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Computing an Average

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CREATING A COMPUTE STATEMENT:

We are working on CAD and EURO. Various components determine trade rates. Huge numbers of these variables are identified with the exchanging connection between two nations, CAD and the EURO. Keep in mind that trade rates are relative and communicated as an examination of the monetary forms of two nations. A portion of the chief determinants of the scale of conversion between two nations are coming up next. Note that these components are in no specific request; the overall significance of these elements is subject to much discussion in the same way as other parts of financial aspects. Here we calculate the exchange rate percentage throughout the year.

[pic 1]

Figure.1: Percentage change in exchange rate

Computing an Average: Exchange rates are defined as the price of one country's' currency in relation to another. Exchange rates may be expressed at the end of the period as the average rate for a period of time or as the rate. The International Monetary Fund classifies exchange rates into three broad categories, reflecting the authorities ' role in determining exchange rates and/or the multiplicity of exchange rates in a country. In the 2014 graph average exchange rate is (-2 %), in 2015 (-19 %), in 2016 (-24 %), in 2017 (-32 %) and in 2018 (-50 %). So we can see that the average exchange rate is gradually increasing over the year.

[pic 2]

Standard Deviation:

A standard deviation is a number used to tell how estimations for a gathering are spread out from the normal (mean), or anticipated esteem. A low standard deviation implies that the larger number is exceptionally close to normal. An elevated deviation of expectation implies the numbers are spread out. Here we show the standard deviation between the euro and CAD exchange rates from 2014 to 2018.

[pic 3]

Fundamental of Regression Analysis:

Regression analysis to measure relationships between variable when established policies. Regression analysis is one of the most used and most powerful multivariate statistical techniques for it infers the existence and form of a functional relationship in the currency. Using the relationship detected it then forecast the future level of accounts receivable based on a forecast of sales or measured by economic growth and interest rate. We work on the CAD interest rate and growth rate and also European interest rate and growth rate. We tried to find out the regression analysis of those interest rate and growth rate.

Basically we want to discuss four types of regression analysis:

  1. Specifying the regression model
  2. Compiling the data
  3. Estimating the regression coefficient
  4. Interpreting the regression result

Specifying the regression model:

Assume that our main goal is to determine the relationship between percentage change in Canadian export to European (CEXP) and percentage in the value of the European dollar (CEURO). Here is the dependent variable is growth rate and the independent variable is interest rate.  

Compiling the data:

Given bellow the CEXP, CEURO, AND CGDP in 5 years (2014- 2018).

period

CEXP

CEURO

CGDP

2014

0.492307692

-0.038461538

-0.119066579

2015

0.536

-0.032

0.004580101

2016

0.47107438

0.165289256

0.047650174

2017

0.365248227

0.056737589

0.057212476

2018

0.476510067

-1

-1

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