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We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

This study aims to identify calendar anomalies that can affect stock returns and asymmetric volatility. Thus, the objective of this study is twofold: on the one hand, it examines the impact of calendar anomalies on the returns of both conventional and Islamic indices in Indonesia, and on the other hand, it analyzes the impact of these anomalies on return volatility and whether this impact differs between the two indices.

The authors apply the GJR-generalized autoregressive conditional heteroskedasticity model to daily data of the Jakarta Composite Index (JCI) and the Jakarta Islamic Index for the period ranging from October 6, 2000 to March 4, 2022.

The authors provide evidence that the turn-of-the-month (TOM) effect is present in both conventional and Islamic indices, whereas the January effect is present only for the conventional index and the Monday effect is present only for the Islamic index. The month of Ramadan exhibits a positive effect for the Islamic index and a negative effect for the conventional index. Conversely, the crisis effect seems to be the same for the two indices. Overall, the results suggest that the impact of market anomalies on returns and volatility differs significantly between conventional and Islamic indices.

This study provides useful information for understanding the characteristics of the Indonesian stock market and can help investors to make their choice between Islamic and conventional equities. Given the presence of some calendar anomalies in the Indonesia stock market, investors could obtain abnormal returns by optimizing an investment strategy based on seasonal return patterns. Regarding the day-of-the-week effect, it is found that Friday’s mean returns are the highest among the weekdays for both indices which implies that investors in the Indonesian stock market should trade more on Fridays. Similarly, the TOM effect is significantly positive for both indices, suggesting that for investors are called to concentrate their transactions from the last day of the month to the fourth day of the following month. The January effect is positive and statistically significant only for the conventional index (JCI) which implies that it is more beneficial for investors to invest only in conventional assets. In contrast, it seems that it is more advantageous for investors to invest only in Islamic assets during Ramadan. In addition, the findings reveal that the two indices exhibit lower returns and higher volatility, which implies that it is recommended for investors to find other assets that can serve as a safe refuge during turbulent periods. Overall, the existence of these calendar anomalies implies that policymakers are called to implement the required measures to increase market efficiency.

The existing literature on calendar anomalies is abundant, but it is mostly focused on conventional stocks and has not been sufficiently extended to address the presence of these anomalies in Shariah-compliant stocks. To the best of the authors’ knowledge, no study to date has examined the presence of calendar anomalies and asymmetric volatility in both Islamic and conventional stock indices in Indonesia.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

This study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.

Employing a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.

The study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.

The study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.

Findings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.

The research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

This paper investigates the information content of implied volatilities inferred from individual stock options quoted over-the-counter (OTC). First, we examine whether the implied volatility has better explanatory power than historical volatility for forecasting future realized volatility of the underlying stock return. Next, we analyze the properties of volatility spreads, the difference between implied volatilities and realized volatilities. Using near-the-money options for 10 firms over the sample period from April 2005 to April 2010, we first demonstrate that the implied volatilities for most firms don’t have additional information beyond what are already contained in historical volatilities. However, the implied volatilities with some specific remaining maturities for two firms dominate historical volatilities in explaining the future realized volatilities. Second, we find that during the period before global financial crisis, the implied volatilities are systematically lower than the future realized volatilities whereas this reversal disappears after the year 2008. This finding suggests that there’s a possibility of the risk loving behavior of the investors in OTC individual stock options market during the pre-global crisis period. Finally, through the comparative analysis of the KOSPI200 index options quoted OTC over the same sample period, we conclude that the OTC individual stock options market has distinctive characteristics like the KRW/USD OTC currency options market.

The purpose of this research is to determine whether the trading of equity index futures contracts on the South African Futures Exchange (SAFEX) results in an increase in the volatility of the underlying spot indices. Since equity index futures contracts were first listed in the USA in 1975, various studies have been undertaken to determine whether the volatility of shares in the underlying indices increases as a result of the trading of such futures contracts. These studies have lead to the development of two schools of thought: [a] Trading activity in equity index futures contracts leads to an increase in the volatility of index shares. [b] Trading activity in equity index futures contracts does not lead to an increase in the volatility of the index shares and could in fact lead to greater stability in equity markets. Although some evidence of higher volatility in expiration periods was found, volatility in the expiration periods was not consistently higher than in the corresponding pre‐expiration period.

The purpose of this paper is to amend the New Keynesian Phillips Curve (NKPC) model to include inflation volatility. It provides results on the determinants of inflation volatility and expected inflation volatility for ordinary least squares and autoregressive distributed lags (1,1) models and for change in inflation volatility and change in expected inflation volatility using error correction mechanism (ECM) models. Output gap affects change in expected inflation volatility alone (in the ECM model) and not in the other models. Major determinants of inflation volatility and expected inflation volatility are identified. To the best of the authors knowledge this is the first paper to augment the NKPC to include inflation volatility.

Recent analysis has indicated the importance of inflation volatility for the monetary transmission mechanism in India (Kapur and Behera, 2012). In the analysis of such monetary policy mechanisms the NKPC has proved to be a useful tool. Thus Patra and Ray (2010) for India and Brissimis and Magginas (2008) for the USA find considerable support for the standard NKPC. The purpose of this paper is to synthesize and integrate these two models by extending the standard NKPC framework to include inflation volatility and test its significance for the case of India.

In the case of inflation volatility output gap, lagged output gap and lagged inflation volatility are all insignificant. The level of inflation has a negative significant impact whereas the level of expected inflation has a positive and significant impact. In the case of expected inflation volatility lagged output gap has a negative and significant impact, the price level has a positive and significant impact whereas expected price has a negative and weakly significant impact. ECM reveals change in inflation variability falls significantly with lagged inflation volatility and lagged inflation and less significantly with change in expected inflation. It rises with lagged expected inflation although the coefficient is only weakly significant. Lagged output gap and change in output gap are insignificant.

This paper makes two original contributions. First, it extends the New Keynesian framework to include inflation volatility. Second, it estimates this model for India. To the best of the authors knowledge this is the first paper to make these contributions.

The development of standardized measures of institution‐wide volatility exposures has so far lagged that for measures of asset price and interest‐rate exposure—largely because it is difficult to reconcile the various mathematical models used to value options. Recent mathematical results, however, can be used to construct standardized measures of volatility exposure. We consider here techniques for reconciling “vegas” for financial options valued using stochastic models that may be mathematically inconsistent with each other.

The purpose of this paper is to examine whether stock market liberalization creates excess stock return volatility in the Qatar Exchange (QSC).

The study utilizes two methods, simple analysis of variance and the EGARCH model with dummy variables.

Results reveal no change in market volatility following the partial removal of the restrictions on foreign participation. Results suggest, however, that the degree of persistence in volatility is high, which implies that once volatility increases it remains high over a long run. In addition, conditional volatility tends to rise when the absolute value of the standardized residuals was large. While, contrary to what has been found in the literature, the return volatility seems to be symmetric.

The finding of volatility persistence and clustering might imply an inefficient stock market. Therefore, policy makers should emphasize and direct their attention toward increasing the efficiency of the stock market.

Being able to make predictions about financial market volatility is of special importance to investors and policy makers since it makes available to them a measure of risk exposure in their investments and decisions.

This paper provides a contribution to the empirical literature on stock market volatility. It is the only study, to the authors' knowledge, that investigates the issue of QSC liberalization and volatility. The authors believe that QSC has its own unique characteristics, and the results of the study depend mainly on the market's specific conditions, the quality of its financial institutions and the extent of financial liberalization obtained.

The Chinese stock market is a typical emerging market with special features that are very different from those of mature markets. The objective of this study is to investigate whether and how these features affect the volatility‐volume relation for Chinese stocks.

This paper examines the roles of the number of trades, size of trades, and share volume in explaining the volatility‐volume relation in the Shanghai Stock Exchange with high frequency trade data used.

The results confirm that the volatility‐volume relation is driven mainly by the number of trades on the Chinese stock market. The number of trades explains the volatility‐volume relation better than the size of trades. Furthermore, some results are obtained that differ from those of mature markets, such as the US market. The results show that the second largest sized trades affect the volatility more than other trades on the Chinese market.

The results show that, in the Shanghai Stock Exchange, informed traders camouflage their private information or manipulation behavior through the second largest sized trades. The results may have important implications for work explaining the volatility‐volume relation on the Chinese stock market, further providing a reference by which to regulate emerging markets.