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金融人工智能:用Python实现AI量化交易
book

金融人工智能:用Python实现AI量化交易

by Yves Hilpisch
August 2022
Intermediate to advanced
394 pages
12h 32m
Chinese
Posts & Telecom Press
Content preview from 金融人工智能:用Python实现AI量化交易
74
3
3.5
 套利定价理论
早期,我们观察到
CAPM
的缺点后会在金融学文献中加以讨论。
CAPM
的一个主要推广是
Ross
1971
1976
)提出的套利定价理论(
APT
)。
Ross
1976
)对其论文做了如下介绍:
本文的目的是严格检验
Ross
1971
提出的资本资产定价套利模型。套利模型是
Sharpe
Lintner
T
reynor
提出的对均值
方差资本资产定价模型的一种替代模
型,该模型已成为解释资本市场上观察到的风险资产现象的主要分析工具。
3.5.1
 假设和结论
APT
CAPM
对多种风险因素的推广。从这个意义上说,
APT
并不认为市场投资组合是
唯一相关的风险因素,而是有相当多的风险类型一起影响股票的表现(预期收益率)。这
些风险因素可能包括规模、波动率、价值和动量。
9
除了这一主要差异之外,该模型还依赖
于类似的假设,比如市场是完美的,在同一固定利率下可(无限制)借贷等。
Poss
1976
)的原始动态版本中,
APT
采用以下形式:
t tt
=++y a Bf
这里,
y
t
M
个观察变量的向量,即
M
个不同股票在时间
t
的预期收益率:
1
2
t
t
t
M
t
y
y
y



=




y
a
M
常数项的向量:
1
2
M
a
a
a



=




a
f
t
F
因素在
t
时刻的向量:
1
2
t
t
t
F
t
f
f
f



=




f
9
有关实践中使用的因素的更多背景信息,请参阅
Bender
等(
2013
)。
规范性金融理论
75
B
M
×
F
所谓因子荷载矩阵:
11 12 1
21
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Publisher Resources

ISBN: 9787115594556