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Shorting Oil, Hedging Tesla

Discussion in 'TSLA Investor Discussions' started by jhm, Mar 15, 2016.

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  1. jhm

    jhm Well-Known Member

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    Thanks! I am for such a degree of simplicity that it forces people to recognize, "Yep, that looks like where the data are headed."

    Hmm, I'll need to think more about how to boil oil demand and EVs down to the most basic elements and properly representing the uncertainty. For a long time, I've convinced myself that demand peaks when new EV sales reach 20% to 30% market share. But doing a better job modeling the volatility of both oil demand growth and EV adoption could give us a better appreciation of just how much latitude there is in the timing of all this.
     
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  2. jhm

    jhm Well-Known Member

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    I want to apply one more variation to the China forecasts. In scenario generation, it is a common practice to use one model or forecast for the mean structure and then build out an error structure on than mean forecast. What this comes down to is that I want to start with Dr Holland's prediction of 7.5% in 2019 and 50% in 2025. I want to take that as a given, as a hypothesis. I literally connect the dots on the logit scale to interpolate from these two points. This is the assumed mean forecast. Then I assume that annual standard deviation (on the logit scale) is 20%, which I derive empirically from the historical data points. So I assume an error structure about the mean that is a random walk. So in the chart below, I provide this predictive envelop along with Dr Holland's (DMH) interpolated scenario.

    China NEV DMH Logistic.png
    China NEV DMH Log Logistic.png

    So we see that this scenario envelop is substantially more narrow than the predictive envelope I built based solely on historical observations (JHM). This is because the JHM envelop includes the uncertainty about the mean growth rate. Indeed on the logit scale the mean is 48.39% with a standard error of 10.09% which is in addition to the volatility of 20.19%. So that is a fair amount of noise to signal. That is good forecasting. But in scenario generation we are allowed to create scenarios to that do no represent all the uncertainty. So one way to think about the DMH scenarios is that under the hypothesis that Dr Maximilian Holland has nailed the mean path, random paths are likely to remain within the envelop 90% of the time. So think of it more like a hypothesis test with the mean path as the null hypothesis.

    So this does demonstrate the value of both kinds of modeling approaches. Dr Holland has done the difficult work of assessing the feasibility of his prediction. My predictive envelope completely includes the Holland's scenario envelope. So that suggest that his approach is entirely consistent with the historical observations and of straightforward interpretation of that trend. This is what good detailed modeling should do. Had Holland's scenario drifted outside my envelope, I would have become concerned that he is projecting things that have little basis in recent history. For example, BNEF is claiming that EV penetration (globally) will only be about 30% by 2030. This is outside of my predictive envelope. Not only is it pessimistic about EV adoption, it is improbable too. Had they predicted 50% by 2030 instead, then I'd say that, while is pessimistic, I do not yet have sufficient data to rule it out as improbably pessimistic.

    Simply put, I can look at Holland's prediction as say, "yep, that looks like where the data is headed." But looking at BNEF, I shake my head think, "No, this opinion is at odds with the historical trend. The observed data are clearly not headed that far in that direction." Moreover, Hollands scenario is incompatible with BNEF. There is no random path that can remain probabilistically close to both forecasts. I.E., one of them is substantially wrong about the future.

    Notice also that my JHM-Mid path is within the envelope of DMH. So my mean structure is not at this point in time a statistically significant departure from Holland's mean structure. My guess is that the way Holland is approaching this is first to observe where the trend is headed, and then look a detailed data to see if there is some material reason to shift the forecast up or down from that basic trend. So long as the battery, auto and policy makers are making commitments that come close to realizing the projected growth rate, there is little reason to bend that projection one way or the other. Intellectually this is anchoring the analysis on recent trends, while being ware of issue that may force trends to change. I suspect that BNEF is more skeptical of historical trend and seeks to anchor a forecast on something else. But when you look more carefully there are often compelling forces that have shaped historic trends, and these forces are dismissed at intellectual peril. For example, consider all the investments and commitments that EV producer and EV consumers have made just to bring about recent history. These are long term commitments. These are things like building a Gigafactory or spending $1000 just to add a charger to your garage. Those who make these commitments are not stupid, and they reasonably expect them to pay off in the long run. So to suggest that the growth trajectory will slow down in some way not yet manifesting in recent history is to suggest that all these investments were ill-considered and will not payoff as expected. The auto industry largely works on a 6-year product development cycle. Of course, not all new products are going to be commercial successes, but the time scale is such there ought to be substantial momentum to the whole industry. The industry can't radically speed up relative to recent history, and it can afford to substantially slow down either. If you take this kind of investment momentum seriously, then you have to accept that trends will largely persist. They can bend a little, they can have short-term hiccups, but they have serious momentum. It is like watching a train try to slow down or accelerate. There is so much momentum at play. There is only so much braking or accelerating that can happen over a certain interval of time. You can predict the train wreck because you know the train can't slow down fast enough to avoid collision. This is why trends are so important. It is the same sort of momentum that makes it so hard for the world to actually reduce carbon emissions growth. It takes huge trillion dollar investments just to halt demand growth for fossil fuels. And the nature of investments is that they do grow exponentially where the opportunity for high growth rates exist. This is exactly what locks EVs into a logistic growth curve. The level of investment grows with the size of the market, fueling exponential growth slowing down only as the market becomes saturated.

    Since I digress here, let me point out one more thing. Policy accommodation easily follows the expansion of an industry. Some energy modelers are inclined to base their energy forecast primarily on policy commitments. But those policy commitments are easily a lagging indicator rather than a leading indicator. For example, EV incentives are likely to decline as EVs become more competitive in the market. Does that mean EV sales will decline? No so fast. If they are declining because it is determined that the are not longer needed, because they have outlived their usefulness to society, then this is policy lagging success. While there can be short-term policy effects like pulling forward sales before a subsidy expires, there need not be any durable impact. For another example, some countries are looking to ban new ICE sales by a certain date. This too is lagging indicator. Few politicians would venture such a policy unless EVs already looked thoroughly capable of replacing all ICE sales by that certain date. For example, no one is legislating that by a certain date all vehicles sold must be hydrogen fuel cell powered. That would be crazy talk because the fuel cell car industry no where looks capable of fulfilling such a mandate. So policy makers are in fact looking at what the EV industry has been doing in recent history and extrapolate from there what may be politically feasible policy. This is very much politicians lagging industry.

    So with China, there is all this concern that political support for NEVs might wane. But why should it. To the extent that EVs become economically competitive apart from subsidies and mandates, we can accept that the government may pivot to other areas where incentives may have a bigger impact. This is just the training wheels coming off. But as China recognizes that they sit on an enormous opportunity to export EVs to other countries, we have got to be expecting that the government will solidly push in that direction. So yes, policy matters, but policy is just part of the bigger process. It will participate in market opportunities as they unfold. Policy is largely an endogenous variable. So policy is as much part of the momentum as it is a catalyst for change. So I am not at all worried that policy support will wane and cause decline in EV adoptions. If anything I believe that policy will become more assertive as EVs advance. Why wouldn't China want to be the world's largest and most important exporter of EVs and batteries?

    So momentum matters. And China looks to be EV dominant by 2025.
     
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  3. jhm

    jhm Well-Known Member

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    China's teapots cut losses
    More reporting on Chinese independent refiners. In some cases refiners are forced to cut production out of concern for local air quality. This of course is in addition to very poor economics. Teapots are losing about $8 on every barrel of oil produced.

    Air pollution issues are not going away. It sounds like China simply has too much refining capacity. As oil demand plateaus and declines, it won't make a whole lot of sense to just keep polluting local air so that refiners can sell into export markets. So China has put quotas on exports. I wonder if it should also consider putting a pollution tax on exports too. The point is there is a huge public cost for excess pollution. Exporters are clearly exposing the public to more pollution than is necessary to run China's domestic economy.
     
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  4. mblakele

    mblakele pre-jackpot member

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    The lessons of Bahrain, a state that tried to wean itself off oil

    I recommend reading the whole article, but here are some excerpts.

    [...]

    All six members of the Gulf Co-operation Council (GCC) have lofty plans to wean their economies off oil. Bahrain is in many ways a forerunner of this effort. It built a financial sector back in the 1980s. More recently it passed a bankruptcy law, allowed 100% foreign ownership of firms and introduced flexible visas that allow some migrants to freelance. “Everything those guys are doing now, we tried already,” says Ausamah al-Absi, who heads the labour regulator. The results have been mixed—with lessons for Bahrain’s neighbours.

    Compared with other Gulf states, the job market in Bahrain looks vibrant. Two-thirds of citizens work in the private sector, compared with 55% in Saudi Arabia and 10% in Kuwait. Unemployment is 4%. In Saudi Arabia, where joblessness is three times higher, the government is raising work-permit fees to drive out migrants. In Bahrain such fees are low. Most migrants toil in low-wage jobs that locals spurn. Bahrainis do not want to lay bricks.

    [...]

    Yet the fiscal picture is bleak. Oil provides about 70% of government revenue—and there is not enough of it. Last year’s deficit was a yawning 12% of gdp. Wealthier Gulf countries had to offer a $10bn bail-out. Bahrain trimmed subsidies for power and water consumption in 2016. But more reforms planned for this year were postponed for fear they would trigger unrest.

    [...]​
     
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  5. TheTalkingMule

    TheTalkingMule Distributed Energy Enthusiast

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    The idea that Saudi Arabia can ever "transition off oil" was thrown out the window once MBS kidnapped, tortured and robbed anyone in the country that wasn't 100% loyal to him. Show me any rational global operation who would ever move to set up shop there. I have pretty good visibility into the global movements of Fortune 100 and even some big PE players and no one outside of energy is moving toward the region, let alone into Saudi Arabia where you can be kidnapped and your wife would be required to STFU at all times.

    A $10B royal family subsidy to build a financial center went absolutely nowhere. If you can't entice banks with billions of free dollars and no rules whatsoever, you're finished. Their entire population is super young and unskilled in the jobs needed for a diversified economy. 2 years from now SA oil/downstream revenues will fall well below their budget(if it isn't already), and chaos will reign until their uprising/civil war is settled. Any other possible path has been removed over the last 2 years. Good times!
     
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  6. renim

    renim Active Member

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    >JHM

    for the audience, these curves are good for forecasting the behavior of the transition, but not the end point. That is an input.
    So while downloading displaced, CDs displace tapes, which displaced LP, it wasn't 100% displacement before the next technology started to scale out.

    we don't know that electric vehicle will go to 100%, that is our assumption. We particularly don't know that plug in electric vehicle will succeed over (say wireless electric vehicle)

    I really don't think hydrogen electric vehicle will be viable anywhere that H2 is derived from methane, buts that is not global. In China hydrogen is cheaper than methane, perhaps in China H2 may become relevant (at a municipal bus level anyway)

    looking forward, the solid oxide fuel cell that Nissan uses ethanol, methane, probably even kitchen scraps if someone fed it that.
    upload_2019-5-27_13-12-46.png


    to be blunt, I don't see the grid surviving 20years in Queensland Australia in its current form, I expect grid defection to occur at scale around 2028 in Qld (expiry feed in tariff). at that point at least one market will be primed for vehicle that runs on rum instead of electrons.
     
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  7. jhm

    jhm Well-Known Member

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    Just to be clear, I am not at all saying that the trajectory cannot be bent in some other direction, but that comes down to some sort of black swan type of emergent issue that is presently not in play in the recent history that the forecast is based upon. We can certainly imagine alternative scenarios. The leading one in my mind is that full autonomy comes much sooner than say 2025. We really have not seen in recent history how autonomy can change the automotive market, but it clearly would have the potential to radically revise the value of private ownership of autos. So autonomy is not in my model, but could radically bend the curve. Hydrogen, on they other hand, has been in play in the auto market for many years. It just does not compete well. So it is really hard to envision a scenario where hydrogen begins to catch up with EVs to surpass them by 2030. Of course, such competition would effectively kill of ICE even faster. So try to map out how fast HFCEVs would have to grow on an annual basis to catch up with EVs. So again, I'm not saying such disruptions cannot happen, but simply such disruptions have low probability and would be a radical departure from what we have seen to date.

    Another way to look at this is the this forecast is based on all plug-in vehicles. My strong suspicion is that successful hydrogen vehicles will actually be plug in hybrids, hydrogen FC+battery. Batteries will be a cheap way to give FCEVs acceleration power and regenerative braking. The FC is ideally suited as a range extender that functions mostly at an optimal output level. Nikola is doing this with their hydrogen trucks. So one may as well be able to charge the battery from the grid when convenient, and that option would also help mitigate limitations in hydrogen fueling station infrastructure. So there you go, you've got a fancy plug-in vehicle, and that falls into the bucket I'm modeling.
     
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  8. jhm

    jhm Well-Known Member

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    Is The Oil Glut Coming Back? | OilPrice.com


    Let’s get back to our original premise how a collapse in the oil market can hurt the share price of Tesla. Are we risking a glut again? Well, it may be more than a glut.


    IEA was predicting a 1.3 mb/d increase in oil demand over last year. Problem is, demand so far this year is only up 640 kb/d y/y. So the forecasting geniuses at IEA are off by a whopping 660 kb/d.


    To connect this back to EVs (which these savants are challenged to get right), this gap is like a displacement of about 5.5 million ICE vehicles. Well, in 2018, about 2.1 million EVs were sold. Does this explain the 5.5 million vehicle gap? Who says a 1 EV sale only displaces 1 ICE sale? Maybe we have been making a bad assumption here. In 2017 about 96 million motor vehicles were sold. It was supposed to grow by about 3%, but fell by about 0.5% instead. So the new vehicle market was about 3.4 million short of expected growth in 2018. This obviously aggravates the auto industry, and frustrated investors are inclined to vent their anger of Tesla, which boasted record growth. But netting 2.1 from a shortfall of 3.4 million is actually a missed 5.5 million in expected ICE. So this is really not good for the ICE makers of the world.


    Could it be that this shortfall of 5.5 million ICE is also driving the missed 660 kb/d gain in in oil demand? Hmm. The whole idea of displacement is that there are fewer ICE vehicles sold as a result of the entrance of EVs. This does not have to be a 1 to 1 exchange. To be sure there are other factors displacing oil demand as we’ve discussed many times before: battery powered ferries in Scandinavia, stationary batteries replace diesel gensets on tropical islands, etc. So I don’t want to be so cute as to suggest that 2.1 million EVs are displacing 5.5 million. I think that is pushing the ration too far, but a ratio that it somewhat greater than 1 to 1 may in fact be realistic. We have an Osborne effect that at least makes this transitory until EV production can satisfy demand for EVs. Also if high utilization use cases (like high mileage commuters and fleet service) are favoring EVs, that also can increase the ratio. So long as EV demand outpaces EV supply, the impact of EVs on oil demand can be at a multiple greater than 1 to 1 displacement.


    It should be clear that declining ICE sales is the primary way that EVs reduce oil demand. Obviously, other macroeconomic factors can be also at play in a 5.5 million shortfall on ICE growth. But this 5.5M shortfall is problem for oil demand regardless of the causal factors. Does it explain the full 660 kb/d miss in the IEA forecast? No, the IEA forecasters could have made many other mistakes too. But it is clear that they have a huge blind spot when it comes to EVs, solar, wind and stationary batteries all of which can be applying downward pressure to varying degree on oil demand.


    So oil investors too have reason to be frustrated, and they too can vent their anger against Tesla. As long as demand for ICE and oil is threatened and those investors are in pain, Tesla will remain the market whipping boy. These investors are transitioning from “denial” to “anger.” They are in psychological need of an object for their anger. Elon Musk and Tesla fit the bill, and the media are happy to cash in on the rage. I don’t think the beatings will stop until these raging investors fall into a “depression” stage. Tesla is now at a scale where it can inflict material harm on ICE and oil demand. It will be hated and reviled for doing so.


    Does it now make sense to short oil so as to hedge one’s position in Tesla?
     
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  9. TheTalkingMule

    TheTalkingMule Distributed Energy Enthusiast

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    Whoa, is anyone contending that the "growth gap" from 660kb/d to the projected 1.2Mb/d will still be bridged through the end of this year?

    If 2019 ends up with growth below 800kb/d the whole market will implode.
     
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  10. ReddyLeaf

    ReddyLeaf Active Member

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    +1000. Great posts and information! To add to the Osborne effect, younger, more tech savvy people seem to be more interested in Tesla. Perhaps they are delaying automobile purchases until they can afford the lower cost Tesla. Since 2011, we’ve also seen a number of high mileage drivers try to make the 24 KWh Leaf work for 80+ mi commutes, and eventually switch to the longer range Tesla. Low per mile cost vehicles (EV, PHEV, or high mpg hybrids) are best suited to higher mileage driving (taxis, long commutes) in order to reach the TCO cross-over point. While the average Leaf mileage was <40 mi/day, I would expect the longer range EVs will start bringing in the >80 mi/day users, greatly speeding up oil displacement. Add the huge number of electric buses in China, and we’re looking at significant displacement from now on.
     
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  11. Oil4AsphaultOnly

    Oil4AsphaultOnly Active Member

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    I think the missing 3.4million gap is best covered by the "osbourning of the auto industry", where vehicle demand is not meeting expectations as people are all just waiting for more EV's to be available.

    And I forgot, did your model account for the consumption bias, where people who buy EV's are most likely to be the high-mileage consumers? I think you said it did, but I don't remember. If not, then less of the difference needs to be covered by the "osbourning of the auto industry".
     
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  12. ggies07

    ggies07 Supporting Member

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    *waves hand* That would be me. I drive at least 16k miles a year. Also, I know this is a very tiny data point, but my wife who drives an ICE actually uses less gas now because we take my EV everywhere. The only time she drives it is from work and back home now. I'm sure other households are the same that have an EV and an ICE.....could add up to a little bit....
     
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  13. jhm

    jhm Well-Known Member

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    No, I don't think any of my models have tried to do this. The problem is finding data to base the model on. Without clear data, I am disinclined to model a specific feature like that, but I will be quite willing to state how this may impact the direction of potential bias.

    Perhaps when we get some data on the share of EVs used in fleet service, we could pull that out as a special segment. For example, we could model the growth of Tesla Network eventually. We might also know something about the annual mileage of a TN vehicle. If it is say 36k miles, this is 3X the 12k of an average private auto. So a TN vehicle would be worth 3 private EV autos. So this sort of thing could become tractable in the future.
     
  14. jhm

    jhm Well-Known Member

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    So you put about how many miles per year on each car?
     
  15. ggies07

    ggies07 Supporting Member

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    Asked my wife, but she doesn't know off the top of her head and it would take some time to find the paperwork. Like I said, I'm at least 16k a year in an ICE. Since I got my EV at the end of November, so 5 months, I'm already at 13k.
     
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  16. Oil4AsphaultOnly

    Oil4AsphaultOnly Active Member

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    #5156 Oil4AsphaultOnly, May 28, 2019
    Last edited: May 28, 2019
    I did the same thing when I first got my Leaf. Almost all of our local driving was done on the leaf, which skewed the reduction of our gas consumption to 1.5 ICE vehicles displaced by a single BEV.

    displaced about 16k miles per year,
     
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  17. jhm

    jhm Well-Known Member

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    So now I am following up on BNEF battery pack cost prediction. BNEF predicts a pack cost of $94/kWh in 2024. Does this accord to basic statistical analysis? Let's see.
    A Behind the Scenes Take on Lithium-ion Battery Prices | BloombergNEF
    Pack Decline Curve.png





    Pack Experience Curve.png

    So BNEF is getting to their prediction through three steps.
    1) Estimate the experience curve on cumulative battery volume. They get 18% price decline per doubling of volume.
    2) Predict future pack size per vehicle.
    3) Predict future EV sales and compute cumulative pack volume.

    Steps 2 and 3 are opportunities for the analysis to become poorly calibrated and for modeler bias to creep in. I am taking a shorter route.

    1) Estimate experience curve based on cumulative PEVs sold. Pack cost declines 28% per doubling of cumulative PEVs.
    2) Forecast cumulative PEVs to be sold.

    Notice that I don't need to fiddle around with making pack size assumptions, nor is that even appropriate. Cell cost is about 2/3 of total pack cost, but the pack specific costs may appropriately be thought of as one pack as one unit. Also we should expect the capacity per pack to increase as the cost per kWh declines. So my approach will tend to capture that. Another advantage of indexing the learning curve on EVs sold is that is it fundamentally EV sales that will be motivating R&D and scale up investments.

    A critical difference here is that BNEF obtains a learning rate of 18% cost reduction per doubling of kWh volume, but my rate is a reduction of 28% per doubling of cumulative EV sales. So if one were to assume that kWh/EV where to stop growing, you might conclude with BNEF that the pack cost won't come down as fast as my model suggests. So that makes BNEF assumptions for step 2 critical.

    In both modeling cases, though, we need to fight the temptation of thinking that mineral costs set a firm limit to how cheap packs can become. This would only be true if mass and mineral composition of a kWh of capacity were somehow fixed. But with increases in energy density and changes in chemistry, this is simply not true. Part of the experience curve is advancing the chemistry of battery packs finding more dense and low cost options along the way.

    What will slow down the decline of pack costs will the size of the EV market. As EVs saturate the market, they shift to growing a single digit rates, so roughly linear growth. So this make it very hard to keep doubling. Fortunately this is not much of a problem until the 2030s.

    So what about BNEF's 2024 prediction? My model suggest that $100/kWh will be obtained between about 10M to 50M PEVs made (regardless of how long it takes to get there, so my step 2 is not critical.) But assuming my mean logistic forecast in other posts and that the auto market grows about 3% per year, with 95% confidence the $100 threshold will be breached between 2020 and 2023, not as late as 2024. In deed for 2024, I've got a confidence interval from $35 to $78 per kWh. Now as with any predictive statistical model, if conditions fundamentally depart from what has been experienced within the training history, these projections can fail. This is basically the no-black-swans caveat.

    Also in terms of when Peak oil comes, sub-$100/kWh come by 50M cumulative EV sales and oil peaks by about 75M EV sales. So these events seem likely to come just one or two years apart. I still do not see $100 as some magic number when the planets align to make EVs a thing. The fact is every year there is a double digit drop in cost, there will be an increase in EV sales. Moreover, there are many other critical elements to making EVs more powerful and cheaper to build, like improvement in motors, inverters, software control, and more. All of these components also have their own experience curve. So year after year EVs will be increasingly more desirable, more available and more affordable. Singling out the battery pack as having a make or break price risks losing sight of all the many things that advance EV adoption along the way.

    One other little point, at times I've been critical of how BNEF uses a volume weighted average. Tesla appears to be leading the pack. But really this does not matter. Basically, producers that are able to get the cost down lower will tend to grow their sales faster than others. The laggards lose share of volume along the way. Part of what will continue to sustain progress down the experience curve is competition weeding the overpriced packs out of the market. If BNEF were tracking the minimum cost instead of the average cost, we would have more worries about jumps in the technology rather than steady progress to lower prices. So volume weighted averages are just fine by me.
     
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  18. RobStark

    RobStark Well-Known Member

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  19. jhm

    jhm Well-Known Member

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    The Second Machine Age Could Crash Oil Prices | OilPrice.com
    This guy is not too far off. He gets how surprisingly quickly tech can change things. My main concern is that thinks that the timing of the peak is very uncertain and could happen in the second half of the 2020s. So he has not done a sensitivity analysis on how the rate of EV growth impacts the timing of the peak.
     
  20. jhm

    jhm Well-Known Member

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