lOMoARcPSD| 58583460
CHAP3 AND CHAP 4 : y = Br + Baxy (regression
CHAP 3
:
-
QMF QM : Normal distribuon
-
M4B : equaon
:
y = 2 . x + 3
>- x = 1 >- y = 5 Khi tang 1vi>- x = 2 - y = 7 thiy tang 2 vi
>- x = 3 >- y
=
9
Stat
:
Hypothesis tesng
:
S Salary
=
By x grade
y = ax + b
=> Salary = $0 . 7 x grade + 10 M
+ rade = 0 - 10M : radg = 1 + 10M +$0. 7
Ho
B
0
7
Sto : nulhypothesothesis SHe :: B =+ 0 .. 7
ST : B dont (2)
lOMoARcPSD| 58583460
-
/ in
lOMoARcPSD| 58583460
S :B07 -
/W
(3)
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lOMoARcPSD| 58583460
lOMoARcPSD| 58583460
-> B = [14y+ - Tiy = 150, 000 - 30x58 . 300x95, 700
IKE
-
Th 105
,
000
,
0002
-
30
x
58 . 3002
->
3 =
-
0 . 0000158
- = y - Bi = 95 ,700 - 1- 0 . 0000158)x58. 300
lOMoARcPSD| 58583460
>
-
2 = 95700 . 92114
S
Zit
=/250,500 = 94. 5855
SE(X) =S, IxE
?
= 94 . 5851105, 000, 000
TIIt - Th 30
x
105
,
000000
-
30258
,
30%
>- SE(X) =? SE(B) =?
-
Tradional Ecometric : (1) E(Mt) = 0
(2) Var (Mt)
=
82
(constant)
(3) Covariance (Mi
;
Vi) = 0
(4) (ov(ui
=
xi)
=
0
* Thoai man 4 din Kien >
-
B . L . U . E (Chep dinnnghia
+ Best OLS : ordinary least square
+
Linear
+
Unbased
+ Esmator
:
(B , = X
;
B)
+
Step
2
-
Dang Hypothesis Tesng
:
-
lOMoARcPSD| 58583460
+ Step 1 : State the hypothesis· Ho:B = 0 (4(-X
lOMoARcPSD| 58583460
(xacinh) H
:
B
+ 0
lOMoARcPSD| 58583460
lOMoARcPSD| 58583460
-
P-value :
new
p-value < bench-mark
value (5
%
)
reject
null
hypothesis
· T = 62 ; < = 5%; Ho : B = 1 ; + : B < 1(6)
>- Test Stasc = 10. 147. 0548-1 = 2 . 68 ~ +5%:60
-
T-test - rejecon zone
lOMoARcPSD| 58583460
5
%
>
-
Reject
Null
hypothesis
>- Prove alternave hypothesis
B7 1
>- TheSecurity is more risky than market.
Ho : B = 0
He : B + 0
lOMoARcPSD| 58583460
·ente2. 03
lOMoARcPSD| 58583460
- i
n
- 1
.
5%
+2 .
5
%
null
hypothesis
>- In other words that the returns on its shares are completely unrelated to
movements in the market.
CHAPTER 4
:
Mulple linear regression
y = B + B2x2t + Bxt +... + Brint + Mt
lOMoARcPSD| 58583460
CT
:
[B] = (xX)
-
1
x
XY
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lOMoARcPSD| 58583460
>- T-Stasc = 436 . 1 - 397 . 2 x 144 - 4 = 6 . 68
lOMoARcPSD| 58583460
397 .2 2 F(2
;
140)
lOMoARcPSD| 58583460
-3
.
07
>
-
6 . 68t rejecon Zone
lOMoARcPSD| 58583460

Preview text:

lOMoAR cPSD| 58583460 CHAP3 AND CHAP 4 Br : y = + Baxy (regression CHAP 3 : QMF QM : Normal distribution - M4B : equation : y = 2 x + 3 - .
>x = 1 >y = 5 Khi tang 1vi>x = 2 - y = 7 thiy tang 2 vi - - - > x = 3 > y - - = 9 Stat S : Hypothesis testing : Salary = By x grade y = ax + b => Salary $0 = 7 x grade + 10 M . + rade = 0 - 10M : radg = 1 + 10M +$07 . Ho B 07
Sto : nulhypothesothesis SHe B :+ : 0 7 = .. ST : B dont (2) lOMoAR cPSD| 58583460 -/ in lOMoAR cPSD| 58583460 S :B07 - /W (3) lOMoAR cPSD| 58583460 lOMoAR cPSD| 58583460 lOMoAR cPSD| 58583460 B > = [14y+ Tiy = 150, 000 30x58 300x95, 700 - - - . IKE Th 105 000 30 3002 - , , 0002 - x 58 . 3 0 0000158 -> = - . - y Bi 1 0000158)x58 = 95 300 = ,700 0 . - - - . lOMoAR cPSD| 58583460 SZit > 2 92114 - = 95700 . /250,500 = 945855 = . SE(X) 5851105 =S, IxE ?= 94 , 000, 000 . TIIt - Th 30x105 000000 30258 30% , - , SE(X) > =? SE(B) =? - Traditional Ecometric (1) E(Mt) - : = 0 (2) Var (Mt) 82 = (constant) (3) Covariance (Mi ; Vi) = 0 (4) (ov(ui = xi) = 0
* Thoai man 4 din Kien >B L U E (Chep dinnnghia - . . . + Best OLS : ordinary least square + Linear + Unbased + Estimator (B , : = X ; B) + Step 2 Dang Hypothesis Testing : - - lOMoAR cPSD| 58583460 + Step 1 :
State the hypothesis· Ho:B = 0 (4(-X lOMoAR cPSD| 58583460 (xacinh) H : B + 0 lOMoAR cPSD| 58583460 lOMoAR cPSD| 58583460 new P-value p-value < bench-mark - : value (5%) ↳ reject null hypothesis T B 1 ; + B < 1(6) · = 62 ; < = 5%; Ho : = :
> Test Statistic = 101470548-1 68 ~ +5%:60 - = 2 . . . T-test - rejection zone - lOMoAR cPSD| 58583460 5% >- Reject Nullhypothesis >Prove alternative hypothesis - B7 1
> TheSecurity is more risky than market. - Ho B : = 0 He B : + 0 lOMoAR cPSD| 58583460 ente203 · . lOMoAR cPSD| 58583460 - 5% i n 5 - +2 % . 1 . null hypothesis
>In other words that the returns on its shares are completely unrelated to - movements in the market. CHAPTER 4 : Multiple linear regression y B =
+ B2x2t + Bxt +... + Brint + Mt lOMoAR cPSD| 58583460 : CT [B] 1 XY = (xX) - x lOMoAR cPSD| 58583460 lOMoAR cPSD| 58583460 > T-Statistic 4 6 68 = 436 1 - 397 2 x 144 = - . . - . lOMoAR cPSD| 58583460 397 2 2 F(2 ; 140) . lOMoAR cPSD| 58583460 -3.07 >6 68t rejection Zone - . lOMoAR cPSD| 58583460