This report provides information about a company named Apex Spinning and Knitting Mills Limited (ASKML) which is incorporated as a public limited company in 1990. Apex Spinning and Knitting Mills Limited (ASKML) was initially formed for processing and exporting of readymade garments. However, subsequently, state of the art plant and equipment was added for handling all kinds of knitted fabrics and now ASKML is a leading manufacturer and exporter of all kinds of textiles knitted garments. ASKML is export oriented company with production capacity of about 15 million pieces per year. ASKML customers are spread across the Globe. The bulk of the fabrics is converted to garments in Bangladesh and then exported to different parts of the Globe. They export products to North America, EU countries and the South East Asia. In this report, we did technical forecasting of three countries where ASKML exports their product which are Canada, Belgium and Australia. We also did fundamental forecasting of Australia. For technical forecasting, we collected daily based data from 2017 to 2020. Canada and Australia exchange rate fluctuated more and after doing technical forecasting we found that Canadian and Australian currency have high possibility to strongly impact on Bangladeshi Taka either positive or negative. Belgium exchange rate also fluctuated more however furcating shows that it impacts on Bangladeshi currency will be less positive or negative. For fundamental forecasting, we collected yearly based data for fundamental forecasting from 1970 to 2019. After doing it, we found that yearly based exchange rate probability is constantly increased in the forecasting from the year of 2020 to the year of 2025. We also found that if the inflation rate and per capital income increases, the exchange rate decreases which means those are impact negatively on exchange rates. But the interest rate impacts positively on the exchange rates. That is why when the interest rate increases, the exchange rate also increases.

1. Technical & Fundamental Forecasting of
Exchange Rates and its impact on
International Trade of Apex Spinning &
Knitting Mills Limited

2. University of Liberal Arts Bangladesh
Course Title: International Financial Management
Course Code: BUS423
Section: 2
Submitted to:
Dr. Kazi Md Tarique
Assistant Professor
ULAB School of Business (USB)
Submitted by: Group 1
Name ID
Mahmuda Hossain 171011007
Songita Mondol 171011043
Ummay Sahiba Rojone 171011154
Jahid Khan Rahat 171011211
Submission Date: 13th
January, 2021.

3. Letter of Transmittal
13th January, 2021
Mr. Dr. Kazi Md Tarique
Assistant Professor, ULAB School of Business (USB)
University of Liberal Arts Bangladesh (ULAB)
Satmasjid Road, Dhanmondi 4/A, Dhaka 1209
Subject: Submission of final report
Dear Sir,
In terms of the requirement of the report, we have the pleasure to forward herewith our final
report on “Technical & Fundamental Forecasting of Exchange Rates and its impact on
International Trade of Apex Spinning & Knitting Mills Limited”. We tried our best to follow
your guidelines and direction. We use our knowledge what we learn during the course on this
work and we hope that it will meet your expectation and standard of judgement.
Thank you for your kindness and co-operation throughout the course. Consider our limitation
on this work with your kindness.
Yours sincerely,
Name ID
Mahmuda Hossain 171011007
Songita Mondol 171011043
Ummay Sahiba Rojone 171011154
Jahid Khan Rahat 171011211

4. Acknowledgement
We are thankful to Almighty Allah that He blessed us to complete this final report on
“Technical & Fundamental Forecasting of Exchange Rates and its impact on International
Trade of Apex Spinning & Knitting Mills Limited” with efficiency and finish it on time. We
would like to give our sincere gratitude to our respectable faculty Dr. Kazi Md Tarique,
Assistant Professor, ULAB School of Business (USB) for his guidance and supervision to
complete this final report on “Technical & Fundamental Forecasting of Exchange Rates and its
impact on International Trade of Apex Spinning & Knitting Mills Limited”. Our all team
members had work hard and assisted each other during the preparation of this final report. So,
we would like to thank all of our team members for their effort.

5. Executive Summary
This report provides information about a company named Apex Spinning and Knitting Mills
Limited (ASKML) which is incorporated as a public limited company in 1990.
Apex Spinning and Knitting Mills Limited (ASKML) was initially formed for processing and
exporting of readymade garments. However, subsequently, state of the art plant and equipment
was added for handling all kinds of knitted fabrics and now ASKML is a leading manufacturer
and exporter of all kinds of textiles knitted garments. ASKML is export oriented company with
production capacity of about 15 million pieces per year.
ASKML customers are spread across the Globe. The bulk of the fabrics is converted to
garments in Bangladesh and then exported to different parts of the Globe. They export products
to North America, EU countries and the South East Asia.
In this report, we did technical forecasting of three countries where ASKML exports their
product which are Canada, Belgium and Australia. We also did fundamental forecasting of
Australia.
For technical forecasting, we collected daily based data from 2017 to 2020. Canada and
Australia exchange rate fluctuated more and after doing technical forecasting we found that
Canadian and Australian currency have high possibility to strongly impact on Bangladeshi
Taka either positive or negative. Belgium exchange rate also fluctuated more however furcating
shows that it impacts on Bangladeshi currency will be less positive or negative.
For fundamental forecasting, we collected yearly based data for fundamental forecasting from
1970 to 2019. After doing it, we found that yearly based exchange rate probability is constantly
increased in the forecasting from the year of 2020 to the year of 2025. We also found that if
the inflation rate and per capital income increases, the exchange rate decreases which means
those are impact negatively on exchange rates. But the interest rate impacts positively on the
exchange rates. That is why when the interest rate increases, the exchange rate also increases.

6. Table of Contents
1.0 Introduction...................................................................................................................................... 1
2.0 Organizational Profile of Apex Spinning and Knitting Mills ........................................................... 1
2.1 Mission ......................................................................................................................................... 1
2.2 Vision ............................................................................................................................................ 1
2.3 Goals.............................................................................................................................................. 2
2.4 Values............................................................................................................................................ 2
2.5 Major Strengths ............................................................................................................................ 2
2.6 Major Clients................................................................................................................................. 2
2.7 Branches of Business..................................................................................................................... 3
3.0 Methodology ................................................................................................................................... 3
3.1 Time Series.................................................................................................................................... 4
3.2 Method.......................................................................................................................................... 4
4.0 Technical Forecasting ...................................................................................................................... 4
4.1 Technical Forecasting for Canada ................................................................................................. 5
4.2 Technical Forecasting for Belgium ............................................................................................... 7
4.3 Technical Forecasting for Australia............................................................................................... 9
5.0 Fundamental Forecasting...............................................................................................................12
5.1 Summary Output.........................................................................................................................12
5.2 Probability Output.......................................................................................................................14
6.0 Conclusion ......................................................................................................................................16
Appendix Table:1.....................................................................................................................17
Appendix Table:2.....................................................................................................................20
Reference: 1.............................................................................................................................21
Reference: 2.............................................................................................................................21

7. 1.0 Introduction
Currency fluctuation is a natural outcome of floating exchange rates. It is the norm for most
major economies system. Several factors influence exchange rates in Bangladesh. But in this
report, we will focus on interest rate, income of people and inflation effect on the exchange
rate. However, technical and fundamental forecasting will be conducting to predict the
exchange rate. Here we typically determined by the strength or weakness of Apex Spinning
and Knitting Mills international trade based on exchange rate.
2.0 Organizational Profile of Apex Spinning and Knitting Mills
Apex Spinning and Knitting Mills Limited (ASKML) is a 100% export oriented vertically
integrated knitting, dyeing, and finishing and garment factory. The company produces
readymade garment for boys, girls and ladies and men. It was incorporated in 1990. The
company is listed in Dhaka Stock Exchange and Chittagong Stock Exchange in 1994. The
Company produces all-over printed fabrics (reactive, disperse, acid and pigments) using a
range of designs provided by the buyer and/or from its design department. It has over 52 sewing
lines, which are equipped to produce garments. The fifty-two sewing lines are set up to
efficiently produce 2.8 to 3.0 million pieces of garments per month. The Company produces
fabrics ranging from 100% cotton, polyester, nylon, melange, micro-fibers and numerous
blends with or without spandex and yarn dyed or solid dyed fabrics. Its fabric printing includes
all over printing and placement printing sections.
2.1 Mission
To strive hard to be a provider of world class textile and garment products and services and
position the country in the higher value segment of the international textile market.
2.2 Vision
ASKML’s relentless endeavor is towards contributing to the national economic advancement
in a global context by enhancing the country's image as an international provider of quality
products and services.
Page 1

8. 2.3 Goals
To satisfy the customers through technological superiority and synergic synchronization of
man and machine tailoring quality products and services to harvest the reward of responsibility.
2.4 Values
To create a better future for the stakeholders, by maintaining high standards of integrity,
propriety and goodwill in social responsibilities. To assimilate efficient, innovative and state-
of-the-art technology for developing operational infrastructure and to establish linkages and
integrations. To foster conductive environment to groom-up productive talents and to build up
mutually rewarding relationships with employees, clients and the society based on the highest
standard of professionalism.
2.5 Major Strengths
ASKML strength is derived from the strong belief that the social welfare of their employees
and surrounding community is not only necessary but also essential to building a sustainable
organization.
• ASKML have more than 5,995 total employees.
• The company has more than 52 total lines.
• Their total Capacity is 3.0M per month.
• The company gets more that 85% Mobile Payment.
2.6 Major Clients
Page 2

9. 2.7 Branches of Business
ASKML is export oriented company with production capacity of about 15 million pieces per
year. The company exports to North America, EU countries and the South East Asia. We
selected three countries to know the technical analysis and fundamental analysis of ASKML.
The three countries are Australia, Belgium and Canada.
Here we can see that from these three countries, ASKML got higher export revenue from
Belgium in the past 4 years. The lowest amount of export revenue got from Australia among
these three countries in past 4 years.
3.0 Methodology
This study is based on secondary data analysis of the apex spinning and knitting data set of
Technical & Fundamental Forecasting of Exchange Rates. The sources of secondary data are
considered like website:
• https://excelrates.com/
• https://databank.worldbank.org/.../1ff.../Popular-Indicators
Reason for secondary data: The data is already collected, and we do not need to invest any
money, time, or effort into the data collection stages of our study.
419,822
252,453 206,571 302,081
5,656,160
3,780,960 3,800,246
3,191,641
765,155
483,395 545,654 542,792
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
2016 2017 2018 2019
Revenue
in
USD
Years
Export Revenue
Australia Belgium Canada
Page 3

10. 3.1 Time Series
For fundamental forecasting, this research will take place yearly spot exchange rate for USD
on the other hand, technical forecasting will take place daily spot exchange rate for USD.
Forecasting Time Series Data Type Observe Data
Technical Forecasting 22 October 2017 to 7 January 2021 Daily Based 1,174
Fundamental Forecasting 1970 to 2020 Yearly Based 50
3.2 Method
We will use excel forecast formula to find out the 2 years technical prediction of exchange rate.
For fundamental analysis we select dependent variable X as interest, inflation and income of
the people and select independent variable Y as exchange rate. It is done by using excel analysis
regression formula. The formula and step are given below:
Forecasting Formula
Technical Forecasting =FORECAST.LINEAR(x, known year, known xs)
Fundamental Forecasting Step: 1 Data analysis
Step: 2 Select Regression
Step: 3 Select dependent and independent variable.
Step: 4 Select normal probability plot
Step: 5 Create the plot
4.0 Technical Forecasting
For technical forecasting analysis, among the various countries where Apex Spinning and
Knitting Mills Limited (ASKML) exports their products we selected three countries, these
countries are Canada, Belgium and Australia. We collected the daily based data for these three
countries. We collected data on 6 January, 2021. So, from the date of 7 January, 2021 we made
forecasting for the technical analysis. We firstly collected the exchange rates according to the
US Dollar. Then we converted the exchange rates according to the Bangladeshi Taka, so that
we can understand the effect of exchange rates of Canada, Belgium and Australia in the
Bangladeshi Taka in the future by forecasting with the help of previous data. The previous and
Page 4

11. historical data as well as the most important thing of the report that is forecasted data for
Canada, Belgium and Australia are presented below:
4.1 Technical Forecasting for Canada
Date BDT C AD Upper Confidence Lower Confidence
08 Jan 2021 1 0.015056807 0.01 0.02
09 Jan 2021 1 0.015032058 0.01 0.02
10 Jan 2021 1 0.015081611 0.01 0.02
11 Jan 2021 1 0.015027538 0.01 0.02
12 Jan 2021 1 0.015059521 0.01 0.02
13 Jan 2021 1 0.015110749 0.01 0.02
14 Jan 2021 1 0.015140709 0.01 0.02
15 Jan 2021 1 0.015156388 0.01 0.02
16 Jan 2021 1 0.015174435 0.01 0.02
17 Jan 2021 1 0.015111429 0.01 0.02
18 Jan 2021 1 0.01513064 0.01 0.02
19 Jan 2021 1 0.015116017 0.01 0.02
20 Jan 2021 1 0.015147983 0.01 0.02
21 Jan 2021 1 0.015270696 0.01 0.02
22 Jan 2021 1 0.015134186 0.01 0.02
23 Jan 2021 1 0.015103056 0.01 0.02
24 Jan 2021 1 0.015108884 0.01 0.02
25 Jan 2021 1 0.01509051 0.01 0.02
26 Jan 2021 1 0.015119829 0.01 0.02
27 Jan 2021 1 0.015080976 0.01 0.02
28 Jan 2021 1 0.015010004 0.01 0.02
29 Jan 2021 1 0.015004906 0.01 0.02
30 Jan 2021 1 0.014919557 0.01 0.02
31 Jan 2021 1 0.014957256 0.01 0.02
01 Feb 2021 1 0.014994001 0.01 0.02
02 Feb 2021 1 0.014969221 0.01 0.02
03 Feb 2021 1 0.01491541 0.01 0.02
04 Feb 2021 1 0.014962356 0.01 0.02
05 Feb 2021 1 0.014932947 0.01 0.02
06 Feb 2021 1 0.015024415 0.01 0.02
07 Feb 2021 1 0.015084141 0.01 0.02
08 Feb 2021 1 0.015040146 0.01 0.02
09 Feb 2021 1 0.015032145 0.01 0.02
10 Feb 2021 1 0.014964224 0.01 0.02
11 Feb 2021 1 0.015022462 0.01 0.02
12 Feb 2021 1 0.015119129 0.01 0.02
13 Feb 2021 1 0.015062556 0.01 0.02
14 Feb 2021 1 0.01505481 0.01 0.02
Page 5

12. 15 Feb 2021 1 0.015048182 0.01 0.02
16 Feb 2021 1 0.015072095 0.01 0.02
17 Feb 2021 1 0.015017873 0.01 0.02
18 Feb 2021 1 0.01504838 0.01 0.02
19 Feb 2021 1 0.015075328 0.01 0.02
20 Feb 2021 1 0.015014447 0.01 0.02
21 Feb 2021 1 0.014971386 0.01 0.02
22 Feb 2021 1 0.015017779 0.01 0.02
23 Feb 2021 1 0.015055939 0.01 0.02
24 Feb 2021 1 0.015086501 0.01 0.02
25 Feb 2021 1 0.015033988 0.01 0.02
26 Feb 2021 1 0.015032508 0.01 0.02
27 Feb 2021 1 0.01507497 0.01 0.02
28 Feb 2021 1 0.015094298 0.01 0.02
Table-1: Showed Canadian Doller against BDT
Graph-1: Showed Canadian Doller against BDT
In the graph, all the data are the historical and forecasted data of the exchange rates of Canada
from 22 October, 2017 to 22 April 2022. All the data from 22 October, 2017 to 6 January, 2021
are previous data and indicates in color blue. After that area in the graph, from 7 January, 2021
to 22 April, 2022 are the forecasting data and indicates in color red in the graph. In the
forecasting, there are three indicators in the graph. In the middle, the thick bold line is the most
possible forecasting area. The upper line is the upper confidence bound and the lower line is
the lower confidence bound. We took the confidence level 95% here.
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
0.02
22
Oct
2017
02
Dec
2017
12
Jan
2018
22
Feb
2018
04
Apr
2018
15
May
2018
25
Jun
2018
05
Aug
2018
15
Sep
2018
26
Oct
2018
06
Dec
2018
16
Jan
2019
26
Feb
2019
08
Apr
2019
19
May
2019
29
Jun
2019
09
Aug
2019
19
Sep
2019
30
Oct
2019
10
Dec
2019
20
Jan
2020
01
Mar
2020
11
Apr
2020
22
May
2020
02
Jul
2020
12
Aug
2020
22
Sep
2020
02
Nov
2020
13
Dec
2020
23
Jan
2021
05
Mar
2021
15
Apr
2021
26
May
2021
06
Jul
2021
16
Aug
2021
26
Sep
2021
06
Nov
2021
17
Dec
2021
27
Jan
2022
09
Mar
2022
19
Apr
2022
CAD Forecast(CAD) Lower Confidence Bound(CAD) Upper Confidence Bound(CAD)
Page 6

13. If the economic factors that influences the exchange rates make effects positively, then the
exchange rates will be increased, and it may reach the upper confidence bound. And if the
economic factors that influences the exchange rates make effects negatively, then the exchange
rates will be decreased, and it may reach the lower confidence bound.
Here we can see that, the exchange rate of Canada is fluctuating more often in the historical
data and also very fluctuating in the forecasted data and also the possible fluctuating area is
large. So, this Canadian currency CAD have high possibility to make either strong positive or
negative impact on Bangladeshi Taka and also in the Export of Apex Spinning and Knitting
Mills Limited according to the forecasted area, and also from the historical data, exchange rate
can be fluctuated as the previous years.
4.2 Technical Forecasting for Belgium
Date BDT EUR Upper Confidence Lower Confidence
08 Jan 2021 1 0.009679573 0.01 0.01
09 Jan 2021 1 0.009679317 0.01 0.01
10 Jan 2021 1 0.00967906 0.01 0.01
11 Jan 2021 1 0.009678804 0.01 0.01
12 Jan 2021 1 0.009678548 0.01 0.01
13 Jan 2021 1 0.009678291 0.01 0.01
14 Jan 2021 1 0.009678035 0.01 0.01
15 Jan 2021 1 0.009677779 0.01 0.01
16 Jan 2021 1 0.009677523 0.01 0.01
17 Jan 2021 1 0.009677266 0.01 0.01
18 Jan 2021 1 0.00967701 0.01 0.01
19 Jan 2021 1 0.009676754 0.01 0.01
20 Jan 2021 1 0.009676497 0.01 0.01
21 Jan 2021 1 0.009676241 0.01 0.01
22 Jan 2021 1 0.009675985 0.01 0.01
23 Jan 2021 1 0.009675728 0.01 0.01
24 Jan 2021 1 0.009675472 0.01 0.01
25 Jan 2021 1 0.009675216 0.01 0.01
26 Jan 2021 1 0.00967496 0.01 0.01
27 Jan 2021 1 0.009674703 0.01 0.01
28 Jan 2021 1 0.009674447 0.01 0.01
29 Jan 2021 1 0.009674191 0.01 0.01
30 Jan 2021 1 0.009673934 0.01 0.01
31 Jan 2021 1 0.009673678 0.01 0.01
01 Feb 2021 1 0.009673422 0.01 0.01
02 Feb 2021 1 0.009673165 0.01 0.01
03 Feb 2021 1 0.009672909 0.01 0.01
Page 7

14. 04 Feb 2021 1 0.009672653 0.01 0.01
05 Feb 2021 1 0.009672397 0.01 0.01
06 Feb 2021 1 0.00967214 0.01 0.01
07 Feb 2021 1 0.009671884 0.01 0.01
08 Feb 2021 1 0.009671628 0.01 0.01
09 Feb 2021 1 0.009671371 0.01 0.01
10 Feb 2021 1 0.009671115 0.01 0.01
11 Feb 2021 1 0.009670859 0.01 0.01
12 Feb 2021 1 0.009670602 0.01 0.01
13 Feb 2021 1 0.009670346 0.01 0.01
14 Feb 2021 1 0.00967009 0.01 0.01
15 Feb 2021 1 0.009669834 0.01 0.01
16 Feb 2021 1 0.009669577 0.01 0.01
17 Feb 2021 1 0.009669321 0.01 0.01
18 Feb 2021 1 0.009669065 0.01 0.01
19 Feb 2021 1 0.009668808 0.01 0.01
20 Feb 2021 1 0.009668552 0.01 0.01
21 Feb 2021 1 0.009668296 0.01 0.01
22 Feb 2021 1 0.009668039 0.01 0.01
23 Feb 2021 1 0.009667783 0.01 0.01
24 Feb 2021 1 0.009667527 0.01 0.01
25 Feb 2021 1 0.00966727 0.01 0.01
26 Feb 2021 1 0.009667014 0.01 0.01
27 Feb 2021 1 0.009666758 0.01 0.01
28 Feb 2021 1 0.009666502 0.01 0.01
Table -2: Showed Belgium Euro against BDT
Graph-2: Showed Belgium Euro against BDT
0
0.002
0.004
0.006
0.008
0.01
0.012
22
Oct
2017
28
Nov
2017
04
Jan
2018
10
Feb
2018
19
Mar
2018
25
Apr
2018
01
Jun
2018
08
Jul
2018
14
Aug
2018
20
Sep
2018
27
Oct
2018
03
Dec
2018
09
Jan
2019
15
Feb
2019
24
Mar
2019
30
Apr
2019
06
Jun
2019
13
Jul
2019
19
Aug
2019
25
Sep
2019
01
Nov
2019
08
Dec
2019
14
Jan
2020
20
Feb
2020
28
Mar
2020
04
May
2020
10
Jun
2020
17
Jul
2020
23
Aug
2020
29
Sep
2020
05
Nov
2020
12
Dec
2020
18
Jan
2021
24
Feb
2021
02
Apr
2021
09
May
2021
15
Jun
2021
22
Jul
2021
28
Aug
2021
04
Oct
2021
EUR Forecast(EUR) Lower Confidence Bound(EUR) Upper Confidence Bound(EUR)
Page 8

15. In the graph, all the data are the historical and forecasted data of the exchange rates of Belgium
from 22 October, 2017 to 22 April 2022. All the data from 22 October, 2017 to 6 January, 2021
are previous data and indicates in color blue. After that area in the graph, from 7 January, 2021
to 22 April, 2022 are the forecasting data and indicates in color red in the graph. In the
forecasting, there are three indicators in the graph. In the middle, the thick bold line is the most
possible forecasting area. The upper line is the upper confidence bound and the lower line is
the lower confidence bound. We took the confidence level 95% here.
If the economic factors that influences the exchange rates make effects positively, then the
exchange rates will be increased, and it may reach the upper confidence bound. And if the
economic factors that influences the exchange rates make effects negatively, then the exchange
rates will be decreased, and it may reach the lower confidence bound.
Here we can see that, the exchange rate of Belgium is also fluctuating in the historical data, but
less fluctuating in the forecasted data and also the possible fluctuating area is not very large.
So, as the graph this Belgium currency EUR have less possibility to make strong positive and
negative impact on Bangladeshi Taka and also in the Export of Apex Spinning and Knitting
Mills Limited according to the forecasted area, but from the historical data, exchange rate can
be fluctuated as the previous years.
4.3 Technical Forecasting for Australia
Date BDT EUR Upper Confidence Lower Confidence
08 Jan 2021 1 0.015297667 0.02 0.02
09 Jan 2021 1 0.015298286 0.02 0.02
10 Jan 2021 1 0.015298906 0.01 0.02
11 Jan 2021 1 0.015299525 0.01 0.02
12 Jan 2021 1 0.015300145 0.01 0.02
13 Jan 2021 1 0.015300764 0.01 0.02
14 Jan 2021 1 0.015301384 0.01 0.02
15 Jan 2021 1 0.015302003 0.01 0.02
16 Jan 2021 1 0.015302623 0.01 0.02
17 Jan 2021 1 0.015303242 0.01 0.02
18 Jan 2021 1 0.015303862 0.01 0.02
19 Jan 2021 1 0.015304481 0.01 0.02
20 Jan 2021 1 0.015305101 0.01 0.02
21 Jan 2021 1 0.01530572 0.01 0.02
22 Jan 2021 1 0.01530634 0.01 0.02
23 Jan 2021 1 0.015306959 0.01 0.02
24 Jan 2021 1 0.015307579 0.01 0.02
Page 9

16. 25 Jan 2021 1 0.015308198 0.01 0.02
26 Jan 2021 1 0.015308817 0.01 0.02
27 Jan 2021 1 0.015309437 0.01 0.02
28 Jan 2021 1 0.015310056 0.01 0.02
29 Jan 2021 1 0.015310676 0.01 0.02
30 Jan 2021 1 0.015311295 0.01 0.02
31 Jan 2021 1 0.015311915 0.01 0.02
01 Feb 2021 1 0.015312534 0.01 0.02
02 Feb 2021 1 0.015313154 0.01 0.02
03 Feb 2021 1 0.015313773 0.01 0.02
04 Feb 2021 1 0.015314393 0.01 0.02
05 Feb 2021 1 0.015315012 0.01 0.02
06 Feb 2021 1 0.015315632 0.01 0.02
07 Feb 2021 1 0.015316251 0.01 0.02
08 Feb 2021 1 0.015316871 0.01 0.02
09 Feb 2021 1 0.01531749 0.01 0.02
10 Feb 2021 1 0.01531811 0.01 0.02
11 Feb 2021 1 0.015318729 0.01 0.02
12 Feb 2021 1 0.015319349 0.01 0.02
13 Feb 2021 1 0.015319968 0.01 0.02
14 Feb 2021 1 0.015320588 0.01 0.02
15 Feb 2021 1 0.015321207 0.01 0.02
16 Feb 2021 1 0.015321827 0.01 0.02
17 Feb 2021 1 0.015322446 0.01 0.02
18 Feb 2021 1 0.015323066 0.01 0.02
19 Feb 2021 1 0.015323685 0.01 0.02
20 Feb 2021 1 0.015324305 0.01 0.02
21 Feb 2021 1 0.015324924 0.01 0.02
22 Feb 2021 1 0.015325544 0.01 0.02
23 Feb 2021 1 0.015326163 0.01 0.02
24 Feb 2021 1 0.015326782 0.01 0.02
25 Feb 2021 1 0.015327402 0.01 0.02
26 Feb 2021 1 0.015328021 0.01 0.02
27 Feb 2021 1 0.015328641 0.01 0.02
28 Feb 2021 1 0.01532926 0.01 0.02
Table -3: Showed Australian Doller against BDT
Page 10

17. Graph -3: Showed Australian Doller against BDT
In the graph, all the data are the historical and forecasted data of the exchange rates of Australia
from 22 October, 2017 to 22 April 2022. All the data from 22 October, 2017 to 6 January, 2021
are previous data and indicates in color blue. After that area in the graph, from 7 January, 2021
to 22 April, 2022 are the forecasting data and indicates in color red in the graph. In the
forecasting, there are three indicators in the graph. In the middle, the thick bold line is the most
possible forecasting area. The upper line is the upper confidence bound and the lower line is
the lower confidence bound. We took the confidence level 95% here.
If the economic factors that influences the exchange rates make effects positively, then the
exchange rates will be increased, and it may reach the upper confidence bound. And if the
economic factors that influences the exchange rates make effects negatively, then the exchange
rates will be decreased, and it may reach the lower confidence bound.
Here we can see that, the exchange rate of Australia is also very fluctuating in the historical
data, but less fluctuating in the forecasted data and the possible fluctuating area is large. In the
previous data, at a point that is in the month of March, 2020 the rate was so mush fluctuating
and was so high and just before the forecasting period the rate was also very fluctuating and
was very low. This Australian currency AUD have possibility to make strong positive and
negative impact on Bangladeshi Taka and also in the Export of Apex Spinning and Knitting
0
0.005
0.01
0.015
0.02
0.025
22
Oct
2017
28
Nov
2017
04
Jan
2018
10
Feb
2018
19
Mar
2018
25
Apr
2018
01
Jun
2018
08
Jul
2018
14
Aug
2018
20
Sep
2018
27
Oct
2018
03
Dec
2018
09
Jan
2019
15
Feb
2019
24
Mar
2019
30
Apr
2019
06
Jun
2019
13
Jul
2019
19
Aug
2019
25
Sep
2019
01
Nov
2019
08
Dec
2019
14
Jan
2020
20
Feb
2020
28
Mar
2020
04
May
2020
10
Jun
2020
17
Jul
2020
23
Aug
2020
29
Sep
2020
05
Nov
2020
12
Dec
2020
18
Jan
2021
24
Feb
2021
02
Apr
2021
09
May
2021
15
Jun
2021
22
Jul
2021
28
Aug
2021
04
Oct
2021
AUD Forecast(AUD) Lower Confidence Bound(AUD) Upper Confidence Bound(AUD)
Page 11

18. Mills Limited according to the forecasted area, and also from the historical data, exchange rate
can be so much fluctuated as the previous years.
5.0 Fundamental Forecasting
As Apex Spinning and Knitting Mills Limited (ASKML) is an export-oriented company and
the exports its product in various countries of the world. Among these countries, we did the
fundamental forecasting analysis on the country Australia. We collected yearly based data for
fundamental forecasting from 1970 to 2019. That means, we took the previous and historical
data for 50 years. We took the data for 50 years of three major macroeconomic factors and
these are inflation rate, per capita income and interest rate. Then we forecasted exchange rates
for six years from 2020 to 2025.
5.1 Summary Output
Regression Statistics
Multiple R 0.874235
R Square 0.764287
Adjusted R Square 0.748914
Standard Error 0.000176
Observations 50
Here in the above table, the regression statistics what we calculated in the Excel are presented.
0.874235 is the value of multiple R, R square is 0.764287 that means 76.43%. So, the relation
between the macroeconomic variables and the exchange rates are quite high. That means, the
fluctuations and changes in the variables will have impact in the exchange rate changes and its
fluctuations. The adjusted R square is 0.748914 that means 74.89% which is also high. The
standard error is 0.000176 and the total observation is 50.
ANOVA
df SS MS F Significance F
Regression 3 4.59E-06 1.53E-06 49.71752 1.78E-14
Residual 46 1.42E-06 3.08E-08
Total 49 6.01E-06
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19. Coefficients Standard
Error
t Stat P-value Lower
95%
Upper
95%
Intercept 0.016486 0.000102 161.8928 4.68E-65 0.016281 0.016691
Inflation Rate (%) -1.5E-05 9.24E-06 -1.62884 0.110178 -3.4E-05 3.55E-06
Per Capital Income
(USD)
-1.8E-08 1.89E-09 -9.26128 4.41E-12 -2.1E-08 -1.4E-08
Real Interest Rate 5.83E-06 8.73E-06 0.668052 0.507439 -1.2E-05 2.34E-05
Here from the above table, in the left side the variables are the major three macroeconomic
variables. Variable 1 is inflation rate, variable 2 is per capita income and variable 3 is interest
rate. The coefficient indicates the relationship among these three macroeconomic variables
(inflation rate, per capita income, interest rate) and the exchange rates.
From the table, we can see that the coefficient is negative in variable 1 that means, the inflation
rate has negative impact on the exchange rates. So, if the inflation rate increases, the exchange
rate decreases. We can also see from the table that, the coefficient is negative in variable 2 that
means, the per capita income has also negative impact on the exchange rates. So, if the per
capita income increases, the exchange rate decreases. On the other hand, we can see from the
table that the coefficient is positive in variable 3 that means, the interest rate has positive impact
on the exchange rates. So, if the interest rate increases, the exchange rate also increases.
We can also see the standard error, t stat, P -value, lower bound and upper value of the variable
1, variable 2, variable 3, these three macroeconomic variables and also the intercepts.
Page 13
-15
-10
-5
0
5
10
15
20
25
30
Historical Data
Inflation Rate (%) Real Interest Rate Per capital Growth

20. As we mentioned before that, we collected data of 50 years from the year of 1970 to 2019. In
the graph we can see the comparisons of three factors over this period of years. Here we can
see that, the factors are not constant but very fluctuating. And as the factors have either negative
or positive strong impact on the exchange rates, that’s so much fluctuating in the factors is one
of the major reasons of changes in the exchange rates. So, the exchange rates also fluctuate as
a result what we have shown and mentioned in the technical analysis.
5.2 Probability Output
Year Forecasted Australian Doller
2020 0.015126
2021 0.015228
2022 0.015297
2023 0.015309
2024 0.015337
2025 0.015339
Table -4: Showed Australian Doller against BDT
Here from the table and from the scatter chart, the yearly based exchange rate probability is
constantly increased in the forecasting from the year of 2020 to the year of 2025. The
probability is 0.015126 in the year of 2020, and then the probability is 0.015228 in the year of
2021, the probability is 0.015297 in the year of 2022, the probability is 0.015309 in the year
of 2023, the probability is 0.015337 in the year of 2024, and the probability is 0.015339 in
the year of 2025 from the forecasted exchange rate probability shown in the table and in the
scatter chart.
Graph -4: Showed Australian Doller against BDT
0.015125604
0.015227639
0.015297047
0.015309342
0.015337438 0.015339254
0.0151
0.01515
0.0152
0.01525
0.0153
0.01535
2019 2020 2021 2022 2023 2024 2025 2026
Year
Exchange Rate Probability Plot
Page 14

21. Therefore, if the exchange rate or the exchange probability will increase in Australia in the
future according to the forecasting from the impact of three macroeconomic variables which
are inflation rate, per capita income and interest rate of Australia, it will directly impact on the
exports and imports of Australia with other countries. As in the forecasting data indicates the
rises in the exchange rates of Australia and if the probability of forecasted exchange rates will
turn real in the future then it definitely will make changes in the exports and imports of
Australia as well as in the exports and imports of other related countries which countries have
trading with Australia.
If the exchange rates will increase in Australia, the exports in other trading countries of
Australia will be decreased for the increased prices of exported goods and commodities. On
the other hand, if the Australian exchange rates will increase in future, the foreign trade will
increase, as well as the imports from other trading counties of Australia will be also increased
for the decreased prices of imported goods and commodities.
The increase and decrease in exports and imports will also impact the exports and imports of
Bangladesh. Thus, it will impact the exports of Apex Spinning and Knitting Mills Limited
(ASKML). Because, if the imports of Australia will increase in future that means the exports
of Apex Spinning and Knitting Mills Limited (ASKML) Bangladeshi company’s export will
also increase because this company exports their products in Australia. So, it the exchange rates
will increase in Australia, the imports will also increase from the outside trading countries. So
that, the Australian people will import their goods and commodities from the outside export-
oriented companies like Apex Spinning and Knitting Mills Limited (ASKML) company and
that’s the reason that their exports might be increased in the future.
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22. 6.0 Conclusion
For the purpose of our report, we selected the garment industry among all other industry firstly.
Then we selected a company of garment industry which is Apex Spinning and Knitting Mills
Limited (ASKML) Company. It is mainly an export-oriented company what we mentioned
before. In our report, we gave short explanation about the company, its mission, vision, goals,
values, major strengths, major clients of the company, some exports country of the company.
Among those exports country we selected three exports countries of the company, Australia,
Belgium and Canada for doing the technical forecasting analysis for our report. We have shown
in a chart, the export revenues generated from exporting to these three countries. In the
technical forecasting analysis, the fluctuating of exchange rates in Australia, Belgium and in
Canada in the previous daily based data and based on those data we forecasted the future
possible exchange rates and the possible fluctuating area. In the fundamental forecasting
analysis, the impact of three macroeconomic variables inflation rate, per capita income and
interest rate, how the trading system will react, the impact on the exports and imports of
Australia and how the impacts related with the exports of our selected company, forecasting
the future exchange rate with the impact of macroeconomic variables based on the historical
data, all these things we have tried to present in our report. In the methodology part of our
report, we have mentioned the techniques we have used for calculating the technical and
fundamental forecasting analysis.
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23. Page 17
Appendix Table:1

24. Page 18

25. Page 19

26. Date Inflation
Rate (%)
Per Capital
Income (USD)
Real Interest Rate
(%)
Exchange rate Per capital
Growth (%)
12/31/1970 3.4392 3270 7.108333333 0.01624483
12/31/1971 6.1381 3470 7.008333333 0.016191658 6.116207951
12/31/1972 6.0241 3880 5.083333333 0.016191658 11.81556196
12/31/1973 9.0909 4640 6.983333333 0.016191658 19.58762887
12/31/1974 15.4167 5940 13.15833333 0.016236559 28.01724138
12/31/1975 15.1625 7210 8.525 0.016323999 21.38047138
12/31/1976 13.3229 7850 9.24 0.016328725 8.876560333
12/31/1977 12.3098 8070 10.2125 0.016221198 2.802547771
12/31/1978 8.0049 8460 9.843333333 0.016255465 4.832713755
12/31/1979 9.122 9580 9.773333333 0.016255465 13.23877069
12/31/1980 10.1358 10810 12.0275 0.016255465 12.83924843
12/31/1981 9.4877 11850 15.03833333 0.016223561 9.620721554
12/31/1982 11.3518 12060 16.83416667 0.016091113 1.772151899
12/31/1983 10.0389 11570 12.19916667 0.015991975 -4.063018242
12/31/1984 3.9604 12010 12.1 0.016027381 3.802938634
12/31/1985 6.7347 11990 15.9825 0.016051421 -0.166527893
12/31/1986 9.0504 12280 16.45166667 0.016062788 2.418682235
12/31/1987 8.533 12530 13.75 0.016041961 2.035830619
12/31/1988 7.2159 14100 12.8 0.016285849 12.52992817
12/31/1989 7.5339 15560 17.61166667 0.016389708 10.35460993
12/31/1990 7.333 17300 14.54333333 0.016455801 11.18251928
12/31/1991 3.1767 18190 10.22583333 0.016138438 5.144508671
12/31/1992 1.0122 18500 6.465833333 0.016147104 1.704233095
12/31/1993 1.7537 18860 5.151666667 0.016195678 1.945945946
12/31/1994 1.9696 18830 5.656666667 0.016132799 -0.159066808
12/31/1995 4.6278 19250 7.725833333 0.016251634 2.230483271
12/31/1996 2.6154 20440 7.151666667 0.016228497 6.181818182
12/31/1997 0.2249 21900 5.395833333 0.016262268 7.142857143
12/31/1998 0.8601 21740 5.001666667 0.016247178 -0.730593607
12/31/1999 1.4831 21430 5.011666667 0.016178072 -1.425942962
12/31/2000 4.4574 21120 6.1775 0.016207019 -1.446570229
12/31/2001 4.4071 20110 4.899166667 0.016301548 -4.78219697
12/31/2002 2.9816 19990 4.746666667 0.015974611 -0.596718051
12/31/2003 2.7326 21120 4.895833333 0.016127078 5.652826413
12/31/2004 2.3433 25480 5.478333333 0.016101835 20.64393939
12/31/2005 2.6918 30310 5.644166667 0.016065632 18.95604396
12/31/2006 3.5553 34090 5.988333333 0.016087472 12.47113164
12/31/2007 2.3276 37300 6.6675 0.016081754 9.4162511
12/31/2008 4.3503 42330 6.973333333 0.016083659 13.48525469
12/31/2009 1.7711 44050 3.434166667 0.015966118 4.063312072
12/31/2010 2.9183 46630 4.683333333 0.015936853 5.856980704
12/31/2011 3.3039 50320 4.848333333 0.015297047 7.913360498
12/31/2012 1.7628 60210 3.728333333 0.015125604 19.65421304
12/31/2013 2.4499 66020 2.78 0.015398031 9.649559874
12/31/2014 2.4879 65150 2.678333333 0.015375668 -1.31778249
12/31/2015 1.5084 60500 2.255833333 0.015227639 -7.137375288
12/31/2016 1.277 54140 1.988333333 0.015309342 -10.51239669
12/31/2017 1.9486 51600 1.74 0.015339254 -4.691540451
12/31/2018 1.9114 53250 1.948333333 0.015337438 3.197674419
12/31/2019 1.6108 54910 1.344166667 0.015444431 3.117370892
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Appendix Table: 2

27. Reference: 1
Title: Download historical exchange rates from the ECB to excel
Website title: Excelrates.com
URL: https://excelrates.com/
Reference: 2
Title: World Development Indicators | DataBank
Website title: Databank.worldbank.org
URL: https://databank.worldbank.org/indicator/FP.CPI.TOTL.ZG/1ff4a498/Popular-
Indicators
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