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This paper aims to provide the necessity to activate long-term exchange-traded derivatives (ETD) in Korea. In the era of aging, low interest rates and low economic growth, the investment demand for long-term financial products, and its hedging demand have steadily increased. Unfortunately, long-term ETD do not trade in Korea, and this study presents political suggestions to invigorate long-term ETD based on overseas cases and empirical analysis. Specifically, this study suggests the necessity to activate exchange traded funds (ETFs) options, long-term Korea treasury bond futures and options and long-term Volatility Index of Korea Composite Stock Price Index future and options. The introduction of those long-term ETD not only contributes to providing long-term investment and hedging vehicles but also reduces market inefficiencies in the Korean industry of ETFs, bonds and structured products.

The purpose of this paper is to examine the performance of US mutual funds that invest primarily in emerging market equities and bonds.

The study adopts the Morningstar classification of mutual funds and uses the Lipper US Mutual Fund Database through FactSet to obtain monthly returns and various metrics for emerging market equity and bond mutual funds covering the period from January 2000 to May 2017. Several descriptive statistics for these funds are reported as well as various risk-adjusted performance measures. Alphas are computed for different sub-periods using different factor models to mitigate potential biases.

The results show that diversified emerging market funds generate some significant alphas for their investors during the study period. Emerging market bond funds, on the other hand, do not provide any significant positive alphas; mostly alphas are negative. An analysis of sub-period performance suggests that these funds do not consistently provide excess returns, showing great variations from one period to another.

The emerging market funds provide US investors with an alternative source of exposure for their portfolios. Emerging markets differ from developed markets on a wide range of market and economic characteristics, including size, liquidity, and regulation. This study contributes to the scarce literature on these types of funds and provides a comprehensive performance assessment against various benchmarks during a period that encompasses significant bear and bull markets across the world.

This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p – VAR(p) – for multivariate system.

Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information.

It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market.

There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions.

This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.

This study aims to examine the return predictability of variance risk premium, which is defined as the difference between risk-neutral variance and expected realized variance, on KOSPI 200 index returns. Although extant literature shows that variance risk premium estimated from U.S. index options has a predictive power on underlying returns, little study has been conducted in KOSPI 200 index returns. In addition, there is no conclusion for the predictive power of variance risk premium in other financial markets. In this paper, we can find the predictive power of S&P500 variance risk premium on KOSPI200 index returns as well as on S&P500 index returns, but cannot find the predictive power of KOSPI200 variance risk premium on both indices. These results are consistent to Londono (2012) and Bollerslev et al. (2013). The poor performance of KOSPI200 variance risk premium is explained by the assumption that U.S. economy is a leader economy, while Korea economy is a follower economy. To support this conclusion, we conduct Vector Auto-Regression (VAR) using two variance risk premiums. Two premiums have bi-directional lead-lag relationship but S&P500 variance risk premium is informationally superior to KOSPI200 variance risk premium regarding return predictions.

The purpose of this study is to examine empirically the conditional correlation between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as: Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

In this study, the authors use for the first time the GARCH-DECO (1,1) to examine empirically the conditional nexus between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as; Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

From the empirical findings, the authors conclude the existence of a highly significance of conditional heteroscedasticity parameters can demonstrate us to distinguish the nature of the volatility dependency between S&P500 index and Dow Jones Industrial index and three selected meat commodities indices.

This can find clear the significance of relationship in the process of financialization of the major US index and meat commodities indices in the case of this paper.

As cryptocurrencies continue to gain viability as an asset class, institutional investors and publicly traded firms have started taking investment positions in digital currencies. What firms may not be considering, however, is the effect these assets may have on their risk profiles. This study aims to (1) measure the effect of cryptocurrencies on the risk and return characteristics of publicly traded companies; (2) decipher the motives behind holding cryptocurrencies as an asset class; and (3) determine whether one reason for holding is more effective than another. To conduct this research, the four largest publicly traded holders of cryptocurrency as well as four of the most prominent cryptocurrencies are explored.

The cross-sectional analysis approach has been used to analyze the daily returns, volatility, betas and Sharpe Ratios of firms during periods without cryptocurrency strategies and during periods with cryptocurrency strategies.

The impact of the cryptocurrency asset class on common stock performance and corporate disclosures are documented. The importance of risk disclosures on cryptocurrency holdings is emphasized: Firms must better inform their stakeholders through comprehensive disclosures in financial statements. Firms utilize cryptocurrencies for various reasons such as treasury management tools or as direct sources of income. Consequently, the impact on returns and risks varies substantially.

To the best of the authors’ knowledge, this is one of the first studies on cryptocurrency investments in the treasury departments of publicly traded companies. The study contributes to the literature by extracting relevant information regarding company risk reporting and cryptocurrency risk at firms. The conclusions also promote firm transparency with detailed reporting of cryptocurrency holding risks.

This paper conducts a factor analysis using the implied variances of S&P 500 index options and KOSPI 200 index options. After estimating the factors that influence variance risks, we rotate the factors to decompose them into a common factor and local factors. The results show that 10~12 percent of variance risks in both markets is explained by the common factor and 65 percent of S&P 500 implied variances and 70 percent of KOSPI 200 implied variances are explained by each local factor, which is in contrast to the results for bond markets that the most variation of interest rates could be explained by a common factor. To figure out the source of common and local factors, additionally, we adopt the regression models that incorporate the risk-neutral (RN) variance, skewness, and kurtosis as explanatory variables. Approximately, the common factor is mainly determined by the RN variance of the S&P 500 index and RN higher moments of the KOSPI 200 index. In contrast, the S&P 500 local factor is influenced by the RN variance of the S&P 500 index and the KOSPI 200 local factor is explained by the RN higher moment of the KOSPI 200 index.

Based on stakeholder, agency and institutional theory, this study aims to examine the role of institutional ownership in the relationship between environmental, social and governance practices and CEO compensation.

Utilizing a fixed-effect panel regression analysis, this research utilized a panel data approach, analyzing data spanning from 2014 to 2021, focusing on US companies listed on the S&P500 stock market index. The dataset encompassed 219 companies, leading to a total of 1,533 observations.

The analysis identified that environmental scores significantly impact CEO equity-linked compensation, unlike social and governance scores. Additionally, it was found that institutional ownership acts as a moderating factor in the relationship between the environmental score and CEO equity-linked compensation, as well as the association between the social score and CEO equity-linked compensation. Interestingly, the direction of these moderating effects varied between the two relationships, suggesting a nuanced role of institutional ownership.

This research makes a unique contribution to the field of corporate governance by exploring the relatively understudied area of institutional ownership's influence on the ESG practices–CEO compensation nexus.

The aim of the study was to analyze the performance of Black-Litterman (BL) portfolios using a views estimation procedure that simulates investor forecasts based on technical analysis.

Ibovespa, S&P500, Bitcoin and interbank deposit rate (IDR) indexes were respectively considered proxies for the national, international, cryptocurrency and fixed income stock markets. Forecasts were made out of the sample aiming at incorporating them in the BL model, using several portfolio weighting methods from June 13, 2013 to August 30, 2022.

The Sharpe, Treynor and Omega ratios point out that the proposed model, considering only variable return assets, generates portfolios with performances superior to their traditionally calculated counterparts, with emphasis on the risk parity portfolio. Nonetheless, the inclusion of the IDR leads to performance losses, especially in scenarios with lower risk tolerance. And finally, given the impact of turnover, the naive portfolio was also detected as a viable alternative.

The results obtained can contribute to improve investors practices, specifically by validating both the performance improvement – when including foreign assets and cryptocurrencies –, and the application of the BL model for asset pricing.

The main contributions of the study are: performance analysis incorporating cryptocurrencies and international assets in an uncertain recent period; the use of a methodology to compute the views simulating the behavior of managers using technical analysis; and comparing the performance of portfolio management strategies based on the BL model, taking into account different levels of risk and uncertainty.