Financial Conditions Index’s

Construction and Its Application on

Financial Monitoring and Economic

Forecasting

Zheng Guihuan

June, 2014

Outline

• Overview

• Introduction of the FCI construction

method

• Calculate China’s FCI

• FCI can reflect the situation of financial

operation in China

• FCI can predict the economic trends

better

• Conclusion

1. Overview (1)

• Definition of Financial Conditions Index (FCI) :

– a comprehensive index which is constructed based on

the combination of variables, such as currency price (For

example, money, exchange rate), and asset price (For

example, stock index and house price).

• FCI can make up the shortage of using the

conventional indexes, such as money supply and

interest rate, in measuring the financial conditions

and forecasting the economic trend.

1. Overview (2)

• In 1990s, Central Bank of Canada developed

the Monetary Conditions Index (MCI).

• MCI has been widely applied in many central

banks and international institutions.

• With the development of economy and finance,

the information of asset price has been paid

more and more attention to evaluate financial

situation.

• Some researchers developed FCI that adding

some asset price variables into the

combination of index.

2. Introduction of FCI construction method

The

Construction

Model

Selection

of the

Indicators

Calculate

the

weights

Constructing FCI

2.1 Indicator selection

Type Indicators

Money Supply narrow money supply(M1),broad money

supply(M2)

Exchange Rate

bilateral exchange rate

exchange rate index, such as efficient exchange

rate from BIS

Interest Rate

market interest rate: short term interest rate,

bond interest rate, bond interest margin

policy interest rate: deposit or loan benchmark

interest rate

Capital Market market value/GDP, price earnings ratio, stock

wealth owned by household, stock price

Real Estate Price house average price, real estate climate indices

2.2 Common forms of the FCI

2.3 Classification of the methods building

the FCI

• Reduced Aggregate Demand Equation model

•The VAR model

• Weighted principal components

Calculate the weights in FCI based on the

coefficients of equation.

Calculate the weights based on the impact level.

Take the significance probability of the principal

component as the weights

The shortage of existing methods

• One problem is about the estimation

models. Deviation from equilibrium of

each variable need to be estimated in the

common measuring form of the FCI,

which may cause large error.

• Another one is about the determination of

the weights, whose estimation models will

differ depending on the purpose of FCI.

The innovation of this paper (1)

• we select the percent change rate of the

variable as indicators to construct the FCI,

which not only effectively describe the

indicators, but also avoid errors arising from of

gap measuring.

The innovation of this paper (2)

• Second, the Principal Component

Analysis and Dynamic Factor methods are

both introduced to build FCI.

• Dynamic Factor method can directly

extract factor sequences which depict the

characterized fluctuation of variables,

without determining weights.

3. Calculate China’s FCI

Type Indicators Sign Data resources

Money supply

M2, the current growth rate of balance at period-end M2 People’s Bank of China

Interest rate

7 days interbank funding weighted average nominal

interest rates in The national interbank funding

center

Exchange rate

RMB’s nominal effective exchange rate index, the

current growth rate ex Bank for International

Settlements

Stock index

Shanghai securities composite index, the current

growth rate stock Shanghai Stock Exchange

House price

Commercial housing sales price(Commercial housing

sales divided by the number of commercial housing sales area), the current growth rate

hp National Bureau of Statistics

FCI

-1.5

-1

-0.5

0

0.5

1

1.5

2

-10

-5

0

5

10

15

20

25

30

20

00

-01

20

00

-07

20

01

-01

20

01

-07

20

02

-01

2002-0

7

20

03

-01

20

03

-07

20

04

-01

20

04

-07

20

05

-01

20

05

-07

2006-0

1

20

06

-07

20

07

-01

20

07

-07

20

08

-01

20

08

-07

20

09

-01

20

09

-07

20

10

-01

20

10

-07

2011

-01

2011

-07

20

12

-01

20

12

-07

20

13

-01

FCI_Dynamic Factor

FCI_Principal Component Analysis(right axis)

FCI and MCI

-1.5

-1

-0.5

0

0.5

1

1.5

2 2000-0

1

2000-0

8

2001-0

3

2001-1

0

2002-0

5

2002-1

2

2003-0

7

2004-0

2

2004-0

9

2005-0

4

2005-1

1

2006-0

6

2007-0

1

2007-0

8

2008-0

3

2008-1

0

2009-0

5

2009-1

2

2010-0

7

2011-0

2

2011-0

9

2012-0

4

2012-1

1

2013-0

6

prudent monetary policies

prudent monetary policies moderates the money

supply and credit

mode- rately tight to

tight

moderately loose

monetary policy

prudent monetary policies

FCI

MCI

4. FCI can reflect the situation of financial

operation in China

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

20

05

-03

20

05

-09

2006

-03

20

06

-09

20

07

-03

20

07

-09

20

08

-03

20

08

-09

20

09

-03

20

09

-09

20

10

-03

20

10

-09

2011

-03

2011

-09

20

12

-03

20

12

-09

20

13

-03

20

13

-09

20

14

-03

FCI

5. FCI can predict the economic trends

better (1)

• FCI performs better as a leading indicator of

CPI

coefficient of

correlation

leading

length(months)

FCI 0.72 10

M2 0.48 12

interest rate -0.41 12

exchange

rate 0.59 11

5. FCI can predict the economic trends

better (2)

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

96

98

100

102

104

106

108

110

2005-0

3

20

05

-09

20

06

-03

20

06

-09

20

07

-03

20

07

-09

20

08

-03

20

08

-09

20

09

-03

20

09

-09

20

10

-03

20

10

-09

2011

-03

20

11

-09

20

12

-03

20

12

-09

20

13

-03

20

13

-09

20

14

-03

CPI-TC

FCI(right axis)

• FCI performs better as a leading indicator of

GDP

5. FCI can predict the economic trends

better (3)

coefficient of

correlation

leading

length(quarters)

FCI 0.82 2

M2, interest

rate and

exchange rate

No passing the statistical test，and

the anteriority is not significant

5. FCI can predict the economic trends

better (4)

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

0

5

10

15

20

25

20

05

-03

20

05

-09

20

06

-03

20

06

-09

20

07

-03

20

07

-09

20

08

-03

20

08

-09

20

09

-03

20

09

-09

20

10

-03

2010-0

9

2011

-03

2011

-09

20

12

-03

2012-0

9

20

13

-03

20

13

-09

20

14

-03

GDP-TC

FCI(right axis)

6. Conclusion

• FCI can better reflect the situation of China's financial

operation, and can better predict the economic trends.

Therefore, FCI can serve as an important reference

index, whose performance is superior to single financial

variables.

• Though the literature found that introducing asset-price

variable into MCI to design FCI is an important

approach to improve the MCI’s performances in

economic forecasting and policy decision-making, but

assets price in China's FCI provides limited information.

With further developing of the financial market, asset

prices information will be more important.