2012.03.21 - Presentation-March_2012_05

Prévia do material em texto

BRIC AND THE U.S. FINANCIAL CRISIS: 
AN EMPIRICAL INVESTIGATION OF 
STOCKS AND BONDS MARKETSSTOCKS AND BONDS MARKETS
Marcelo Bianconi Joe A. Yoshino Mariana O. M. de Sousa*
Tufts University University of Sao Paulo University of Sao Paulo
March 21, 2012
What is this paper about?p p
 Brazil, Russia, India and China (BRIC)
2
 Brazil, Russia, India and China (BRIC)
 Class of middle-income emerging market economies of 
relatively large size that could potentially provide the 
needed steam to enhance economic growth in the world 
economy. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What is this paper about?p p
 U.S. 2008 - The largest and most complex financial 
3
 U.S. 2008 The largest and most complex financial 
crisis to date 
One of the main characteristics of the crisis was how 
rapidly it spread from the U.S. housing market to its 
financial market and then to the rest of the world.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
BRIC:
 China and India
4
 China and India
 Economies with most population living in rural areas, 
and relatively closed
 State-controlled capital markets. 
 Their development strategy is export led, based on 
domestic industrialization for export markets
 They are commodity importers.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
BRIC:
 Brazil and Russia
5
 Brazil and Russia
 Have most of their population living in urban areas. 
 Primarily natural resource-based economies and well  Primarily natural resource based economies and well 
known commodity exporters. 
 Their capital markets, while developed at very 
different periods and pace, are much more open and 
currently subject to relatively lower state controls.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What is this paper about?p p
6
Figure 1 – GDP (var. % 2006-2010) 
GDP var. YoY % : BRIC X G7
12.7
14.2
China
Índia
Rússia
4.0
6.1
5.2
7.5
9.6 9.2
10.3 9.7 9.9
6.2 6.8
10.4
8.2 8.5
5.2
4.0
2 6 2 2 2.8
Brasil
Rússia
G7*
‐0.3
2.6 2.2
‐0.2
‐3.7
2.8
2
0
0
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2
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Note: The growth rates of real GDP in the U.S. in the period are: 
2006: 2.62% 
‐7.8
*G7: Canada, France, Germany, Italya, Japan, UK and USA.
Source: IMF‐WEO 2011
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
2007: 1.89%
 2008: -0.34% 
 2009: -3.55% 
2010: 2.98% 
What is this paper about?p p
Thi f th 
7
This paper focuses on the 
measurement of transmission of measurement of transmission of 
financial shocks from the U.S. to 
stocks and bonds markets of 
th BRIC t ithe BRIC countries
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What is this paper about?p p
Can this group of emerging economies be 
8
Can this group of emerging economies be 
considered insulated from the financial 
t f th U S ? stress of the U.S.? 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What is this paper about?p p
Can this group of emerging economies be 
9
Can this group of emerging economies be 
considered insulated from the financial 
t f th U S ? stress of the U.S.? 
Can this group provide diversification 
opportunities?
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What is this paper about?p p
Can this group of emerging economies be 
10
Can this group of emerging economies be 
considered insulated from the financial 
t f th U S ? stress of the U.S.? 
Can this group provide diversification 
opportunities?
 Can this group perform the role of the  Can this group perform the role of the 
locomotive in sustaining world economic 
th?
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
growth?
What we do here…
 First, examine unconditional volatility measures of 
11
 First, examine unconditional volatility measures of 
BRIC and U.S. markets and use the heat map tool 
developed by the IMF (2008, 2009a,b) to p y ( , , )
understand how volatility spreads across the BRIC 
nations over time. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What we do here…
 Second, use information from the heat maps to 
12
 Second, use information from the heat maps to 
estimate simple short term VARs to understand the 
impact of a simple measure of financial stress, p p ,
based upon the S&P500 volatility index VIX and 
the spread between the UK Libor and the U.S. 
federal Funds rate, the TED spread, on the returns 
to stocks and bonds in the BRIC countries. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What we do here…
 Third, use Johansen’s (1988) cointegration
13
 Third, use Johansen s (1988) cointegration
framework to examine long term relationships 
among BRIC countries and the U.S. financial stress g
measure. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What we do here…
 Fourth, use multivariate GARCH methods and 
14
 Fourth, use multivariate GARCH methods and 
dynamic conditional correlations of Engle (2002) to 
examine conditional dynamic volatility and y y
correlations of BRIC market returns, distinguishing 
between own autocorrelations and news effects.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What do we find…
15
 TBD…
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature Review
 Claessens et. al. (2000)
16
 Claessens et. al. (2000)
 contagion between countries can be defined as a 
significant increase in the links between international 
markets after a shock in a country or a group of 
countries. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature Review
 Forbes and Rigobon (2000) 
17
 Forbes and Rigobon (2000) 
 show the links between countries can be measured by 
many different statistics such as correlation in asset 
returns, the probability of a speculative attack, or even 
the transmission of shocks or volatility and bilateral 
l ti f t d i d relations of trade in goods. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…
 U.S. financial crisis, the early empirical evidence:
18
 U.S. financial crisis, the early empirical evidence:
 Eichengreen and Park (2008); Eichengreen et al 
(2009), Dooley and Hutchson (2009); Llaudes et al 
(2010)
 Beginning of the Subprime crisis, from June 2007 to 
August 2008, the emerging economies response was 
limited. 
 The decoupling period since developed and 
developing countries’ growth rates seemed to be 
h di i i di i 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
heading in opposite directions. 
Literature…
 After the Lehman Brother’s bankruptcy in the U.S. in 
19
 After the Lehman Brother s bankruptcy in the U.S. in 
September 2008, the crisis got to its most critical 
period and its transmission to emerging markets p g g
started to be felt more intensely. 
 This second phase is known by many as the re-coupling
period.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…
20
Figure 2: MSCI x MSCI- BRIC 
S Bl bSource: Bloomberg 
450
500
MSCI INDEX
decoupling
300
350
400
450
100
150
200
250
recoupling
0
50
dez‐02 dez‐03 dez‐04 dez‐05 dez‐06 dez‐07 dez‐08 dez‐09
MSCI MSCI BRIC
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
MSCI MSCI BRIC
Literature…
 Aloui et. al (2011) 
21
 Aloui et. al (2011) 
 Study the co-movements between the BRIC stock 
markets and the U.S. during the period of the global 
financial crisis. 
 They find that dependency on the U.S. is higher and 
more persistent to Brazil-Russia than for China-India
We also find similar results here.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…
 Chittedi (2009) 
22
 Chittedi (2009) 
 Found cointegration relationships between BRIC 
countries and the U.S., UK and Japan. 
 Shows India is far less integrated with the global 
markets. 
Our results in this paper show that for bond markets, 
India is insulatedfrom the other BRIC nations. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…
 Morales (2011) 
23
 Morales (2011) 
 Finds evidence of weak integration among Chinese 
financial markets, energy markets and the U.S. stock 
market. 
…shows that the Brazilian, Indian and Russian markets 
are more sensitive to international shocks arisen from 
U.S. markets and also to oil markets instability 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…
 Bhar and Nikolova (2009a, b) 
24
 Bhar and Nikolova (2009a, b) 
 Explored cointegration of the BRIC with their respective 
regions and the world in the post-liberalization period. 
 They found that India has the highest level of 
integration on a regional and world level amongst the 
BRIC countries followed by Brazil, Russia and lastly 
China. 
 They also found the existence of diversification  They also found the existence of diversification 
opportunities for China, given its closed nature of the 
financial system. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature… Multivariate GARCH models and 
dynamic conditional correlationsdynamic conditional correlations
 Mun and Brooks (2011) explore the roles of news 
25
 Mun and Brooks (2011) explore the roles of news 
and volatility in explaining the changes in 
correlations between national stock markets during g
the global financial crisis. 
 They show that the majority of the correlations are 
better explained by volatility rather than news. 
 Here, we find that for stock returns, news and volatility 
 ll i t t b t f b d t d t k are equally important, but for bond returns and stocks 
and bonds jointly, the role of news is less important than 
volatility for the BRIC nations in the 2005-2010 period.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
y p
Literature…Stocks and bonds correlations: 
 Stocks and Bonds: 
26
 Stocks and Bonds: 
 Two different classes of assets where bonds usually 
have seniority over stocks and serve as more short term 
hedge against volatility in stock markets. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…Stocks and bonds correlations: 
 Baur (2007) shows empirically 
27
 Baur (2007) shows empirically 
 in emerging markets, the level of stock-bond correlation 
depends more on cross country influences than on stock 
and bond market interaction. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…Stocks and bonds correlations: 
 Aslanidisy and Christiansenz (2011) 
28
 Aslanidisy and Christiansenz (2011) 
…examine the realized stock-bond correlation based 
upon high frequency returns and find that correlation 
dependence behaves differently when the correlation is 
large negative and large positive.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Literature…Bonds markets: 
 Bond markets: 
29
 Bunda et al (2009) …empirically assess comovements in 
emerging market bond returns relating to external and 
domestic factors during episodes of heightened market domestic factors during episodes of heightened market 
volatility. 
 Between 2003 and 2008, they find that the comovement of 
i k t b d t t b d i b emerging market bond returns appears to be driven more by 
external events, and that contagion in bond markets during this 
period was very low. 
H fi d th t l l i t t l th th  However, we find that news play a less important role than the 
own autocorrelation of volatility and correlations in explaining 
bond returns and the joint behavior of bonds and stocks. 
Th di b d l i d 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 The discrepancy may be due to our more recent sample period 
of 2005-2010 and our focus on the BRIC nations. 
Literature…Bonds markets: 
 Siklos (2011) examines 
30
 Siklos (2011) examines 
…the determinants of bond yield spreads for 22 
emerging markets in the period 1998–2009. 
 He finds that the global financial crisis raised yield 
spreads in all emerging markets, except in Asia, which 
suggests that bond markets in that region were 
decoupled from those in other parts of the world. 
Our findings regarding the insulation of India’s bond Our findings regarding the insulation of India s bond 
market are consistent with Siklos’ findings. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Data:
 Daily data from January 2, 2003 to July 21, 2010 for the stock 
k i bl 
31
market variables. 
 The stock return of the BRICs we use are: 
 Brazil - IBOVESPA: São Paulo Stock Exchange Index; 
 Russia - Russian Trading System; 
 India – Bombay Stock Exchange; 
 China – Shanghai Stock Exchange. 
 Our daily series of the Emerging Markets Bond Indexes (EMBI) for 
the BRIC countries is based on the JPMorgan Bank index as the 
benchmark government bond yields for emerging markets and are 
from January 31, 2005 to July 21, 2010. from January 31, 2005 to July 21, 2010. 
 The U.S. variables are the daily 
 Chicago Board of Trade VIX implied volatility index
 Spread between the LIBOR and the US Fed Funds rate known as TED 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 Spread between the LIBOR and the US Fed Funds rate, known as TED 
spread.
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: STOCKS MARKETSAND SHORT TERM VARS: STOCKS MARKETS
32
Figure 3: BRIC Stock Markets – (Log) Levels and Volatility 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
 
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: STOCKS MARKETSAND SHORT TERM VARS: STOCKS MARKETS
 One tool: The Heat Map
33
p
 Tool elaborated by the IMF(2009a,b, 2010a,b) to show the evolution 
of financial stress by an index that identifies periods in which the 
financial variables being studied reach higher levels of unconditional financial variables being studied reach higher levels of unconditional 
volatility. 
 Our main use here is to show the transmission of the crisis across BRIC 
countries countries. 
 The index is based on a simple computation of z-scores basically 
taking the number of standard deviations away from the mean for a 
b i d base period. 
 As Blanchard (2008) points out, the larger the change in the 
indicator, or the higher the volatility of the indicator, the higher the 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
value of the index.
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: STOCKS MARKETSAND SHORT TERM VARS: STOCKS MARKETS
 Heat Map for Stocks
34
 
Figure 4: Heat Map Stocks 
India ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
Russia ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
Brazil ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
China ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
USA ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
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above 3.5 between 0.5 e 2
between 2 and 3.5 below 0.5
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: BONDS MARKETSAND SHORT TERM VARS:BONDS MARKETS
35
Figure 5a: BRIC EMBI – (Log) Levels and Volatility 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
 
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: BONDS MARKETSAND SHORT TERM VARS: BONDS MARKETS
36
Figure 5b: Spreads Federal Funds rate over EMBI returns; Libor rate over EMBI returns 
 
By Row: Spread – Federal Funds rate and Brazil-EMBI, Russia-EMBI, China-EMBI, India-EMBIy p
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
By Row: Spread – Libor rate and Brazil-EMBI, Russia-EMBI, China-EMBI, India-EMBI 
 
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: BONDS MARKETSAND SHORT TERM VARS: BONDS MARKETS
 One tool: The Heat Map
37
p
Figure 6: Heat Map EMBI 
India ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
Russia ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
Brazil ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
China ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##China ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
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above 3 5 between 0 5 e 2
 
 
above 3.5 between 0.5 e 2
between 2 and 3.5 below 0.5
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARSAND SHORT TERM VARS
 VIX and TED as Measures of U.S. Financial Stress
38
 Linear sum of the z-scores of the:
 Implied volatility index VIX of the Chicago Exchange market
 TED spread, the difference between the Libor and the U.S. Federal 
Funds rate
scoreTEDzscoreVIXzFinStress  __
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARSAND SHORT TERM VARS
 VIX and TED as Measures of U.S. Financial Stress
39
scoreTEDzscoreVIXzFinStress 
 This variable will be used to measure the sources of risks from 
th U S k t t th BRIC t i 
__
the U.S. market to the BRIC countries. 
 This follows the guidelines of Balakrishnan et al (2009), however on 
a minimalist dimension that captures the basic event of the U.S. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
financial crisis without any specifics regarding sectoral sources.
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARSAND SHORT TERM VARS
40
Figure 7: The Financial Stress Index 
Note: The index is the z-score of the VIX index plus the z-score of the TED spread.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
ote: e de s t e sco e o t e de p us t e sco e o t e sp ead.
 
Digression: Great Moderation
Source: G. Hardouvelis
41
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARSAND SHORT TERM VARS
42
 Short Term VARs  Short Term VARs 
 Main ingredients:
 Returns on Stocks Returns on Stocks
 Returns on Bonds
 FinStress (change) FinStress (change)
 Order impact for VARs obtained from Heat Maps
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: STOCK RETURNSAND SHORT TERM VARS: STOCK RETURNS
43
 Financial Stress (change)  Return Brazil  Return Russia  Return India  Return China
Figure 8: Orthogonolized Impulse Response Function – Short Term VAR – Stock Returns 
 
Row: Shocks in change in Financial Stress variable. Response of stock returns in Brazi
China, India, Russia.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
China, India, Russia. 
 
TRANSMISSION OF FINANCIAL CRISIS 
AND SHORT TERM VARS: BONDS RETURNSAND SHORT TERM VARS: BONDS RETURNS
44
 Financial Stress (change)  Return Brazil  Return Russia  Return India  Return China.
Figure 9: Orthogonolized Impulse Response Function – Short Term VAR – Bond Returns 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
y Row: Shocks in change in Financial Stress variable. Response of bond returns in Brazil
China, India, Russia.
TRANSMISSION OF FINANCIAL CRISIS AND SHORT TERM VARS:
STOCKS & BONDS RETURNS JOINT DYNAMICSSTOCKS & BONDS RETURNS JOINT DYNAMICS
45
 Financial Stress (change)  Stock Return Brazil  EMBI Return Brazil  Stock Return Russia  EMBI Return Russia 
Stock Ret rn China  EMBI Ret rn China  Stock Ret rn India  EMBI Ret rn IndiaStock Return China  EMBI Return China  Stock Return India  EMBI Return India
Figure 10: Orthogonolized Impulse Response Function – Short Term VAR 
Joint Dynamics Stock and Bond Returns 
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
Shocks in change in Financial Stress variable. 
Row 1: Response of bond returns in Brazil, Russia. 
Row 2: Response of stock returns in Brazil, Russia. 
Row 3: Response of bond returns in China, India. 
Row 4: Response of stock returns in China, India. 
 
TRANSMISSION OF FINANCIAL CRISIS AND SHORT 
TERM VARS: SUMMARY TERM VARS: SUMMARY 
46
 Stocks react initially negatively  Stocks react initially negatively 
 Bonds go in the opposite direction 
(positively) at least for Brazil Russia and (positively) at least for Brazil, Russia and 
China
Eff h li d d  Effects are very short lived and temporary 
with Brazil and Russia showing more similar 
d i dynamic patterns
What about long run, volatility, correlations… 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Long Run…g
47
 Cointegration… Cointegration…
 Johanssen (1988)…
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
STOCKS MARKETS - COINTEGRATIONSTOCKS MARKETS COINTEGRATION
48
 Level unit roots – YES
 Trace and Eigenvalue Tests – ONE COINTEGRATING 
RELATIONSHIP
F i g u r e 1 1 : V e c t o r E r r o r C o r r e c t i o n M o d e l : C o i n t e g r a t i n g r e l a t i o n s h i p – S t o c k R e t u r n s 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
STOCKS MARKETS - COINTEGRATIONSTOCKS MARKETS COINTEGRATION
49
 Level OIRF:
Figure 12: Vector E rror Correct ion Model (VECM) - S tocks 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 Response to Shock in Financial Stress on: 1. Stock Index Brazil; 2. Stock Index
Russia; 3. Stock Index China; 4. Stock Index India.
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
STOCKS MARKETS - COINTEGRATIONSTOCKS MARKETS COINTEGRATION
50
 Speeds of Adjustment:p j
Table 3: Speed of Adjustments to Cointegrating Relationship – Stocks
D_lbrazil 
L._ce1 0.000144 
 (0.000256) 
D_lrussia 
L ce1 -0 000725*L._ce1 0.000725 
 (0.000305) 
D_lchina 
L._ce1 0.0000127 
 (0.000235) 
D_lindia 
L._ce1 -0.000874*** 
(0 000225) (0.000225) 
N 1881 
Standard errors in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
 
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS MARKETS - COINTEGRATIONBONDS MARKETS COINTEGRATION
51
 Level unit roots – YES
 Trace and Eigenvalue Tests – ONE COINTEGRATINGRELATIONSHIP
ܨ݅݊ܵݐݎ݁ݏݏݐ ൅ 	1.97 ܧܾ݉݅_ܤݎܽݖ݈݅ݐ െ 2.01 ܧܾ݉݅_ܴݑݏݏ݅ܽݐ ൅ 4.11 ܧܾ݉݅_ܫ݊݀݅ܽݐ െ
	1.51	ܧܾ݉݅_ܥ݄݅݊ܽݐ ൅ ܥ݋݊ݏݐ ൌ 0. 
Figure 14: Vector Error Correction Model: Cointegrating relationship - Bonds 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS MARKETS - COINTEGRATIONBONDS MARKETS COINTEGRATION
52
 Level OIRF: Figure 15: Vector E rror Correct ion Model (VECM ): Bondsg ( )
 Response to Shock in Financial Stress on: 1. Bond Index Brazil; 2. Bond Index 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
p ;
Russia; 3. Bond Index India; 4. Bond Index China.
 
 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS MARKETS - COINTEGRATIONBONDS MARKETS COINTEGRATION
53
 Speeds of Adjustment:p j
Table 8: Speed of Adjustment to Cointegrating Relationship – Bonds
D_lbrazil 
L._ce1 0.00303** 
(2.85) (2.85) 
D_lrussia 
L._ce1 0.00471** 
 (3.12) 
D_lindia 
L._ce1 -0.00160*** 
 (-8.77) 
D lchinaD_lchina 
L._ce1 0.00877** 
 (2.82) 
N 1363 
t statistics in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS & STOCKS MARKETS - COINTEGRATIONBONDS & STOCKS MARKETS COINTEGRATION
54
 Level unit roots – YES
 Trace and Eigenvalue Tests – TWO COINTEGRATING RELATIONSHIP
ܨ݅݊ܵݐݎ݁ݏݏݐ ൅ 	1.63	ܧܾ݉݅_ܤݎܽݖ݈݅ݐ െ 1.33 ܧܾ݉݅_ܴݑݏݏ݅ܽݐ ൅ 	3.08 ܧܾ݉݅_ܫ݊݀݅ܽݐ െ
	1.95	ܧܾ݉݅_ܥ݄݅݊ܽݐ ൅ ܥ݋݊ݏݐ ൌ 0 (4a) 
ܵݐ݋ܿ݇ݏ_ܤݎܽݖ݈݅ݐ ൅ 0.61 ܵݐ݋ܿ݇ݏ_ܴݑݏݏ݅ܽݐ ൅ 0.31 ܧܾ݉݅_ܴݑݏݏ݅ܽݐ െ 1.72 ܧܾ݉݅_ܫ݊݀݅ܽݐ െݐ ݐ ݐ ݐ
0.16	ܵݐ݋ܿ݇ݏ_ܥ݄݅݊ܽݐ െ 0.66 ܧܾ݉݅_ܥ݄݅݊ܽݐ ൅ ܥ݋݊ݏݐ ൌ 0 (4b) 
F i g u r e 1 7 : V e c t o r E r r o r C o r r e c t i o n M o d e l : C o i n t e g r a t i n g r e l a t i o n s h i p s 
J o i n t B e h a v i o r S t o c k s - B o n d s 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 C E _ 0 1 = E q u a t i o n ( 4 a ) 
C E _ 0 2 = E q u a t i o n ( 4 b ) 
 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS & STOCKS MARKETS - COINTEGRATIONBONDS & STOCKS MARKETS COINTEGRATION
55
 Level OIRF:
igure 18: Vector Error Correction Model (VECM): Joint Behavior Stock Returns and Bond Retur
Plots are Shock in Financial Stress on: 1. Stocks-Brazil; 2. EMBI-Brazi; 3. 
Stocks-Russia; 4. EMBI-Russia. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Response to Shock in Financial Stress on: 1. Stocks-China; 2. EMBI-China; 3. 
Stocks-India; 4. EMBI-India. 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS & STOCKS MARKETS - COINTEGRATIONBONDS & STOCKS MARKETS COINTEGRATION
56
 Speeds of Adjustment:p j
Table 13: Adjustments to Cointegrating Relationship – Stocks-Bonds 
D_lstocks_brazil 
L._ce1 -0.0000341 
 (0.000749) 
L._ce2 -0.0121** 
 (0.00454) 
D_lbonds_brazil 
L._ce1 0.00324** 
(0 00119) (0.00119) 
L._ce2 -0.00444 
 (0.00720) 
D_lstocks_russia 
L._ce1 -0.000481 
 (0.000911) 
L._ce2 -0.00558 
 (0.00552) 
D_lbonds_russia 
L._ce1 0.00414* 
(0 00168) (0.00168) 
L._ce2 0.00575 
 (0.0102) 
D_lstocks_india 
L._ce1 -0.000211 
 (0.000658) 
L._ce2 -0.0101* 
 (0.00399) 
D_lbonds_india 
L._ce1 -0.00193*** 
 (0.000203) 
L._ce2 0.00606*** 
 (0.00123) 
D_lstocks_china 
L._ce1 0.000912 
 (0.000726) 
L._ce2 -0.00854 
 (0.00440) 
D_lbonds_china 
L._ce1 0.00327 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
_
 (0.00345) 
L._ce2 0.0959*** 
 (0.0209) 
N 1363 
Standard errors in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
Conditional Volatility…y
57
 Arch…Engle (1982)… Arch…Engle (1982)…
 Arch family…
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
STOCKS RETURNS - MGARCHSTOCKS RETURNS MGARCH
58
Table 4: ARCH Effects – Stock Returns 
ARCH_ret_brazil 
L.arch 0.0761*** 
 (3.30) 
 
_cons 0.000360*** 
(17 43) (17.43) 
ARCH_ret_russia 
L.arch 0.285*** 
 (5.37) 
 
_cons 0.000346*** 
 (14.14) 
ARCH ret chinaARCH_ret_china 
L.arch 0.157** 
 (2.89) 
 
_cons 0.000296*** 
 (14.22) 
ARCH_ret_india 
L.arch 0.224***
 (5.03) 
 
_cons 0.000212*** 
 (14.56) 
N 1882 
t statistics in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS RETURNS - MGARCHBONDS RETURNS MGARCH
59
Table 9: Multivariate Garch – Arch Effects – Bond Returns 
ARCH_dlbrazil 
L.arch 0.295*** 
 (3.50) 
 
_cons 0.00177*** 
 (6.23) 
ARCH_dlrussia 
L h 0 394***L.arch 0.394***
 (3.62) 
 
_cons 0.00343*** 
 (6.16) 
ARCH_dlchina 
L.arch 1.705*** 
(4.69) (4.69) 
 
_cons 0.00296*** 
 (5.13) 
ARCH_dlindia 
L.arch 0.245 
 (1.86) 
 
_cons 0.0000224*** 
 (5.73) 
N 1364 
t statistics in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS & STOCKS RETURNS - MGARCHBONDS & STOCKS RETURNS MGARCH
60
Table 14: Multivariate Garch – Arch Effects – Stock and Bond Returns 
ARCH_dlstocks_brazil 
L.arch 0.102** 
(0 0345) (0.0345) 
_cons 0.000450*** 
 (0.0000345) 
ARCH_dlbonds_brazil 
L.arch 0.163** 
 (0.0504) 
_cons 0.00107*** 
 (0.0000830) 
ARCH_dlstocks_russia 
L arch 0 265***L.arch 0.265***
 (0.0771) 
_cons 0.000489*** 
 (0.0000441) 
ARCH_dlbonds_russia 
L.arch 0.240*** 
 (0.0623) 
_cons 0.00209*** 
 (0.000164) 
ARCH dlstocks chinaARCH_dlstocks_china 
L.arch 0.125* 
 (0.0559) 
_cons 0.000490*** 
 (0.0000412) 
ARCH_dlbonds_china 
L.arch 1.122*** 
 (0.208) 
_cons 0.00206*** 
 (0.000301) ( )
ARCH_dlstocks_india 
L.arch 0.233*** 
 (0.0674) 
_cons 0.000286*** 
 (0.0000260) 
ARCH_dlbonds_india 
L.arch 0.173 
 (0.0924) 
_cons 0.0000151***
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
_
 (0.00000165) 
N 1364 
Standard errors in parentheses* p<0.05, ** p<0.01, *** p<0.001 
Conditional Correlation…
61
 DCC…Engle (2002)… DCC…Engle (2002)…
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
MGARCH – DYNAMIC CORRELATIONSMGARCH DYNAMIC CORRELATIONS
62
The dynamic conditional correlation model of Engle (2002) is given by 
ݍ݅,݆ ,ݐ ൌ ߩ݅,݆തതതത ൅	ߣ1൫ߝ݅,ݐെ1݆ߝ ,ݐെ1 െ ߩ݅,݆തതതത൯ ൅ ߣ2൫ݍ݅,݆ ,ݐെ1 െ ߩ݅,݆തതതത൯	; 		݅ ൌ 1,2,… ; ݆ ൌ 1,2, (2) 
where ݍ݅,݆ ,ݐ is the time varying conditional correlation of the endogenous variables, ߩ݅,݆തതതത is
the constant unconditional correlation of the bond and stock returns ൫ߝ݅ ݐ 1݆ߝ ݐ 1൯ arethe constant unconditional correlation of the bond and stock returns, ൫ߝ݅,ݐെ1݆ߝ ,ݐെ1൯ are
standardized residuals of the bond and stock returns, and	ߣ1, ߣ2 are adjustment parameters
in the correction mechanism (2) for the dynamic conditional correlations, assumed to be
common to all endogenous variables. In particular, ߣ1 is the news parameter which
captures the deviations of the standardized residuals from the unconditional correlation,
while	ߣ2 is the decay adjustment parameter that captures the autocorrelation of the
correlations themselves. In effect, the process (2) is such that correlations rise when
returns move together and fall when they move in opposite direction see Engle (2002)
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
returns move together and fall when they move in opposite direction, see Engle (2002).
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
STOCKS RETURNS – MGARCH - CORRELATIONSSTOCKS RETURNS MGARCH CORRELATIONS
63
Table 5: Unconditional Correlations – Stock Returns 
corr(FinStress, Ret_Brazil) 
_cons -0.462*** 
 (-21.49) 
corr(FinStress, Ret_Russia) 
_cons -0.197*** 
 (-7.89) 
corr(FinStress, Ret_China) 
_cons 0.0000571 
 (0.00) 
corr(FinStress, Ret_India) 
_cons -0.129*** 
 (-4.88) 
corr(Ret Brazil, Ret Russia) ( _ , _ )
_cons 0.279*** 
 (11.72) 
corr(Ret_Brazil, Ret_China) 
_cons 0.108*** 
 (4.65) 
corr(Ret_Brazil, Ret_India) 
_cons 0.211*** 
 (8.30) 
corr(Ret_Russia, Ret_China) 
cons 0 0918***_cons 0.0918***
 (3.86) 
corr(Ret_Russia, Ret_India) 
_cons 0.260*** 
 (11.05) 
corr(Ret_China, Ret_India) 
_cons 0.146*** 
 (6.26) 
Adjustment 
lambda1 0.0191 
(1 24) (1.24) 
 
lambda2 0.365 
 (0.79) 
df 
_cons 4.083*** 
 (20.13) 
N 1882 
[Adjustment]lambda1 – [Adjustment]lambda2 = 0 
[Adjustment]lambda1 = 0 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
 chi2( 2) = 11.28 
 Prob > chi2 = 0.0036 
t statistics in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
STOCKS RETURNS – MGARCH - CORRELATIONSSTOCKS RETURNS MGARCH CORRELATIONS
64
Figure 13: Predicted Dynamic Conditional Correlations – Stock Returns 
 Correlations of Financial Stress measure: By Row: Stock returns-Brazil; Stock returns 
Russia; Stock returns China; Stock returns India. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC 
rrelations By Row: Russia-Brazil; China-Brazil; India-Brazil; China-Russia; India-Russi
India-China.
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS RETURNS – MGARCH - CORRELATIONSBONDS RETURNS MGARCH CORRELATIONS
65
Table 10: Unconditional Correlations – Bond Returrns 
corr(Fin Stress, ret_brazil) 
_cons 0.455*** 
 (14.97) 
(Fi St t i )corr(Fin Stress, ret_russia) 
_cons 0.352*** 
 (10.71) 
corr(Fin Stress, ret_china) 
_cons 0.196*** 
 (5.73) 
corr(Fin Stress, ret_india) 
_cons 0.0123 
 (0.35) 
corr(dlbrazil_ret_russia) 
_cons 0.695***
 (33.65) 
corr(dlbrazil_ret_china) 
_cons 0.343*** 
 (10.30) 
corr(dlbrazil_ret_india) 
_cons 0.0622 
 (1.73) 
corr(dlrussia_ret_china) 
_cons 0.345***_
 (11.32) 
corr(dlrussia_ret_india) 
_cons 0.0865* 
 (2.45) 
corr(dlchina_ret_india) 
_cons -0.0546 
 (-1.66) 
Adjustment 
lambda1 0.0209** 
 (3.13) ( )
 
lambda2 0.914*** 
 (52.58) 
df 
_cons 2.564*** 
 (20.75) 
N 1364 
[Adjustment]lambda1 – [Adjustment]lambda2 = 0 
[Adjustment]lambda1 = 0 
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 chi2( 2) = 2996.88 
 Prob > chi2 = 0.0000 
t statistics in parentheses 
* p<0.05, ** p<0.01, *** p<0.001 
 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS RETURNS – MGARCH - CORRELATIONSBONDS RETURNS MGARCH CORRELATIONS
66
Figure 16: Predicted Dynamic Conditional Correlations – Bond Returns 
 rrelations of Financial Stress measure: By Row: Bond returns-Brazil; Bond returns Russi
Bond returns China; Bond returns India. 
 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
rrelations By Row: Russia-Brazil; China-Brazil; India-Brazil; China-Russia; India-Russi
India-China.
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS & STOCKS RETURNS – MGARCH -
CORRELATIONS
67
Table 15: Unconditional Correlations – Stock and Bond Returns 
corr(stocks_brazil,bonds_brazil) -0.486*** 
 (0.0259) 
corr(stocks_brazil,bonds_russia) -0.302*** 
(0 0301) (0.0301) 
corr(stocks_brazil,bonds_china) -0.139*** 
 (0.0289) 
corr(stocks_brazil,bonds_india) 0.00261 
 (0.0305) 
corr(bonds_brazil,stocks_russia) -0.298*** 
 (0.0297) 
corr(bonds_brazil,stocks_china) -0.0336 
 (0.0301) 
corr(bonds brazil,stocks india) -0.163***( _ , _ )
 (0.0313) 
corr(stocks_russia,bonds_russia) -0.265*** 
 (0.0292) 
corr(stocks_russia,bonds_china) -0.0581 
 (0.0314) 
corr(stocks_russia,bonds_india) 0.000667 
 (0.0276) 
corr(bonds_russia,stocks_china) -0.0236 
 (0.0294) 
corr(bonds russia stocks india) 0 144***corr(bonds_russia,stocks_india) -0.144***
 (0.0298) 
corr(stocks_china,bonds_china) -0.0235 
 (0.0302) 
corr(stocks_china,bonds_india) 0.0219 
 (0.0302) 
corr(bonds_china,stocks_india) -0.00496 
 (0.0295) 
corr(stocks_india,bonds_india) 0.000624 
 (0.0305) 
Adjustment 
lambda1 0.0139*** 
 (0.00370) 
lambda2 0.861*** 
 (0.0337) 
df 3.472*** 
 (0.162) 
N 1364 
( 1) [Adjustment]lambda1 – [Adjustment]lambda2 = 0 
( 2) [Adjustment]lambda1 = 0 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
 
 chi2( 2) = 1057.23 
 Prob > chi2 = 0.0000 
_____________________________________________________ 
Standard errors in parentheses* p<0.05, ** p<0.01, *** p<0.001 
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS: 
BONDS & STOCKS RETURNS – MGARCH -
CORRELATIONS
68
Figure 19: Predicted Dynamic Conditional Correlations - Joint Behavior Stock-Bond Returns 
Correlations By Row: EMBI-Brazil,Stocks-Brazil; EMBI-Russia,Stocks-Russia; EMBI-China, 
Stocks-China; EMBI-India-Stocks-India. 
Correlations By Row: EMBI-Russia,Stocks-Brazil; EMBI-China,Stocks-Brazil; EMBI-India, 
tocks-Brazil; EMBI-China-Stocks-Russia; EMBI-India,Stocks-Russia; EMBI-India,Stocks-Chin
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Correlations By Row: Stocks-Russia,Bonds-Brazil; Stocks-China,Bonds-Brazil; Stocks-
China,EMBI-Russia; Stocks-India,EMBI-Brazil; Stocks-India,EMBI-China; Stocks-India,EMBI-
R ssia
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS:
SUMMARY
69
 Stocks:
 …evidence suggests that Brazil and Russia respond more to the U.S. 
financial stress measure and are more correlated among each other 
relative to India and China at least in the short term. 
l l i hi b k k i B il  …long term relationship between stock market returns in Brazil, 
India and the U.S. measure of financial stress is significant, but only 
India is approaching the longer term in a significant rate of speed in 
this periodp
 Russia responds more to conditional volatility news, but neither news 
nor autocorrelation of correlations play a predominant role in the 
case of dynamic conditional correlations of stock returns
 The correlations among all parties have increased since the 
beginning of the financial crisis in this case.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS:
SUMMARY
70
Stocks:
Table 16: Qualitative Effect of U.S. Financial Stress on BRIC Stocks Markets
Stocks 
Markets 
Effect of U.S. Financial Stress to: 
 Brazil Russia India China 
Short Term 
VAR 
Impulse 
Responses 
 
 
Negative 
 
 
Negative 
 
 
Negative 
 
 
Null 
Responses 
Returns 
VECM 
Long Term 
Cointegration 
Levels 
 
Positive 
 
Null* 
 
Negative 
 
Null* 
VECM 
Impulse 
Responses 
Levels 
 
 
Negative 
Permanent 
 
Negative 
Permanent; 
Significant Speed 
 
Negative 
Permanent; 
Significant 
 
 
Negative 
Temporary Levels Permanent Significant Speed 
of Adjustment 
Significant 
Speed of 
Adjustment 
Temporary 
 
ARCH 
wn Conditional 
Volatility News 
Returns 
 
Yes 
 
Yes 
 
Yes 
 
Yes 
MGARCH 
Unconditional 
C l ti 
 
Negative 
 
Negative 
 
Negative 
 
Null* 
Correlations 
Returns 
MGARCH 
Dynamic 
Conditional 
Correlations 
Returns 
 
Negative 
> After 
September 
2008 
 
Negative 
> After 
September 
2008 
Negative, Small 
> After 
September 
2008 
 
 
Negligible 
*Not statistically significant. 
Source: Tables 2-5; Figures 8, 12, and 13. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS:
SUMMARY
71
 Bonds:
 …evidence for bonds is very different than for stocks both qualitatively 
and quantitatively. 
 The bonds market shows that in the long term all EMBI indexes for Brazil, 
Russia India and China are related to the U S financial stress measure Russia, India and China are related to the U.S. financial stress measure. 
 All BRIC countries display significant conditional heteroskedasticity with 
Russia the most responsive country to conditional volatility news, while China 
does respond and shows signs of volatility instability in its bond returns 
i d index. 
 The own correlations are more important in determining the evolution of the 
conditional correlations of bond returns relative to the unexpected news.
 The dynamic conditional correlations among bond returns of all BRIC  The dynamic conditional correlations among bond returns of all BRIC 
nations have increased after the September 2008 event, but not for India-
EMBI which is seen to be insulated and uncorrelated to other BRIC countries.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS:
SUMMARY
72
 Bonds:
Table 17: Qualitative Effect of U.S. Financial Stress on BRIC Bonds Markets 
Bonds 
Markets 
Effect of U.S. Financial Stress to: 
 Brazil Russia India China 
Short Term 
VAR 
Impulse 
Responses 
Returns 
 
Positive 
 
Positive 
 
Null 
 
Positive 
VECM 
Long Term 
Cointegration 
Levels 
Negative; 
Significant 
Speed of 
Adjustment 
Positive; 
Significant 
Speed of 
Adjustment 
Negative; 
Significant 
Speed of 
Adjustment 
Positive; 
Significant 
Speed of 
Adjustment 
VECM 
Impulse 
Responses 
Levels 
Positive 
Permanent 
Positive 
Permanent 
Negative 
Permanent 
Positive 
Permanent 
ARCH 
wn Conditional 
Volatility News 
Returns 
 
Yes 
 
Yes 
 
Null* 
 
Yes, 
Not Stable 
MGARCH 
Unconditional 
 
Positive 
 
Positive 
 
Null* 
 
Positive Unconditional 
Correlations 
Returns 
Positive Positive Null Positive 
MGARCH 
Dynamic 
Conditional 
Correlations 
Returns 
 
Positive 
> After 
September 
2008 
 
Positive 
> After 
September 
2008 
 
 
Negligible 
 
 
Positive, 
> After 
September 
2008 
* Not statistically significant. 
Source: Tables 6-10; Figures 9 15 and 16
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Source: Tables 6-10; Figures 9, 15, and 16.
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS:
SUMMARY
73
 Bonds & Stocks:
 …joint dynamic behavior of stocks and bonds displays
 one long run relationship between U.S. financial stress and BRIC bond returns
 another for stocks and bonds of BRIC countries only, independent of the U.S. 
financial stress measure financial stress measure. 
 Stock and bond returns are significantly negatively correlated for Brazil 
and Russia, but not significant for China and India. 
 Bond returns in Russia are significantly negatively correlated with stock g y g y
returns in India. The largest correlations are between Brazil and Russia. 
 In the stock-bonds multivariate model, the own correlations are more 
important in determining the evolution of the conditional correlations 
relative to the unexpected news relative to the unexpected news. 
 The pattern of dynamic conditional correlations is that the correlations 
between stock and bond returns increase after the Lehman event in 
September 2008, except for bond returns in India.
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
COINTEGRATION, ARCH AND DYNAMIC CONDITIONAL CORRELATIONS:
SUMMARY
74
 Bonds & Stocks: Bonds & Stocks:
Table 18: Joint Behavior of Stocks and Bonds Returns: BRIC Correlations
 
BRIC 
Correlations 
 
 
STOCKS 
 
Unconditional Brazil Russia India China 
BONDS 
Brazil Negative Negative Negative Null* 
Russia Negative Negative Negative Null* 
India Null* Null* Null* Null* 
China Negative Null* Null* Null* 
 
STOCKS 
 
Dynamic Dynamic 
Conditional Brazil Russia India China 
BONDS 
Brazil 
Negative 
Negative 
> After 
September 
2008 
Negative 
> After 
September 
2008 
 
Negative, 
Small 
Russia Negative 
> After 
Negative 
> After 
Negative 
> After 
 
Negative, 
September 
2008 
September 
2008 
September 
2008 
Negative, 
Small 
India Null Null Null Null 
 
China 
Negative 
> After 
September 
2008 
Negative 
> After 
September 
2008 
Negative 
> After 
September 
2008 
Negative 
> After 
September 
2008 
* Not statistically significant. 
Source: Table 15; Figure 19
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
Source: Table 15; Figure 19.
BRIC and the U.S. Financial Crisis: 
An Empirical Investigation of Stocks and Bonds MarketsAn Empirical Investigation of Stocks and Bonds Markets
75
 We were set to answer three basic questions. q
 First to determine whether or not BRIC can be 
considered insulated from the financial stress of the 
U.S.
 The answer seems to balance towards the negative. 
W f d h B il d R i hff d We found that Brazil and Russia are the most affected 
countries followed by China, and India much less so. 
We also found that the conditional correlations of stock We a so ou d a e co d o a co e a o s o s oc 
and bond returns with the U.S. financial stress increased 
after the ‘official’ start of the financial crisis in 
September 2008 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
September 2008. 
BRIC and the U.S. Financial Crisis: 
An Empirical Investigation of Stocks and Bonds MarketsAn Empirical Investigation of Stocks and Bonds Markets
76
 We were set to answer three basic questions. We were set to answer three basic questions.
 Second, whether or not BRIC can provide diversification 
opportunities. pp
 Our findings indicate that BRIC bonds markets respond 
positively in the very short term to U.S. financial stress, but 
th b d k t i I di d t h d f th the bond market in India seems more detached from other 
BRIC bond markets and respond quantitatively less to the 
U.S. financial stress measure overall. 
 Also, the stock market of China responded much less to U.S. 
financial stress relative to the other countries in this period. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
BRIC and the U.S. Financial Crisis: 
An Empirical Investigation of Stocks and Bonds MarketsAn Empirical Investigation of Stocks and Bonds Markets
77
 We were set to answer three basic questions. q
 Third, whether or not BRIC can perform the role of 
locomotive in sustaining world economic growth. 
 It is less clear to us whether this is the case given our 
evidence. 
 Yes: We found that, in the long run, bond markets deviate , g ,
much more from the U.S. financial stress measure than bonds 
and stocks of the BRIC nations deviate among themselves. 
 No: However we found evidence of relative increase in  No: However, we found evidence of relative increase in 
volatility after the crisis thus pointing to potential 
interdependencies and contagion effects. 
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
What’s next?
78
 Several potential avenues for future research… Several potential avenues for future research…
March 21, 2012Bianconi , Yoshino, Sousa; BRIC
79
Thank You!
March 21, 2012Bianconi , Yoshino, Sousa; BRIC