Zaäfri A. Husodo

Noise and Efficient Variance in the Indonesia Stock Exchange

In this study we applied the realized variance based estimator to extract the information from noise and efficient variance from the Indonesia Stock Exchange (IDX). The stocks in the sample are stratified by trading frequency every six months from 2000 to 2007. The standard deviation of noise variance has changed to a lower level after the first half of 2004 implying an improvement of market quality in the Indonesia Stock Exchange. Using Bandi and Russells (2006) method, it is found that the average optimal sampling frequency to estimate the efficient realized variance is 9-minute. The relation between the standard deviation of the noise variance and the square root of the efficient realized variance is positive and significant. From the information asymmetry hypothesis, the positive and significant relationship implies that the higher uncertainty about the fundamental value of asset increases the risk of transacting with traders with superior information. Furthermore, the variance ratio of the average daily efficient realized variance to the daily open-to-close variance reveals that the private information is a significant trading component in the Indonesia Stock Exchange.

Empirical Test of Fama French Three Factor Model and Illiquidity Premium in Indonesia

This study explores Fama French Three Factor Model and illiquidity premium in Indonesia. The objective of this research is to find evidence about the effect from market beta, size, value, and liquidity to the stock excess return in Indonesia. We use Amihud (2002) illiquidity as a proxy for illiquidity. This study uses Ordinary Least Squares (OLS) regression with monthly time series data over 10 years, from 2003 to 2013, and use dummy variable to make difference in crisis period and non-crisis period. We devided the portfolios into 12 portfolios, sorted by size-illiquidity and book-to-market (BM)-illiquidity. The results showed that market beta (excess market return) consistently positive and significant in each portfolio, when sorted by both criterion. Size factor (SMB) has explanatory power to explain illiquidity factor (ILLIQ) and vice versa. We also find that stocks with small size outperformed stocks with big size. HML coefficient increases when the book-to-market increased, whereas the SMB coefficient increases when liquidity decreases. This could be an indication that the small stock is more difficult to be traded (illiquid). The values of adjusted R2 are in the range of 0.58-0.88, it means that the value is quite big and the model can be used (applicable) on the stock market in Indonesia. Overall, we conclude that there are market risk premium, size premium, value premium and illiquidity risk premium which can explain the excess return in Indonesia. Subprime mortgage crisis statistically has no effect in all portfolios. The results supported Fama and French (1992, 1993) and the results of Lam and Tam (2011).

On the Robustness of the Extended Fama-French Three Factor Model

The aim of this paper is to examine the validity of the four-factor asset pricing as a comparison the standard Fama-French three factor model using U.S. monthly stock return data from period January 1963 to December 2010. Monthly stock return are constructed into 25 portfolio while the four-factor model includes the market factor (beta), the size factor (SMB), the book-to-market factor (HML), and the ‘momentum’ factor (MOM) which represents winners minus losers in terms of returns. Time series regressions following Fama and French (1993) are employed which includes the three-factor model as well as the four-factor model. Results indicated that the four-factor model to some extent have significant capability in explaining the variations in average excess stock return which consistent with Carhart (1997). R2 from the four-factor model is just slightly higher than the three factor model yet it provides indicative for the robustness of the model. Meanwhile, the January seasonals are also able to be absorbed by the risk factors including the market, SMB, HML, and MOM. Since the four-factor model seems capable in explaining the variation of the stock returns then application of this model in emerging markets may provide guidance for investor in understanding the market condition.

Intraday Speed of Price Adjustment in the Jakarta Stock Exchange

High frequency study at individual level in the Jakarta Stock Exchange is conducted in this research to reveal the dynamics at intraday level. Several apparent patterns emerge from analyzing the relation among the speed of adjustment coefficients, noise, and noise variance. It is found that the noise and noise variance are at a low level when the speed of adjustment coefficients achieves a fair level. The speed of adjustment coefficients, both at market and individual level show a periodic adjustment pattern at a daily interval. This justifies the importance of studying the dynamics of the price discovery as estimated in the speed of adjustment coefficient. Another important finding is that there is a positive relationship between the uncertainty of asset fundamental values and the corresponding bid-ask spreads. This reflects higher uncertainty about the fundamental value of the asset increases the risk of transacting with traders with superior information.

How Integrated are the ASEAN Capital Markets

We analyze the ASEAN stock markets from a market microstructure perspective, focusing on liquidity and volatility. We find Indonesia and Thailand share similar patterns and magnitude of liquidity and volatility, indicating partial integration happens naturally for these two markets. Further analysis on the sensitivity of stock exchange performance to international information reveals that, again, Indonesia and Thailand are the most sensitive to international financial market information. This finding indicates that Indonesia and Thailand may have substantial foreign investors’ presence in their stock markets. Further empirical evidence shows that while integration would provide greater liquidity in ASEAN stock markets, the liquidity risk is also transmitted among them. We find the transmission of systematic liquidity risk in the region could happen in only one day. Our analysis of dynamic integration reveals time-varying integration in the ASEAN region from 2000 to 2012. Without government intervention, ASEAN capital markets show the most stable integration during 2005-2007. Unfortunately, integration does not hold in the long-term or it is short term in nature.

Intraday Speed of Adjustment and the Realized Variance in the Indonesia Stock Exchange

We examine the intraday trading and price dynamics for frequently traded stocks at the Indonesian Stock Exchange. Using trade price, time series generated at one, two, three, five, ten, fifteen, thirty and sixty-minute intervals, we estimate the speed of adjustment and the corresponding realized variance of these series. The objective of the estimation is to infer the noise impact to the deviation of observed prices from their fundamental value. The result from the speed of adjustment estimate is consistent with the realized variance estimator. Both conclude that the 50 most frequently traded stocks in the Indonesia Stock Exchange adjust to new information within 30 minutes. At the interval, the coefficient of the speed of price adjustment is insignificantly different from zero implying negligible noise impact to the observed price. Concurrently, the realized variance starts to stabilize at 30-minute interval purporting fading impact of noise to the realized variance estimate. The evidence justifies the use of realized variance at various intervals as a reliable indicator of price discovery rate in the Indonesia Stock Exchange.

Liquidity Premium Persistency in the Indonesia Stock Exchange

We study the liquidity premium persistence in the Indonesia Stock Exchange employing Liu (2006) liquidity measure, LMx from 2006 to 2010. This research attempts to reveal the liquidity premium dynamics during the tranquil and volatile period in the Indonesia Stock Exchange. It is found that the liquidity premium exist only in the short period during 2008 crisis. The remaining period under investigation fails to provide significant evidence of liquidity premium in the Indonesia Stock Exchange.

Liquidity Premium Persistence in the Indonesia Stock Exchange (IDX)

We study the liquidity premium persistence in the Indonesia Stock Exchange employing Liu (2006) liquidity measure, LMx from 2006 to 2010. This research attempts to reveal the liquidity premium dynamics during the tranquil and volatile period in the Indonesia Stock Exchange. It is found that the liquidity premium exist only in the short period during 2008 crisis. The remaining period under investigation fails to provide significant evidence of liquidity premium in the Indonesia Stock Exchange.

Realized Volatility and Liquidity in the Indonesia Stock Exchange

This study is conducted to shed more lights on the relationship between volatility and liquidity in the Indonesia Stock Exchange (IDX). We extend the research by investigating risk premium and excess return relationship employing intraday volatility, measured by realized volatility, and liquidity, measured by high-low spread estimator. We found inconsistent relationship between liquidity and volatility in the IDX. Further, we also found that the liquidity is important in the asset pricing in Indonesia stock market.

An Analysis of Temporal Relation between Monetary Conditions and Illiquidity Premium in Indonesia

The objective of this research is to find evidence of a systematic relation between monetary conditions and temporal variation in the price of liquidity in Indonesia. Specifically, following an expansive monetary policy shift, funding conditions improve and market-wide liquidity increases, which is especially beneficial for illiquid securities. The improved liquidity and funding conditions reduce the returns required for holding illiquid securities. Consequently, illiquid stocks experience relatively large price increases when monetary conditions become expansive; hence, the measured return spread between illiquid and liquid stocks expands substantially. Overall, the evidence supports the claim that the price of asset liquidity is dependent on monetary conditions.