FIN 6306 Quantitative Methods in Finance
Chapter 3:
Calculus Applied to Finance
1
Readings / Excel Functions /
Web Links
Readings:
QMF* Ch.3
Calculus Applied to Finance
Bonds and Stocks
EMI* Chapters 1,2
Bond Pricing
The Yield Curve
Excel Functions:
DAT
FREQUENTLY ASKED QUESTIONS
How valuable is the Bloomberg Product Certificate?
Employers place great emphasis on having well-trained employees. In an
increasingly competitive market, the more tools you have in your educational
arsenal the better. That is w
FIN 6306 Quantitative Methods in Finance
Chapter 1:
Interest Rates and Asset Returns
1
Introduction
Study of Finance: Analysis of Benefits of Making Investments
Goal of Investments Enhance Wealth and Income of investors
Enhancement: Return
Enhancement as
FIN 6306 Quantitative Methods in Finance
Chapter 5:
Sampling, Estimation and
Hypothesis Testing
1
Outline
Introduction
Sampling Theory
Sampling Distributions of sample statistics
Distribution of the Sample Mean
Central limit theorem
Estimation and Confide
FIN 6306 Quantitative Methods in Finance
Chapter 9:
Portfolio Optimization
1
Optimization
Introduction
Definitions
Constrained Optimization
Optimization under
equality constraints:
using Lagrange
multipliers
Quadratic programming
with inequalities
Linear
FIN 6306 Quantitative Methods in Finance
Chapter 4:
Probability Distributions:
Applications to Asset Returns
1
Reading / Excel Functions / Web Links
Readings:
Excel Functions:
Data Get External Data
QMF* Ch. 4
Probability Distributions: Data Data Analys
FIN 6306 Quantitative Methods in Finance
Chapter 2:
Presentation of Data and
Descriptive Statistics
1
Reading / Excel Functions / Web Links
Readings:
Excel Functions:
Data Get External Data
QMF* Ch. 2
Data Data Analysis Histogram
Presentation of Data a
FIN 6306 Quantitative Methods in Finance
Chapter 9b:
Variance, Covariance and
Correlation;
Basic Portfolio Concepts
1
Outline
Random Variable
Portfolio Returns and Variance
Expected Value and Variance of a Discrete RV
Covariance Matrix
Risk and Diversific
Excel Help Set 6: Sampling? Estimation and Hypothesis Testing
w NORMDIST
a NORMSDIST
NORMINV
NORMSINV
TDIST
7 TINV
a CHIDIST
~ CHHNV
FDIST
w FINV
a ZTEST
m TTEST
CONFIDENCE
NORMDIST function returns the normal distribution for the specied mean and st
QUANTITATIVE METHODS IN FINANCE
FIN6306
Office Hours:
Fall 2013
Mon/Wed 9:00 11:00 AM
Tues/Thurs 9:00 11:00 AM
Or by appointment
Dr. Liping Ma
Office: TBD
Email: Liping.Ma@utdallas.edu
Phone: TBD
Other Information I strongly urge you to use email (the abo
Single CF
Inputs
Single Cash Flow
Discount Rate / Period
Number of Periods
Future Value using a Time Line
Period
Cash Flows
Future Value of Each Cash Flow
Future Value
Future Value using the Formula
Future Value
Future Value using the FV Function
Future V
FIN 6306 Quantitative Methods in Finance
Chapter 7:
Time Series Analysis
1
Outline
Basics
Univariate Stochastic Models
Tools for Analyzing Time Series
Autocorrelation and partial autocorrelation
Cointegration
Autoregressive processes, integration, moving
(page 30 investments)
Inputs
Rate Convention: 1 = EAR, 0 = APR
Annual Coupon Rate (CR)
Annualized Yield to Maturity (YTM)
Number of Payments / Year (NOP)
Number of Periods to Maturity (N)
Face Value (FV)
Outputs
Discount Rate / Period (DR)
Coupon Payment
HW 4a:
1. X ~ Normal( 100, 20)
135 100
) P( Z 1.75)
20
From the Z-table, P(0 Z 1.75) 0.4599
P( X 135) P( Z
So P(Z 1.75) 0.5 P(0 Z 1.75) 0.5 0.4599 0.0401
Also, using the excel function
P( X 135) 1 P( X 135) 1 NORMDIST (135,100,20, true)
1 0.9599 0.0401
HW 5c:
1. This a small sample problem in which the sample comes from a normal population with a
known standard deviation. Therefore, we use Z-distribution (standard normal) in the
solution.
We would like to test the population mean is 6% or not based on t
HW 6a:
11. a. From the output, the regression model is:
y b 0 b1 x
0.287 0.802(8.00)
6.129
b. The variance of the prediction error, s 2 of Y, given X is
f
_
1 (1 x) 2
s 2 s 2 [1
]
f
2
n (n 1) s x
(4.243) 2 (1 1 / 12
(8 2.3) 2
(12 1)(38.51)
20.884
So
HW 6a:
11. a. From the output, the regression model is:
y b 0 b1 x
0.287 0.802(8.00)
6.129
b. The variance of the prediction error, s 2 of Y, given X is
f
_
1 (1 x) 2
s 2 s 2 [1
]
f
2
n (n 1) s x
(8 2.3) 2
(4.243) (1 1 / 12
(12 1)(38.51)
20.884
2
So
q-cfw_,
g
cfw_r1
el
tJ
s
*t*r
\I)
r\
$i
*t
Vt
a
qr?
#
o
(.: '
tt
cfw_rt
q.
d
*
o
E
Lr)
ut
cfw_.t
ffl
c
i
tq.l
Vr
f
-(f* r\n
ffi
x
tn
rfl
c
rj'\a\
cl
t
i
fi#q3,()
i
fi
ft
."ci
l
!
l
(J
I
w
tu,
o
ttl
w
1*r
=
o
E
fi
es
o
T
[.fcr o
ift
f;\
ta
f"cfw_
[t".9F-r\
Company Name
S&P 500 COMP-LTD HORTON INC CORP
DR
DANA
DANAHER CORP
DARDEN RESTAURANTS INC
DEERE & CO
DELL INC DEVON ENERGY CORPDISNEYA DOLLAR GENERAL CORP
DILLARDS INC -CL (WALT) CO
DOMINION RESOURCES (R R) & SONS CO
DONNELLEY INC CORP DOW CHEMICAL
DOVER
a.
Machine 1: 14,000/3,000= 4.67 years or 4 years and 8 months
Machine 2: 21,000/4,000= 5.25 years OR 5 years and 3 months
b.
machine 1 is payback period is less than acceptable which is five years and acceptable
c.
The firm accepts the first machine beca
a)
Expected rate of return investment X
$1,500 + $21,000-$20,000/$20,000
$2,500/$20,000= 12.5 %
Expect rate of return investment Y
$6,800+55,000-55,000/$55,000
$6,800/$55,000= $12.36%
b)
Douglas should recommended investment X because with X gives more re
A) Calculate Everdeens 2015 earnings per share (EPS).
Net Profit before taxes is $436,000
Company's tax rate is 40%
Preferred stock dividends is $64,000
Common stock outstanding is 170,000 shares
Calculate Everdeens 2015 earnings per share (EPS).
Net prof