This lesson will teach you how to take into account the impact of hedging on realized sale prices, and how to set up base, downside, and upside cases. Then we’ll tie together all the revenue assumptions to calculate the total revenue by segment for XTO.
Price Hedging and Revenue by Segment Transcript
In this lesson, we’re going to pick up from where we had left off previously, where we had gone through and established several different scenarios for the price of commodities here, in this case oil, natural gas liquids, and natural gas. We had figured out the price differential between the market prices of these commodities and then what XTO energy can actually realize on a historical basis here.
And then we looked at it on a projected basis and we saw how even if the market price of a commodity is $7.00, due to market forces, expenses, the fact that the number of buyers and sellers may not always equal each other, they may be differences in what they’re asking and expecting, they’re not always going to receive $7.00. They might only receive $6.22 in this example.
So, this takes us to almost the conclusion of the revenue side of XTO, and the final step here is to figure out what they look like, in terms of hedging. Now, again, the purpose of hedging is to make sure that, even if there’s a huge drop in resource prices, they do not experience a huge drop along with those prices, in terms of their revenue.
So, if we look at what happened here, in terms of gas prices. So, 2008 they’re at a relatively high level here, $9.00 per thousand cubic feet. And then in 2009, they suddenly dropped to around $4.00.
So, let’s take a look at what hedging does here. So the realized price is around $8.04 versus $3.67, so still a pretty big difference there. But then after hedging, look at this, it’s $7.81, in 2008, so a bit lower than the $8.04. But, then, in 2009, because they hedged their prices, they’re actually getting $7.13 per thousand cubic feet of natural gas, as opposed to the $3.67 that they would ordinarily receive on the market.
So, this is basically how hedging works. When prices fall to a very low level like that, hedging ensures that they receive a price somewhere above that level. When they’re in somewhat, the middle of the range, to the base case here, there’s not going to be a tremendous difference. Typically, though, you assume that the price is slightly higher than what they would ordinarily receive on the open market.
And, if you look at the historical data, you’ll see why, that this is just the trend, historically. And then in the upside case, so when prices are at a high, so $9.00 or $10.00 per thousand cubic foot of natural gas, then you have a case where the realized price after hedging is going to be less than that. So, in this case, even if it’s $10.00, due to hedging and the fact that they have contracts that are betting against the price of gas going up as well, they may only get $8.00 or $9.00 after the commitments, represented by those contracts, and futures are taken into account here.
So, to figure out how hedging actually works, and how it’s going to effect everything here, we could take a couple of approaches. One approach is to go into their filings, and if you look at the PDF handout that I’ve created, that I’ve called ‘Derivatives’, here, they go into a lot of detail on the different derivative instruments they have. The different natural gas futures, swaps, crude oil futures, and so on. So, they go into the fair value on the assets and liabilities side of this.
They go into the effect, in terms of their cash flow. And if you wanted to, you could hunt through the filing and you could try to estimate how much of their production they actually have hedged. So you could say, for example, OK, 50% of 2010 production is hedged at a certain price per thousand cubic foot equivalent, or priced per barrel of oil. And you could try to project that forward.
The problem with that method is that it’s very, very, very difficult to pull off, because companies frequently change their derivatives, their contracts and their hedging positions, and that is in fact why we even bother to list them on the balance sheet and go into detail, because they change them so frequently that it’s really important to list them as current assets, current liabilities, or sometimes long term assets, long term liabilities, depending on the time period.
But, long story short, is that companies are always changing how their hedging themselves, how much their hedging, the exact percentages. So, in this case, it’s not going to be particularly productive to actually go through, and to figure out everything, in terms of hedging and derivatives, by looking through their 10-K filing here. It’s something we could consider, but it’s just very, very difficult to estimate models.
So, once again, we’re going to go with a somewhat more simplistic approach here that is going to get us very, very close and is going to get us basically the same results, even though it’s a lot easier to calculate and a lot easier to understand here.
So the first thing we’re going to do is look at this on a historical basis, and see what kind of impact hedging has had on these prices. So first off, for natural gas, we’re going to take the average realized sale price after hedging, here. And then we’re going to divide by the sale price before the hedging. In other words, the realized price, what they would ordinarily get based on the market times the price differential based on how much they can actually receive off of these market prices.
So for gas it’s around 95%. Let’s just copy this across and look at it for all five years now. So, for gas, it’s normally in the 100%-200% range. So, hedging is making a huge difference here. If we look at, somewhat, average gas prices in 2006 and 2007, so $7.23 and $6.86, hedging is giving us around 120% of that price, around 20% higher here. In years that were above average, so 2005, 2008, it looks like hedging is giving us around 95-100% of that price, so probably around 90-95% here when we have really high gas prices.
Natural gas liquids. So this one is interesting. It looks like they’ are not really hedging this one at all. The only difference here is in 2008, these rose to a very high level, because oil prices were at an all time high in 2008 over the course of the year. And, it looks like in this case, despite that, they still didn’t really have any hedging in place. They still realized close to the entire price here.
So for natural gas liquids, it’s 100% in four out of these five years, which means that XTO is really not hedging their natural gas liquid production much at all, compared to the gas production and oil production.
On the oil production side, again, we see roughly 90% in years like 2005 and 2008, when we had sudden climbs in oil prices. So, 2005, prices were much lower in the earlier part of the decade here. 2008 they also jumped to a high level, but they’re still realizing around 90%-95% of those prices here. So 89% and 94% in 2008. Now in 2006 and 2007, prices were in around the $70 per barrel range.
And so they realized around 100% of those, so hedging really didn’t have too much of an impact there. Similar to gas, although it looks like they did some more hedging with gas, because it had around 20% impact when prices were in a more standard base line scenario level. And then, of course in 2009, when prices fell dramatically, on both oil and gas, they realized around 200% or close to 200% of those prices.
So, based on this, we could take a couple approaches. We could just do a simple average over these five years and use that to establish it. What I’m going to do instead, though, is go back to the inputs page and to our resource price cases right here, which we already filled in for gas and oil and natural gas liquids. And for the oil and gas hedge price percentages here, I’m going to enter some assumptions for the downside, base, and upside cases.
So for the downside case, I’m going to enter 150% right here. For the base case, I’m going to enter 110%. And then for the upside case I’m going to enter 90%. And again, these are basically following the historical data, almost exactly. The downside case, the 150% is quite a bit lower than these 200% numbers, but 2009 was an unusual year here, so we’re not going to be quite as aggressive with our hedging assumption.
We’re going to just go with 150%, rather than the 200% that they have. The baseline years, 2006 and 2007, around 120% for gas, just over 100% for oil. So, I’m going to say 110% right here. And then for the upside case here, 90%, again, coming from 2005 and 2008 we saw it in the 90%-95% range, so I’m going to be a little bit more conservative and say 90% for the hedging here.
And, again, we’re not going to get into the exact mechanics of these futures contracts, because there’s just not enough detail in the filings, and it’s imprecise anyways, they change their positions all the time. So, it’s best to just look at this in relation to the resource prices themselves. As opposed to going in and trying to estimate this based on individual futures or other types of swaps or derivatives that they have on commodities.
So, now to select this, we’re going to use the same exact OFFSET formula that I have right here where we’re, basically, just setting the start point and then selecting the case, subtracting one, and using that to select the right row.
So we have 110% right here. And now, we want to take a similar approach that we used for the market prices themselves, here at the top, where we filled in the base case, the downside case and upside case here from 2010 – 2014. Which was not completely necessary, but still good to do, just in case we decide to change the model. And we decide to have different prices in every year here. So, I’d like to do the same thing for the hedge prices as a percent of the pre-hedge prices here as well.
So for the base case, let’s go back and we’re going to take this 110% number right here and just copy that down. I can then anchor each one of these with ‘F4’. And then for the selected case, we can take the same exact formula we used here, OFFSET for the price case, apply that there, and then for the label, again, we’re just going to use the same exact formula, right here for the hedge prices.
So, we’re in the base case scenario here. Now for the rest of these, to copy this across, we already have these anchored so, I can just select these, ‘Control + R’, to copy this across. And now to fill this in for the hedge prices as a percent of the pre-hedged prices for all of these commodities.
So, for gas, we are going to link to the selected case here at the bottom so 110% here. Same for oil, we’re going to link to the same exact thing. We’re assuming the same percentage for oil and gas. Again, because historically, they were pretty closely linked to one another. Oil is a little below gas, in terms of hedging, but overall very, very closely linked. So that’s why we’re using the same hedging assumption for both oil and gas here.
For natural gas liquids, though, we’re going to assume that this stays constant at 100%. In other words, they have no hedging going on here in future years. Again, consistent with the historical data where they have minimal to no hedging for NGL’s. I’m also going to footnote this with ‘Shift + F2’, to say ‘assuming no hedging based on historical data’. So we have that. Now let’s copy all of these across with ‘CTRL + R’.
And now let’s go up here and actually fill in the averaged realized sale prices after hedging. So, again, what this means is when you get to XTO Energy’s revenue, how much are they actually getting? We know they’re production levels, up here at the top. We know how many billion cubic foot equivalent of energy they’re producing each year here, or each day if you want to look at it on a daily basis.
So we know that. How much money are they actually getting? How much revenue are they actually bringing in on either a billion cubic foot basis for gas or a millions of barrels basis for oil and natural gas liquids.
So to fill this in, we are going to go up to our average realized sale prices before hedging and we’re simply going to take the number here and then multiply by the percentage right here. So 110% for gas, copy this down and around.
And so we see the difference right here. We have $6.22 for gas and then we have $6.84 due to hedging. For natural gas, it’s $41.94 and $41.94, because we have no hedging. For oil $69.81 and then $76.79 in the base case with hedging. Now just to show you how this would change in the downside or upside cases.
Let’s go back and let change this to the downside case now. So now in the downside case, we have gas prices at $4.00 per thousand cubic foot, we have oil prices at $50 per barrel. $3.56 for the realized prices $46.54 for oil and $27.96 for natural gas liquids. So in this case the hedging is protecting us from this downside scenario. So rather than only $3.56 for our prices, we can get $5.33 for our gas here. Rather than $46.54 for oil we can get $69.81.
So, this is exactly the role of hedging in the downside scenario. It protects us. So if oil or gas takes a sudden dive our revenues still will go down, but it won’t go down quite as much as if we had no hedging in place here.
Now in the upside scenario, let’s go back and change this to upside scenario three here. So in this case, we have much higher prices. We have $8.89 realized for natural gas, and then we have $55.93 for NGLs and then $93.08 for barrels of oil. But hedging, in this case, we see the downside that if you have really high prices, hedging, and the expenses associated with these contracts and the commitments with the futures will reduce how much you can actually realize.
So in this case, we’re only realizing $8.00 on gas and we’re only realizing $83.77 on the oil here. So it’s still roughly falling the upside, downside, and base case scenarios, but you see the role of hedging here. It’s really insulating us from sudden climbs or sudden drops in the price of commodities on the open market.
So, that’s how we’ve set up hedging in our model and this is really the standard way to do it. When you get to banks you might see commodity price decks or an equity research even commodity price decks. This is really all they’re doing. They’re looking at different cases for the price of commodities and natural resources. They’re assuming a differential and then they’re using a percentage assumption for the impact of hedging on those prices.
So let’s go back now and change this back to the base case scenario. And we can now go in and fill in the revenue by segment for XTO Energy. Now for two of the segments, here, for gas gathering, process and marketing, this is referring more to the down stream and, possibly, midstream segments. This is very, very small. Other revenue is also very, very small. These are just hard-coded numbers and we’re going to go with very simple assumption with these.
The three that we really care about are gas, natural gas liquids and oil. So for gas, now, let’s take our average realized sale price after hedging for gas. And then, go up, and multiply by the total annual production of gas. This is in billions of cubic feet. Our rate for gas here is in thousands of cubic feet. So the unit difference means that we’re going to get millions here, for the dollar amount here for revenue.
So we have gas, let’s do the same for natural gas liquids and oil. And the same math applies, we’re going from dollars per barrel versus millions of barrels here. And so that’s how we get to millions of dollars for the numbers here at the bottom. So, let’s take this now and just copy this across for all of the years.
I’m going to use ‘ALT + ESF’ for this one because I’ve formatted the 2009 numbers, the 2009 column here to be bold. So we have this in place and for these last two items here at the bottom, gas gathering, processing and marketing, and other, the first one is small but still significant. So we’re going to take an average over these five years. Take the average of that and just carry that average across.
We’re assuming that they’re not paying too much attention to this segment of their business, which is why it’s not growing here, it’s just staying constant each year. And then for other, I’m just going to hard-code this as zero. And assume that this, which is already very minimal is simply zero for future years. So we have that. And now let’s sum up the total revenue here. And I’m going to copy this across with ‘CTRL + R’. So we get total revenue going from nine billion to around $12.4 billion here in the base case.
We also like to get revenue growth when we have the total revenue for XTO now. So we’re going to take the 2006 number, divide by the 2005 number, subtract one. And copy this across with ‘ALT + ESF’ as well. So we actually have revenue declining slightly in 2010, which is not unusual. If commodity prices decline, revenue for an oil, gas or mining company is probably going to decline, even if they increase production. And then staying at around 9% to 10% dropping to around 7%-8% in the last two years here. So this is the baseline scenario.
We could also look at the downside and upside scenarios. So the downside scenario, two here. So in this case revenue is barely changing. It drops sharply in 2010 and then goes up to around $10 billion in 2014, but overall it’s only growing by around a billion between 2010 and 2014. So this is under the assumption that commodity prices fall quite sharply and, simply, do not recover over this five year period.
Now for the upside case, let’s take a look at this now, revenue is growing by quite a bit more than the base case. The base case ended at around $12 billion, we’re going up to $14 billion here in year five. So this assumes that there is a commodity boom, and that prices stay high for five years into the future here.
Now, once again, I’d like to always check the numbers against what equity research has, so I’m going to change this back to the base case. And I want to compare this to the Deutsche Bank and RBC reports, so DB report right here. Let’s just go in and see what they have for revenue right now. So sales, right here. So, 2010, they have around eight billion for revenue and then $7.8 billion in 2011.
So, we are quite a bit higher than they are this is our base case. If we change it to the downside case, though, it’s actually fairly close. So, they have dropped around $8 billion, we have an even steeper drop $7.2 billion then going back to $8 billion in 2011. And theirs is around the same level in 2011 as ours, different by around $100 million. So they have a, somewhat, more pessimistic scenario here, but not wildly off from our downside case.
I’m going to change this back to the base case and now let’s look at the RBC report as well. So for this one let’s go to page three and see what they have for revenue. So they’re listing oil and gas revenues over here, net, not clear what this is including so it may be a little bit lower than ours but, we’ll just take a look at it anyway. 2009 they have $8.9 billion, we have around the same, but they are excluding gas gathering, processing, marketing and other from that number.
So around $9 billion. And then they have it dropping to around $8.4 billion in 2010 going back up to $9.3 billion in 2011. So they are somewhat more optimistic than Deutsche Bank in their projections, either for the production, which we know to be true, and possible also for the commodity prices that they are assuming. Ours we have going to $8.9 billion then jumping back up to $9.8 billion. So ours follows the RBC one decently closely off by a couple hundred million, but still in roughly the same pattern of dropping slightly in 2010, then going back up in 2011.
So that’s ours compared to equity research and keep in mind that for oil and gas and commodities companies, it’s not going to look like the typical company, where it’s growing at 15%, 15%, 10%,10% and so on, it’s really completely dependent on commodity prices for the most part.
You can change production, yes, you can acquire more companies, yes, but ultimately if prices drop a lot, your revenue is probably going to drop. So oil and gas and commodity companies are almost like investing in just those markets. Just investing in oil or gas as opposed to the company itself in many cases.
So we’ve now completed these three scenarios on the revenue side of XTO Energy. And the next step, now that we have their revenue all figured out here, and the different scenarios set up, is we’re going to look at their expenses per thousand cubic foot equivalent of energy production here. So we’re going to go through and look at this on a unit by unit basis for each expense.
We’re going to figure out what they look like overall, which expenses are linked to production, which expenses are not linked to production. And then, when we’re done with that we can finally get started with their three statements linking everything together. And seeing what a completed three statement model for XTO would look like.
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