Throughout the recent process of evolution of the electric car, the main obstacle for its introduction into the market has been the battery. Lithium-ion (Li-ion) batteries were first launched by Sony (NYSE:SNE) for use in electronics about twenty years ago. As of now, they appear to have taken over all options available for the new world in motion. However, apart from my analyses regarding the main determinants of adoption of lithium batteries (especially for electric vehicles), there have been no other contributions to the clarification of this important topic.
Over the last two years or so, the main thrust of my original argument, namely that oil prices, technological development, and resistance to change may determine the final adoption of lithium batteries, has been improved upon and now stands as follows: (i) the effect of oil prices on adoption is measured in terms of annual prices and their volatility in relation to corresponding average values for a given period of time; (ii) the effect of technological development on adoption of Li batteries is considered in terms of both different kinds of Li-ion batteries and beyond (e.g. Li-Sulfur or Li-air batteries); (iii) the effect of resistance to change (also extended to acceptance of change) is analyzed at three levels: Consumers or individuals, companies, and governments; (iv) there are interactions among these determinants of adoption of Li batteries and a feedback mechanism; and (v) the Li supply chain is thought of as demand-supply flows of Li resources, Li batteries and electric vehicles (EVs) which, as shown in a previous article, can be explained as a self-regulating process, a resource constraint, and a self-reinforcing mechanism.
In this article I will review and update my discussion about (i)-(iii) in an attempt to identify the demand and supply fundamentals of lithium in terms of prospects for a comprehensive electrification of the global automotive industry. The paper will close with a brief discussion about Bolivia’s lithium (and other evaporite resources) perspectives. This contribution is based on my recent presentation at the ”Metals for Energy and the Environment” conference organized by Metal-Pages held on June 1-3, 2011 in Las Vegas, USA.
Due to its extension, the article has been divided into three parts. In the first part of this contribution I review and extend my arguments regarding the influence of oil prices on adoption of lithium batteries, including a brief analysis of oil ETFs as possible investment options during the transition of the global automotive industry to electric propulsion.
In other articles, I have argued that not only oil prices but also their volatility (as measured by yearly standard deviations) in relation to average values of both variables for a given period of years may affect adoption of lithium batteries. The definition of an appropriate time period in a previous contribution was the result of the following analysis.
To begin with, this effort was constrained by data availability: Whereas WTI at Cushing provided daily oil prices for the period 01/02/1986 – 12/30/2009, Brent offers such information for the period 05/20/1987 – 12/30/2009 only. Secondly, from 1986 or 1987 up to 1999, oil prices averaged each year no more than 24,53 dollars a barrel (depending on the data utilised), but from 2000 on they started to climb and would never come back to previous figures. However, 1998 was an atypical year since it reflected the lowest values for both complete series. So it appeared reasonable to establish 1998-2009 as the period of analysis for this study.
For the present investigation, the time period was extended to include all the information on daily oil prices available today that permits to build annual time series since 1986 (for WTI) and 1988 (for Brent) up to 2010.
As shown in Table 1 and Figures 1 and 2, on the one hand, yearly average oil prices clearly reflect figures well above their corresponding total averages for the period 1986-2010 (when using WTI data) and the period 1988-2010 (when using Brent data) over the last 7 years, respectively. Note also here that the 2010 figure is the second highest average of the complete series, having only been surpassed by that of 2008, which was the year that registered the maximum daily oil price since the oil crises. On the other, except for one year, 1990, similar results were attained for yearly standard deviations. It is important to emphasize, however, that volatility shows indeed a somewhat different behaviour. As in the case of yearly oil prices, volatility reaches its utmost value in 2008 and the figures for 2007 and 2009 are also very significant in relation to the rest of the years. Nevertheless, unlike yearly average oil prices, yearly standard deviations plunged in 2010 to levels similar to 2004, which is precisely when both yearly average oil prices and volatility started to consistently supersede total averages of both variables for the whole period under consideration. In addition, it is quite noticeable that the standard deviation number attained in 1990 was also much higher than the average volatility, regardless of which data base is utilized.
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Overall, the above results seem to indicate that the average oil prices were less sensitive than their average volatility to the effects of extreme events such as the Gulf War in 1990, as well as the financial crisis and the economic recession that the developed countries faced between 2007 and 2009. Likewise, we need to point to the role of each variable in the adoption of alternative energy technologies in general and of lithium batteries in particular. In this connection, the influence of the oil market on the adoption of lithium batteries would be mostly related to average prices of the fossil fuel, a variable that may only be reinforced by their volatility. However, the variability of oil prices per se would not be sufficient to motivate the world’s most important carmakers to direct their attention towards lithium if, for instance, the average oil prices returned to levels reached prior to 2004. It then follows that the relative stability of oil prices in 2010 probably affected (negatively) to a certain extent the adoption of lithium-ion batteries, but it didn’t put it into question.
At this point, there is a need for reiterating the argument I made in my presentation at the 2010 Lithium Supply and Markets (LS&M) conference, namely that because average oil prices as well as their volatility remained above the corresponding average values for the entire period of analysis: (i) both the trend towards electrification in the global automotive industry and the adoption of advanced lithium–ion batteries to cope with this development remained invariable; and (ii) in spite of the decline of oil prices in 2009 and their low variability in 2010, both major carmakers and battery producers continued investing billions of dollars in the development of different electric vehicles and advanced lithium batteries. I am also in a position to ratify
that both car and battery makers may be placing more emphasis on both yearly oil prices and volatility in relation to total average numbers over a given period of years rather than simply yearly figures of those variables for their decision to invest in the development of electric cars and advanced lithium batteries.
As I have argued before, the transition to electric propulsion in the global car industry may still take a number of years. In the meantime, investors have an opportunity to make money by investing in oil. In this connection, oil ETFs might be an option.
According to a recent article published on the Wall St. Cheat Sheet, there are top 10 ETFs for oil; six for long term investment and four for short. These ETFs are characterized for tracking in one way or another oil prices. With the aid of three charts and a table, I tried to find out which ETF performed better since the beginning of the year. Figures 3 and 4 were used to compare the long-term ETFs, as well as the short-term ones, respectively. Figure 5 shows the evolution of WTI oil prices. Lastly, in Table 2 the Year to Date (YTD) returns as well as the volume of shares traded for all the different oil ETFs are shown.
In general, long-term oil ETFs tracked WTI oil prices reasonably well. However, three clear trends were identified. First, the Pro shares Ultra DJ – AIG Crude Oil ETF (NYSEARCA:UCO) was seen to perform much worse than WTI oil prices when oil prices went down and much better when oil prices went up. Hence it was seen to be the riskiest one even in times of relatively low volatility of oil prices. Nevertheless, on the positive side, this fund is the second most liquid one. Second, throughout the period under consideration, the United States Oil Fund (NYSEARCA:USO) and the i Path S&P GSCI Crude Oil Total Return (NYSEARCA:OIL) followed closely the oil prices and behaved as if they were just one ETF. These are the most liquid and the third most liquid long-term ETFs, respectively. Third, Power Shares DB Oil Fund (NYSEARCA:DBO), United States 12 Month Oil (NYSEARCA:USL) Power Shares DB Crude Oil ETN (NYSEARCA:OLO) also tracked WTI oil prices fairly well but performed always better than USO and OIL. The downside to these three ETFs was that they were much less liquid than USO and OIL. Note, however, that DBO showed the best performance (as measured by YTD returns) of all ETFs and, with approximately 330,000 shares a day, it appears to be getting close to liquidity.
As for the short-term ETFs, they essentially resemble a reverse mirror of WTI prices (and to some extent to long-term ETFS as well) and don´t seem to be an interesting investment option because in all cases their performance was negative. Also, except for SCO, their liquidity (as measured by the approximate number of shares traded a day) was also relatively low.
Based on all the above considerations, my recommendation would be to invest in DBO. This is consistent with a recent article that found that this ETF may indeed be “a better way to gain exposure to crude oil.”
Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.