Secondary data analysis of Pakistan key macroeconomic variables on the KSE_100_Index. The analysis provide a ready insight to descriptive statistics, correlation, linear & multi-stage regression, qualitative & quantitative forecast patterns and much more. For the study,IBM SPSS and Microsoft EXCEL solution is used. Secondary data is sourced from trending economics for 18-years (wef January 2000 to June 2018)
Noah Blanton's Drivers of Supply and Demand for Oregon Real Estate Market UpdateAaron Stelle
Noah’s Drivers of Supply and Demand:
A clearer picture is emerging in Oregon.
· Where is the real estate market in the Portland area and where is it likely headed?
· Are people still moving to Oregon?
· What is the hidden risk of low interest rates? Are they going up or down?
· Is the local economy recovering and should we be concerned with the employment rate?
· Is there a long lasting housing shortage building?
· Is there a foreclosure surge just around the corner?
2 Effective Strategies to Transform Your Net Profit. FAST.Victor Ang
These slides show the 4 common methods most CEOs use to transform their Net Profit but to no avail.
There are only 2 most effective strategies to transform your Net Profit as shown in these slides.
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I can be reached at www.victor@crossbowconsultinggroup.com to answer any questions that you may have.
Thanks for watching this slide show.
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www.crossbowconsultinggroup.com
victor@crossbowconsultinggroup.com
Epic Research is performing a basic role as a leading financial advisory firm by providing good recommendations for,KLSE Stocks, Comex and Forex and all other segments with the help of experts and it maintains high accuracy.
Noah Blanton's Drivers of Supply and Demand for Oregon Real Estate Market UpdateAaron Stelle
Noah’s Drivers of Supply and Demand:
A clearer picture is emerging in Oregon.
· Where is the real estate market in the Portland area and where is it likely headed?
· Are people still moving to Oregon?
· What is the hidden risk of low interest rates? Are they going up or down?
· Is the local economy recovering and should we be concerned with the employment rate?
· Is there a long lasting housing shortage building?
· Is there a foreclosure surge just around the corner?
2 Effective Strategies to Transform Your Net Profit. FAST.Victor Ang
These slides show the 4 common methods most CEOs use to transform their Net Profit but to no avail.
There are only 2 most effective strategies to transform your Net Profit as shown in these slides.
These 2 strategies have been used by our clients from different industries with great success.
If you apply as mentioned in these slides, your Net Profit will be transformed as well.
I can be reached at www.victor@crossbowconsultinggroup.com to answer any questions that you may have.
Thanks for watching this slide show.
Victor Ang
CEO
www.crossbowconsultinggroup.com
victor@crossbowconsultinggroup.com
Epic Research is performing a basic role as a leading financial advisory firm by providing good recommendations for,KLSE Stocks, Comex and Forex and all other segments with the help of experts and it maintains high accuracy.
Analysis of effect of inflation on savings of individuals in india for past 1...ANIRBAN BHATTACHARYA
Analysis of effect of inflation on savings India: Real rates give an accurate, historical picture of how an investment is performing. A real rate of return is the annual percentage return realized on an investment, which is adjusted for changes in prices due to inflation. The historical figures for past 10 years from 2009 to 2018 related to inflation and savings interest rate (National Saving Certificate- NSC) having sovereign guarantee and tax benefits was considered for analysis. The real rates (adjusted for Inflation) were negative starting from year 2010 to 2013 and in a positive territory 2014 onwards till 2018. Anyone who could increase their income by 3% y-o-y with increase in expenses @ 13% y- o-y could beat the benchmark index returns.
Analysis of effect of inflation on returns on saving for india real returnsANIRBAN BHATTACHARYA
Analysis showing hoe inflation is affecting individuals real return in India. The analysis includes historical figures for past 10 years from 2009 to 2018 related to inflation and savings interest rate (National Saving Certificate- NSC) having sovereign guarantee and tax benefits.
Conclusion:
The real rates (adjusted for Inflation) were negative starting from year 2010 to 2013 and in a positive territory 2014 onwards till 2018.
Anyone who could increase their income by 3% y-o-y with increase in expenses @ 13% y-o-y could beat the benchmark index returns.
Challenges to extend visibility to complex SAP access authorizations addressed by a QlikView driven, in-house developed SAP Access Authorization Solution
Analysis of effect of inflation on savings of individuals in india for past 1...ANIRBAN BHATTACHARYA
Analysis of effect of inflation on savings India: Real rates give an accurate, historical picture of how an investment is performing. A real rate of return is the annual percentage return realized on an investment, which is adjusted for changes in prices due to inflation. The historical figures for past 10 years from 2009 to 2018 related to inflation and savings interest rate (National Saving Certificate- NSC) having sovereign guarantee and tax benefits was considered for analysis. The real rates (adjusted for Inflation) were negative starting from year 2010 to 2013 and in a positive territory 2014 onwards till 2018. Anyone who could increase their income by 3% y-o-y with increase in expenses @ 13% y- o-y could beat the benchmark index returns.
Analysis of effect of inflation on returns on saving for india real returnsANIRBAN BHATTACHARYA
Analysis showing hoe inflation is affecting individuals real return in India. The analysis includes historical figures for past 10 years from 2009 to 2018 related to inflation and savings interest rate (National Saving Certificate- NSC) having sovereign guarantee and tax benefits.
Conclusion:
The real rates (adjusted for Inflation) were negative starting from year 2010 to 2013 and in a positive territory 2014 onwards till 2018.
Anyone who could increase their income by 3% y-o-y with increase in expenses @ 13% y-o-y could beat the benchmark index returns.
Challenges to extend visibility to complex SAP access authorizations addressed by a QlikView driven, in-house developed SAP Access Authorization Solution
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
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BONKMILLON Unleashes Its Bonkers Potential on Solana.pdf
Macroeconomic_Indicator_Effect_KSE_100_Index
1. 1 of 08
EFFECTS OF MACROECONOMIC VARIABLES ON
KSE-100-INDEX
Sayyed Zakir Ali Rizwe
20151-19131
Submitted To:
Muhammad Yasir
MBA Coursework – Business Analytics for Decision Making
IoBM - College of Business Management
2. 2 of 08
Macro-Economic Indicators & Stock Index
Pakistan Stock Exchange: KSE-100-Index
Top 100 Companies with Highest Market
Capitalization
Index represent 88% market value
From-The-Year: 1991 to 2018
Consumer Price Index
weighted average of prices of a basket of
consumer goods and services
Represent the ‘cost of living’
Interest Rate
Cost of debt for the borrower and the
rate of return for the lender
Discount rate or ‘risk free rate’
Exchange Rate
Price of a nation's currency in terms of
another currency
Base currency and a counter currency
[PKR to US$]
3. 3 of 08
Conceptual Framework & Secondary Data
KSE-100-Index
http://www.psx.com.pk
Month-wise index
standing
Dependent Variable
Consumer Price Index
http://www.pbs.org.pk
average CPI taken as the
monthly value
Independent Variable
Interest Rate
http://www.sbp.org.pk
average interest rate as
the month-value
Independent Variable
Exchange Rate
http://www.sbp.org.pk
Average exchange rate
is taken as the monthly
value
Independent Variable
MonthlyData
January2000toJune2018
Secondary data, tests & findings, recorded in following EXCEL sheets & IBM SPSS files
- Main_Project_File [EXCEL] {descriptive statistics| sparklines| pivot-tables| Count-
If| graphs| changes in monthly positions| data preparation for IBM SPSS}
- Project_Test_File [EXCEL] {Correlation, Covariance, Pivot-table | Regression,
standard error, Equation-results, Graphs}
- Project_Test_File_FC_What_If [EXCEL] {qualitative forecast, time-series forecast
using moving average models| what-if analysis and goal seeking}
- IBM SPSS Files [Data file & output-file for Cluster analysis| Histogram| Linear
regression | Scatter plot]
4. 4 of 08
Descriptive Statistics
Mean Geo Mean Mode Median Std. Deviation Sample Variance CoV Percentile Min Max Min Max
Interest Rate 9.27 8.95 7.00 9.00 2.45 6.01 26% 13.50 (1.44) 2.13 5.75 14.50
CPI 128.96 116.22 116.46 119.05 56.99 3248.32 44% 216.57 (1.21) 1.60 60.12 226.68
Exchange Rate 78.95 76.50 51.9 80.00 19.81 392.28 25% 105.48 (1.37) 1.84 51.9 121.47
KSE 100 Index 15666.56 9923.70 NA 11179.97 13631.98 185830973 87% 43,927.61 (1.07) 2.56 1133.44 50591.57
Z-Score Observations
5. 5 of 08
Histogram – Dependent & Independent Variables
• Multi-modal distribution
• Frequent changes in
Monetary policy
• Interest rate of
5.8,8.5,9.0 & 9.5 applied
for 20 or more months
• Unit-frequency
• Between a skewed-right
and bi-modal
distribution
• Reflect ‘intermittent’ CPI
increase
• Close to unit-frequency
• Skewed-right [military
regime, US$ dollar parity
for 5-6 years], followed
by intermittent increase
[democracy],
• Multi-modal distribution
• Unit-frequency
• ‘Skewed-right’ distribution
6. 6 of 08
Scatter Position – Independent & Dependent Variables
KSE-100-Index Vs. IR KSE-100-Index Vs. ER KSE-100-Index Vs. CPI
IR Vs. ER IR Vs. CPI ER Vs. CPI
7. 7 of 08
Correlation Coefficient
Interest-Rate Consumer Price Index Exchange Rate
Interest-Rate 1
Consumer Price Index -0.26 1
Exchange Rate -0.20 0.98 1
Interest Rate & CPI (36.37)
Interest Rate & Exchange Rate (9.53)
CPI & Exchange Rate 1,111.26
Interest Rate & CPI (0.26)
Interest Rate & Exchange Rate (0.20)
CPI & Exchange Rate 0.98
Divided by Product of SD
Covariance
- Interest rate has a
negative correlation with
CPI, exchange-rate and
KSE-100-Index
- CPI has a negative
correlation with interest
rate and a positive
correlation with exchange
rate and KSE-100-index
- Exchange rate has a
negative correlation with
interest rate and a
positive correlation with
CPI and KSE-100-index
- KSE-100-Index has a
negative correlation with
interest rate and a
positive correlation with
CPI and ER
8. 8 of 08
Regression Analysis [Model: 01]
KSE-100-Index = 43462.127 – 2997.263(Interest rate)
-
10,000.00
20,000.00
30,000.00
40,000.00
50,000.00
60,000.00
2000
2000
2000
2001
2001
2001
2002
2002
2002
2003
2003
2003
2004
2004
2004
2005
2005
2005
2006
2006
2006
2007
2007
2007
2008
2008
2008
2009
2009
2009
2010
2010
2010
2011
2011
2011
2012
2012
2012
2013
2013
2013
2014
2014
2014
2015
2015
2015
2016
2016
2016
2017
2017
2017
2018
2018
Linear Regression
Interest Rate vs. KSE 100 Index
Interest-Rate Actual - KSE 100 Index Estimated - KSE 100 Index
KSE-100-Index Vs. Interest Rate
High standard error rate (distance of estimated value to
actual value) and a low adjusted r-square translate in to
only 4.5% of the forecasted/estimated dependent variable
values within a mean distance of 1000 (+/-)points
9. 9 of 08
Regression Analysis [Model: 02]
KSE-100-Index = -12221.810 + 216.264(CPI)
KSE-100-Index Vs. Consumer Price Index
High standard error rate (distance of estimated value to
actual value) even with a better adjusted r-square
(compared to interest rate) translate in to only 21.63% of
the forecasted/estimated dependent variable values falling
within a mean distance of 1000 (+/-)points
0
10000
20000
30000
40000
50000
60000
2000
2000
2000
2001
2001
2001
2002
2002
2002
2003
2003
2003
2004
2004
2004
2005
2005
2005
2006
2006
2006
2007
2007
2007
2008
2008
2008
2009
2009
2009
2010
2010
2010
2011
2011
2011
2012
2012
2012
2013
2013
2013
2014
2014
2014
2015
2015
2015
2016
2016
2016
2017
2017
2017
2018
2018
Linear Regression
CPI vs. KSE 100 Index
CPI Actual - KSE 100 Index Estimated KSE 100 Index
10. 10 of 08
Linear Regression: Step-Wise
KSE-100-Index = 7193.184 + 195.980 (CPI) – 1811.505 (IR)
KSE-100-Index Vs. CPI and Interest Rate
With a 95% confidence interval (or α =
0.05), critical value of 1.97 is
determined by referring degree-of-
freedom from a two-tail test table
Model-1: value of t-statistic [-12.590 &
31.397] is outside critical value ± 1.97
Model-2: value of t-statistic [5.239,
40.518 & -16.112] is outside critical
value of ± 1.97
Null hypothesis is rejected; same is also
stated by the significance value of 0.00
that is less than 0.05
(10,000.00)
-
10,000.00
20,000.00
30,000.00
40,000.00
50,000.00
60,000.00
2000
2000
2000
2001
2001
2001
2002
2002
2002
2003
2003
2003
2004
2004
2004
2005
2005
2005
2006
2006
2006
2007
2007
2007
2008
2008
2008
2009
2009
2009
2010
2010
2010
2011
2011
2011
2012
2012
2012
2013
2013
2013
2014
2014
2014
2015
2015
2015
2016
2016
2016
2017
2017
2017
2018
2018
Linear Regression [Model-2]
CPI & Interest Rate
Interest-Rate CPI Actual - KSE 100 Index ABS [Act-FC]
11. 11 of 08
Qualitative Forecast – Interest Rate & Exchange Rate
Qualitative Methods of Forecasts
Informed opinion and judgment
Delphi method, market research
Qualitative Method - Patterns
Interest rates are driven on
central bank monetary policy.
Reasonable to state that interest
rate cyclically increases and
decreases, roughly by 10% to
15% in 3-5 years cycle
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
January 51.9 59.25 59.90 58.17 57.20 59.15 59.85 60.40 62.45 78.90 83.53 85.40 89.60 97.70 105.42 100.90 104.93 104.59 110.52
February 51.9 60.31 59.95 58.11 57.20 59.15 59.97 60.85 62.40 78.90 83.53 85.50 90.80 96.73 104.90 100.90 104.59 104.61 110.53
March 51.9 60.75 59.95 57.81 57.08 59.36 60.12 60.88 62.55 80.35 83.75 85.00 90.60 98.30 96.76 101.80 104.73 104.66 115.42
April 51.9 61.25 59.95 57.70 57.43 59.28 60.12 60.68 64.50 80.00 83.90 85.39 89.46 98.40 98.25 101.75 104.82 104.73 115.54
May 52.06 63.37 60.05 57.64 57.65 59.28 59.70 60.71 66.20 80.85 83.97 84.70 92.17 98.40 98.70 101.90 104.83 104.66 115.55
June 52.23 63.46 60.05 57.85 58.00 59.70 60.10 60.50 68.10 81.26 85.45 86.00 94.50 97.55 98.50 101.75 104.75 104.65 121.47
July 53.38 63.95 60.05 57.75 58.30 59.64 60.23 59.90 71.15 82.85 85.20 86.65 93.39 101.60 98.60 101.75 104.84 105.30
August 54.7 63.95 59.35 57.71 58.72 59.64 60.23 60.66 75.40 82.80 84.18 87.10 93.50 104.30 99.76 104.13 104.68 105.05
September 58.28 64.00 58.95 57.90 59.10 59.70 60.54 60.63 77.90 82.95 86.15 87.50 93.23 104.31 101.29 104.48 104.46 105.25
October 57.35 61.30 58.87 57.38 61.08 59.72 60.50 60.64 81.20 83.55 85.85 85.56 94.49 105.87 101.83 105.48 104.77 105.10
November 57.8 60.75 58.39 57.24 59.65 59.72 60.85 61.10 78.30 83.40 85.70 86.73 96.50 108.48 100.46 105.48 104.80 105.23
December 57.8 59.90 58.35 57.30 57.54 59.74 60.77 61.75 78.75 84.30 85.65 89.70 95.71 105.60 100.45 104.74 104.30 110.40
Annual Net 5.90 0.65 (1.55) (0.87) 0.34 0.59 0.93 1.35 16.30 5.40 2.12 4.30 6.11 7.90 (4.97) 3.83 (0.63) 5.81 10.95
Exchange Rate are driven on
accumulated reserves; maintained
better in military rule with better
overall governance & lower import
bill vs. democracy where the
position is turned the other way
around
No specific pattern until radicle
shift from foreign currency
reserves to market economy
12. 12 of 08
Qualitative Forecast – CPI & KSE 100 Index
Consumer price index is heavily
influenced by petroleum prices
driven on OPEC demand &
supply and government imposed
fix levies
Upward trajectory
KSE-100-Index has more dips in the
first 6-months (January to June),
compared to later 6-months where
it maintains an upward trajectory
Therefore, the best time to invest
in stocks is in first 6-months, in the
month of February, May and June
and in August and to sell in
January, April and July
13. 13 of 08
Quantitative Forecast – Naïve & Moving Average Model
Moving Average forecast
provide more accurate
forecast (MAPE & MAE) as
compared to the Naïve
model
In both moving average
models, the forecast
accuracy drops on
increasing number of
months for moving average
determination
Model-2 (average of 3/5/7
months is marked as
forecast of the 'middle
month') provides more
accurate forecast compared
to model-1 (average of
3/5/7 months is marked as
Forecast for 'the month')
FC Error (%age) Mean FC Error
Interest Rate 1.44% 0.143
Exchange Rate 0.89% 0.722
Consumer Price Index 0.74% 0.974
KSE-100-Index 5.63% 727.453
Most Recent Month
FC Error (%age) Mean FC Error FC Error (%age) Mean FC Error FC Error (%age) Mean FC Error
Interest Rate 1.42% 0.140 2.73% 0.265 4.05% 0.388
Exchange Rate 0.72% 0.583 1.20% 0.970 1.66% 1.338
Consumer Price Index 0.66% 0.856 1.23% 1.592 1.81% 2.338
KSE-100-Index 4.44% 567.382 6.76% 906.647 8.70% 1202.175
Moving Average [3M] Moving Average [5M] Moving Average [7M]
Take Average of 3/5/7 Months AND Mark it as Forecast for 'the Month'
FC Error (%age) Mean FC Error FC Error (%age) Mean FC Error FC Error (%age) Mean FC Error
Interest Rate 0.78% 0.078 1.17% 0.116 1.61% 0.159
Exchange Rate 0.42% 0.354 0.57% 0.471 0.68% 0.560
Consumer Price Index 0.24% 0.336 0.36% 0.497 0.43% 0.600
KSE-100-Index 2.53% 332.668 3.63% 452.316 4.34% 547.915
Moving Average [3M] Moving Average [5M] Moving Average [7M]
Take Average of 3/5/7 Months AND Mark it as Forecast of the 'Middle Month'