Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling
This study examines the sensitivity of commercial bank stock excess returns to the volatility level and financial risk factors, measured by interest rate risk and exchange rate risk across the recent Asian financial crisis horizon, via Multivariate GARCH in Mean (MGARCH-M) model. Application of t...
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my-upm-ir.83072024-01-04T01:26:24Z Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling 2002-02 Hooy, Chee Wooi This study examines the sensitivity of commercial bank stock excess returns to the volatility level and financial risk factors, measured by interest rate risk and exchange rate risk across the recent Asian financial crisis horizon, via Multivariate GARCH in Mean (MGARCH-M) model. Application of time varying risk model into bank's stocks is of special importance as both the financial risk factors and the stock returns volatility varied substantially in the Asian recent financial crisis. Generally, MGARCH (p, q)-M process captures almost all of the linear dependence in both the returns' mean, and the residual's variance of the fitted model. The results of this study further show that in Malaysia, the pattern of risk sensitivity is about the same for both large and small banks during the crisis period. Unlike studies from developed markets, the portfolio partition in the case of Malaysia did not provide significant difference on bank stocks risk exposures. Before the crisis, the excess returns generally followed white noise process and the residual variances have strong GARCH effects, indicating that the current volatility of bank's stocks persisted from past periods. The banks equity returns and its volatility fails to show a pricing relationship with its volatility level and financial risk factors, due to close regulatory framework set by government on the economy system. During the crisis period, commercial banks' hedging activities, and government interventions in both the financial factors, had stabilized the bank stocks' volatility. This can be explained because during crisis, bank stocks' returns followed a white noise process while the GARCH effects in the variances equation are very weak. Furthermore, when the market is in disorder, bank's stocks performance could be better explained by the overall market's performance and the annoyances in the market. After the financial control, due to the unexpected interest rate policy and the merger announcement, large bank's returns are increasingly sensitive to its own volatility. The stock's prices of small banks are only exposed to interest rate volatility but its magnitude is relatively larger than large banks'. The forced consolidation program has stongly affected the confidence of investors on the performance of small banks as the small bank's volatility is significantly driven by the interest rate volatility.It seems that the recent crisis had affected the exposure of bank's stocks to risk. Investors seem to be more actively engaged as reflected by the significant risks concern in bank's stocks pricing. The control and announced consolidation program fail to regain investors' full confidence in bank's stocks. Nevertheless, in view of long run welfare, the increasing risk concern in bank's stocks will contribute to the development of the domestic banks. When the market prices the stocks, the prices will reflect the true value and the performance of the banks. This will further enhance the market efficiency on banking stocks and contribute to future expansion, by ensuring an effective intermediation of fund to the efficient banks. Stocks Finance 2002-02 Thesis http://psasir.upm.edu.my/id/eprint/8307/ http://psasir.upm.edu.my/id/eprint/8307/1/FEP_2002_4_IR.pdf text en public masters Universiti Putra Malaysia Stocks Finance Faculty of Economics and Management Tan, Hui Boon English |
| institution |
Universiti Putra Malaysia |
| collection |
PSAS Institutional Repository |
| language |
English English |
| advisor |
Tan, Hui Boon |
| topic |
Stocks Finance |
| spellingShingle |
Stocks Finance Hooy, Chee Wooi Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling |
| description |
This study examines the sensitivity of commercial bank stock excess returns to the
volatility level and financial risk factors, measured by interest rate risk and exchange
rate risk across the recent Asian financial crisis horizon, via Multivariate GARCH in
Mean (MGARCH-M) model. Application of time varying risk model into bank's stocks
is of special importance as both the financial risk factors and the stock returns volatility
varied substantially in the Asian recent financial crisis.
Generally, MGARCH (p, q)-M process captures almost all of the linear dependence in
both the returns' mean, and the residual's variance of the fitted model. The results of
this study further show that in Malaysia, the pattern of risk sensitivity is about the same
for both large and small banks during the crisis period. Unlike studies from developed markets, the portfolio partition in the case of Malaysia did not provide significant
difference on bank stocks risk exposures.
Before the crisis, the excess returns generally followed white noise process and the
residual variances have strong GARCH effects, indicating that the current volatility of
bank's stocks persisted from past periods. The banks equity returns and its volatility
fails to show a pricing relationship with its volatility level and financial risk factors,
due to close regulatory framework set by government on the economy system.
During the crisis period, commercial banks' hedging activities, and government
interventions in both the financial factors, had stabilized the bank stocks' volatility.
This can be explained because during crisis, bank stocks' returns followed a white
noise process while the GARCH effects in the variances equation are very weak.
Furthermore, when the market is in disorder, bank's stocks performance could be better
explained by the overall market's performance and the annoyances in the market.
After the financial control, due to the unexpected interest rate policy and the merger
announcement, large bank's returns are increasingly sensitive to its own volatility. The
stock's prices of small banks are only exposed to interest rate volatility but its
magnitude is relatively larger than large banks'. The forced consolidation program has
stongly affected the confidence of investors on the performance of small banks as the
small bank's volatility is significantly driven by the interest rate volatility.It seems that the recent crisis had affected the exposure of bank's stocks to risk.
Investors seem to be more actively engaged as reflected by the significant risks concern
in bank's stocks pricing. The control and announced consolidation program fail to
regain investors' full confidence in bank's stocks. Nevertheless, in view of long run
welfare, the increasing risk concern in bank's stocks will contribute to the development
of the domestic banks. When the market prices the stocks, the prices will reflect the
true value and the performance of the banks. This will further enhance the market
efficiency on banking stocks and contribute to future expansion, by ensuring an
effective intermediation of fund to the efficient banks. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Hooy, Chee Wooi |
| author_facet |
Hooy, Chee Wooi |
| author_sort |
Hooy, Chee Wooi |
| title |
Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling |
| title_short |
Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling |
| title_full |
Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling |
| title_fullStr |
Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling |
| title_full_unstemmed |
Bank Stock Returns And Financial Volatility: A MGARCH-M Modeling |
| title_sort |
bank stock returns and financial volatility: a mgarch-m modeling |
| granting_institution |
Universiti Putra Malaysia |
| granting_department |
Faculty of Economics and Management |
| publishDate |
2002 |
| url |
http://psasir.upm.edu.my/id/eprint/8307/1/FEP_2002_4_IR.pdf |
| _version_ |
1794018737158881280 |