Stock Prices as a leading Indicatator of the East Asian Financial Crisis.

Stock Prices as a Leading Indicator of the East Asian Financial Crisis Simon Broome Economics Department National University of Ireland, Maynooth and Bruce Morley* Economics Group University of Wales, Aberystwyth September 2003 Abstract: Using a basic currency crisis model, we assess the effectiveness of stock prices as a leading indicator of the East Asian currency crisis in 1997 and 1998. Stock prices are incorporated into a basic monetary model, through the wealth effect postulated by Friedman (1988). In addition to the domestic stock price, we also incorporate the stock prices of Hong Kong, China and Japan to determine their ability to predict the crisis. Using monthly data, the results indicate that the domestic stock price is a significant leading indicator, however the main stock prices indicator of the crisis is the Hong Kong stock price. In addition the US price level is also a highly significant predictor of the crisis. Causality tests suggest evidence of bi-causality between the stock markets and foreign exchange markets. JEL. F30, E44 Key Words: Currency Crisis, Stock Prices, Monetary Model. * Address for correspondence: Dr B.Morley, Economics Group, SMB, UW Aberystwyth, Aberystwyth, SY23 3DD, UK. Tel. +(01970) 622522, E-mail: [email protected], Fax + (01970) 622740. I Introduction The aim of this paper is to primarily determine whether the domestic stock market can be used as a leading indicator during a regional currency crisis, as in East Asia during 1997 and 1998. Further we investigate whether the major stock markets within East Asia had any effect on the currencies suffering the crisis and can also be used as an early warning system. A particular feature of the East Asian crisis was the almost simultaneous decline in asset prices and currencies, as international investors moved their capital out of the respective domestic markets. This resulted in a subsequent depreciation of the exchange rate as the domestic currency was sold. However the degree of severity of the crisis varied across East Asia, as did the extent of the decline in the domestic stock markets. To date most models for predicting currency crises have concentrated on leading indicators from either the banking sector or the current account (e.g., Kaminsky et al., 1998, Kwack, 2001). When stock prices have been included, it has been limited to only domestic stock prices. In this paper we suggest a simple monetary based model, in which stock prices can be incorporated as a leading indicator of currency crises. We also investigate whether foreign stock prices are a significant leading indicator, based on three theories concerning the origins of the South East Asian currency crisis. When investigating the relationship between stock prices and exchange rates, the main concern is usually over the direction of causality between these variables. There are theoretical reasons for causality to run in both directions, as suggested by Bahmani-Oskooee and Sohrabian (1992) and Granger et al (2000). The empirical 2 evidence is equally ambiguous, although Granger et al (2000) finds evidence of causality running from stock markets to exchange rates during a currency crisis, but their study uses daily data rather than monthly data. In this study we too assume causality is from stock prices to exchange rates. Following the introduction, we assess the interrelationship between stock prices and exchange rates during a currency crisis. We then derive a simple model of currency crises, in which stock markets are incorporated through the demand for money function. The next section describes the data and assesses the results from the empirical models. Finally we give our conclusions and suggest some implications for future policies. II Currency Crises and Stock Prices The main attempt to incorporate the domestic stock market into empirically based currency crisis models has been Kaminsky and Reinhart (1996) and Kaminsky et al (1998). These models incorporate a number of real, financial and political variables in purely empirical models, to identify which are significant and also the length of the signalling horizon. They use the “signals” approach, which in general involves a one step ahead probability of a devaluation, in the context of a multivariate probit or logit type model. The domestic stock markets are generally found to be a significant leading indicator of currency crises, over a number of different currency crises in the recent past. In the study by Kaminsky et al. (1998), stock prices are found to be the fourth best predictor of currency crises. 3 There has been a certain amount of debate in the literature as to the direction of causality between stock prices and exchange rates. Granger et al. (2000) show that causality runs from domestic stock prices to exchange rates. They offer some theoretical support for a bi-directional relationship between the stock market and foreign exchange market, but only over the short run. They argue that a change in exchange rates would change the market value of all firms that trade internationally. This would depend on whether the firms are net importers or exporters, such that if in aggregate most firms were net exporters, a devaluation would have a beneficial affect on those firms profitability and therefore stock market value. This causal relationship is termed the traditional approach, although it does not specify the sign of the effect. In contrast to this approach, both Bahmani-Oskooee and Sohrabian (1992) and Granger et al. (2000) stress the importance of the portfolio approach to analysing the relationship between stock prices and exchange rates. This suggests that a rise in stock prices, increases the domestic wealth of investors, facilitating a rise in the demand for money. Following the consequent rise in interest rates, capital is attracted into the domestic economy appreciating the domestic currency. This approach assumes there is a negative relationship between stock prices and exchange rates, with causality running from the stock market to the foreign exchange market. Wu (2001) provides evidence of the negative relationship between equities and exchange rates in South East Asia. This explanation is the most relevant to this relationship during a currency crisis. We have conducted a set of Granger causality tests between domestic stock prices and exchange rates, as with other studies, there is evidence of bicausality between the stock market and foreign exchange markets. When causality 4 runs from stock prices to the exchange rate, there is a negative relationship, which suggests the portfolio approach is most important in South East Asia. Apart from the US stock market, we have investigated whether the crisis could have originated from any of the main neighbouring stock markets, in Japan, Hong Kong and China. Although the crisis began in Thailand in 1997, others have suggested the crisis began earlier than this, with both China/ Hong Kong and Japan being suggested as contenders. Fernald et al (1999) have suggested that the rise in China’s economic strength during the 1990’s added to the crisis. They focused on the 1994 devaluation and subsequent strong export performance as the cause of the troubles, as China captured export markets, which had previously been dominated by the Association of Southeast Asian Nations (ASEAN) countries. This facilitated current account problems, reduced company profitability and culminated in the general financial demise of the area. It has also been argued that a further source of the crisis could have been Hong Kong, which in 1997 was officially returned to China from the UK. Initially this had a positive effect on Hong Kong’s share prices, but as the date for the handover approached, so concern about investment in Hong Kong increased. Some argue that another source of the crisis was Japan. Following rapid rises in the stock market during the 1980’s, the early and mid 1990’s saw a reversal of this trend, with some sharp falls. At the same time the Japanese economy experienced an era of stagnant growth and lack of demand. This facilitated a decline in demand for ASEAN imports and a fall in investment flows to these countries. The financial crisis in Japan culminated in the failure of Yamaichi corporation in 1997, the fourth largest financial institution. This in turn caused another large fall in the Japanese stock market. 5 If either Japan or China/ Hong Kong were the instigators of this crisis, then a measure of their financial troubles could be a useful leading indicator for the currency crises in East Asia. To determine if this is the case, we have incorporated the stock market indices of China, Hong Kong and Japan into the basic monetary based model, along with the domestic stock market index. III Model The following model is based on the Krugman (1979) model of currency crisis, with stock market effects incorporated through the money demand specification. As with Edin and Vredin (1993), this is only used as a basis for the empirical investigation and as with the leading indicator literature in general, other leading indicators are also incorporated into the empirical tests, without specific theoretic modeling. The stock market is included in the money demand function2 for three reasons, as suggested by Friedman (1988). It primarily acts as a wealth effect, as a rise in stock prices increases nominal wealth. Additionally a rise in stock prices reflects a rise in expected returns from risky assets. To offset this rise in risk, agents switch away from long-term bonds to safer monetary assets. Thirdly a rise in stock prices implies a rise in financial transactions and thus transactional demand for money. These imply a positive relationship between money and stock prices. There could also be a negative relationship through a substitution effect. As stock prices rise, agents substitute the 2 The stock market could have been related to other macroeconomic variables, such as consumption, output and investment. However given the monetary basis of most currency crisis models, we have incorporated it into the money demand function. 6 more attractive equities for money. However as with Friedman (1988) we assume the positive effect dominates. As with the conventional monetary model, we assume purchasing power parity (PPP) and uncovered interest parity (UIP) 3hold; (1) epp tt  * t Where, e is the exchange rate, p are domestic prices and p* are foreign prices. Ede dt ii tt () *  (2) Where i are domestic interest rates and i*are foreign rates. Money demand takes the following form: mp y i s tt t t t       (3) Where m is domestic money balances, y is domestic income and s is a domestic stock market index. We have assumed that the domestic money supply is purely accommodating. By rearranging the above equations, we get: 3 As with currency crisis models in general based on the monetary model, we have assumed PPP and UIP, although empirical studies question whether the former holds due to trade impediments and transport costs and the latter due to the presence of a risk premium. 7 dt de sypime ttttt    ** (4) To test for the effects of stock prices on the exchange rate, we have chosen a standard empirical model, based on equation4 (4). This suggests the crisis is a function of: ),,,*,*,,,( xsresrerdspiymfcc      (5) Where cc is the rate of change in the exchange rate for the month when the exchange rate is in a crisis condition,Δ m is the domestic money supply (M1), y is output, i* is the US interest rate, p* is the US price level, ds is the domestic stock market index, rer is the change in the real exchange rate, res are foreign currency reserves and xs are the relevant foreign stock market indexes (All variables are in logs and in change form). As with Edin and Vredin (1993) we have also included the real exchange rate, rather than the nominal exchange rate and added foreign exchange reserves. The relevant foreign stock market indexes are the US, Japan, Hong Kong and China. The US stock market is included because the East Asian currencies are pegged to the dollar, the Japanese markets have traditionally had a strong effect on the region as a whole. China has recently undergone important political changes which have affected 4 An alternative approach would have been to include a variety of other relevant variables relating to the banking sector, current account and political factors, as in Kaminsky et al. (1998). However in order to provide a theoretical basis for the empirical tests, the emphasis is on variables relating to the Friedman based monetary model. In addition it would not be possiblt to incorporate all the potential leading indicators into the model, so we have concentrated on the stock market area. 8 their financial markets and Hong Kong has been transferred from UK to Chinese control. In addition to the main leading indicator tests, we have also included some Granger Causality tests, between the exchange rates and domestic stock prices. In addition we have included some causality tests between the exchange rates and foreign stock price variables. The basic tests is: tititit tititit vess usee        12110 12110     (6) Where e is the exchange rate, s is the stock price variable and u and v are error terms. As with Blomstrom et al. (1996) we have included country dummy variables and use the t-statistic on the lagged explanatory variable to determine if there is evidence of causality. IV Data and Results The countries included in the investigation are those that experienced the worst problems during the crisis. This includes Thailand, Malaysia, South Korea, Indonesia and the Philippines. The data is all monthly, running from January 1996 to December 1999, so including months where a crisis was evident as well as months in which the exchange rate was relatively stable. The exchange rate is expressed as the domestic currency in terms of the US dollar, the foreign explanatory variables are the respective US variables. This reflects the fact that the relevant currencies were 9 Kaminsky, G. and. Reinhart, C.M., 1996. The twin crises: The causes of banking and balance of payments problems. International Finance Discussion Paper 544, Washington: Board of the Governors of the Federal Reserve System (March). Kaminsky, G., Lizondo, S. and Reinhart, C.M., 1998. Leading indicators of currency crises. IMF Staff Papers, 1-47. Krugman, P., 1979. A model of balance f payments crisis. Journal of Money, Credit and Banking, 11, 311-325. Kwack, S. Y., 2000. An empirical analysis of the factors determining the financial crisis in Asia. Journal of Asian Economics, 11, 195-206. Loungani, P., 2000. Comrades or competitors?: Trade links between China and other East Asian countries. Finance and Development, 37, 1-5. Radelet, S. and Sachs, J.D., 1998 The East Asian financial crisis: Diagnosis, remedies, prospects. Brookings Papers on Economic Activity, 1-89. Wu, Y. 2001., Exchange rates, stock prices, and money markets: evidence from Singapore. Journal of Asian Economics, 12, 445-458. Table 1. Causality tests between Stock prices and Exchange rates. Δe Δds 16 Δe(-1) Δds(-1) ΔHKS(-1) -0.087 (1.674)** -0.074 (1.159) 0.182 (1.916)** ΔUSS(-1) ΔCHS(-1) ΔJPS(-1) 0.070 (0.499) -0.076 (1.683)** -0.209 (1.927)** Notes: T-statistics are in parentheses. E and ds are the domestic exchange rate and stock price respectively. HKS, USS, CHS and JPS and Hong Kong, US, China and Japan’s stock prices respectively. ** indicates significance at the 10% level of significance. Only lagged explanatory variable included. Table 2. Probit Models using panel data from Thailand, Malaysia, South Korea, Philippines and Indonesia 17 Variable 1 2 3 4 ΔM (-1) ΔDS (-1) ΔUSP (-1) -1.157 (1.709) -0.620* (2.363) -107.181* (11.195) -1.136 (1.681) -0.585* (2.186) -1.3.874* (9.488) -1.095 (1.596) -0.572* (2.170) -102.311* (9.916) -1.131 (1.442) -0.320 (0.847) -110.289* (10.234) ΔUSS (-1) USi (-1) ΔY (-1) 0.064 (0.308) -0.608 (1.312) -0.393 (0.615) 0.073 (0.351) -0.629 (1.363) 0.007 (0.032) -0.708 (1.514) 0.057 (0.240) -0.636 (1.253) ΔRER (-1) ΔRES (-1) ΔTHS(-1) 0.283 (0.807) 0.281 (0.807) 0.206 (0.577) -0.796 (1.453) 0.090 (0.232) -0.471 (1.651) L-L Probability -122.031 70% -121.841 71% -120.956 73% -97.229 68% Notes: t-statistics are in parentheses. Probability is the probability of a predicted outcome occurring from the 115 possible outcomes, acting as a pseudo-R2. M is the money supply, DS is the domestic stock price, USP, Usi and USS are US prices, interest rates and stock prices respectively. Y is output and THS are Thailand’s stock prices, RER is the real exchange rate and RES are reserves. L-L is the restricted log likelihood A * indicates significance at the 5% level. Table 3. Probit Models using panel data from Thailand, Malaysia, South Korea, Philippines and Indonesia, including foreign stock prices. 18 19 Variable 1 2 3 4 ΔM (-1) ΔDS (-1) ΔUSP (-1) -1.061 (1.596) -0.445 (1.668) -107.643* (12.306) -1.129 (1.665) -0.500 (1.860) -109.676* (11.680) -1.116 (1.655) -0.594 (2.265) -106.075* (11.008) -1.071 (1.609) -0.476 (1.747) -116.063* (10.558) ΔUSS (-1) USi (-1) ΔY (-1) 0.041 (0.188) -0.573 (1.266) 0.082 (0.391) -0.535 (1.150) 0.110 (0.519) -0.683 (1.450) 1.069* (1.224) 0.064 (0.278) -0.578 (1.234) ΔRER (-1) ΔJPS (-1) ΔCHS (-1) 0.040 (0.114) 0.175 (0.500) -0.493* (2.292) 0.253 (0.718) -0.602* (1.093) -0.035 (0.097) -0.512 (0.820) -0.047 (0.164) ΔHKS (-1) L-L Prob -0.974* (3.072) -117.412 72% -119.494 72% -121.431 71% -1.141* (2.234) -116.428 73% Notes: See Table 1 and 2.