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This paper investigates the pricing of Nikkei 225 Options using the Markov Switching GARCH (MSGARCH) model, and examines its practical usefulness in option markets. We assume that investors are risk-neutral and then compute option prices by using Monte Carlo simulation. The results reveal that, for call options, the MSGARCH model with Student's t-distribution gives more accurate pricing results than GARCH models and the Black-Scholes model. However, this model does not have good performance for put options. [ABSTRACT FROM AUTHOR]

We investigate alternative unconditional and conditional distributional models for the returns on Japan's Nikkei 225 stock market index. Among them is the recently introduced class of ARMA-GARCH models driven by α-stable (or stable Paretian) distributed innovations, designed to capture the observed serial dependence, conditional heteroskedasticity and fat-tailedness present in the return data. Of the eight entertained distributions, the partially asymmetric Weibull, Student's t and asymmetric α-stable present themselses as the most viable candidates in terms of overall fit. However, the tails of the sample distribution are approximated best by the asymmetric α-stable distribution. Good tail approximations are particularly important for risk assessments. [ABSTRACT FROM AUTHOR]

Bouman and Jacobsen ( American Economic Review 92(5), 1618–1635, 2002) examine monthly stock returns for major world stock markets and conclude that returns are significantly lower during the May–October periods versus the November–April periods in 36 of 37 markets examined. They argue that, in general, the Halloween strategy outperforms the buy and hold strategy thereby casting doubt on the validity of the efficient market paradigm. More recently, Maberly and Pierce ( Econ Journal Watch 1(1), 29–46, 2004) re-examine the evidence for U.S. equity prices and conclude that Bouman and Jacobsen’s results are not robust to alternative model specifications. Extending prior research, this paper examines the robustness of the Halloween strategy to alternative model specifications for Japanese equity prices. The Halloween effect is concentrated in the period prior to the introduction of Nikkei 225 index futures in September 1986. After the internationalization of Japanese financial markets in the mid-1980s, the Halloween effect disappears. [ABSTRACT FROM AUTHOR]

I present evidence that transactions of the stock futures of a flawed market index cause mispricing in individual stocks. In particular, I analyze whether stocks overweighted on the index are mispriced, especially when market movements driven by futures trading are observed. To detect such movements, I use a qualitative indicator based on daily stock market news and a quantitative indicator based on the intraday lead-lag relationship between the spot and futures markets. I first find that overweighted stocks experience higher (lower) returns when an upward (downward) market movement driven by futures trading occurs. Second, they experience lower (higher) returns after such periods, i.e., their performance is reversed. These findings suggest that overweighted stocks experience significant trading pressure from the transactions of the index futures, resulting in mispricing of individual stocks. By contrast, such price behavior is not observed for non-constituent stocks. These results strongly support the view that the transactions of stock futures of a flawed index cause mispricing in individual stocks. [ABSTRACT FROM AUTHOR]

In this study, we investigate ordering patterns of different types of market participants in Tokyo Stock Exchange (TSE) by examining order records of the listed stocks. Firstly, we categorize the virtual servers in the trading system of TSE, each of which is linked to a single trading participant, by the ratio of cancellation and execution in the order placement as well as the number of executions at the opening of the afternoon session. Then, we analyze ordering patterns of the servers in the categories in short intervals for the top 10 highest trading volume stocks. By classifying the intervals into four cases by returns, we observe how different types of market participants submit or execute orders in the market situations. Moreover, we investigate the shares of the executed volumes for the different types of servers in the swings and roundabouts of the Nikkei 225 index, which were observed in September in 2015. The main findings of this study are as follows: Server type A, which supposedly includes non-market making proprietary traders with high-speed algorithmic strategies, executes and places orders along with the direction of the market. The shares of the execution and order volumes along with the market direction increase when the stock price moves sharply. Server type B, which presumably includes servers employing a market making strategy with high cancellation and low execution ratio, shifts its market making price ranges in the rapid price movements. We observe that passive servers in Server type B have a large share and buy at low levels in the price falls. Also, Server type B, as well as Server type A, makes profit in the price falling days and particularly, the aggressive servers in the server type make most of the profit. Server type C, which is assumed to include servers receiving orders from small investors, constantly has a large share of execution and order volume. [ABSTRACT FROM AUTHOR]

In this paper, we examine the nature of transmission of stock returns and volatility between the U.S. and Japanese stock markets using futures prices on the S&P 500 and Nikkei 225 stock indexes. We use stock index futures prices to mitigate the stale quote problem found in the spot index prices and to obtain more robust results. By employing a two-step GARCH approach, we find that there are unidirectional contemporaneous return and volatility spillovers from the U.S. to Japan. Furthermore, the U.S.'s influence on Japan in returns is approximately four times as large as the other way around. Finally, our results show no significant lagged spillover effects in both returns and volatility from the Osaka market to the Chicago market, while a significant lagged volatility spillover is observed from the U.S. to Japan. [ABSTRACT FROM AUTHOR]

Options on stocks are priced using information on index options and viewing stocks in a factor model as indirectly holding index risk. The method is particularly suited to developing quotations on stock options when these markets are relatively illiquid and one has a liquid index options market to judge the index risk. The pricing strategy is illustrated on IBM and Sony options viewed as holding SPX and Nikkei risk respectively. [ABSTRACT FROM AUTHOR]

We evaluate stock market indexes by the Aumann–Serrano (AS) performance index for multi-period gambles and one-period gambles and the Sharpe ratio. Our results show the AS performance index is more distinct for multi-period gambles than for one-period gambles in evaluation of the Japanese stock market indexes. In other words, a favorable evaluation score as compared to the Sharpe ratio becomes even better in multi-period gambles than in one-period gambles while an unfavorable evaluation score compared to the Sharpe ratio becomes even worse in multi-period gambles than in one-period gambles. [ABSTRACT FROM AUTHOR]

In this paper we explore some recent trends in the financial market and also report some studies of the Singapore futures markets. A characterization of trends shows that national securities markets are much closer than before. This means the linkages between securities and their derivatives and amongst themselves have be come much stronger. Secondly, the advent of sophisticated risk products and instruments and the knowledge to use them effectively would become a common theme together with the idea of value enhancements. Thirdly, computerizations and the internet will play an increasingly important role. So will empirical financial research become increasingly microscopic. The discussion will be supported by the experiences of the Singapore futures markets and various empirical research evidences. The paper also provides a detailed study of causality-in-variance test of information transmission between SIMEX and Osaka Stock Exchange on the Nikkei 225 stock index futures trading prior to, during, and immediately after the announcement of the collapse of Barings. The results are indicative of very strong international market linkages and a portent of things to come. [ABSTRACT FROM AUTHOR]

Using data on IPOs that are issued in Japan during January 1975-March 1989, we examine the deliberate underpricing and overreaction hypotheses to explain high initial returns at offering dates. Specifically, we analyze the cross-sectional pattern of the short- and long-run performance of IPOs. The obtained results indicate that the deliberate underpricing theories which we examine are unable to explain the high initial returns on the Japanese IPOs. Furthermore, for the average of the IPOs, the empirical results are not consistent with the overreaction hypothesis. However, there is evidence consistent with the hypothesis that for a certain minority group of IPOs, the high initial returns occur due to overreactions by investors. We interpret the overall results as indicating that the high initial returns on the Japanese IPOs can be attributed to a mixture of both underpricing and investor overreaction. We conjecture that the binding regulations in Japan led to underpricing. [ABSTRACT FROM AUTHOR]

How does the market react when more or fewer investors are allowed to trade certain stocks? Stock Connect, a cross-border investment channel between mainland China and Hong Kong, provides a natural testing ground. Investors are allowed to trade a list of qualified stocks from the stock market on the other side, and when a stock is removed from the list, investors can only sell but cannot buy that stock. We find that the inclusion of stocks is correlated with abnormal returns, implying downward-sloping demand curves for stocks. The effect weakens over time and disappears in about 40 trading days. There are no abnormal returns when stocks are removed from the list. On the other hand, when investors can only sell some stocks, they have a significantly higher propensity to sell. Their trading style becomes more contrarian for such stocks, and they tend to trade in small amounts. After 6 months, their investment behavior returns to that before the removal. [ABSTRACT FROM AUTHOR]

In this paper, we shall propose a useful approach to evaluate concretely the MEMM (minimal entropy martingale measure) for the typical geometric Lévy processes such as compound Poisson, stable, VG (Variance Gamma), CGMY (Carr-Geman-Madan-Yor), NIG (Normal Inverse Gaussian), etc. In addition, we shall estimate the parameters of geometric Lévy processes and value the European call option and Asian call option using the Nikkei financial data. [ABSTRACT FROM AUTHOR]

The GARCH model is modified to capture the effect on volatilities of the consecutive number of positive or negative shocks. The new model is tested against the Shanghai Shcomp and Nikkei225 indices and found particularly useful in analyzing the Shcomp index. Similarly, the EGARCH model is extended along the same line as the GARCH model and is applied to the same sets of data. Stationarity of the new GARCH (1, 1) model is proved, and also derived is the asymptotic distribution of the quasi-maximum likelihood estimator. [ABSTRACT FROM AUTHOR]

The objective of this paper is to determine the best predictor of equity market crashes by focusing particularly on volatility and market liquidity. In finance, volatility has traditionally been regarded as the best measure of market risk. However, this paper shows that the forecast value of market liquidity, in particular our modified calculated market depth, predicts equity market crashes much more accurately than does the forecast values of EGARCH or Implied Volatility. [ABSTRACT FROM AUTHOR]

The main objective of this study is to check the short-term stress of COVID-19 pandemic on the American, European, Asian, and Pacific stock market indices and furthermore the correlation between all the stock markets during the pandemic. Secondary data of 41 stock exchange from 32 countries have been collected from investing.com website from 1st July 2019 to 14th May 2020 for the stock market and the COVID-19 data has been collected according to the first cases reported in the country, stocks market are classified either developed or emerging economy, further divided according to the subcontinent i.e. America, Europe, and Pacific/Asia, the main focus in the data is the report of first COVID-19 cases. The study reveals that there is volatility in the all the 41 stock market (American, Europe, Asia, and Pacific) after reporting of the first case and volatility increase with the increase of COVID-19 cases, moreover, there is a significant negative relationship between the number of COVID-19 cases and 41 major stock indices of American, Europe, Asia and Pacific, European subcontinent market found more effected from the COVID-19 than another subcontinent, there is Clustering effect of COVID-19 on all the stock market except American's stock market due to smart capital investing. [ABSTRACT FROM AUTHOR]

We examine a discrete–time optimal pair–trade execution problem with generalized cross–impact. This research is an extension of Fukasawa et al. (2020b), which considers the price impact of aggregate random orders posed by small traders with a Markovian dependence. We focus on how a risk–averse large trader optimally executes two correlated assets to maximize his/her expected utility from the terminal wealth over a finite horizon. A Markov decision process modeling constitutes the basis for the formulation of the optimal pair–trade execution problem. Then, under some regularity conditions, the backward induction method of dynamic programming enables us to derive the optimal pair–trade execution strategy and its associated optimal value function. The trading orders of each risky asset posed by small traders do affect the optimal execution volume of both risky assets. Moreover, numerical results with simulation experiments show that the cross–impact affects the optimal execution strategy and a round–trip trade exists for the large trader to utilize a 'statistical' arbitrage and to increase his/her expected utility under our model setting of cross–impact. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic causes a huge number of infections. The outbreak of COVID-19 has not only caused substantial healthcare impacts, but also affected the world economy and financial markets. In this paper, we study the effect of the COVID-19 pandemic on financial market connectedness and systemic risk. Specifically, we test dynamically whether the network density of pandemic networks constructed by the number of COVID-19 confirmed cases is a leading indicator of the financial network density and portfolio risk. Using rolling-window Granger-causality tests, we find strong evidence that the pandemic network density leads the financial network density and portfolio risk from February to April 2020. The findings suggest that the COVID-19 pandemic may exert significant impact on the systemic risk in financial markets. [ABSTRACT FROM AUTHOR]

Exploiting the classical R/S and modified R/S analysis, we first reveal the evidence of long-term memory in liquidity, volume, and volatility. Thereafter, we estimate the fractionally integrated autoregressive moving average (ARFIMA) models by both the exact-maximum likelihood (EML) and the modified-profile likelihood (MPL) methods. Furthermore, based on the theory of financial economics, we extend the simple ARFIMA models to the Multi-Factor ARFIMA models by incorporating the mutual relationships among financial market variables and present the effectiveness of the Multi-Factor ARFIMA models in financial markets. [ABSTRACT FROM AUTHOR]

This is a note on computation of the implied volatility in theBlack-Scholes formula to evaluate an accuracy of the computation. [ABSTRACT FROM AUTHOR]

Motivated by the exponential growth of the cryptocurrency market and the need for more empirical work to understand the dynamics of the young financial market, this paper, through time- and frequency-varying techniques examines the extent of linkages between leading cryptocurrencies and diverse traditional assets of emerging economies. Using variants of the multivariate conditional heteroscedasticity models and a dummy, we assess the economic potential, each for Bitcoin and Ripple, from the perspective of an emerging market investor. The results, from both time and frequency analyses indicate that the two major cryptocurrency assets have not yet coupled with the emerging assets, as weaker to lower-moderate correlations characterise movements of the pairs. Additionally, our results unveil a multifaceted economic benefit of Bitcoin and Ripple, however, this varies across emerging asset classes (forex and equities), country-specific assets, and regional emerging market groupings. The findings hold some implications for investors, regarding portfolio diversification and risk management. [ABSTRACT FROM AUTHOR]

This study examines the capital structure of Japanese private firms. Using a dataset over a period of more than thirty years, the study shows that the leverage ratios of private firms remain stable over the long term and exhibit greater persistence than do those of public firms. Regression analysis shows that the firms' future leverage ratios are significantly positively related to initial leverage ratios. Most of the variation in leverage ratios can be explained by unobservable factors. Private firms are found to have a significantly higher leverage ratio than public firms. Adjustment to the target leverage ratio is slower for private firms than for public firms, reflecting the high adjustment costs of the former. [ABSTRACT FROM AUTHOR]

In order to improve upon the performance of a managed portfolio, we propose the use of Marginal Value-at-Risk (MVaR) to ascertain the desirability of assets for inclusion in the managed portfolio, prior to obtaining the optimal managed portfolio. In particular, this is applied on a larger index which comprises of a greater number of assets than a benchmark index and the larger index includes all the assets from the benchmark index. The resulting MVaR index includes exactly the same number of assets as the benchmark index. An empirical study with S&P BSE 100 as the benchmark index, with the MVaR index being derived from S&P BSE 200, with five different optimization problems shows outperformance by the MVaR portfolio over the benchmark portfolio. This highlights the advantage of the inclusion of MVaR resulting in improved performance of the managed portfolio. [ABSTRACT FROM AUTHOR]

By analyzing not only an overnight return but also a midday-recess return, namely, a stock return during midday-recess, I analyze whether and why market closures affect cross-sectional stock returns. I find strong persistence in overnight and midday-recess returns, with both returns positively associated with each other. Moreover, these out-of-trading-hours returns are negatively associated with returns during trading hours. I analyze whether these associations are explained by a different investor clientele outside trading hours (the open of the trading session) compared to during trading hours (intraday and closing of the trading session). I find that institutional ownership increases more with returns during trading hours; the finding indicates that those returns are mainly determined by institutional investors, while midday-recess and overnight returns, that is, returns outside trading hours, are not. Overall, my results support the view that market closures do affect cross-sectional returns and the influence is attributable to differences in the investor clientele. [ABSTRACT FROM AUTHOR]

This study proposes an extension of the realized stochastic volatility model by incorporating realized quarticity RQ into the volatility process. We employ an efficient Riemann Manifold Hamiltonian Monte Carlo method in a Markov Chain Monte Carlo algorithm to estimate parameters that could not be sampled directly. We investigate the empirical performance of the proposed model using data for six equity indices and 24 individual stocks listed on the Tokyo Stock Exchange. Parameter estimates and two Bayesian model selection criteria reveal evidence supporting RQ-based models that are driven by the maximum value of RQ data. That model consistently outperforms benchmark realized stochastic volatility models in capturing spikes in volatility caused by large RQ values. Including such stylised facts as the asymmetric effect of returns-volatility and heavy tailed returns, our results reveal that the proposed models exhibit a weaker correlation between stock returns and volatility and heavier tails in equity returns. [ABSTRACT FROM AUTHOR]

This study investigates the trading dynamics between institutional, foreign and retail investors during QE and post-QE exit in the Japanese stock market. A theoretical framework is developed to classify all transactions into trading, short-selling or information flow. Using weekly data from 2014 to 2015, our results show: Firstly, during QE tapering, there is short-selling by foreign retail investors. There is also information flow from Foreign Retail Sales to Local Institutional Sales as well as Foreign Retail Purchases to Local Retail Purchases. Net buyers are local and foreign institutional investors; Secondly, in post-QE exit, there is short-selling by foreign institutional investors. Moreover, Foreign Institutional Purchases is found to precede Local Retail Purchases. Net sellers are local and foreign retail investors. Hence, it can be concluded that foreign investors are dominant player during QE tapering and post-QE period. As a policy suggestion, both local and foreign investors should be provided with more incentive to trade in the local bourse. The regulator should also ensure timely disclosure of material public information by listed firms to ensure a level playing field for all market participants. [ABSTRACT FROM AUTHOR]

This study revisits calendar anomalies in Japanese stock returns to examine whether they can be explained by market conditions. Results of the OLS and GARCH (1,1) regression models show that most of the well-known calendar anomalies no longer exist in Japanese stock returns when conventional methodologies are used. These calendar anomalies became evident during the Japanese bubble period and disappeared subsequently. To provide new evidence on calendar anomalies in Japanese stock returns, we examine calendar anomalies based on market conditions. We show that the day-of-the-week, January, turn-of-the-month, Halloween and Dekansho-bushi effects became evident in UP market conditions only. They were never evident in DOWN market conditions. All these anomalies are still found to be significant in UP market conditions. Our explanation is consistent throughout the whole sample period and is robust against the choice of index used to measure market returns. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the success factors of financial derivatives markets in Asia. The selected countries include Thailand, Malaysia, Singapore, South Korea, Japan and Hong Kong. The success factors of financial derivatives markets in Asia are examined by employing the panel regression. The empirical results show that size, volatility, and liquidity of spot market are significant factors for the success of financial derivatives markets in sample countries. Further, tick size, contract size, and option-type also enhance trading volumes while product age is not statistically significant. The results from this study provide important implications in developing the financial derivatives market which plays an important role in the capital market. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) is a flexible yet tractable technique in control engineering that recently has gained much attention in the area of finance, particularly for its application to portfolio optimization. In this paper, we extend the MPC with linear feedback setting in Yamada and Primbs (in: Proceedings of the IEEE conference on decision and control, pp 5705-5710, 2012) by incorporating the following two important and practical issues: The first issue is gross exposure (GE), which is the total value of long and short positions invested in risky assets (or stocks) as a proportion of the wealth possessed by a hedge fund. This quantity measures the leverage of a hedge fund, and the fund manager may limit the amount of leverage by imposing an upper bound, i.e., a GE constraint. The second issue is related to transaction costs, where the MPC algorithm may require frequent trades of many stocks leading to large transaction costs in practice. Here we assume that the transaction cost is proportional to the change in the amount of money (i.e., the change of absolute values of long or short positions) invested in each stock. We formulate the MPC strategy based on a conditional mean-variance problem which we show reduces to a convex quadratic problem, even with gross exposure and proportional transaction cost constraints. Based on numerical experiments using Japanese stock data, we demonstrate that the incorporation of the transaction cost constraint improves the empirical performance of the wealth in terms of Sharpe ratio, which may be improved further by adding the GE constraint. [ABSTRACT FROM AUTHOR]

In this paper, while focusing on the impact that the global financial crisis had on the stock markets of China, Japan, and the United States, the stock-price volatilities and linkage between these three countries are analyzed. In addition, the relationships between macroeconomic variables (real-economy variables and monetary-policy variables) and stock price volatility in each country are investigated. The estimation results of the EGARCH model revealed that although China's stock price volatility was far greater than those of Japanese and US stock prices, China was less affected by the global financial crisis in 2007 than Japan and the United States. For China, stock price volatility was greater in the early 1990s, shortly after the stock market had been established, than in 2007 when the global financial crisis occurred. Furthermore, it has been revealed that the linkage of Chinese, Japanese, and US stock prices has increased since the global financial crisis. Moreover, Granger causality testing revealed China's realeconomy variables and monetary-policy variables do not affect China's stock price volatility. [ABSTRACT FROM AUTHOR]

This study employs big data and text data mining techniques to forecast financial market volatility. We incorporate financial information from online news sources into time series volatility models. We categorize a topic for each news article using time stamps and analyze the chronological evolution of the topic in the set of articles using a dynamic topic model. After calculating a topic score, we develop time series models that incorporate the score to estimate and forecast realized volatility. The results of our empirical analysis suggest that the proposed models can contribute to improving forecasting accuracy. [ABSTRACT FROM AUTHOR]

We consider option pricing for a foreign exchange (FX) rate where interventions by an authority may take place when the rate approaches to a certain level at the down side. We formulate the forward FX model by a diffusion process which is stopped by a hitting time of an absorption boundary. Moreover, for a deterministic volatility case with a moving absorption whose level is described by an ordinary differential equation, we obtain closed-form formulas for prices of a European put option and a digital option, and Greeks of the put option. Furthermore, we show an extension of the pricing formula to the case where the intervention level is unknown. In numerical examples, we show option prices for different strikes for the absorption model and the extended model. We compare the model prices with the market prices for EURCHF options traded before January 2015 with the absorption model, and also show experiments of the extended model as an application to the pricing under uncertain views on the intervention. [ABSTRACT FROM AUTHOR]

For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (Math Comput Simul 81:1272-1289, ; N Am J Econ Finance 26:289-309, ) have proposed the separating information maximum likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable finite sample properties and asymptotic properties when the sample size is large when the hidden efficient price process follows a Brownian semi-martingale. We shall show that the SIML estimation is useful for estimating the integrated covariance and hedging coefficient when we have round-off errors, micro-market price adjustments and noises, and when the high-frequency data are randomly sampled. The SIML estimation is consistent, asymptotically normal in the stable convergence sense under a set of reasonable assumptions and it has reasonable finite sample properties with these effects. [ABSTRACT FROM AUTHOR]

This paper examines influence of interest rates on bull and bear markets in Tokyo stock exchange. Japan implemented a zero interest rate policy (ZIRP) from February 1999 to August 2000 and quantitative easing (QE) from March 2001 to March 2006. Because the relationship between Japanese equity price and interest rates apparently is inconsistent, it is needed to identify whether and how interest rates might affect a current market trend or initiate a market reversal. This study examines whether changes in Japan's policy interest rate-the unsecured overnight call rate-prompt changes in the Tokyo Stock Price Index (TOPIX). The question we seek to answer is how TOPIX was affected by policies such as ZIRP and QE from bubble era until today. This paper shows that the call rate altered the direction of the TOPIX, market peaks and troughs appeared after call rates changed, and Japanese equities reacted more strongly to call rates during the 2000s. [ABSTRACT FROM AUTHOR]

The stochastic volatility model of Heston (Rev Financ Stud 6(2):327-343, ) has found difficulty in describing some of the important features of implied volatility dynamics, leading to a quest for multifactor extensions as well as the incorporation of time-dependent model parameters. In this paper, an asymptotic expansion approach to the multifactor Heston model with time-dependent parameters is developed. The results of Benhamou et al. (SIAM J Financ Math 1(1):289-325, ) are extended and it is shown that the extension to the multifactor model involves an extra expansion term that captures the interaction between variance factors. The expansion formula under constant parameters can be explicitly computed and the incorporation of time-dependent parameters is straightforward under the framework. As illustration, a two-factor model is calibrated to data of index options and variance swaps and it is found that it is possible to distinguish a short-term and long-term variance factor from the implied volatility surface and variance swap rates. Moreover, the two-factor model is able to reproduce the shapes of the implied volatility surface during various market scenarios. [ABSTRACT FROM AUTHOR]

The Markowitz portfolio optimization model, popularly known as the Mean-Variance model, assumes that stockreturns follow normal distribution. But when stock returns do not follow normal distribution, this model wouldbe inadequate as it would prescribe sub-optimal portfolios. Stock market literature often deliberates that stock returns are non-normal. In such context the Markowitz model would not be sufficient to estimate the portfolio risks. The purpose of this paper is to expand the original Markowitz portfolio theory (mean-variance) via adding the higher order moments like skewness (third moment about the mean) and kurtosis (fourth moment about the mean) in the return characteristics. The research paper investigates the impact of including higher moments using multi-objective programming model for portfolio stock selection and optimization. The empirical results indicate that the inclusion of higher moments had a considerable impact in estimating the returns behavior of portfolios. The portfolios optimized using all the four moments, generated higher returns for the given level of risk in comparison to the returns of the Markowitz model during the study period 2000-2011. The results of this study would be immensely useful to fund managers, portfolio managers and investors as it would help them in understanding the Indian stock market behavior better and also in selecting alternative portfolio selection models. [ABSTRACT FROM AUTHOR]

In this paper, we design a valuation model for intangible assets using panel data, and empirically investigate the model validity. The approach using panel data is an evaluation method that uses unobserved firm-specific effects based on panel analysis. Our model first estimates production function using panel analysis, and then develops cost function using a duality approach. Next, we discount added value and costs resulting from intangible assets using fixed effects. Empirical analysis using the model compares the estimated parameter values in the nonlinear profit function consisting of production function and cost function with those in the production function alone, which becomes linear after logarithmic conversion, and finds that the two are generally similar. Additionally, the market value of equity is more closely associated with both the book value of equity and the value of intangible assets than with the book value of equity alone. These results support the validity of the model for evaluating intangible assets. This model is easy to apply in practice and is based on a simple idea. Further discussion of this model is warranted given the increasing importance attached to the value of intangible assets. [ABSTRACT FROM AUTHOR]

Using high-frequency data, this study investigates price discovery in the newly established stock index (CSI300) futures market in China. Our empirical results reveal new evidence that the CSI300 index futures market play a dominant role in the price discovery process about one year after its inception and new information is disseminated more rapidly in the stock index futures market than the stock market. This is different from findings in the previous literature. Our results also imply that the index futures market has evolved and can be used as a price discovery vehicle. Thus the CSI300 stock index futures market plays an important role in the capital markets in China. [ABSTRACT FROM AUTHOR]

This paper extends the previous analyses of the forecastability of Japanese stock market returns in two directions. First, we carefully construct smoothed market price-earnings ratios and examine their predictive ability. We find that the empirical performance of the price-earnings ratio in forecasting stock returns in Japan is generally weaker than both the price-earnings ratio in comparable US studies and the price dividend ratio. Second, we also examine the performance of several other forecasting variables, including lagged stock returns and interest rates. We find that both variables are useful in predicting aggregate stock returns when using Japanese data. However, while we find that the interest rate variable is useful in early subsamples in this regard, it loses its predictive ability in more recent subsamples. This is because of the extremely limited variability in interest rates associated with operation of the Bank of Japan's zero interest policy since the late 1990s. In contrast, the importance of lagged returns increases in subsamples starting from the 2000s. Overall, a combination of logged price dividend ratios, lagged stock returns, and interest rates yield the most stable performance when forecasting Japanese stock market returns. [ABSTRACT FROM AUTHOR]

For the estimation problem of mean-variance optimal portfolio weights, several previous studies have proposed applying Stein type estimators. However, few studies have addressed this problem analytically. Since the form of the loss function used in this problem is not of the quadratic type commonly used in statistical studies, there have been some difficulties in showing analytically the general dominance results. However, dominance results are given here of a class of Stein type estimators for the mean-variance optimal portfolio weights when the covariance matrix is unknown and is estimated. The class of estimators is broader than the one given in a previous study. The results we have obtained enable us to clarify conditions for some previously proposed estimators in finance to have smaller risks than the estimator which we obtain by plugging in the sample estimates. [ABSTRACT FROM AUTHOR]

China has become recognized a fourth world economy and is playing a much more important role than ever before in the world economy. In this paper, we study the relationship between the China and the international main stock markets, including the stock markets in the U.S., the U.K., Japan and Hong Kong. Both long-term and short-term dynamic linkages between the China and the international main stock markets are explored by applying a Markov-Switching Vector Error Correction Model (MS-VECM), which takes into account the three regimes of depression, boom and speculation in the market. Our new findings with the data under study include: (i) There has been a significant trend of long-term co-movement between the China and the international stock markets since 1999. (ii) In short term, the stock market in China has been impacted directly or indirectly by the international main stock markets, which varies under different regimes. This impact is still weak in the depression regime, but strong in the boom regime, and, in particular, it has become very strong through the co-integration error correction in the regime of speculation. These findings are different from those documented in the literature and are potentially interesting for international investment and risk management. [ABSTRACT FROM AUTHOR]