Financial liberalization and stock market volatility: the case of Indonesia

Abstract

This article examines the relationship between financial liberalization and stock market volatility in Indonesia. By looking at the time series properties of the Jakarta Composite Index (JCI) we identify breaks in stock market volatility which coincide with the timing of major policy events. Our main findings are (i) a significant decrease in volatility after the ‘official’ opening of the stock market to foreign participation; (ii) a significant increase in volatility in the year before market opening following reforms that eased entry requirements and the issuance of brokerage licenses and (iii) a significant increase in volatility at the time of the Asian crisis followed by a significant decrease in the second and sixth years after the crisis.

Acknowledgements

The authors gratefully acknowledge financial support from the ESRC (awards PTA-026-27-1437 and PTA-026-27-0874) and would also like to thank Jun Du and two anonymous referees for their useful comments. The usual disclaimer applies.

Notes

¹ For instance excess volatility makes investors more averse to holding stocks due to uncertainty, which leads to a higher risk premium and upwards pressures on interest rates, hampering both the volume and the productivity of investment and, therefore, reducing growth (De Long et al., 1989; Federer, 1993). Excessive volatility may also increase the value of the ‘option to wait’ thereby delaying investment (Bekaert and Harvey, 1997).

² Hadiz and Robinson (2005) note that ‘there are few developing economies where the influence of market-oriented technocrats and international agencies such as the World Bank has been so embedded in the policy process as in Indonesia and where relationships between the government and western economists have been so close.’

³ A World Bank study grimly observed that ‘Indonesia is in deep crisis. A country that achieved decades of rapid growth, stability, and poverty reduction is now near economic collapse … no country in recent history, let alone the size of Indonesia, has ever suffered such a dramatic reversal of fortune’ (World Bank, 1998).

⁴ Kim and Singal (2000) examined changes in the level and volatility of stock returns, inflation and exchange rates around market openings for 18 emerging economies including Indonesia. However, they excluded Indonesia from their analysis of stock return volatility around market openings due to insufficient data. Chang et al. (1995) analysed the intraday price volatility of Indonesian stocks (i.e. they examine the first-order serial dependence between overnight returns and following daytime returns and between overnight returns and preceding daytime returns).

⁵ The stock market in Indonesia is made of three stock exchanges: the Jakarta Stock Exchange (JSX), originally opened in 1912 under the Dutch colonial government and re-opened in 1977, as well as two smaller ones, the Surabaya Stock Exchange (SSX) established in 1989, and an over-the-counter market known as Bursa Paralel (created in 1988 and merged with the SSX in 1994). The SSX (and Bursa Paralel) is facilitating three markets: stock trading for small and medium scale companies, bond trading/reporting for corporate and government bonds and derivatives trading for stock index futures.

⁶ It is worth mentioning that the standard t-test for the equality of means of distinct samples is also reported in order to give the reader an idea of the corresponding changes of the mean returns. However, the reader should bear in mind that the t-test not only exhibits moderate size distortions when the tested samples are nonnormal but it also requires that the samples have equal (unknown) variances. Consequently, since all the other tests show that all segments have different variances, the t-test is rather unreliable whenever it suggests that the means are different.

⁷ The most elaborate GARCH model refers to the model that has the highest number of statistically significant lagged parameters.

⁸ The corresponding conditionally heteroscedastic structure is given by

where , u_t is i.i.d. N(0, 1), and

⁹ Note that this is the only segment in which we have identified some very small deviations from risk neutrality.

¹⁰ The corresponding conditionally heteroscedastic structure is given by

where , u_t is i.i.d. N(0, 1) and

¹¹ The decree came after Minister of Finance Sumarlin's press conference on 5 August 1989. During the conference Mr Sumarlin reportedly said that 49% of all stocks could be sold to foreign investors. A mini-boom occurred in the capital market on the basis of rumors that the stock of the Penanaman Modal Asing (PMA) (a join venture firm) would be eligible for purchase by foreigners (Cole and Slade, 1996).

¹² Ariff and Khalid (2005) pointed out that foreign direct investments increased from an average of about US$250 million to US$600 million in the early years after market opening. The total inflow of foreign direct investments in the 1991–1997 period amounts to a US$23 billion injection of capital representing an average of 15% of GDP. Next to China, this is the largest flow of foreign investments. Portfolio investment also increased considerably.