Presentation at SCAI 2019

1. ECONOMIC CAUSAL CHAIN
AND
PREDICTABLE STOCK RETURNS
Nomura Asset Management Co., Ltd
The University of Tokyo
Kei Nakagawa, Shingo Sashida, Hiroki Sakaji, Kiyoshi Izumi

2. Contents
1. Introduction
2. Proposed Method
3. Empirical Study
4. Related Works
5. Conclusion
2

3. 1. Introduction
▪ Is it possible to predict the future stock return ?
3
No … Efficient Market Hypothesis (EMH) [Fama,70]
Yes … Lead-lag effects using a supply chain network [Cohen, 08]
Lead-lag effects using an economic causal chain network
[Our Study]

4. 1. Introduction
▪ What is the Lead-lag ?
The one (lagging) variable is delayed to the values of another
(leading) variable.
4t
Leading Stock
Lagging Stock
price
Lead-lag
Buy
Up

5. 5
✓ Cohen et al. measured lead-lag effects using a supply chain
network. [Cohen, 08]
1. Introduction
Customer
Supplier Customer
Supplier Customer
distribution
Lead-lag
supply chain network
Large
fluctuation of
stock return
Lag
Company B
Lead
Company C
Company A
distribution
Customer Momentum

6. 1. Introduction
▪ What is an Economic Causal Chain?
6
- The economic causal chain refers to a cause and effect network.
- The network constructed by the texts of Japanese financial statement summaries.
Financial statement summaries
(Text Data)
Cause
Effect
The financial statements summary:
a common form report that disclosed when a listed company announces its
financial performance.

7. 1. Introduction
▪ What is an Economic Causal Chain? (example)
7
Company A :
As semiconductor demand recovers,
semiconductor manufacturers are increasing their capital investment.
Company B :
With the expansion of capital investment by semiconductor manufacturers,
sales of control systems for semiconductor manufacturing equipment increased.
Effect Sentence
Cause Sentence
Causality

8. 8
✓ We do not use a supply chain network
but an economic causal chain network.
Cause
Effect Cause
Effect Cause
Lead-lag
Large
fluctuation of
stock return
Lag
Company B
Lead
Company C
Company A
Economic causal chain network
Causal
Relationship
2. Proposed Method ~ Outline

9. ▪ How to construct Economic Causal Chain?
9
financial statement
summaries
- The economic causal chain has been constructed by following 3 steps
[Sakaji, 17]
Cause
Effect
- [Step1] Extracts sentences
- [Step2] Obtains cause-effect expressions
Cause
Effect Cause
Effect
Company B
Company A
- [Step 3]
Constructs Economic Causal Chain
Company A
Report
2. Proposed Method ~ Construction

10. ▪ Construct Economic causal chain
-Step 1.
Extraction of Causal Sentences
10
- Find the clue expression
by syntactic and
semantic features.
“半導体の需要回復を受けて半導体メーカーが設備投資を増やしている。”
(handoutai no jyuyoukaifuku woukete
hanndoutaime-ka- ga setsubitoushi wo Fuyashiteiru)
The following pattern of particles and clue expressions:
.. を受けて... を... (... no ... woukete ... wo ...)
Clue expression
Semantic features
2. Proposed Method ~ Construction
As semiconductor demand recovers, semiconductor
manufacturers are increasing their capital investment.

11. ▪ Construct Economic causal chain
-Step 2.
Extracting Cause–Effect Expressions
11
- Obtain cause-effect
expressions from the
extracted sentences in step 1
using 5 syntactic patterns.
2. Proposed Method ~ Construction

12. ▪ Construct Economic causal chain
-Step 2.
Extracting Cause–Effect Expressions
12
2. Proposed Method ~ Construction
半導体メーカーの
背景に、
半導体製造装置向け制御システムの
設備投資の
拡大を
販売が
伸びた。
Cause
Clue
Effect

13. ▪ Construct Economic causal chain
-Step 3.
Construct Economic Causal Chain
13
Cause
Effect Cause
fEffect
Company B
Company A
Check Similarity:
Between the effect of company A and the cause of company B
with word2vec [Mikolov, 13]
Cause
Effect Cause
Effect
Company B
Company A
Similarity?
?
2. Proposed Method ~ Construction
Similarity > 0.5

14. ▪ Construct Economic causal chain
-Step 3.
Definition of the Chain Count of causality :
It indicates how strong the causality is
14
Key: Company A, Company B,
Issued Date(A), Issued Date (B)
Chain Count
2. Proposed Method ~ Construction
Pair A
Pair B
# of the Pair A # of the Pair B
>
A has stronger cause-
effect relationship
Expect:
The lead-lag effect of Pair A
examined more clearly

15. 3. Empirical Study ~Methodology
✓ We examine the lead-lag effect using the economic causal chain
▪ Test period : December 2012 - January 2019
▪ An investment universe : TOPIX500
Step1.
Divide the stocks of TOPIX500 into five by their returns in the previous month.
15
Q5
Q4
Q3
Q2
Q1
Sorting
By Return
High
Low TOPIX500
Previous month’s
returns

16. 3. Empirical Study ~Methodology
Step2.
Identified the ’effect’ (lagging) stock group using causal relationships.
16
Q5
Q4
Q3
Q2
Q1
High
Low
Cause
(Leading)
Economic causal chain
network
Effect
(Lagging)
Q5’
Q4’
Q3’
Q2’
Q1’
Cause
Effect Cause
Company B
Company A
Lead-lag exists ?

17. 3. Empirical Study ~Methodology
Step3.
Buy the most positive returns group and sell most negative
returns group.
17
Q5
Q4
Q3
Q2
Q1
High
Low
Cause
(Leading)
Economic causal chain
network
Effect
(Lagging)
Q5’
Q4’
Q3’
Q2’
Q1’
Buy (Long)
Sell (Short)
2. Portfolios = Q5’ – Q1’
1. Portfolios = buy each group

18. 3. Empirical Study ~Result
18
Quantile Return[%] Risk[%] R/R
1 19.52 18.57 1.05
2 19.46 16.6 1.17
3 18.09 15.58 1.16
4 16.75 15.37 1.09
5 14.99 15.63 0.96
- Without using causal chain network
➢ Portfolio 1 (buy each group)
- Using causal chain network
Threshold Quantile Return[%] Risk[%] R/R
2 1 16.95 15.75 1.08
2 2 16.85 15.81 1.07
2 3 18.02 16.23 1.11
2 4 16.88 15.7 1.08
2 5 17.08 15.73 1.09
10 1 10.51 17.85 0.59
10 2 16.43 16.58 0.99
10 3 16.16 17.05 0.95
10 4 16.40 17.06 0.96
10 5 17.43 18.42 0.95
The short-term
reversal effect

19. 3. Empirical Study ~Result
Threshold Return[%] Risk[%] R/R
2 0.13 1.67 0.08
4 0.33 3.05 0.11
6 1.57 4.05 0.39
8 5.50* 9.74 0.56
10 6.92* 13.03 0.53
* denotes significance at the 0.1 level.
19
Return[%] Risk[%] R/R
- 4.53 11.52 - 0.39
- Without using causal chain network
➢ Portfolio 2 (long-short : Q5’ – Q1’)
- Using causal chain network
The short-term
reversal effect
The return is higher
as the threshold is
increased

20. ✓ Why the lead-lag exists?
20
3. Empirical Study ~ Discussion
- Investors read financial statement summaries
- Investors are properly aware of the causal chain
read
- under-reaction of the investor
- the limited investor attention
investors

21. 4. Related Works
✓ There are many studies that have examined the lead-lag effect.
21
Author Method Data
Cohen (2008) supply chain network Supply chain
(the Compustat segment files)
Menzly (2006), Shahrur (2010) supply chain network on an industry basis Supply chain
(CRSP)
Rapach (2015) the LASSO regression Returns
(Kenneth French’s Data Library)
Our study Economic causal chain network Text
(Japanese financial statement summaries)
We used chain network only using text data.

22. 5. Conclusion
✓ We proposed the method to predict the stock prices using the
economic causal chain.
✓ We confirmed that the lead-lag effect exists using the causal chain.
22

23. 5. Conclusion
➢ Future tasks
✓ The analysis of the broader investment universe
✓ The analysis of the higher-order causality relationship
23
TOPIX500
The broader
universe
Lead-lag exists ?
The higher-order
causality

24. References
[Cohen, 08] Economic links and predictable returns.
The Journal of Finance, 63(4):1977–2011, 2008.
[Rapach, 15] Industry interdependencies and cross-industry return predictability
[Menzly, 06] Cross-industry momentum.
[Shahrur, 10] Return predictability along the supply chain: the international evidence.
Financial Analysts Journal, pages 60–77
24
[Sakaji, 17] Discovery of rare causal knowledge from financial statement
summaries.
[Mikolov, 13] Distributed representations of words and phrases and their compositionality