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As global exchanges have listed volatility derivatives competitively, volatility has been recognized as a new investment vehicle and/or a hedging means for traditional financial assets such as stocks and bonds. Following this trend, KRX has begun to announce VKOSPI from KOSPI200 index options prices since April 13, 2009 and listed VKOSPI futures on November 17, 2014. However, VKOSPI futures has still not been activated than those listed in developed countries. In this paper, we investigate the informational efficiency of VKOSPI futures and analyze the illiquidity problem of VKOSPI futures. More specifically, we execute a VAR analysis of VKOSPI, VKOSPI futures, VIX and VIX futures to find out their lead-lag relations. In addition, we further conduct a Granger causality test, impulse response analysis and variance decomposition to examine their dynamic relations. According to the results, we find that VKOSPI leads VKOSPI futures and that VIX and VIX futures lead VKOSPI and VKOSPI futures significantly. Based on the results above, lastly, we propose several policies to make the VKOSPI futures market more active and informative.

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.

This study verifies the existence of implied volatility distortion by the rapid growth of structured products such as Equity Linked Securities (ELS) in Korean financial markets and provides the policy implications to overcome such a distortion. The most ELS products issued in Korea have a step-down auto-callable payoff structure consisting of short position in down-and-in barrier put options and long position in digital call options. Financial companies which have issued ELS are exposed to the volatility risk, i.e. long vega position, and tend to execute the volatility transactions of short vega. For instance, the financial companies issue Equity-Linked Warrants or sell listed/over-the-counter vanilla options, both of which have short position in volatility risk. Accordingly, the demand for selling volatility is stronger than for buying volatility in the Korean financial markets. According to the empirical results, we conform that the rapid growth of the ELS products induces the pressure for lowering volatility and furthermore, the volatility spreads, defined as the difference between implied volatility and realized volatility, also decrease with respect the amount of the newly issued ELS. Lastly, to mitigate the volatility distortion effect, we suggest to list VKOSPI-related derivatives securities such as VKOSPI futures and options, which in turn balance the trading demands for selling and buying volatilities.

This paper presents 6 time-series that have negative correlation with KOSPI200 Index and a quantitative trading methodology based on stochastic control chart using these time-series. The proposed quantitative trading framework detects trade (long or short) timing by monitoring whether a time-series touches 4 trigger lines, which play a role as control limits in control chart. In other words, a time-series upwardly touches one of trigger line, then the framework take a short position on KOSPI200 Index Futures, while in case of downward touch, it takes a long position. The 6 time-series are derived from VKOSPI and USD Futures Index that are negatively correlated with KOSPI200 Index, and have a significance that prevents disclosure of trading strategies by processing and transforming the original time-series. Computational experiments using real KOSPI200 futures index for recent 4 years are conducted to show the excellence of the proposed investment strategies against benchmark strategies under quantitative trading framework.

ELS (Equity Linked Security) is the structured product which is one of the fast grown and the most successful in Korean financial markets. In particular, ELS with the index of stocks as underlying asset (‘index ELS') has shown a remarkable growth since 2010. This paper has analyzed the hedging effects of index ELS to the KOSPI200 index and futures market. It verifies that the hedging of index ELS has not shown any significant effect to the return of KOSPI200 index and futures, but it seems that it effects on the volatility. In other words, as ELS issue amount increases, VKOSPI tends to decrease because ELS issuer which has long vega position is trying to hedge it.

The purpose of this paper is to examine the volatility spillover and lead-lag relationship between the Chicago Board Options Exchange volatility index (VIX) and the major agricultural future markets before and during the Coronavirus disease 2019 (COVID-19) outbreak.

The methods used were the vector autoregression-Baba, Engle, Kraft and Kroner-generalized autoregressive conditional heteroskedasticity method, the Wald test and wavelet transform method.

The findings indicate that prior to the COVID-19 outbreak, there was a two-way volatility spillover impact between the majority of the sample markets. In comparison, volatility transmission between the VIX index and the agricultural future market was significantly lower following the COVID-19 outbreak, the authors observed greater coherence at higher frequencies than at lower frequencies, implying that the interdependence between the two VIX indices and the agricultural future market was stronger over a longer time-frequency domain and the VIX’s signalling effect on various agricultural future prices after the COVID-19 outbreak was significantly lower.

The authors conducted the first comprehensive investigation of the VIX’s correlation with major agricultural futures, especially during COVID-19. The findings contribute to a better understanding of the risk transmission mechanism between the VIX and major agricultural commodities futures contracts. And our findings have significant implications for investors and portfolio managers, as well as for policymakers who are concerned about the price of agricultural futures.

This paper aims to propose the implied volatility index for the US dollar–Indian rupee pair (INRVIX). The study seeks to examine whether INRVIX truly reflects future USDINR (US Dollar-Indian rupee) volatility and signals profitable currency trading strategies.

Two measures of INRVIX are constructed and compared: a model-free version based on the methodology adopted by the Chicago Board of Options Exchange (CBOE) and a model-dependent version constructed from Black–Scholes–Merton-implied volatility. The proposed INRVIX is computed by tweaking some parameters of the CBOE methodology to ensure compatibility with the microstructure of the Indian currency derivatives market. The volatility forecasting ability of INRVIX is compared to that of a generalized autoregressive conditional heteroscedasticity (1,1) model. Ordinary least squares regression is used to examine the relationship between n-day-ahead USDINR returns and different quantiles of INRVIX.

Results indicate that INRVIX based on the model-free approach reflects ex post volatility in a better manner than its model-dependent counterpart, although neither measure is found to be an unbiased and efficient forecast. Subsample analysis across tranquil and turbulent periods corroborates the results. The volatility forecasting performance of INRVIX is found to be better than that of forecasts based on historical time-series. These results are consistent with similar studies of developed market currencies. The study does not find any significant relationship between extreme levels of INRVIX and the profitability of trading strategies based on such levels, which is contrary to results from the equity options market.

Foreign exchange volatility affects the costs of international trade and the external sector competitiveness of Indian multinationals. It is a significant risk factor for financial institutions and traders in the financial markets. An implied VIX for the USDINR could serve as an indicator of expected foreign exchange risk. It could thus provide a signal for a possible intervention in the forex market by the regulator. Regulators could introduce volatility derivative contracts based on the INRVIX. Such contracts would enable hedging of the pure volatility risk of dollar–rupee exposure. Thus, the study has practical implications for investors, hedgers, regulators and academicians alike.

To the author’s knowledge, this is one of a few studies to construct an implied VIX for an emerging currency like the rupee. The study is based on up-to-date sample data that includes the recent COVID-19 market crash. A novel contribution of this paper is that in addition to examining whether INRVIX contains information about future USDINR volatility, and it also examines the signalling power of INRVIX for currency trading strategies.

Based on the theoretical framework, this paper analyzes the sentiment-herding relationship in emerging stock markets (ESMs). First, it aims to examine the effect of investor sentiment on herding. Second, it seeks the direction of causality between sentiment and herding time series.

The present study applies the Exponential Generalized Auto_Regressive Conditional Heteroskedasticity (EGARCH) model to capture the volatility clustering of herding on the financial market and to investigate the role of the investor sentiment on herding behaviour. Then the vector autoregression (VAR) estimation uses the Granger causality test to determine the direction of causality between the investor sentiment and herding. This study uses a sample consisting of stocks listed on the Shanghai Composite index (SSE) (348 stocks), the Jakarta composite index (JKSE) (118 stocks), the Mexico IPC index (14 stocks), the Russian Trading System index (RTS) (12 stocks), the Warsaw stock exchange General index (WGI) (106 stocks) and the FTSE/JSE Africa all-share index (76 stocks). The sample includes 5,020 daily observations from February 1, 2002, to March 31, 2021.

The research findings show that the sentiment has a significant negative impact on the herding behaviour pointing out that the higher the investor sentiment, the lower the herding. However, the results of the present study indicate that a higher investor sentiment conducts a higher herding behaviour during market downturns. Then the outcomes suggest that during the crisis period, the direction is one-way, from the investor sentiment to the herding behaviour.

The findings may have implications for universal policies of financial regulators in EMs. We have found evidence that the Emerging investor sentiment contributes to the investor herding behaviour. Therefore, the irrational investor herding behaviour can increase the stock market volatility, and in extreme cases, it may lead to bubbles and crashes. Market regulators could implement mechanisms that can supervise the investor sentiment and predict the investor herding behaviour, so they make policies helping stabilise stock markets.

The originality of this paper lies in investigate the sentiment-herding relationship during the Surprime crisis and the Covid-19 epidemic in the EMs.

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

This paper aims to address the importance of behavioural finance issues among real investors. It analyses whether private investors are susceptible to extrapolation bias and whether this bias affects market prices.

A qualitative coding of message board posts facilitates the construction of sentiment proxies. Using linear techniques, it is tested whether after-hours sentiment is positively predicted by daily share return and whether daily share return exhibits positive autocorrelation.

Private investors are impaired by extrapolation bias, while market prices remain unaffected. Probably, sophisticated professional investors benefit by offsetting the irrational private investor transactions.

As the sample of German blue-chip banks is small and covers a period during the Eurozone crisis, the findings should be generalised with caution. Future research might use a different sample and explore whether non-crisis periods provide comparable results.

Investors should not take for granted the neoclassical assumption that all market participants always act rationally and according to self-interest.

Irrespective of whether market prices are efficient, a level playing field between private and professional investors is necessary. Otherwise, confidence in the financial marketplace is not guaranteed and society may incur welfare losses.

The approach of extracting sentiment from a German share message board through qualitative content analysis (QCA) is unique for analysing extrapolation bias. This paper is valuable in drawing attention to the importance of rational investment behaviour among private investors.