William T. Lin

Computing a Multivariate Normal Integral for Valuing Compound Real Options

We extend the Geske (1979) model to a multivariate normal integral for the valuation of a compound real option. We compared the computing speeds and errors of three numerical integration methods, namely, Drezners improved Gauss quadrature method, Monte Carlo method and Lattice method, together with appropriate critical value finding methods. It is found that secant method for finding critical values combined with Lattice method and run by Fortran took merely one second, Monte Carlo method 120 seconds. It is also found that the real option decreases with interest rate, not necessarily positively correlated with volatility σ, a result different from that anticipated under financial option theory. This is mainly because the underlying of real option is a non-traded asset, which brings dividend-like yield into the formula of compound real options. Dividend-like yield rises with the multiplication of correlation coefficient ρ and σ. High ρ indicates the poor diversification advantage of the new investment project in relation to the existing market portfolio, and the value of real call option decreases with σ. Conversely, when ρ is low, the proposed project provides better diversification advantage and the real call option rises with σ. Irrespective of the value of ρ, when interest rate increases, the value of real call option drops, especially when ρ is high, the value of the project is dominated by interest rate.

Sequential Capital Budgeting as Real Options: The Case of a New DRAM Chipmaker in Taiwan

We evaluate the initial public offering price of a new DRAM chipmaker in Taiwan in accordance with the compound real call options model of Lin (2002). The worldwide average sales price is the underlying variable, and the average production cost of the new DRAM foundry is the exercise price. The twin security is defined as a portfolio of DRAM manufacturing firms publicly listed in Taiwan stock markets. We estimate the dividend-like yield with two methods, and find that the yield is negative. The negative dividend-like yield results from the negative correlation between the newly constructed DRAM foundry and its twin security, implying the diversification advantage of a new generation of DRAM foundry with a relative low cost of investment opportunity. We solve the critical value for the multivariate normal integral with the secant method, approximating the integral with the lattice method. It has been found that there is only a 4.6% difference between the market IPO price and the estimated one.

An Analysis of Long Memory in Volatility for Asian Stock Markets

One of the important questions in studies of asset return and volatility has been how long the effects of shocks persist. In this article, the modified R/S statistic of Lo (1991) and the robust semiparametric method of Lobato and Robinson (1997) are applied to investigate the long memory properties in return and volatility of Asian financial markets. For the return series, we find little evidence of long memory, while the empirical results support the hypothesis of long memory in volatility for Asia-Pacific stock markets. We also discuss the possible causes of spurious long memory effect in volatility, namely aggregation, size distortion, and shifts in variance. Our empirical evidence shows that spurious long memory effect in volatility might occur as a result of shifts in variance for some Asian stock markets.

Does Trading Remove or Cause Friction

This study shows that trading causes friction in the market. However, when the market opens, trading of individuals removes market friction, while that of institutional trading does not. The situation during the rest of the day is just the opposite. The uneven behavior of trading noise across investors and time of day makes it a specific, rather than general, transaction cost, contrary to Stolls (2000) finding. Intraday trading activity suppresses both order width and depth, as proxies for trading intensity, and therefore creates noise or friction in the market. Our findings support the proposed financial transaction tax in the European Union.

Important Factors of Estimated Return and Risk: The Taiwan Evidence

This paper seeks to identify which factors are important for estimating portfolios expected return and standard deviation in the Taiwan stock market. We have summarized from the existing empirical literature a total of 26 factors that may have explanatory power. The results of our evaluation show that except for the trading volume, the remaining 25 factors do not seem to help explain the average stock returns during the July 1985–June 1999 period. However, the power of the trading volume to account for the expected returns on the stock is affected by any changes in the sample or by the use of a different evaluation model. We suggest three potential explanations of why all 26 factors show no stable power to explain average returns on Taiwan stocks: high volatility, selection bias, and market differences. Moreover, we find that all of the 26 factors are important in capturing the systematic covariation in stock returns.

Individual Investor Trading Around Earnings Announcements: Noise or Information? Evidence from an Emerging Market

This paper studies whether individual investors have information advantage before earnings announcements on an emerging market using a unique data set of TWSE. Consistent with existing research on American market, it is surprising that pre-event individual investor trading is also positively correlated with stock returns on and after earnings announcements dates in Taiwan. However, the sign of correlation between individual investor trading and stock return around earnings announcements shows weak evidence of noise trading rather than information advantage, which is opposite to that of American stock market.

Does Trading Remove or Bring Frictions

We explore in this paper how trading noise, when considered as a market friction, reacts to trading activity. Transactions cost is a good explanation for intraday trading behavior in the market according to our data. Particularly, we show that in general trading brings friction to market. However, trading friction at market open is the lowest during the day, as trading causes less friction then relatively. This is due to the behavioral difference among investors. When market opens, individual trading removes, while institutional trading brings, market friction. Situation in the rest of the day is just the opposite, where individual, instead of institutional, trading brings friction. The uneven behavior of trading noise across investors and time of day makes it a specific, rather than general, transactions cost, as opposed to Stoll (2000). Intraday trading activity suppresses both order width and depth, as proxies for trading intensity, therefore creates more noise or friction in the market. Width and depth contribute to trading noise in a polarized way, so that individual trading hurts friction in small cap stocks at open, but benefits it at close. Institutional trading brings extremely strong friction to large cap stocks, but less so at market close. So trading noise as a specific, rather than general, transactions cost is prominent only to certain investors, at certain time and for certain stocks in the market. Our findings lend itself to the justification of the new financial transactions tax proposed by the European Union.

Searching Out of Trading Noise: A Study of Intraday Transactions Cost

We attempt to identify in this paper the role of trading noise as a transactions cost to market participant in the sense of Stoll (2000), especially in the presence of trading concentration. Applying the measures of Hu (2006) and Kang and Yeo (2008), we analyze the noise proportion in intraday stock returns and its interaction with investor herding and search cost. Although this noise is high on individual orders and low on institutional orders, its behavior at market open is entirely different from the rest of the day. Noises for small cap stocks, unlike volatilities, are lower than those for large cap stocks. We also found that noise relates positively to trading volume, but inversely to holdings and turnover ratio of institutional investors. Responses from institutional and individuals are quite the opposite. The noise proportion generated by individual order rises with institutional turnover and search cost encountered, while that of institutional order behaves just oppositely. At market open, behaviors of noise from institutional and individual orders just switch mutually, and then switch back afterwards. Also, noise from high-cap stocks is actually more responsive than that from low-cap ones across investors. So trading noise is a specific transactions cost, prominent to only certain investors, at certain time and for certain stocks in the market, rather than a general market friction as argued in Stoll (2000). This transactions cost is inversely related to search costs encountered in trading, which depends on investor, trading hour of day and market capitalization of stocks.

Raw Material Convenience Yields and Business Cycle

This paper extends the methodology of Milonas and Thomadakis (1997) to estimate raw material convenience yields with futures prices during the period 1996 to 2005. We define the business cycle of a seasonal commodity with demand/supply shocks and find that the convenience yields for crude oil and agricultural commodity exhibits seasonal behavior. The convenience yield for crude oil is the highest in the winter, while that for agricultural commodities are the highest in the initial stage of the harvest period. The empirical result show that WTI crude oil is more sensitive to high winter demand and that Brent crude oil is more sensitive to shortages in winter supply. The theory of storage points out that the marginal convenience yield on inventory falls at a decreasing rate as inventory increases which could be verified through those products affected by seasonality, but could not be observed by products affected by demand/supply. Convenience yields are negatively related to interest rates The negative relationship implies that the increase in the carry cost of commodity – namely the interest rate – would cause the yield of holding spot to decline. We also show that convenience yields may explain the price spread between WTI and Brent crude oil as well as the ratio between soybean and corn. Our estimated convenience yields are consistent with Fama and French (1988) in that commodity prices are more volatile than futures prices at low inventory level, verifying the Samuelson (1965) hypothesis that future prices have fewer variables than spot prices at lower inventory levels.