors and offers an incentive to firms to provide accurate and reliable information. Then, market participants will have less uncertainty regarding news from firms. As a result, the response to unexpected news may be smaller in common law countries. Third is that we investigate the response in different sub periods (see Appendix C). In many cases, it appears that the response in the period 2000e2005 is significantly stronger than that in the period 2006e2010. This can best be seen by looking into the cumulated abnormal returns (Table C.2). We have the impression that this result can be related to the recent turmoil in the energy markets (see also [8]). Fourth and last is that we compare the 40% largest reserve revisions with the 40% smallest ones (see Appendix D). We do not compare the top-50 with the bottom-50 (ranking on the basis of size) as the difference between revisions around the mean is relatively small. Instead, we skip the median 20% revisions. The result is that we lose 20% of the observations. As expected, we find that in particular for negative revisions, there is a significant difference between small and large revisions (see Table D.1). In the case of cumulated abnormal returns, we find that the difference between small and large revisions is very clear for both positive and negative revisions (see Table D.2). This result can be related to the difference in the materiality between large and small reserve revisions.
4. Conclusion We investigate the stock market response regarding news about 100 P90 reserve revisions for international energy companies during 2000e2010. We find that upward revisions result in an average increase of about 1.60% of the energy firm’s market value of equity on the event day. Over a period of six days, the increase is 0.68% and not statistically significant. Downward revisions result in a decrease of about 1.53%. Here, over a period of six days, the change is 4.79% and highly significant. The negative response with respect to downward revisions persists for about a week. The differential between the valuation of positive and negative revisions appears to be statistically significant. This finding is in line with the literature on asymmetries regarding the response to ‘good’ and ‘bad’ news. We also find significant differences between the market valuation of reserve revisions in Australia, Canada, the UK and the US vis-à-vis those elsewhere; those in the former countries appear to be significantly smaller. This may be related to the differences in legal systems among the countries in the sample. In the common law countries, unexpected news is usually accompanied by less uncertainty and, therefore, will result in a less pronounced response. Furthermore, the response to revisions in the period 2000e2005 is stronger than that to reserve revisions in the period 2006e2010. We assume that this is the result of the turmoil in the (energy) markets in the latter period. The response to large revisions is much stronger than that to small revisions. This straightforward result can be related to the materiality of large versus small revisions. Our findings are robust to the modeling of expected stock market returns. Our findings show that technical revisions of proven reserves do impact on the valuation of energy firms. These reserves are a basis for future earnings and, hence, reserve revisions impact on the value of these earnings. We establish that there is an asymmetric response between upward and downward revisions. Especially in the case of downward revisions, the market value of the firm significantly drops. Therefore, it is of the utmost importance for the energy firms to provide accurate and robust estimations of their energy reserves.
Appendix A. Upward versus downward revisions
Table A.1 Day
5 4 3 2 1 0 1 2 3 4 5
Upward revisions (N ¼ 72)
Downward revisions (N ¼ 28)
Differential (upward downward)
AAR
p-value
AAR
p-value
differential
p-value
.0021 .0116 .0099 .0017 .0027 .0160 .0033 .0010 .0100 .0031 .0061
.3103 .0037 .0108 .3442 .2643 .0001 .2209 .4032 .0101 .2363 .0766
.0188 .0051 .0015 .0026 .0019 .0153 .0234 .0170 .0040 .0056 .0020
.0000 .1147 .3579 .2693 .3246 .0002 .0000 .0001 .1745 .0964 .3165
.0167 .0065 .0114 .0009 .0008 .0313 .0201 .0180 .0060 .0025 .0081
.0002 .1283 .0084 .8323 .8507 .0000 .0000 .0000 .1600 .5566 .0589
Table A.2 Day
[-5;5] [-5;-1] [-5;0] [0;5] [1;5]
Upward revisions
Downward revisions
Differential (upward downward)
CAAR
p-value
CAAR
p-value
differential
p- value
.0074 .0006 .0166 .0068 .0092
.0857 .8952 .0002 .1120 .0325
.0760 .0128 .0281 .0632 .0479
.0000 .0000 .0000 .0000 .0000
.0834 .0134 .0447 .0700 .0387
.0000 .0002 .0000 .0000 .0000
Appendix B. International differences Table B.1 Day
2 1 0 1 2 3 4 5
Australia, Canada, UK & US
Rest of the world
Australia, Canada, UK & US vs. Rest of the world
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
AAR
AAR
AAR
AAR
Positive (p-value)
Negative (p-value)
.0043 .0031 .0209 .0087 .0079 .0080 .0025 .0034
.0006 .0059 .0136 .0281 .0165 .0018 .0014 .0109
.0078 .0025 .0156 .0131 .0092 .0111 .0007 .0029
.0105 .0078 .0196 .0123 .0178 .0093 .0225 .0202
.0000 .3998 .0075 .0000 .0000 .0761 .0734 .4186
.0001 .0000 .0172 .0000 .3270 .0043 .0000 .0000
Table B.2 Period
[-5; 5] [-5;-1] [-5; 0] [0; 5] [1; 5]
Australia, Canada, UK & US
Rest of the world
Australia, Canada, UK & US vs. Rest of the world
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
CAAR
CAAR
CAAR
CAAR
Positive (p-value)
Negative (p-value)
.0034 .0031 .0209 .0130 .0079
.0109 .0059 .0136 .0479 .0343
.0029 .0025 .0156 .0118 .0037
.0202 .0078 .0196 .1016 .0821
.4186 .3998 .0075 .2973 .0275
.0000 .0000 .0172 .0000 .0000
B. Scholtens, R. Wagenaar / Energy 36 (2011) 3541e3546
Appendix C. 2000e2005 versus 2006e2010
3545
Appendix E. Overview of the reserve revisions (events)
Table C.1 Day
2 1 0 1 2 3 4 5
2000e2005
2006e2010
2000e2005 vs. 2006 e2010
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
AAR
AAR
AAR
AAR
Positive (p-value)
Negative (p-value)
.0048 .0030 .0163 .0063 .0007 .0207 .0009 .0036
.0033 .0016 .0182 .0275 .0199 .0062 .0092 .0047
.0056 .0049 .0159 .0002 .0015 .0044 .0041 .0040
.0047 .0038 .0023 .0220 .0082 .0065 .0155 .0097
.0000 .0000 .3634 .0000 .2590 .0000 .0000 .3730
.3665 .3066 .0002 .1016 .0000 .4712 .0724 .0006
Table C.2 Period
2000e2005
[-5; 5] [-5;-1] [-5; 0] [0; 5] [1; 5]
2006e2010
2000e2005 vs. 2006 e2010
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
CAAR
CAAR
CAAR
CAAR
Positive (p-value)
Negative (p-value)
.0036 .0030 .0163 .0054 .0217
.0047 .0016 .0182 .0857 .0675
.0040 .0049 .0159 .0132 .0028
.0097 .0038 .0023 .0284 .0260
.3730 .0000 .3634 .0000 .0000
.0006 .3066 .0002 .0000 .0000
Appendix D. Large versus small revisions
Table D.1 Day
2 1 0 1 2 3 4 5
Small revisions (N ¼ smallest 40%)
Large revisions (N ¼ largest 40%)
Large versus Small
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
AAR
AAR
AAR
AAR
Positive (p-value)
Negative (p-value)
.0129 .0011 .0149 .0113 .0048 .0067 .0035 .0074
.0066 .0009 .0093 .0180 .0039 .0059 .0016 .0117
.0177 .0012 .0169 .0108 .0043 .0027 .0110 .0057
.0009 .0037 .0202 .0233 .0281 .0076 .0300 .0098
.0001 .4932 .3977 .0029 .4773 .3057 .1709 .4154
.0000 .0084 .0000 .0000 .0000 .0704 .0000 .0000
Table D.2 Period
[-5; 5] [-5;-1] [-5; 0] [0; 5] [1; 5]
Small revisions (N ¼ smallest 40%)
Large revisions (N ¼ largest 40%)
Large versus Small
Positive revisions
Negative revisions
Positive revisions
Negative revisions
Significance of the differences
CAAR
CAAR
CAAR
CAAR
Positive (p-value)
Negative (p-value)
.0219 .0275 .0126 .0056 .0093
.0019 .0012 .0081 .0007 .0100
.0387 .0146 .0316 .0241 .0071
.1230 .0041 .0243 .1190 .0988
.0000 .0000 .0000 .0099 .0188
.0000 .0070 .0000 .0000 .0000
#
Event date
Firm
Country
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
26-12-2000 9-10-2001 26-11-2002 26-2-2003 26-2-2003 8-7-2003 14-7-2003 9-1-2004 16-1-2004 28-1-2004 2-2-2004 5-2-2004 10-2-2004 17-2-2004 20-2-2004 18-3-2004 18-3-2004 15-4-2004 19-4-2004 18-5-2004 19-5-2004 19-5-2004 29-6-2004 29-6-2004 27-7-2004 17-9-2004 17-11-2004 7-1-2005 17-1-2005 3-2-2005 16-2-2005 31-3-2005 18-7-2005 17-8-2005 20-9-2005 2-10-2005 13-10-2005 1-11-2005 23-11-2005 6-12-2005 26-1-2006 29-1-2006 21-2-2006 5-5-2006 14-5-2006 5-6-2006 5-6-2006 5-6-2006 5-6-2006 5-6-2006 23-8-2006 19-10-2006 16-11-2006 16-11-2006 24-11-2006 5-3-2007 31-5-2007 31-5-2007 31-5-2007 31-5-2007 31-5-2007 31-5-2007 12-6-2007 27-9-2007 22-11-2007 22-11-2007 18-12-2007 1-1-2008 26-1-2008 5-2-2008 7-2-2008
Petroz oil Statoil Murphy Oil Marathon Oil Corp. Hardman Resources Ltd BP Beach petroleum Ltd. Shell Petrobras Redwood Energy Ltd. Nexen Murphy Oil American Forest El Paso Vintage Petroleum Inc. Norsk Hydro BP Yukos Nelson Resources Ltd Cairn Energy Petro Canada Baytex Energy Trust BP Norsk Hydro Arena Resources Inc. Yukos Yukos ConocoPhillip Find Energy Ltd. Shell Santos ltd. Toreador Resources Cairn Energy Cano Petroleum Cairn Energy Canada Southern Petroleum Ltd. Chevron Eni Group Apex Resources Group Inc Devon Energy Repsol Petro- Canada ConocoPhillips Australian Worldwide Exploration Ltd. Cairn Energy Exxon Mobile Corp. Petro- Canada Chevron Murphy Oil Norsk Hydro ROC Oil Co Ltd. Canada Southern Petroleum Ltd. Husky Energy Woodside Petroleum AED oil Lukoil Rosneft Kumho Petrochemical Hyundai Corp. Daewoo GS Caltex Korea Gas Corp BP Toreador Resources Australian Worldwide Exploration Ltd. New-Zealand Oil and Gas DNO ASA Cairn Energy ROC Oil Co Ltd. Transglobe Energy Corp. Petrobras
Malaysia Norway USA Canada Australia UK Australia Netherlands Brazil Canada Canada USA USA USA USA Norway UK Russia Canada UK Canada Canada UK Norway USA Russia Russia USA Canada Netherlands Australia France UK USA UK Canada USA Italy USA UK Spain Canada USA Australia UK USA Canada USA USA Norway UK Canada Canada Australia Australia Russia Russia Korea Korea Korea Korea Korea UK France Australia New-Zealand Norway UK UK USA Brazil
(continued on next page)
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(continued ) #
Event date
Firm
Country
72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
7-2-2008 7-2-2008 7-2-2008 3-3-2008 1-4-2008 14-4-2008 27-6-2008 17-7-2008 7-8-2008 7-8-2008 7-10-2008 18-11-2008 30-12-2008 16-2-2009 25-2-2009 8-3-2009 12-3-2009 1-6-2009 29-8-2009 2-9-2009 8-10-2009 26-10-2009 13-12-2009 14-1-2010 29-1-2010 1-2-2010 9-2-2010 10-2-2010 17-2-2010
BG Group Galp Energia West Siberian Resources Ltd Pacific Rubiales Eni Group Gastar Explorations Ltd. Shell Dejour Enterprises Ltd Shell OMV BP Manas Petroleum BPZ Resources Bankers Petroleum Pan-Orient Energy Corp. Austral Pacific Energy Ltd. 3D Oil Stuart Petroleum Ltd. Gulf Keystone Petroleum OGX Nordic Oil and Gas Ltd BPZ Resources Statoil Gulf Keystone Petroleum Transglobe Energy Corp. Toreador Resources Alliance Oil Company Ltd Mediterranean Oil & Gas Plc Marathon Oil Corp.
UK Portugal Russia Canada Italy Canada Netherlands Canada Netherlands Austria UK Switzerland USA Canada Canada Australia Australia Australia UK Brazil Canada USA Norway UK USA France Russia Italy Canada
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