My question is twofold:
When calculating value at risk, let's say the price of an asset or portfolio is falling 1% every month for 12 months. If I tried to calculate standard deviation, it will show up as 0 and no meaningful VAR calculation possible. Is there another way to measure VAR that takes into account consistent declines like this?
Can you recommend a source that explains simply how to calculate portfolio VAR in Python?
Thanks you.
Related
In the bank we are using the average price from six vendors. But we now and then entcounter wrong prices due to the fact that one or more vendors some time publish an incorrect price and this affects the average price. I seek inspiration/suggestions to most effecient/correct way and which formula/logic to use to exclude these price outliers. Here below you see an example of the problem. The prices in red text are considered outliers.
Remaining challenge when only three vendors publish a price and when one of these is a outlier. How do I remove/exclude this outlier?
Note: SAND=True and FALSK= False.
Hope someone can help us out. Many thanks in advance ;-)
Kind regards
Soren Sig Mikkelsen
Solution1:
Easiest of way to remove is via defining the inter quartile range...
In below screenshot you can see the formulas with calculated values...
Logic is very simple, calculate the inter quartile range of your data & see if any of the 6 value is outside the upper/lower limit, If so then it's outlier...
Solution2:
Using Average & Std Deviation
I know how many customers of each customer-size group each sales representative handles on an annual basis. Is it possible to calculate the likely time/effort required by each customer size based on this data set? Or said differently, I'm trying to find out if larger customers require more or less effort than smaller customers.
Is there a function or formula in Excel that will allow be to answer the above based on the data set below?
To add some context, in case it is helpful. There are 2080 work hours a year. I'm assuming they spend all their time with the customers under their responsibility. I also expect that the largest customers require more time than a small customers, but I dont know how much more. That is what I'm trying to figure out. Some employees do handle a lot more customers than others, so its probably best to look a the relative difference between the customer sizes for each employee...
Customer size is rated from 0 (very small) to 7 (the largest).
Below is a small data extract of a large Data table
The Doobie Brothers garage band is planning a concert. Tickets are set at $20. Based on what other bands have done, they figure they should sell 350 tickets, but that could fluctuate. They figure the standard deviation of sales at 50 tickets. No shows are uniformly distributed between 1 and 10. Fixed costs are 5000.
How profitable is the concert likely to be?
So I am able to enter the excel formula for revenue 50*20 and subtract 5000 for FC, but I am having trouble deciphering how to account for the no show costs. I know that I have to use RANDBETWEEN(1,10) formula, but I am not sure if it gets multiplied or divided by something. Again, I am looking for what to do with the formula in the context of a profit equation.
If it helps, the mean for the number of tickets sold is 350 and stdev is 50, so I used that to get the number of attendees in a simulated sense...That is, NORM.INV(RAND(),350,50)
Of course, this problem may not be realistic in real life because promoters keep the money, but for the purposes of the problem...just assume that no promoters exist here.
I'm trying understand how NPER works. I used the following arguments:
loan amount: 145750
APR : 0.04
monthly payments : 9950/12
called the NPER with the following to obtain the number of periods in years :
=nper(0,04/12;9950/12;145750;0;1)/12
and it returned -11,51. This cannot be correct since 11,51 * 9950 = 114524,5 which is less than the original loan amount.
What has gone wrong?
NPER is effectively performing a balancing act, say borrowing a lump sum now and repaying it in relatively small installments for 'years' to come - or investing a capital amount now in exchange for a series of relatively small returns for 'years' to come. Either way money goes out and money comes in. =NPR sets the one-off (large) element against the stream of (small) elements and allows for the time value of money.
For this to work, the convention is that what goes out is negative and what comes in is positive, though does work either way around.
However, the two must be of opposite sign.
I'm looking to compute and show individual row totals and a Grand Total. I just need the formulae to put in the boxes so the calculation is automatic but the problem is the calculations are a little complicated...
I'm using data validation to select the day type. This is what I think I need:
Assign a price to the day type (either Standard day = £23 or Extended day = £26).
Apply a volume discount where appropriate. If Jack is attending all week (5 days) and the day type is the same for all (all Standard or all Extended), the total cost is £100 (or £120)
Else the total number of days needs to be added up for Jack. (Number of days for each ‘day type’) and priced up.
For his siblings after the first, as above but apply an additional discount of 15%.
The grand total then needs to show at the bottom.
Well, it is not the best of data layouts but this may serve, in L6 and copied down to L13:
=IF(OR(A6="Brother",A6="Sister"),0.85* IF(COUNTIF(B6:F6,"Standard day")=5,100,IF(COUNTIF(B6:F6,"Extended day")=5,120,COUNTIF(B6:F6,"Standard day")*23+COUNTIF(B6:F6,"Extended day")*26)), IF(COUNTIF(B6:F6,"Standard day")=5,100,IF(COUNTIF(B6:F6,"Extended day")=5,120,COUNTIF(B6:F6,"Standard day")*23+COUNTIF(B6:F6,"Extended day")*26)))
and =SUM(L1:L16) in D16.
It would be better practice not to hard code the daily rates/discount, but extracting these from C1:D2 would have increased the length of the formula further.
Note also the result is not £429.95 (you may have changed your example after doing your calculations).