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This study investigates the impact of program trading on the market volatility by separating the volatility into long-run and short-run components using VA-CEGARCH model. This approach allows us to observe the two channels through which the program trading affects the market volatility. We have following results. Program trading and non-program trading both have no impact on the long-run component but do increase short-run component. In case of short-run component‘ program trading has a larger impact compared to non-program trading. Secondly, in both daily and intra-day analysis, arbitrage program trading is found to have a larger impact on short-run components than non-arbitrage program trading.

Thirdly, ARCH effects are found in short-run components of daily analysis and long-run components of intra-day analysis. And the volatility’s asymmetric responses to good or bad news are introduced through long-run components. What is noteworthy is the fact that non-arbitrage program trading is actually found to reduce short-run volatility in the intra-day analysis.

Which means that non-arbitrage program trading, such as hedging transactions, helps promote intra-day market stability. Our findings mean that the short-run component is the main channel by which program trading produce unnecessary market volatility.

The impact of volatility crush can be devastating to an option buyer and results in a substantial capital loss, even with a directionally correct strategy. As a result, most volatility plays are for option sellers, but the profit they can achieve is limited and the sellers carry unlimited risk. This paper aims to demonstrate the dynamics of implied volatility (IV) as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the exploratory factor analysis (EFA), they extract four constructs and the results from the confirmatory factor analysis (CFA) indicated a good model fit for the constructs.

This section describes the methodology used for conducting the study. This includes the study area, study approach, sources of data, sampling technique and the method of data analysis.

Although there is extensive literature on methods for estimating IV dynamics during earnings announcement, few researchers have looked at the impact of expected market maker move, IV differential and IV Rank on the IV path after the earnings announcement. One reason for this research gap is because of the recent introduction of weekly options for equities by the Chicago Board of Options Exchange (CBOE) back in late 2010. Even then, the CBOE only released weekly options four individual equities – Bank of America (BAC.N), Apple (AAPL.O), Citigroup (C.N) and US-listed shares of BP (BP.L) (BP.N). The introduction of weekly options provided more trading flexibility and precision timing from shorter durations. This automatically expanded expiration choices, which in turned offered greater access and flexibility from the perspective of trading volatility during earnings announcement. This study has demonstrated the impact of including market sentiment and liquidity into the forecasting model for IV during earnings. This understanding in turn helps traders to formulate strategies that can circumvent the undefined risk associated with trading options strategies such as writing strangles.

The first limitation of the study is that the firms included in the study are relatively large, and the results of the study can therefore not be generalized to medium sized and small firms. The second limitation lies in the current sample size, which in many cases was not enough to be able to draw reliable conclusions on. Scaling the sample size up is only a function of time and effort. This is easily overcome and should not be a limitation in the future. The third limitation concerns the measurement of the variables. Under the assumption of a normal distribution of returns (i.e. stock prices follow a random walk process), which means that the distribution of returns is symmetrical, one can estimate the probabilities of potential gains or losses associated with each amount. This means the standard deviation of securities returns, which is called historical volatility and is usually calculated as a moving average, can be used as a risk indicator. The prices used for the calculations are usually the closing prices, but Parkinson (1980) suggests that the day’s high and low prices would provide a better estimate of real volatility. One can also refine the analysis with high-frequency data. Such data enable the avoidance of the bias stemming from the use of closing (or opening) prices, but they have only been available for a relatively short time. The length of the observation period is another topic that is still under debate. There are no criteria that enable one to conclude that volatility calculated in relation to mean returns over 20 trading days (or one month) and then annualized is any more or less representative than volatility calculated over 130 trading days (or six months) and then annualized, or even than volatility measured directly over 260 trading days (one year). Nonetheless, the guidelines adopted in this study represent the best practices of researchers thus far.

This study has indicated that an earnings announcement can provide a volatility mispricing opportunity to allow an investor to profit from a sudden, sharp drop in IV. More specifically, the methodology developed by Tan and Bing is now well supported both empirically and theoretically in terms of qualifying opportunities that can be profitable because of the volatility crush. Conventionally, the option strategy of shorting strangles carries unlimited theoretical risk; however, the methodology has demonstrated that this risk can be substantially reduced if followed judiciously. This profitable strategy relies on a set of qualifying parameters including liquidity, premium collection, volatility differential, expected market move and market sentiment. Building upon this framework, the understanding of the effects of persistence and leverage resulted in further reducing the risk associated with trading options during earnings announcements. As a guideline, the sentiment and liquidity variables help to qualify a trade and the effects of persistence and leverage help to close the qualified trade.

The authors find a positive association between the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement. These findings substantiate further the four factors that influence IV dynamics during earnings announcement and conclude that just looking at persistence and leverage alone will not generate profitable trading opportunities.

The impact of volatility crush can be devastating to the option buyer with substantial capital loss, even for a directionally correct strategy. As a result, most volatility plays are for option sellers; however, the profit is limited and the sellers carry unlimited risk. The authors demonstrate the dynamics of IV as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the EFA, they extracted four constructs and the results from the CFA indicated a good model fit for the constructs. Using EFA, CFA and Bayesian analysis, how this model can help investors formulate the right strategy to achieve the best risk/reward mix is demonstrated. Using Bayesian estimation and IV differential to proxy for differences of opinion about term structures in option pricing, the authors find a positive association among the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement.

This paper provides an important perspective to the predictive capacity of Fed and European Central Bank (ECB) meeting dates and production announcements for the dynamic conditional correlation (DCC) between Bitcoin and energy commodities returns and volatilities during the period from August 11, 2015 to March 31, 2018.

To assess empirically the unanticipated component of the US and ECB monetary policy, the authors pursue the Kuttner's approach and use the federal funds futures and the ECB funds futures to assess the surprise component. The authors use the approach of DCC as introduced by Engle (2002) during the period from August 11, 2015 to March 31, 2018.

The authors’ results suggest strong significant DCCs between Bitcoin and energy commodity markets if monetary policy surprises are incorporated in variance. These results confirmed the financialization of Bitcoin and commodity energy markets. Finally, the DCC between Bitcoin and energy commodity markets appears to respond considerably more in the case of Fed surprises than ECB surprises.

This study is a crucial topic for policymakers and portfolio risk managers.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

The authors analyse six actively traded VIX Exchange Traded Products (ETPs) including 1x long, −1x inverse and 2x leveraged products. The authors assess their impact on the VIX Futures index benchmark.

Long-run causal relations between daily price movements in ETPs and futures are established, and the impact of rebalancing activity of leveraged and inverse ETPs evidenced through causal relations in the last 30 min of daily trading.

High frequency lead lag relations are observed, demonstrating opportunities for arbitrage, although these tend to be short-lived and only material in times of market dislocation.

The causal relations between VXX and VIX Futures are well established with leads and lags generally found to be short-lived and arbitrage relations holding. The authors go further to capture 1x long, −1x inverse as well as 2x leveraged ETNs and the corresponding ETFs, to give a broad representation across the ETP market. The authors establish causal relations between inverse and leveraged products where causal relations are not yet documented.

We analyze the dynamic behavior of the volatility of KTB futures price through GARCH models. In conducting this analysis we use two type data. Using dailly data we analyze the return and volatility spill-over effect between KTB spot and futures. Through 15-minute and 5-minute data we analyze return and volatility spill-over effect between KTB futures and won/dollar futures. We find that ARCH and GARCH effect exists in the volatility of KTB futures, but leverage effect does not exist in this data. Volatility spill-over effect was found only in 15-minute data. Lead and lag effect was found in 15-minute data of dollar and KTB futures where dollar return leads KTB futures and KTB volatility leads dollar volatility. In the daily data we found that KTB futures return lead KTB spot return while mutual spill-over existed between spot and futures in volatility data. Since conditional heteroscedasticity exists in KTB futures we need to consider the these effects in building up systems for arbitrage, valuation and risk management.

This study aims to examine what underlies the estimated relation between idiosyncratic volatility and realized return.

Idiosyncratic volatility has a dual effect on stock pricing: it not only affects investors' expected return but also affects the efficiency of stock price in reflecting its value. Therefore, the estimated relation between idiosyncratic volatility and realized return captures its relations with both expected return and the mispricing-related component due to its dual effect on stock pricing. The sign of its relation with the mispricing-related component is indeterminate.

The estimated relation between idiosyncratic volatility and realized return decreases and switches from positive to negative as the estimation sample consists of proportionately more ex ante overvalued observations; it increases and switches from negative to positive as the estimation sample consists of proportionately more ex post overvalued observations. In sum, the relation of idiosyncratic volatility with the mispricing-related component dominates its relation with expected return in its estimated relation with realized return. Moreover, its estimated relation with realized return varies with research design choices and even switches sign due to their effects on its relation with the mispricing-related component.

The novelty of the study is evident in the implication of its findings that one cannot infer the sign of the relation of idiosyncratic volatility with expected return from its estimated relation with realized return.

This study investigated the relationship between the CDS (credit default swap) market with the FX spot (FX swap) market, including the period of recent global financial crisis.

A measure for market efficiency is the condition that the derivative markets dominate the asset market in price discovery. In our case, however, FX market should be leading the CDS market. We found FX (spot and Derivatives) market has co-integration relationship with CDS market. Looking at Gonzalo Granger (GG) and Hasbrouck's price discovery measure, we found the FX spot and derivatives market dominated CDS market in price discovery.

This study has also examined the direction of shock spillover and volatility transmission between Korean CDS spread and Foreign exchange spot (FX swap) markets using the VECM bivariate GARCH approach. Our evidence suggested the presence of bi-directional shock volatility and volatility transmission between the CDS market and FX spot market partially exist. However, volatility spillover effects from CDS market to FX Swap market are stronger than in the reverse direction during the global financial crisis, indicating that the CDS spread signaling sovereign risk play a more important role in influencing the volatility of FX derivatives market.

There are some particular features in FX market. The volatility and shock of CIP deviations reflecting arbitrage opportunities in FX swap market are influenced by those of CDS spread in tranquil period prior to Lehman failure. But after Lehman failure CDS played a crucial role in signaling credit risk in FX derivatives market. We found that higher liquidity and trading volume of market matters more in price discovery and information transmission.

The purpose of this paper is to examine the impact of the Goods and Service Tax (GST) implementation on Malaysian stock market index.

This study used daily closing prices of the Malaysian stock index and futures markets for the period ranging from June 2009 to November 2016. Empirical estimation is based on the generalised autoregressive conditional heteroscedasticity (1, 1) model for pre- and post-announcement of the GST.

Result shows that volatility of Malaysian stock market index increases in the post-announcement than in the pre-announcement of the GST which indicates that educative programs employed by the government before the GST announcement did not yield meaningful result. The volatility of the Malaysian stock market index is persistent during the GST announcement and highly persistent after the implementation. Noticeable increase in post-announcement is in support with the expectation of the market about GST policy in Malaysia.

The finding of this study is consistent with expectation of the market that GST policy will increase the price of the goods and services and might reduce standard of living. This is supported by a noticeable increase in the volatility of the Malaysian stock market index in the post-announcement of GST which is empirically shown during the announcement and after the implementation of GST. Although the GST announcement could be classified as a scheduled announcement, unwillingness to accept the policy prevails in the market as shown by the increase in the market volatility.

Past studies on Malaysian stock market index volatility focus on the impact of Asian and global financial crisis whereas this study examines the impact of the GST announcement and implementation on the volatility of the Malaysian stock market index.

This study examines the impacts of the KTB futures options, newly introduced at the Korea Futures Exchange (KOFEX) on May, 2002, on the intraday volatility and liquidity of the KTB futures markets for the period from January 17, 2002, to August 30, 2002. The results show that the volatility of the KTB futures appears to have increased since the inception of the KTB futures options. However, the increase in volatility largely disappears after controlling for the effects of volume, time-to-maturity, day-of-the-week, and bid-ask bounce. There is some mixed evidence regarding the impact on the liquidity of the KTB futures markets, in the sense that the trading volume has increased significantly whereas the bid-ask spreads have widened too. The KTB futures price changes are more likely to lead the price changes of the KTB futures options by about 15 minutes, which is probably due to the infrequent trading problem on the part of the KTB futures options. Finally, though infrequently traded, the put-futures parity condition is rarely violated, and thus is difficult to be exploited for arbitrage transactions, indicating that the two markets are closely linked each other.