Offering the Latest and Best Natural Gas Storage Modelsm
Version 2.750 - June 30th, 2011
Table of Contents
What Does the Model Consider as "Valuable" in Storage Leases?
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As the user peruses this guide, it is worth noting what the WTM storage model considers as valuable in natural
gas storage leases. This knowledge will help the user interpret the model results and recommendations much more clearly.
Purely and simply, the value in trading natural gas storage derives from being able to trade at same-day
and next-day gas prices ("cash prices"). These prices possess very profitable trends (the most well-known trend is
the winter/summer spread) and high volatility. Having access to a storage facility means that a trader can inject/buy
when cash prices go too low and withdrawal/sell when prices go abnormally high. This ability to trade physical gas so
as to exploit these trends is the optionality in storage.
Much optionality exists in storage, and that optionality is even greater when traders have the ability
to either buy or sell gas from storage at any given time (by being partially filled). Further, if various gas storage
inventory levels are associated with higher maximum daily injection/withdrawal quantities (MDIQs and MDWQs, respectively),
then these levels become especially valuable! The trick for any storage trader is to (1) recognize the high-optionality
inventory levels at any given time, (2) optimally trade toward those levels, (3) remain at those levels only for the term
in which they are valuable, and (4) recognize and trade toward the next set of levels after that term. A lot of this so
called follow-on optionality exists in storage leases, which makes the option value in storage very complex and not
well-behaved relative to other American-type options.
The Storage Optimization Software (SOS tm) from WTM Energy Software, LLC, gives values based on optimal
trading/hedging, identifies the valuable inventory levels, recommends optimal trades each day for getting to those
inventories, recommends optimal delta hedges each day for protecting total value (intrinsic plus extrinsic), and
gives cash-to-prompt trading thresholds each day for buying and selling physical optimally.
In addition to these results, SOS also has a VaR (Value-at-Risk) Calculator that allows
traders to ascertain how well total storage value is protected for any set of desired hedges. VaR
minimizing hedges protect extrinsic value, not just intrinsic value! Thus, if traders prefer to use
different hedges than the SOS recommended hedges, they can use the VaR Calculator to ascertain just
how effective those hedges are. Relating storage hedges to extrinsic value protection is new and is
just another valuable and unique feature of SOS.
Overview of Worksheets Used to Run the Model
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WTM's Storage Optimization Software (SOS tm) is implemented through an Excel workbook
containing 4 main worksheets, 1 calculator worksheet, 1 parameter sheet, and 1 reference sheet. The
4 main sheets and 1 parameter sheet are the ones from which the model extracts input or displays output.
The 1 calculator sheet provides support in dynamic delta hedging. Note that copies of this workbook can
be made for each storage lease, thus relieving traders from changing volume/ratchet inputs as different
leases are valued. An overview of all sheets is now given.
The 4 Main Worksheets
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Three of the 4 main sheets require the user to input a few values concerning the storage
lease on each sheet. After such input, the user clicks a button to run the storage model. The model
may take several minutes to run, depending upon the storage lease term and winter/summer spreads in prices
and volatilities, but upon completion the output will appear on the fourth main worksheet, "4-Output." The
specific outputs shown are
1. Total dollar storage value for the amount of gas inventory currently stored
2. Dollar storage value per unit of maximum capacity
3. Recommended physical trade for the current day
4. Recommended forward price deltas assuming the current inventory is held over until the next trading day
5. One-day-95% VaR of the delta-hedged storage value
6. Intrinsic Values and corresponding intrinsic hedges
7. Threshold cash-to-prompt spreads for optimal injection/withdrawal
8. A table of storage values, recommended physical trades, futures deltas, and VaRs for the whole range of inventory levels
Note that the values are given for the current inventory and do not include the average cost of gas for obtaining that
inventory: Adding the average cost of gas to the model value gives one an idea of performance-to-date.
A sample and partial screen shot of these results is given below.
Only a partial screen shot is shown above, where some of the results in (1) through (4) and (6) are shown, and
part of the results table in (8) is shown just below that. The rest of the results table's storage values, hedging deltas,
and VaRs are not shown.
The threshold cash-to-prompt spreads give the spread to the prompt price that the cash price must pass in
order to inject or withdrawal optimally. Note that this spread could be positive for injections (usually for very low
inventories) or negative for withdrawals (usually for very high inventories). The results table discussed is output
from the model to give the trader an idea of which inventory levels possess the most optionality for cash-price plays.
Specifically, the inventories where the recommended physical trade is zero are typically the levels possessing the most
optionality. These levels typically coincide with the highest VaRs.
1 Also, if the trader subsequently injects or withdrawals
on the current day, then the trader should consult the results table for the correct hedging deltas associated with the new
inventory.
The table also shows which value is more important that day: intrinsic or extrinsic. If the region of
high-optionality inventories is in the middle, extrinsic is more the focus; if the region is near full or empty,
intrinsic is more the focus.
The 1 Calculator Worksheet
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The 1 previously mentioned calculator worksheet supports the trader in dynamic hedging. It allows for the
trader to perform what-if scenarios for hedging total storage value, both intrinsic and extrinsic! Specifically, the
trader can enter a set of proposed hedges into the VaR Calculator, click a button, and the VaR of the storage value
hedged with those proposed hedges appears. The VaR of the storage value hedged with optimal hedges is also shown
for comparison. If the two VaRs are close, the trader can be confident that the set of proposed hedges will protect
total storage value well. Thus, traders may now assess tradeoffs of locking-in intrinsic versus the effect on
protecting extrinsic.
The 1 Parameter Worksheets
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The 1 parameter sheet allows for three pieces of input: the short-term mean-reversion speed, the
long-term mean-reversion speed, and capacity constraint on the net-delta. This last parameter is a percentage
of tolerance (i.e., enter 10% as 10.0), relative to the lease's maximum capacity, of how far off the calculated
optimal delta hedges are allowed to be from fully hedged. For example, both a value of 10.0 (meaning 10%) for
this parameter and a value of 1 million MMBtus for the maximum capacity mean that the current inventory plus
calculated injection delta hedges must be within 100,000 MMBtus of the calculated withdrawal delta hedges (but
the total capacity hedged may be under the maximum capacity by more than 100,000 units, i.e., the parameter does
not constrain this from happening). Thus, the optimal delta hedges calculated are calculated under the constraint
implied by this parameter.
The two mean-reversion speeds are referenced in the white-paper as a and b, respectively. This paper
is on our website and may be downloaded and printed.
The model has default estimated values for the mean-reversion speeds but allows for input of
them since different mean-reversion speeds may apply for different storage locations. If the user wishes to
override the default values, then the user must estimate these parameters outside the model and input them on
the parameter worksheet. Within the model, these parameters are considered constants during valuations.
Note that the default values are a = 9.0 and b = 0.1. These values were estimated using data on different
storage years, cycle-rates, and gas hubs around North America, so one may use these values if one cannot estimate
them for the time being.
The 1 Reference Worksheets
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The 1 previously mentioned reference sheet contains data and results that allow (1) for various
other worksheets in the workbook to operate, (2) for your company to run the model (the model only works for
certain company codes), and (3) for easier support from WTM if the calculation module should somehow fail. This
sheet should not be deleted or modified in any way!
We now discuss the individual worksheets in detail.
The Worksheets in Detail
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The storage model runs on the input of the four following worksheets: The sheets are named
"1-StartHere," "2-PriceInputData," "3-VolumeInputData," and "Parameters." Not much input is entered on
each sheet, but once the data is properly input, the user may click the button "Get Results" on sheet "4-Output"
to run the storage model and get results.
The 1 calculator sheet and 1 reference sheet are explained further below.
Worksheet "1 - StartHere"
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Upon opening the workbook (under "Enable Macros"), the cursor will be placed immediately on the
sheet labeled "1-StartHere." Only 3 dates are to be entered on this sheet: the beginning storage lease date,
the ending storage lease date, and the date for which the valuation is run, which is usually the current date
(all in mm/dd/yyyy format).
Two click-buttons appear on the sheet. The "Erase and Rebuild This Sheet" button is used to
clear the sheet and reload various cells with proper labeling and formatting for data entry. The dates are
to be entered in the light-blue highlighted cells in "mm/dd/yyyy" format.
When all 3 dates are entered, the user clicks the other button, "Enter Dates and Click Here." The
input dates are immediately checked for correctness, other sheets are updated based on the entered dates, and
the next worksheet is shown. However, if an error exists with the dates, then an error message appears that
tells the user about the problem. A screen shot of this sheet is shown below.
Worksheet "2 - Price Input Data"
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This second worksheet is for input of market data: forward prices, physical premiums, contract
volatilities, and interest rate data. On this sheet, 4 click buttons are present.
The button labeled "Get Prices, Vols, Rates" is used to load all values from row 12 downward (the values
in cells B4 and B5 are always entered manually, and cell B7 is calculated). Note that since WTM does not know how
you store this data currently, your IT department will have to modify the VBA code connected with this button in the
back of this workbook in order to collect this data automatically. Until then, prices, vols, and rates will have to
be entered manually.
The button labeled "Erase and Rebuild This Sheet" is used to clear the sheet and reload various cells with
proper labeling and formatting for data entry. All input is entered in the light-blue highlighted cells, and the forward
contract months (e.g. Apr-2005) and option expirations (e.g. mm/dd/yyyy format) that can be input are filled into the
sheet automatically into their respective columns. Also, those contract months and expirations that are required entry
are so marked (more on what is and is not required is given later).
The button labeled "Click to Fill in Dates" is just like the "Erase and Rebuild This Sheet" button with
one major exception: All prices, rates, and volatilities that were on the sheet previously will not be erased;
only contract months, option expirations, and which of them is required input are modified. Such a feature reduces
redundant price/rate/volatility input.
Clicking the button labeled "Enter Data and Click Here" immediately causes all data to be checked for correctness,
and the next worksheet is shown if all data are validated. If, on the other hand, a problem exists with the data, then an
error message appears that tells the user about the problem.
The data entered on this worksheet consist of 3 groups:
(1) - cash and BalMo-to-prompt spreads, forward prices, and physical premium data,
(2) - volatility data, and (3) - interest rate data. A screen shot of this worksheet is now given.
Cash and BalMo-to-Prompt Spreads, Forward Prices and Physical Premium Data
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The current cash and BalMo-to-prompt spreads per MMBtu are entered into the light-blue highlighted cells
marked accordingly. They are required input and must be a number that makes sense. These numbers come from the traders
around 8am as the cash market trades.
Forward price data is entered into four columns just below, and the cells are shaded in light-blue. The first
of the columns should already have contract months, such as "Apr-2005," filled in. If not, or if you are unsure about which
contract months to input and where, then click either the button "Click to Fill in Dates" or "Erase and Rebuild This Sheet,"
and the correct contract months will be shown.
The second column of the forward price data is for NYMEX prices per MMBtu. If the price's spreadsheet row is
marked as required (the mark is to the right of the cell containing the price), then a number strictly greater than zero
must be entered. If the price is not marked as required, then a price may or may not be entered at the user's choice, but
no gaps must exist between expirations. Any contract months in the first column not required and not having prices entered
next to them must be erased; otherwise, the model will prompt the user with an error message to supply prices.
The third and fourth columns are for location basis and physical premium per MMBtu, respectively. Both
must be entered, even if zero, next to every entered NYMEX price, and these numbers can be positive or negative. However,
any NYMEX price, its basis, and its physical premium must sum (the sum is the physical price) to be strictly greater than zero.
Volatility Data
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Two columns of data (shaded in light-blue) are available for data entry: option expiration in mm/dd/yyyy format
and percentage volatility. The required option expirations should be automatically filled on the sheet and correspond to
NYMEX expirations. If the expirations are not filled, or if you are unsure about which contract months to input
(and where to input), then click either the button "Click to Fill in Dates" or "Erase and Rebuild This Sheet," and
the expirations will be shown in their correct placement.
For each option expiration, a single percentage volatility is entered (i.e., 50% is entered as 50.0). This
volatility is merely the implied volatility of the contract corresponding to the option expiration. For example, if the
prices are for a location very near Henry Hub, then the NYMEX implied volatilities will do. For a location far from Henry
Hub, scaling the NYMEX implied volatilities will do.
Interest Rate Data
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A set of two columns on the right of the worksheet, highlighted in light-blue, are used to input this data.
Zero-coupon instruments on either LIBOR or Treasury strips can be used, but the company's WACC is more conservative.
The data are entered starting from top to bottom and in ascending expiration order (no empty rows in the midst of the
data should appear).
The first column is the maturity in mm/dd/yyyy format. The second column is for the continuously
compounded yield-to-maturity, which must be entered as a percentage strictly greater than zero (i.e., enter 10% as 10.0).
The longest maturity must be greater than or equal to the lease end-date.
Worksheet "3 - Volume Input Data"
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This third worksheet is for input of operational data: maximum capacity, current capacity, fuel charges
(both injection and withdrawal), commodity charges (both injection and withdrawal), ratchets, minimum requirements,
and ad-valorem taxes. On this sheet, 2 click buttons are present.
The button labeled "Erase and Rebuild This Sheet" is used to clear the sheet and reload various cells with
proper labeling and formatting for data entry. All input is entered in the light-blue highlighted cells.
Clicking the button labeled "Enter Data and Click Here" immediately causes all data to be checked for
correctness, and the next worksheet is shown if all data are validated. If, on the other hand, a problem exists
with the data, then an error message appears that tells the user about the problem.
The data entered on this worksheet consist of 5 groups: (1) - inventory data such as maximum capacity,
current inventory, (2) - transaction costs, (3) - ratchet information, (4) - minimum requirement data, and
(5) - ad-valorem taxes. A partial screen shot of this worksheet is now given.
Inventory Data
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The "Capacity in MMBtus" is the maximum capacity of the storage lease and must be a number strictly greater than
zero. The "Current MMBtu Inventory" is the amount of MMBtus currently in storage and must be a number greater than or equal to
zero, but less than or equal to the maximum capacity.
Fuel and Commodity Charge
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Two fuel charges per calendar month must be entered: one for injection and one for withdrawal. These are to
be entered as percentages greater than or equal to zero (i.e., 1.5% is entered as 1.50). These fuel charges are
applied in the same way that fuel charges are applied in gas transportation: The percentage is applied to a grossed-up
volume such that the delivered volume is left remaining after applying the charge.
Two commodity charges per calendar month must be entered: one for injection and one for withdrawal. These
are to be entered as numbers greater than or equal to zero and are in dollars per MMBtu.
If bid/ask spreads or transportation costs to/from the storage facility are involved, one may adjust these
fuel and commodity charges accordingly (bid/ask spreads are just like extra commodity charges; transport may add both
extra fuel and commodity charges).
Ratchet Information
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The ratchet information consists of 25 columns highlighted in light-blue. The first column, "Level in MMBtus,"
is the starting-volume of the ratchet. The second and third columns, respectively, are for the MDIQs and MDWQs for each
January of the lease term for that starting-volume. Both the MDIQs and MDWQs are entered in MMBtus, and they apply to
volumes greater than or equal to the starting-volume but strictly less than the next ratchet starting-volume, and only
for each January of the lease term. The fourth and fifth columns, respectively, are the MDIQs and MDWQs for each February
of the lease term, etc. The last two columns, respectively, are the MDIQs and MDWQs for each December of the lease term.
The ratchet starting-volumes must be entered in strictly ascending order, starting from zero, and with no
gaps in the data. Except for the first starting-volume, which is always zero, all volumes must be strictly greater than
zero. The MDIQs and MDWQs must be numbers greater than or equal to zero. Only data entered in the light-blue cells are
considered by the model.
The ratchet data presented to the storage trader are usually not given in a way that can be directly input
on this worksheet. The proper way to create the ratchet lines to be filled on the worksheet is as follows:
1. start from 0 inventory and enter 0, its MDIQs, and its MDWQs on the first line of the ratchet
section, respectively, for each calendar month;
2. going from 0 inventory, determine the next inventory level for which either an MDIQ or an MDWQ changes
due to a ratchet or month; enter that level value, the MDIQs, and the MDWQs on the next line of the ratchet section,
respectively (if either the MDIQ or the MDWQ changed at that inventory level or month, but not both, then the value
for the one that didn't change is still entered on the line, and its value is equal to its value on the
previous line);
3. continue performing step 2 until you reach the final inventory level for which the MDIQs and MDWQs no
longer change up to the maximum capacity (therefore, the volume level of the last line in the ratchet section is a number
strictly less than the maximum capacity).
For example, if a ratchet schedule is presented as follows . . .
0 inventory up to 499,999 the MDIQ is 10,000,
500,000 and over the MDIQ is 20,000,
the MDWQ is always 15,000,
no injection in January is permitted,
then two lines are input on the ratchet schedule as follows:
|
|
Jan |
Feb |
|
Start Volume |
Inj |
Wth |
Inj |
Wth |
1. |
0 |
0 |
15,000 |
10,000 |
15,000 |
2. |
500,000 |
0 |
15,000 |
20,000 |
15,000 |
Minimum Requirement Data
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Three columns of data, highlighted in light-blue, are entered. The first column is the minimum
requirement volume in MMBtus, while the second and third columns are the beginning and ending dates for
which the requirement applies. The volumes are entered in MMBtus and must be numbers greater than or
equal to zero. The dates are entered in mm/dd/yyyy format, the beginning and ending dates may be the same,
and those dates can be any date in the remaining lease term, including the current date or the end-date of the lease.
Note that no data whatsoever has to be entered in the minimum requirements section for the model to
run. Also note that the requirements must start from the top and work down with no gaps in the data (but do not
have to be in any date order). Lastly, only data entered in the light-blue cells are considered by the model.
Ad-Valorem Data
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Three columns of data, highlighted in light-blue, are entered. The first column is the date the tax
is figured on any working gas inventory, the second is the percentage tax (i.e., 1% is entered as 1.0), the
third is the dollar per MMBtu tax. The model allows for both types of taxes to be entered at once.
Worksheet "Parameters"
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This sheet is the final input sheet and holds three pieces of data: the short-term mean-reversion
speed, the long-term mean-reversion speed, and capacity constraint on the net-delta. This last parameter
is a percentage of tolerance, relative to the lease's maximum capacity, of how far off the calculated
optimal delta hedges are allowed to be from fully hedged. For example, both a value of 10.0 (meaning 10%)
for this parameter and a value of 1 million MMBtus for the maximum capacity mean that the current inventory
plus calculated injection delta hedges must be within 100,000 MMBtus of the calculated withdrawal delta hedges
(but the total capacity hedged may be under the maximum capacity by more than 100,000 units, i.e., the parameter
does not constrain this from happening). Thus, the optimal delta hedges calculated are calculated under the
constraint implied by this parameter.
The two mean-reversion speeds are referenced in the white-paper as a and b, respectively. Note that
the white-paper can be downloaded and printed from the web site. These two inputs are needed to run the model,
but their values will probably change only very infrequently. 2 Estimated values for a are typically in the 9.0
or over range, while estimated values for b are typically around 0.1. In the SOS model, a can be thought of as
representing short-term weather effects on cash prices, while b can be thought of as representing longer-term
supply/demand effects. For example, a spike in weather affects the cash price for several days, but that effect
usually diminishes quickly; however, a new set of commercial customers coming on-line would cause movements in
whole strips of forward prices due to these firms securing long-term supplies of natural gas.
The typical estimated values for both a and b are greatly different from the mean reversion speeds
estimated from a one-factor model: The one-factor speeds are typically estimated to be 1.5 to 2.0 and can be
thought of as an average of the short-term and long-term mean-reversion speeds.
The SOS model allows for input of estimated mean-reversion speeds since different speeds may apply for
different storage locations. The user must estimate these values outside the model, but within the model, they are
considered constants during valuations.
When one clicks the button "Erase and Rebuild This Sheet," the sheet is cleared, cells are
reformatted and reloaded with proper labeling for data entry, and default mean-reversion speeds are filled
in. The default values are a = 9.0 and b = 0.1. These default values were estimated using data on different
storage years, cycle-rates, and gas hubs around North America, so one may use these values if one cannot estimate
them for the time being. A screen shot of this sheet is below.
Note that both a and b have upper and lower bounds within the model. If either input value violated its bounds
during a model run, then the bound value is used within the model, and the input value will be overwritten with the
bound value after the model finishes. Bounds facilitate stable calibration, but one should not find the bounds very
constraining. The following bounds are in effect:
|
Upper Bound |
Lower Bound |
a |
150.00 |
5.00 |
b |
1.5 |
0.05 |
Very, very rarely will credible estimates of a or b be outside these bounds.
Worksheet "4 - Output"
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WE RECOMMEND THAT YOU SAVE THE WORKBOOK PRIOR TO EACH VALUTATION; doing so will cause all of your
input to be saved if Excel should end abnormally during a valuation, which is extremely rare but does happen.
Running the Model
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On this worksheet 2 click buttons are present. The button labeled "Erase and Rebuild This Sheet"
is used to clear the sheet and reload various cells with proper labeling and formatting.
Clicking the button labeled "Get Results" immediately causes all the data entered on all
before-mentioned worksheets to be checked for correctness. If a problem exists with the data, then an
error message appears that tells the user about the problem. If not, then the model runs for a few minutes
and produces the output that was shown above in the "Overview" section. On most of today's PCs, the model
takes about 8 minutes per year of storage trading in the lease to run.
Interpreting Odd-Looking Output
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At certain times, especially when the storage lease end-date is near, the model's recommended
physical trades will look odd. Specifically, the results table on the sheet "4-Output" will show several
pockets of inventory levels for which the recommended trade is zero. Below is an example of such output.
Notice the output says that we should trade to one of three inventory regions, depending upon our current
inventory: the region of 5,000 to 25,000, 60,000, and 75,000. First, note that a ratchet exists at 60,000 in which the
maximum daily withdrawal quantity dramatically increases (mathematically, ratchets are the cause of several such pockets
occurring) Also note that 20 days are left in the storage lease in this example.
At first glance, the output looks wrong, especially for inventories of 60,000 and greater. The output
is correct; here is the intuition. Recall that storage value occurs from trading on profitable trends in cash prices,
and that having some gas in storage allows one the added optionality of profiting from both up and down trends. Since
the lease end-date is only 20 days away, a high-optionality inventory region from 5,000 to 25,000 makes sense: One can
take advantage of both up and down trends in cash prices without the threat of leaving gas in storage by the lease end-date.
Further, attempting to inject to 60,000 so as to take advantage of the higher withdrawal rate does not make sense if it will
take several consecutive days of injection to do so.
However, if your current inventory is 55,000, then injecting one more day allows one to profit from higher
withdrawal rates on subsequent days. And if one is at 65,000, then withdrawing only 5,000 allows one to still profit
from higher withdrawal rates on subsequent days. This reasoning explains why an inventory of 60,000 has added value.
Lastly, the inventory of 75,000 becomes significant since the higher withdrawal rate just happens to be
15,000/day: At 75,000, one may withdrawal at 15,000/day for two days, as opposed to just one day for inventories
below 75,000 but greater than or equal to 60,000. Thus, being at 75,000 has added value over being at, say, 60,000.
This reasoning explains a lot of the "saw-tooth" pattern seen in recommended trades across
inventories. But at higher inventories in this example, the saw-tooth pattern is not present since one must
keep withdrawing, rather than choosing particular days to withdrawal, so as to not leave gas in storage by
the lease end-date.
Worksheet "VaRCalculator"
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This worksheet is utilized after the storage model runs and results display on sheet "4-Output." This
sheet's main purpose is to aid the user in assessing how hedges not proposed by the model protect total storage value,
both intrinsic and extrinsic value, for the current inventory. Storage traders typically lay hedges on to lock-in
intrinsic value; however, those hedges may not do an adequate job of protecting extrinsic value (which is protected
more by hedges that reduce daily VaR), especially if physical and financial storage positions are adjusted frequently!
This sheet allows traders a way of assessing extrinsic protection among different sets of proposed hedges.
On this sheet, the user inputs a proposed set of hedges, clicks a button, and the VaR of the whole
position (storage values hedged with the proposed hedges) is displayed in a yellow-highlighted cell. Next to that
in another yellow-highlighted cell is the VaR using optimal hedging. This result is displayed as reference for the
user to know how VaR may be minimized. Thus, if the two VaRs are close in value, then the trader may be confident that
the proposed hedges protect extrinsic storage value.
Also on this sheet, 2 click buttons are present. The button labeled "Erase and Rebuild This Sheet" is used
to clear the sheet and reload various cells with proper labeling and formatting for data entry. All input is entered in
the light-blue highlighted cells. This button should be clicked anytime the user is unsure of where inputs should go.
Clicking the button labeled "Get VaR" immediately causes all data entered on this worksheet to be
validated. If a problem exists, then an error message appears that tells the user about the problem. If not,
then the two before-mentioned VaRs appear in yellow-highlighted cells.
The input labeled "Held-Over Inventory" allows the user to input the amount of stored gas (in MMBtus) to be
held over from the current day to the next (how well the hedges protect extrinsic is dependent upon held-over inventory).
Thus, the model does not assume that the user will follow the recommended physical trade that day. The "Held-Over Inventory"
must be greater than or equal to zero and less than or equal to the maximum capacity.
Just below the "Held-Over Inventory" is a range of cells to input the proposed set of
hedges (in MMBtus; longs are positive numbers, shorts are negative). The tenors of the forward contracts
used in hedging are displayed just to the left of the input cells (Click "Erase and Rebuild This Sheet" to
update the contract tenors). The tenors' range starts from the current date and goes to the storage end-date.
If less than 2 tenors remain in the storage lease, the model will display 2 tenors (so the user can always use at
least 2 contracts to hedge). A screen shot of this worksheet is shown below.
Note that one can see the VaR of the un-hedged storage lease (at the held-over inventory) by entering zeros
for all the contract hedges. Doing this gives the user an idea of how much total risk needs to be hedged.
Trouble Shooting
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The Calibration Failed to Converge
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If the model calibration fails, a very rare event, then no results are displayed, and an error message
saying "Calibration failed to converge . . ." will appear. This is usually caused from either bad forward price or
from an incompatible value for the mean-reversion speeds.
Recheck the price/rate/volatility inputs on sheet 2-PriceInputData for errors. If no errors are
found, then go to the sheet Parameters and increase the Short-Term Mean-Reversion speed by 5.0 and the Long-Term
Mean-Reversion speed by 0.1.
Merely rerun the model after these changes. If the model fails again, adjust the cash and BalMo
prices to be closer to the prompt price (by just a small amount). If the problem persists, contact WTM at
. A copy of your input may be required, so be sure to save the workbook.
The Run-Time Is Exceedingly Long
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Long run-times (approximately 30 minutes) do not mean that the model will not finish or results
will not be shown: The model eventually finishes and shows results. Long run-times occur when either (1) current
forward curves have a lot of spread, or (2) the volatilities have a large spread.
Other Excel Worksheets Freeze While Running the Model
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While working in other Excel workbooks while the model is running, those workbooks may freeze
(or work more slowly). The freeze is temporary and ceases when the model finishes. Cutting, copying and
pasting in another workbook while the model is running typically causes a workbook to freeze temporarily.
The Excel Screen Whites Out
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On rare occasion, when the model is running and while other Windows tasks are being performed,
Windows becomes confused. This confusion may lead to the following:
(1) - part or all of the worksheet is whited out
(2) - your PC processing gets slower
These problems do not cause results to not calculate or to not be shown: The model eventually
finishes as usual, and output is displayed. One sign that the model is still running is to place the
mouse pointer within the spreadsheet, whether the spreadsheet is whited out or not, and see if the hourglass
icon appears. If it does, the model is still running and will eventually display output. If the hourglass
does not appear and output is not displayed, then Windows has faltered (extremely rare): End the Excel program
through the Task Manager (after Excel ends and if the operating system is Windows XP or better, an "error"
dialog box appears asking the user to click on either "send report" or "don't send." Click on "don't send").
When one ends the Excel spreadsheet through the task manager, PC performance may decline. We
recommend you restart your PC if slowness occurs.
Deltas and VaRs Look Incorrect
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On extremely rare occasion, Windows becomes very confused and appears to corrupt memory used by
the model (this has only happened one time that we know). The model may still display results that may not be
accurate. One sign that results are not accurate is a high VaR. VaRs are typically less than one-tenth of
one-percent of storage value, and VaRs over ten percent can indicate a problem.
For this problem, merely restart your PC and rerun the model.
Spreadsheet Does Not Run
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This problem may be due to either your license expiring, the macros not being enabled, or an
input error with no corresponding error message (please tell us if this occurs; we always want an error
message to display for improper input). If the input is correct and your license is up to date, then
contact WTM with this problem (email a description of the problem to
. A copy of your input may be required, so be sure to save the workbook.
A Debug Dialog Box Appears Stating That the DLL Not Found by VBA
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This message appears when the storage valuation DLL module has been moved from its pre-assigned folder
path. Specifically, the VBA code in "Module1" in the workbook contains VBA "Declare" statements that tell the workbook
which Windows folder the valuation DLL module is in (The Declare statements are at the top of "Module1"). The path clause
in each Declare statement must state the full path to the DLL module, starting with the disk drive (e.g., c:\SOSbyWTM\ . . .).
To fix this problem, either move the DLL module to the path given in the Declare statements or change the path
in each of the three Declare statements in each workbook to be the path of the DLL module.
All Other Problems
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The above list of troubles is exhaustive at this time; however, we understand that other
errors not listed above may occur. If such errors occur, especially errors in which a debug dialog box
occurs similar to the one shown below, then save the workbook with its input and contact WTM at
.
We will be happy to explore the problem and get your model running again, usually within a few hours.
Contact Information
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WTM Energy Software, LLC
6422 Cottonwood Park Lane
Houston, TX 77041
(713) 849-2180 office and fax
(832) 671-1122 mobile
inquire@WTMenergy.com (For non-trouble shooting inquiries)
support@WTMenergy.com (For trouble shooting inquiries)
www.WTMenergy.com
1 - The VaR in this model measures the dispersion of storage values from the (linear) forward contract hedges;
thus, the VaR is a measure of non-linearity (gamma) in storage values, which can only occur from optionality.
2 - The quantitative analysts should be in charge of estimating these inputs
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