1,720,971 research outputs found
THE INCREMENTAL VALUE OF A FUTURES HEDGE USING REALIZED VOLATILITY
No full text[[abstract]]A number of prior studies have developed a variety of multivariate volatility models to describe the joint distribution of spot and futures, and have applied the results to form the optimal futures hedge. In this study, the authors propose a new class of multivariate volatility models encompassing realized volatility (RV) estimates to estimate the risk-minimizing hedge ratio, and compare the hedging performance of the proposed models with those generated by return-based models. In an out-of-sample context with a daily rebalancing approach, based on an extensive set of statistical and economic performance measures, the empirical results show that improvement can be substantial when switching from daily to intraday. This essentially comes from the advantage that the intraday-based RV potentially can provide more accurate daily covariance matrix estimates than RV utilizing daily prices. Finally, this study also analyzes the effect of hedge horizon on hedge ratio and hedging effectiveness for both the in-sample and the out-of-sample data. (C) 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:874-896,2010[[note]]SSC
OPTIMAL FUTURES HEDGING UNDER MULTICHAIN MARKOV REGIME SWITCHING
No full text[[abstract]]Most of the existing Markov regime switching GARCH-hedging models assume a common switching dynamic for spot and futures returns. In this study, we release this assumption and suggest a multichain Markov regime switching GARCH (MCSG) model for estimating state-dependent time-varying minimum variance hedge ratios. Empirical results from commodity futures hedging show that MCSG creates hedging gains, compared with single-state-variable regime-switching GARCH models. Moreover, we find an average of 24% cross-regime probability, indicating the importance of modeling cross-regime dynamic in developing optimal futures hedging strategies. (c) 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:173-202, 2014[[note]]SSC
The real R&D options value incorporating technological risk management
No full text[[abstract]]Purpose - The paper aims to evaluate the real research and development (R&D) options value through the proposed model that can jointly consider the two types of risk management activities, i.e. hedging risks and making use of risks. Hedging is an important risk-management tool that can diversify R&D risk internally since R&D organizations cannot transfer technological risks to another entity by conventional loss financing methods. Making use of risks means R&D organizations can benefit from proactively managing risks, and then can create management-flexibility value from the real option reasoning viewpoint. Design/methodology/approach - Using the real options pricing approach, the paper provides an applicable assessment method for R&D projects that can jointly consider the aforementioned two types of risk management activities. The paper also investigates the value-enhancing effects of R&D risk management activities via interviews survey and secondary data analyses in the pharmaceutical industry of Taiwan. Findings - Through numerical analyses, the results indicate that the hedging management can serve to be effective mechanisms of risk reduction as well as value enhancement for R&D projects. Additionally, the value-enhancing effect of hedging management is more significant for those R&D projects with even higher risk-level. The results of empirical study also are consistent with the model prediction. Originality/value - To achieve great performance of R&D risk management, R&D organizations need to implement both the types of risk management activities. By this real-options valuation approach incorporating together those risk management activities, R&D projects portfolio can be evaluated adequately.[[note]]SC
Effective options trading strategies based on volatility forecasting recruiting investor sentiment
No full text[[abstract]]This study investigates an algorithm for an effective option trading strategy based on superior volatility forecasts using actual option price data for the Taiwan stock market. The forecast evaluation supports the significant incremental explanatory power of investor sentiment in the fitting and forecasting of future volatility in relation to its adversarial multiple-factor model, especially the market turnover and volatility index which are referred to as the investors' mood gauge and proxy for overreaction. After taking into consideration the margin-based transaction cost, the simulated trading indicates that a long or short straddle 15 days before the options' final settlement day based on the 60-day in-sample-period volatility forecasting recruiting market turnover achieves the best average monthly return of 15.84%. This study bridges the gap between option trading, market volatility, and the signal of the investors' overreaction through the simulation of the option trading strategy. The trading algorithm based on the volatility forecasting recruiting investor sentiment could be further applied in electronic trading and other artificial intelligence decision support systems. (C) 2010 Elsevier Ltd. All rights reserved.[[note]]SC
SYSTEMIC RISK IN TAIWAN STOCK MARKET
No full text[[abstract]]Recent financial crises resulted from systemic risk caused by idiosyncratic distress. In this research, taking Taiwan stock market as an example and collecting data from 2000 to 2010 which contained the 2001 dot-corn bubble and the 2007-2009 financial crisis, we adopt the CoVaR model to empirically explore the impact of sector-specific idiosyncratic risk on the systemic risk of the system and attempt to investigate the links between financial crises, systemic risk and the idiosyncratic risk of a sector-specific anomaly. The result showed sector-specific marginal CoVaR, i.e., Delta CoVaR, perfectly explained Taiwan stock market disturbance during the 2001 dot-corn bubble and 2007-2008 financial crisis. Thus, by identifying the larger Delta CoVaR sectors, i.e. the systemic importance sectors, and by exploring the risk indicators, independent variables, of these systemic importance sectors, investors could practically employ the sector-specific Delta CoVaR measure to deepen the systemic risk scrutiny from a macro into a micro prudential perspective.[[note]]SSC
A study of US and China's volatility spillover effects on Hong Kong and Taiwan
No full text[[abstract]]Many international investors have taken interest in the Hong Kong, Taiwan, and China stock markets for diversification to explore higher returns owing to their rapid economic growth and increased link with international capital markets over the past decades. As correlation is primary component for asset risk managing, asset pricing and portfolio allocating, which are concerns for investors, it is crucial to clarify the co-movement of these stock markets. The aim of this paper was to compare the effect of volatility of China and U.S. stock market respectively on the Taiwan and Hong Kong. Both vector autoregressive (VAR) and multivariate generalized autoregressive conditional heteroskedastic (MGARCH) model were employed for two separated sub-periods: 1996-2005 and 2006-2009. Results indicated that while China's rapid economic growth and its integration with Taiwan and Hong Kong, its stock market was considerably independent and its co-moments with other (international) markets were still not significant. It's useful information for investors that China stock market, with low co-moments with others, would be a good risk diversified investment and that U.S. stock market, with high co-moments with others, would be a good pricing indicator.[[note]]SSC
Dynamics of stock market integration between the US and the BRIC
No full text[[abstract]]This study investigates the evolving pattern of integration and Granger-causality relationships between the developed US and developing BRIC stock markets. The study uses both the linear Engle-Granger cointegration test and the nonlinear Enders-Siklos cointegration test for comparative analysis, and it expands the consistent momentum threshold autoregressive model and the threshold error correction model by time-varying approaches for dynamic analysis. The evidence demonstrates that both long-run time-varying nonlinear cointegration relationships and short-run time-varying Granger-causality relationships exist between the stock markets of US-Brazil, US-India, US-Russia and US-China (US-BRIC). Furthermore, these relationships were altered in the short-run during 2007/2008, when the subprime mortgage financial crisis in the US occurred. The empirical results demonstrate that the stock markets of Brazil, Russia and China have begun exerting significant influences on the Dow Jones to some extent after 2006, and the Dow Jones index continues to play a dominant role and increasingly, Granger-causing shifts in the emerging markets of Russia, India and China. The findings demonstrate the time-varying nature of the nonlinear cointegration and Granger-causality relationships, and also indicate that the potential benefits from international risk diversification may have gradually diminished between these studied markets.[[note]]SSC
A Multiplicative Approach to Derive Weights in the Interval Analytic Hierarchy Process
No full text[[abstract]]This paper proposes a multiplicative approach to solve defective issues in lexicographic goal programming of the analytic hierarchy process (LGPAHP). Although the LGPAHP can handle inconsistent interval comparison matrices, it generates different weights in the upper and lower triangular interval judgments. Instead of adopting additive constraints, the proposed method uses multiplicative constraints to cope with deficiencies inherent in the LGPAHP. Moreover, since two deviation variables are used to cope with inconsistent cases, weights can be flexibly derived, without specifying any advance tolerance parameters. Four examples are presented to illustrate the proposed method in more detail.[[note]]SC
Do firms' earnings management practices affect their equity liquidity?
No full text[[abstract]]This study investigates the relationship between earnings management and equity liquidity, positing that as incentives arise for the manipulation of firm performance through earnings management (due partly to conflicts of interest between firm insiders and outsiders), greater earnings management may signal higher adverse selection costs. If earnings manipulation reveals aggressive accounting practices, liquidity providers tend to widen bid-ask spreads to protect themselves. The empirical results indicate that companies with higher earnings management suffer lower equity liquidity. (C) 2009 Elsevier Inc. All rights reserved.[[note]]SSC
A linearization method for quadratic minimum spanning tree problem
No full text[[abstract]]The crisp and fuzzy quadratic minimum spanning tree (Q-MST) problem can be formulated as a linear, model, and thus, the global optimum can be obtained by the proposed method. Conventionally, the Q-MST problem, which contains a quadratic term in the objective function, is solved by genetic algorithm and other heuristic methods. However, these methods cannot guarantee to obtain a global optimal solution. To address this issue, the proposed method transforms the quadratic term into linear formulations for crisp and fuzzy Q-MST problems, and yields the global optimum solutions by linear integer programming. Two examples are given to demonstrate the proposed method in greater detail.[[note]]SC
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