Today we will build a mortgage payment calculator using excel. But we will not build a boring excel sheet, we will build a mortgage calculator that is easy to play with.
A mortgage payment is a monthly installment that you pay towards a loan. Any mortgage loan will typically have,
- loan amount
- duration of the loan (also called as tenure of mortgage) in years
- interest rate (APR) per year
Given these 3 parameters, we can easily determine the monthly installment amount (this will be the same amount for all months during loan tenure)
We are going to use Excel’s form controls (more on this below) to build a mortgage payment calculator like this:
Why you should not be boring and use the form controls
A form control is a button or check box or scrollbar or some other click-able thing you see in Windows. Do you know that you can add the very same controls to Excel spreadsheet to make the it interactive?
For example,
- instead of asking a user to enter “yes” or “no” in a cell, you can ask them to click a check box.
- instead of taking “age” in a cell, you can use a scroll bar and set the values from 0 to 100.
This way of gathering inputs is more fun, engaging and interactive.
Now that you find form controls hot and attractive, lets proceed and make a house loan payment calculator.
How is mortgage payment calculated?
As I said above, any mortgage (or housing loan) will have 3 parts – loan amount (p), loan tenure (n) and annual interest rate (r).
Given the values of P, N and R, we can find the monthly payments using Excel’s PMT formula like this:
=PMT(R/12,N*12,P)
[Related: PMT formula syntax & examples]
[Related: Amortization Schedule in Excel]
We are dividing interest rate (R) by 12 since R is annual interest rate and we make monthly payments.
We are multiplying loan duration (N) with 12 since we are going to make monthly payments.
Making the mortgage calculator in Excel
We will use scroll-bar controls to take numeric inputs required (P,N and R) for the payment calculation. And we feed these values to PMT formula to find the monthly installment amount.
Step 1: Add a Scroll-bar Control
We will use this scroll bar to take “loan amount” input. To keep it simple, we will ask users to enter input in ‘000s. So, if the loan is $120,000, the input should be 120.
First add a scroll-bar form control to your excel sheet. To do this go to Developer Ribbon > Insert > Scroll-bar Form Control in Excel (related: enable developer toolbar in Excel)
Add a Scroll-bar Control
Once selected, just add the control to spreadsheet by clicking anywhere.
Step 2: Set Properties for this Scroll-bar
To set the properties for the scrollbar control, right click on it and go to “format control” option. Now go to “Control” tab.
Here set minimum and maximum values for the scroll bar. To keep our model simple, just set minimum as 35 and maximum has 500.
Also, select a cell to link the scrollbar. When you do this, excel links the scroll bar to the selected cell. So whenever scroll bar is updated the cell gets updated too (and vice-a-versa). See this illustration:
Step 3: Add Remaining Scroll bars
Repeat the same steps for 2 other scroll bars. One for interest rate and one for loan tenure.
Make sure you set the minimum and maximum values in a reasonable range.
Step 4: Plug the values in to PMT formula
Now that the scroll bars are ready, just write the PMT formula. Assuming you have linked scroll bars like this:
- Loan amount in cell A1
- Interest rate in cell A2
- Loan tenure (years) in cell A3
The formula will be,
=PMT((A2/12)%,A3*12,A1)
Remember, PMT returns value in negative numbers (as it is the amount we need to pay, not get). But you can make it positive (for display purposes) by multiplying it with -1 like this = -PMT((A2/12)%,A3*12,A1)
Step 5: Play with your Model
Now your mortgage payment calculator is ready. You can play with it by testing various combinations and finding monthly payments. You can easily see what happens when you increase loan tenure or decrease interest rate.
Download Excel Mortgage Payment Calculator
Here is the excel mortgage payment calculator file. Download and play with it.
Bonus – Making an Amortization Schedule
You can easily extend this model to add an amortization schedule to see how much of each monthly payment is towards principal and how much is for interest.
- You can calculate principal portion for any month using PPMT formula like this
=PPMT(R/12,M,N*12,P). Here “M” is the month for which you want principal amount. - You can calculate interest portion for any month using IPMT formula like this
=IPMT(R/12,M,N*12,P).
Full tutorial: Loan Amortization Schedule with Excel.
Do you love form controls?
Do you use form controls in your spreadsheets? I find them pretty intuitive and use them wherever I can. I have made many complex spreadsheet models easy to understand and work with by just adding form controls. The beauty is that, they require no programming or anything. You just add them and link them to a cell.
What about you? Do you love form controls? Where do you use them most?
Learn More about Excel Form Controls:
20 Responses to “Simulating Dice throws – the correct way to do it in excel”
You have an interesting point, but the bell curve theory is nonsense. Certainly it is not what you would want, even if it were true.
Alpha Bravo - Although not a distribution curve in the strict sense, is does reflect the actual results of throwing two physical dice.
And reflects the following . .
There is 1 way of throwing a total of 2
There are 2 ways of throwing a total of 3
There are 3 ways of throwing a total of 4
There are 4 ways of throwing a total of 5
There are 5 ways of throwing a total of 6
There are 6 ways of throwing a total of 7
There are 5 ways of throwing a total of 8
There are 4 ways of throwing a total of 9
There are 3 ways of throwing a total of 10
There are 2 ways of throwing a total of 11
There is 1 way of throwing a total of 12
@alpha bravo ... welcome... 🙂
either your comment or your dice is loaded 😉
I am afraid the distribution shown in the right graph is what you get when you throw a pair of dice in real world. As Karl already explained, it is not random behavior you see when you try to combine 2 random events (individual dice throws), but more of order due to how things work.
@Karl, thanks 🙂
When simulating a coin toss, the ROUND function you used is appropriate. However, your die simulation formula should use INT instead of ROUND:
=INT(RAND()*6)+1
Otherwise, the rounding causes half of each number's predictions to be applied to the next higher number. Also, you'd get a count for 7, which isn't possible in a die.
To illustrate, I set up 1200 trials of each formula in a worksheet and counted the results. The image here shows the table and a histogram of results:
http://peltiertech.com/WordPress/wp-content/img200808/RandonDieTrials.png
@Jon: thanks for pointing this out. You are absolutely right. INT() is what I should I have used instead of ROUND() as it reduces the possibility of having either 1 or 6 by almost half that of having other numbers.
this is such a good thing to learn, helps me a lot in my future simulations.
Btw, the actual graphs I have shown were plotted based on randbetween() and not from rand()*6, so they still hold good.
Updating the post to include your comments as it helps everyone to know this.
By the way, the distribution is not a Gaussian distribution, as Karl points out. However, when you add the simulations of many dice together (i.e., ten throws), the overall results will approximate a Gaussian distribution. If my feeble memory serves me, this is the Central Limit Theorem.
@Jon, that is right, you have to nearly throw infinite number of dice and add their face counts to get a perfect bell curve or Gaussian distribution, but as the central limit theorem suggests, our curve should roughly look like a bell curve... 🙂
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I'm afraid to say that this is a badly stated and ambiguous post, which is likely to cause errors and misunderstanding.
Aside from the initial use of round() instead of int(),.. (you've since corrected), you made several crucial mistakes by not accurately and unambiguously stating the details.
Firstly, you said:
"this little function generates a random fraction between 0 and 1"
Correctly stated this should be:
"this little function generates a random fraction F where 0 <= F < 1".
Secondly, I guess because you were a little fuzzy about the exact range of values returned by rand(), you have then been just as ambiguous in stating:
"I usually write int(rand()*12)+1 if I need a random number between 0 to 12".
(that implies 13 integers, not 12)
Your formula, does not return 13 integers between 0 to 12.
It returns 12 integers between 1 and 12 (inclusive).
-- As rand() returns a random fraction F where 0 <= F < 1, you can obviously can only get integers between 1 and 12 (inclusive) from your formula as stated above, but clearly not zero.
If you had said either:
"I usually write int(rand()*12) if I need a random number between 0 to 11 (inclusive)",
or:
"I usually write int(rand()*12)+1 if I need a random number between 1 to 12 (inclusive)"
then you would have been correct.
Unfortunately, you FAIL! -- repeat 5th grade please!
Your Fifth Grade Maths Teacher
Idk if I'm on the right forum for this or how soon one can reply, but I'm working on a test using Excel and I have a table set up to get all my answers from BUT I need to generate 10,000 answers from this one table. Every time, I try to do this I get 10,000 duplicate answers. I know there has to be some simple command I have left out or not used at all, any help would be extremely helpful! (And I already have the dice figured out lol)
Roll 4Dice with 20Sides (4D20) if the total < 20 add the sum of a rerolled 2D20. What is the average total over 10,000 turns? (Short and sweet)
Like I said when I try to simulate 10,000turns I just get "67" 10,000times -_- help please! 😀
@Justin
This is a good example to use for basic simulation
have a look at the file I have posted at:
https://rapidshare.com/files/1257689536/4_Dice.xlsx
It uses a variable size dice which you set
Has 4 Dice
Throws them 10,000 times
If Total per roll < 20 uses the sum of 2 extra dice Adds up the scores Averages the results You can read more about how it was constructed by reading this post: http://chandoo.org/wp/2010/05/06/data-tables-monte-carlo-simulations-in-excel-a-comprehensive-guide/
Oh derp, i fell for this trap too, thinking i was makeing a good dice roll simulation.. instead of just got an average of everything 😛
Noteably This dice trow simulate page is kinda important, as most roleplay dice games were hard.. i mean, a crit failure or crit hit (rolling double 1's or double 6's) in a a game for example dungeons and dragons, if you dont do the roll each induvidual dice, then theres a higher chance of scoreing a crit hit or a crit failure on attacking..
I've been working on this for awhile. So here's a few issues I've come across and solved.
#1. round() does work, but you add 0.5 as the constant, not 1.
trunc() and int() give you the same distributions as round() when you use the constant 1, so among the three functions they are all equally fair as long as you remember what you're doing when you use one rather than the other. I've proven it with a rough mathematical proof -- I say rough only because I'm not a proper mathematician.
In short, depending on the function (s is the number of sides, and R stands in for RAND() ):
round(f), where f = sR + 0.5
trunc(f), where f = sR + 1
int(f), where f = sR + 1
will all give you the same distribution, meaning that between the three functions they are fair and none favors something more than the others. However...
#2. None of the above gets you around the uneven distribution of possible outcomes of primes not found in the factorization of the base being used (base-10, since we're using decimal; and the prime factorization of 10 is 2 and 5).
With a 10-sided die, where your equation would be
=ROUND(6*RAND()+0.5)
Your distribution of possible values is even across all ten possibilities.
However, if you use the most basic die, a 6-sided die, the distributions favor some rolls over others. Let's assume your random number can only generate down to the thousandths (0.000 ? R ? 0.999). The distribution of possible outcomes of your function are:
1: 167
2: 167
3: 166
4: 167
5: 167
6: 166
So 4 and 6 are always under-represented in the distribution by 1 less than their compatriots. This is true no matter how many decimals you allow, though the distribution gets closer and closer to equal the further towards infinite decimal places you go.
This carries over to all die whose numbers of sides do not factor down to a prime factorization of some exponential values of 2 and 5.
So, then, how can we fix this one, tiny issue in a practical manner that doesn't make our heads hurt or put unnecessary strain on the computer?
Real quick addendum to the above:
Obviously when I put the equation after the example of the 10-sided die, I meant to put a 10*RAND() instead of a 6*RAND(). Oops!
Also, where I have 0.000 ? R ? 0.999, the ?'s are supposed to be less-than-or-equal-to signs but the comments didn't like that. Oh well.
How do you keep adding up the total? I would like to have a cell which keeps adding up the total sum of the two dices, even after a new number is generated in the cells when you refresh or generate new numbers.
So, how do you simulate rolling 12 dice? Do you write int(rand()*6) 12 times?
Is there a simpler way of simulating n dice in Excel?
I've run this code in VBA
Sub generate()
Application.ScreenUpdating = False
Application.Calculation = False
Dim app, i As Long
Set app = Application.WorksheetFunction
For i = 3 To 10002
Cells(i, 3).Value = i - 2
Cells(i, 4).Value = app.RandBetween(2, 12)
Cells(i, 5).Value = app.RandBetween(1, 6) + app.RandBetween(1, 6)
Next
Application.ScreenUpdating = True
Application.Calculation = True
End Sub
But I get the same distribution for both columns 4 and 5
Why ?
@Mohammed
I would expect to get the same distribution as you have effectively used the same function