Euro, the currency used by 17 European countries, has made a record vs USD the green buck this week. It is being traded now at the rate of 1.4235$.

Wondering what is the most common value for the euro, I decided to do this small analysis. The aim is to find at which rate the euro has been traded the most in the past years. Here is my work:

- I have downloaded the historical records for euro from Forex Historical data, The settings were:

Currency: eur/usd

Data end: 02 April 2011

Number of points: 2000

Time interval: 1 day

Date output format: d/m/y

Here is the csv file I get: Q1_1D_2000

Then I did the same thing but with data ending at 20 August 2003, I get this file: Q1_1D_2000 (1)

So this study will be about the history of the Euro from **03 November 1997 till 03 April 2011 (14 years)**

- Next step was to create 2 files one for the minimum per day and the other for the maximum per day, here are these two files: min and max
- Knowing that the very minimum of the euro during the last 14 years is 0.8229 and the very maximum is 1.6041, which means a difference of 0.7812, I have decided to create an array of 9000 integers to count the number of occurrence of each value from 0.8 to 1.7 with a resolution of 0.0001 ( Integer 0 represent the rate of 0.8, integer 1 represents 0.8001, integer 2 for 0.8002 and so on till integer 8999 which represents the rate of 1.6999)
- Let’s explain what I did next through an example: At 03/12/2003 the minimum was 1.2064 the maximum during that day was 1.2129, I supposed that the euro varied uniformly from the minimum to the maximum that day, so that for each counter from 1.2064 (Integer number 4064) till 1.2129 (Integer number 4129) I add 1.
- Programming this in C#, here is the core of the code:

double[] min = File.ReadAllLines(“min.txt”).SelectMany(s => s.Split(‘ ‘)).Select(s => double.Parse(s)).ToArray();

double[] max = File.ReadAllLines(“max.txt”).SelectMany(s => s.Split(‘ ‘)).Select(s => double.Parse(s)).ToArray();int[] points = new int[9000];

int[] diff=new int[700];

int i,j;

for (i = 0; i < min.Length; i++)

{

for(j=(int)(min[i] * 10000)-8000;j<=(int)(max[i] * 10000)-8000;j++) points[j]++;

diff[(int)(max[i] * 10000) – (int)(min[i] * 10000)]++;

}

- The results are then written, I have organised them into an Excel file, here it is: Results from 1997

**Facts from 1997 till 2011:**

- Rate of 1.2799 is the one with the maximum number of occurrences of 141
- The category of 1.2-1.3 is the most probable one, taken to 0.01 resolution the category of 1.27 is the most probable one
- 50% of time euro was less than 1.235 and 50% of the time more than this value
- The arithmetic average of the euro taking in consideration the counters is 1.215
- The widest difference between a maximum and a minimum in 1 day is 0.0555, the most probable difference in one day between the maximum and the minimum is 0.0095

Now this study gives a wide vision of the euro over the last 14 years, it is not accurate because not all the countries were in euro zone all the time, to narrow the study down, I repeat it just over the last 5 years (from 1/1/2006 till now).

**Here is the new results from 1/1/2006 till now: ** Results 2006

**Facts from 2006 till 2011:**

- Rate of 1.2819 is the one with the maximum number of occurrences of 116
- The category of 1.3-1.4 is the most probable one, taken to 0.01 resolution the category of 1.27 is the most probable one
- 50% of time euro was less than 1.358 and 50% of the time more than this value
- The arithmetic average of the euro taking in consideration the counters is 1.369
- The widest difference between a maximum and a minimum in 1 day is 0.0555, the most probable difference in one day between the maximum and the minimum is 0.0106

Good afternoon! Dropped in to let you know your poem is featured today in Poetic License. Thank you again for allowing me to share it!

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