Signal Processing - May 2017 - 23
chance. Two commonly used methods can verify this: 1) conduct statistical significance analysis with out-of-sample
data and 2) have reasonable economic explanations for the
identified factor. Even then, the results are still confirmatory
rather than conclusive because there are no certain physical
laws in the market activities, it is unknown whether the same
model will hold over time, and controlled experiments cannot
be conducted to test the model. Because researchers always
operate on hypotheses in economic and business studies, the
burden of proof is on their side, especially when results contradict with conventional wisdom or well-recognized theories,
such as the EMH.
Efficient market theory and behavioral economics
An efficient capital market is a market that is efficient in processing information: asset prices fully reflect available information.
An efficient market does not necessarily mean that the stock
price follows the random-walk model or any existing model.
EMH
Because of the similarity to many noisy signals in SP applications, the stock return series is fascinating to many SP
researchers. It is tempting to look into the historical stock
charts trying to identify money-making patterns and hope that
an autoregressive moving average (ARMA) model can fit the
chart. It is often all too easy for SP researchers to think that
they may be able to predict stock price using sophisticated SP
models to make free money.
However, as the expected utility theory suggests, the source
of excess return is the risk that investors carry. In contrast
with a physical system, two parties are involved in any financial transaction. In a free market, the two parties agree on a
(fair) price for the transaction. In market equilibrium, the price
should reflect all available information in the market, such that
the transaction is merely an RP changing hands. For example,
if both seller and buyer predict that the price of an asset will
go up tomorrow, the price should go up today. A rational seller
will not sell if the price is lower than what he or she predicts.
The efficiency of information processing in the market is
indeed a natural consequence of competition in a free market.
In the 1960s, Eugene Fama, a 2013 Nobel Laureate in Economics, was one of the first using computers to study stock
prices. Based on his empirical study, he proposed that security prices at any time fully reflect all available information
[4]. Such a market is called an efficient market. See "Efficient
Capital Markets-Different Forms."
Holding the utility function constant, we can argue that the efficient market means that the stock price tomorrow is unpredictable,
as all available information has been incorporated into today's
price. The market only moves by new information, not by known
information. See "Fundamental Analysis, Technical Analysis, and
Quantitative Analysis" for different types of stock analysis.
Joint hypothesis testing and its implications in SP
To test the market efficiency, we need to have a market equilibrium model, i.e., an asset-pricing model, such as the
Efficient Capital Markets-Different Forms
An efficient capital market is a market that is efficient in
processing information and asset prices fully reflect
available information. Markets have different forms of
efficiency.
* Weak form: current prices fully reflect all information
in past prices. Technical analysis using past price patterns will not produce profits.
* Semistrong form: current prices fully reflect past prices
and all publicly available information. Fundamental
analysis (e.g., studying financial statements) will not
produce profits.
* Strong form: current prices fully reflect all information, public and private. Insider trading will not produce profits.
Evidence
1) For the weak form, the random-walk stock price model has been empirically validated for short-term stock
returns in many tests, i.e., the short-term stock return
series is not statistically different from white noise
and therefore is unpredictable.
2) For the semistrong form, a large number of event
studies have compared the stock returns before and
after corporate news events, such as stock split and
earning announcements, showing that the information is incorporated into the stock price almost
immediately.
3) For the strong form, insider trading makes profit, indicating that the strong-form market efficiency does
not hold. However, mutual fund managers who have
more private information than the general public do
not outperform on a consistent basis.
CAPM, the FF three-factor model, or the random-walk
model. We need to test whether the properties of expected
returns implied by the market equilibrium asset-pricing
model are observed in actual returns. The main difficulty in
testing market efficiency indeed lies in the joint hypothesis
test: when the test fails-i.e., we find credible anomaly in
price behavior-we do not know whether the market is inefficient, a conclusion people often jump to, or the asset-pricing
model used is wrong. Note that while the random-walk model
is a simple (hypothetical) form for an efficient market (an
idea popularized by a bestselling book [37]), an efficient
market does not necessarily mean that the stock price follows
the random-walk model or any existing model, as many
people have assumed.
While all empirical scientific research is more or less subject to the joint hypothesis test, in SP, researchers do not pay
much attention to 1) statistical significance and confidence
of model estimation, 2) error distribution of the estimation
IEEE Signal Processing Magazine
|
May 2017
|
23
Table of Contents for the Digital Edition of Signal Processing - May 2017
Signal Processing - May 2017 - Cover1
Signal Processing - May 2017 - Cover2
Signal Processing - May 2017 - 1
Signal Processing - May 2017 - 2
Signal Processing - May 2017 - 3
Signal Processing - May 2017 - 4
Signal Processing - May 2017 - 5
Signal Processing - May 2017 - 6
Signal Processing - May 2017 - 7
Signal Processing - May 2017 - 8
Signal Processing - May 2017 - 9
Signal Processing - May 2017 - 10
Signal Processing - May 2017 - 11
Signal Processing - May 2017 - 12
Signal Processing - May 2017 - 13
Signal Processing - May 2017 - 14
Signal Processing - May 2017 - 15
Signal Processing - May 2017 - 16
Signal Processing - May 2017 - 17
Signal Processing - May 2017 - 18
Signal Processing - May 2017 - 19
Signal Processing - May 2017 - 20
Signal Processing - May 2017 - 21
Signal Processing - May 2017 - 22
Signal Processing - May 2017 - 23
Signal Processing - May 2017 - 24
Signal Processing - May 2017 - 25
Signal Processing - May 2017 - 26
Signal Processing - May 2017 - 27
Signal Processing - May 2017 - 28
Signal Processing - May 2017 - 29
Signal Processing - May 2017 - 30
Signal Processing - May 2017 - 31
Signal Processing - May 2017 - 32
Signal Processing - May 2017 - 33
Signal Processing - May 2017 - 34
Signal Processing - May 2017 - 35
Signal Processing - May 2017 - 36
Signal Processing - May 2017 - 37
Signal Processing - May 2017 - 38
Signal Processing - May 2017 - 39
Signal Processing - May 2017 - 40
Signal Processing - May 2017 - 41
Signal Processing - May 2017 - 42
Signal Processing - May 2017 - 43
Signal Processing - May 2017 - 44
Signal Processing - May 2017 - 45
Signal Processing - May 2017 - 46
Signal Processing - May 2017 - 47
Signal Processing - May 2017 - 48
Signal Processing - May 2017 - 49
Signal Processing - May 2017 - 50
Signal Processing - May 2017 - 51
Signal Processing - May 2017 - 52
Signal Processing - May 2017 - 53
Signal Processing - May 2017 - 54
Signal Processing - May 2017 - 55
Signal Processing - May 2017 - 56
Signal Processing - May 2017 - 57
Signal Processing - May 2017 - 58
Signal Processing - May 2017 - 59
Signal Processing - May 2017 - 60
Signal Processing - May 2017 - 61
Signal Processing - May 2017 - 62
Signal Processing - May 2017 - 63
Signal Processing - May 2017 - 64
Signal Processing - May 2017 - 65
Signal Processing - May 2017 - 66
Signal Processing - May 2017 - 67
Signal Processing - May 2017 - 68
Signal Processing - May 2017 - 69
Signal Processing - May 2017 - 70
Signal Processing - May 2017 - 71
Signal Processing - May 2017 - 72
Signal Processing - May 2017 - 73
Signal Processing - May 2017 - 74
Signal Processing - May 2017 - 75
Signal Processing - May 2017 - 76
Signal Processing - May 2017 - 77
Signal Processing - May 2017 - 78
Signal Processing - May 2017 - 79
Signal Processing - May 2017 - 80
Signal Processing - May 2017 - 81
Signal Processing - May 2017 - 82
Signal Processing - May 2017 - 83
Signal Processing - May 2017 - 84
Signal Processing - May 2017 - 85
Signal Processing - May 2017 - 86
Signal Processing - May 2017 - 87
Signal Processing - May 2017 - 88
Signal Processing - May 2017 - 89
Signal Processing - May 2017 - 90
Signal Processing - May 2017 - 91
Signal Processing - May 2017 - 92
Signal Processing - May 2017 - 93
Signal Processing - May 2017 - 94
Signal Processing - May 2017 - 95
Signal Processing - May 2017 - 96
Signal Processing - May 2017 - 97
Signal Processing - May 2017 - 98
Signal Processing - May 2017 - 99
Signal Processing - May 2017 - 100
Signal Processing - May 2017 - 101
Signal Processing - May 2017 - 102
Signal Processing - May 2017 - 103
Signal Processing - May 2017 - 104
Signal Processing - May 2017 - 105
Signal Processing - May 2017 - 106
Signal Processing - May 2017 - 107
Signal Processing - May 2017 - 108
Signal Processing - May 2017 - 109
Signal Processing - May 2017 - 110
Signal Processing - May 2017 - 111
Signal Processing - May 2017 - 112
Signal Processing - May 2017 - Cover3
Signal Processing - May 2017 - Cover4
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201809
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201807
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201805
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201803
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201801
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1117
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0917
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0717
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0517
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0317
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0117
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1116
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0916
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0716
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0516
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0316
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0116
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1115
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0915
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0715
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0515
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0315
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0115
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1114
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0914
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0714
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0514
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0314
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0114
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1113
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0913
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0713
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0513
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0313
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0113
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1112
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0912
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0712
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0512
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0312
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0112
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1111
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0911
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0711
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0511
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0311
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0111
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1110
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0910
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0710
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0510
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0310
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0110
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1109
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0909
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0709
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0509
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0309
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0109
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1108
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0908
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0708
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0508
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0308
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0108
https://www.nxtbookmedia.com