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Appendix 13A. Alternative Specifications Of APT By Cheng Few Lee Joseph Finnerty John Lee Alice C Lee Donald Wort

Appendix 13A . Alternative Specifications Of APT

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By Cheng Few Lee Joseph Finnerty John Lee Alice C Lee Donald Wort. Appendix 13A . Alternative Specifications Of APT. Appendix 13A : Alternative Specifications Of APT. - PowerPoint PPT Presentation

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Page 1: Appendix  13A .  Alternative Specifications Of APT

Appendix 13A. Alternative Specifications

Of APT

ByCheng Few LeeJoseph Finnerty

John LeeAlice C Lee

Donald Wort

Page 2: Appendix  13A .  Alternative Specifications Of APT

Appendix 13A: Alternative Specifications Of APTBy using the relationship between premium (excess) return and the factor scores, Jobson (1982) has derived a multivariate linear-regression model for testing the APT:

(13A.1)where = excess return for company i at time t; = intercept term; = respective betas for excess return on company i and the excess returns on all other (N) companies;

= excess returns on all other (N) companies in the market at time t; and

= error term at time t.

2

1

n

it i j jt jtj

r r i j

itri

j

jtr

jt

Page 3: Appendix  13A .  Alternative Specifications Of APT

Appendix 13A: Alternative Specifications Of APT

•Even more significantly, Jobson has shown that his model can hold when the independent observations of are some subset k of the total set of returns, n. This testable form of the Jobson derivation can be defined:

(13A.2)

•where i ≠ j and k < n.

jtr

1

k

it i j jt jtj

r r

3

Page 4: Appendix  13A .  Alternative Specifications Of APT

Appendix 13A: Alternative Specifications Of APT• Jobson’s model is similar to that proposed by Lloyd and Lee

(1976) and Lee and Lloyd (1978), who utilized an econometric model called a “block recursive system” to explain the covariability among company returns:

Where L = number of jointly determined (dependent) variables;K = number of exogenous explanatory variables;

• = coefficients on the jointly determined variables;• = coefficients on the exogenous variables;• = general economic or firm-related variables;• = returns on the Lth security in the model; and = error term.

1 11 11 12 12 1 1 1

21 1 21 21 22 22 2 2 2

1 1 2 2 1 2 1 2 2

......

... ...

k k

k k

L L LL L L L L L L Lk Lk L

R X X Xr R X X X

r R r R R R X X X

1LL

Lk

LkX

LR L

4

Page 5: Appendix  13A .  Alternative Specifications Of APT

Appendix 13A: Alternative Specifications Of APT• As evidenced for the high explanatory potential of the bock recursive system,

Table 13A.1 shows the eight stock clusters or subsystems, the ordering of securities within the subsystem, and a comparison of the percentage of variation in the individual security’s return explained by the Sharpe market model and the percentage explained by the block recursive model.

Table 13A.1Grouping of Companies Based on Correlation with Common Factor

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Page 6: Appendix  13A .  Alternative Specifications Of APT

Appendix 13B. Lee And Wei’s Empirical

Results

ByCheng Few LeeJoseph Finnerty

John LeeAlice C Lee

Donald Wort

Page 7: Appendix  13A .  Alternative Specifications Of APT

Appendix 13B: Lee And Wei’s Empirical Results• Lee and Wei (2012) have proposed a multi-factor, multi-indicator

approach to test the CAMP and the APT.

• This approach is able to solve the measuring problem in the market portfolio in testing the CAPM; and it is also able to directly test the APT by linking the common factors to the macroeconomic indicators.

• Table 13B.1 describes 11 economic-state variables which are used by Lee and Wei (2013) to identify common factors of the APT model.

• Table 13B.2 describes the regression relationship between the factors and economic variables. Other detailed empirical results can be found in Lee and Wei

• (2013).

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Page 8: Appendix  13A .  Alternative Specifications Of APT

Appendix 13B: Lee And Wei’s Empirical Results

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Page 9: Appendix  13A .  Alternative Specifications Of APT

Appendix 13B: Lee And Wei’s Empirical Results

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Page 10: Appendix  13A .  Alternative Specifications Of APT

Appendix 13B: Lee And Wei’s Empirical Results

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