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The purpose of the paper is to study the explainability of expected and unexpected trade volume and open interest as information flow, and the asymmetric effects of unexpected shocks to the information flow on volatility in Indian commodity markets.

After having dissected into expected and unexpected components, the effects of trade volume and open interest on volatility are tested. A new interaction term is also added to measure asymmetry. Four commodities, namely, cumin, soy oil and pepper in food commodity category and guar seed in non-food commodity category are selected for the present study. These four commodities are selected based on their economic and trading importance, i.e. weight in the index and trading volume (liquidity).

It is mostly found that unexpected volatility is positively related to the volatility, and the effect of the unexpected component is more than the expected component of the trading volume. The expected open interest is negatively related to volatility while the unexpected open interest is found to be positively related in all the commodities. The effects of unexpected component are higher than the expected open interest. The effects of positive unexpected shocks to the trade volume are more than those of negative unexpected shocks. The evidence of asymmetry in unexpected shocks to open interest is inconclusive. However, the inclusion of volume of trade and open interest could not vanish away the volatility. This indicates that the trading volume and open interest are not the variable with mixed distribution. Thus, it contrasts the assumption of mixed distribution hypothesis, and they do not proxy the flow of information.

It is the unexpected information flow that matters more than the expected one. Positive unexpected shocks to trade volume are more influential than the negative shocks. However, trade volume and open interest are not good proxy of information flow in the Indian commodity markets. This study would definitely broaden the horizon of managers and policymakers to understand the volatility better.

The paper is unique in terms of understanding the effect of expected and unexpected trade volume and open interest and the asymmetric effects of unexpected shocks to volume and open interest in the Indian commodity markets.

This paper aims to investigate the predictability of stock returns under risk and uncertainty of a set of 11 emerging equity markets (EEMs) during the pre- and post-crash periods.

Listed indices are considered to serve the proxy of stock markets with a structural break in data for the period: 2000-2014. As preliminary results highlight the significant autocorrelations in stock returns, Threshold-GARCH (1,1) model is used to estimate the conditional volatility, which is further decomposed into expected and unexpected volatility.

Results highlight that the volatility has symmetric impact on stock returns during the pre-crash period and asymmetric impact during the post-crash period. While testing the relationship of stock returns, a significant positive (negative) relationship is found with expected volatility during the pre-crash (post-crash) periods. The stock returns are found positively related to unexpected volatility.

Business, political and other market conditions of sample stock markets are fundamentally different. These economies were liberalized in different years, which may affect the degree of integration with international equity markets.

The findings highlight that investors consider the impact of expected volatility in forecasting of stock returns during the growth period. They realize returns in commensurate to risk of their portfolios. However, they significantly reduce their investments in response to expected volatility during the recession period. The positive relationship between stock returns and unexpected volatility highlights the fact that investors realize extra returns for exposing their portfolios to unexpected volatility.

Pioneer efforts are made by using T-GARCH (1,1) procedure to analyse the problem. Given the emergence of emerging equity markets, new insight in dynamics of stock returns provide interesting findings for portfolio diversification under risk and uncertainty.

The purpose of this paper is twofold, first, to develop an effective tool to assess the performance of the overall economy by creating an assessment ratio that reflects the two top priorities of monetary policy, promoting economic growth and maintaining price stability, and second, to use the annual assessment ratios to build two subsamples, outperformance (better than the historical average) and underperformance, to examine and compare the changes in impacts of monetary and fiscal policy tools on important economic variables in different economic conditions, instead of different time periods.

The assessment ratio is defined as the gross domestic product (GDP) gap/standard deviation of inflation. Essentially, this Growth/Volatility ratio quantifies the price volatility-adjusted long-term output growth, that is, the long-term output growth given 1 per cent of the standard deviation of inflation. The growth has a positive impact on the ratio, while the effect of price volatility is negative. The ratio reflects not only the Fed’s dual goal but also the fundamental economic conditions. A higher value of the ratio indicates that the economy can better handle inflation risk in driving the long-term output growth. As the inflation level is adjusted in the numerator (GDP gap), not the denominator, no matter the Fed is engaging in the fight against inflation, or for reflation (promoting inflation) to prevent deflation and pursue price stability (Bernanke, 2002), the ratio remains consistent with the Fed’s dual goal and prefers a higher value.

Results of this study suggest that impacts of monetary and fiscal policy tools on key economic variables may be cyclic as the economic condition changes. The policy tools can significantly affect inflation volatility and the price volatility-adjusted long-term real output growth in the subpar economic conditions identified with lower assessment ratios. The effects become insignificant when the general economic performance exceeds the historical average. More importantly, results of this study indicate that the funds rate can effectively lower the price volatility, while the fiscal tools can promote long-term real output growth in the subpar economic conditions. Therefore, when inflation volatility spikes and the real output growth slows, the decisive and timely monetary and fiscal policy decisions become necessary to enhance policy effectiveness.

The assessments of effectiveness of monetary policy in the literature are based on some or all of four descriptive statistics: inflation, inflation volatility, output growth, and growth volatility. Each of them measures only one aspect of an economic phenomenon and cannot reflect the well-known conflicting relationship between maintaining price stability and promoting economic growth. For instance, from the policy perspective, a higher price volatility combined with a higher GDP growth rate for one period may or may not outperform another period with lower price volatility and growth rate. However, the assessment ratio created in this study considers both price volatility and economic growth simultaneously and can, therefore, be used as an effective measure of the overall economic performance.

The purpose of this paper is to examine cross-correlation in stock returns of SAARC countries, conditional and unconditional volatility of stock markets and to test efficient market hypothesis (EMH).

Stock indices of India, Bangladesh, Sri Lanka and Pakistan are considered to serve as proxy for stock markets in SAARC countries. Data consist of daily closing price of stock indices from 2000 to 2011. Since preliminary testing indicated presence of serial autocorrelation and volatility clustering, family of GARCH models is selected.

Results indicate presence of serial autocorrelation in stock market returns, implying dependence of current stock prices on stock prices of previous times and leads to rejection of EMH. Significant relationship between stock market returns and unconditional volatility indicates investors’ expectation of extra risk premium for exposing their portfolios to unexpected variations in stock markets. Cross-correlation revealed level of integration of South Asian economies with global market to be high.

Business cycles and other macroeconomic developments affect most companies and lead to unexplained relationships. The paper finds stock markets to exist at different levels of development as economic liberalization started at different points of time in SAARC countries.

Correlation between stock indices of SAARC economies are found to be low which is in line with intra-regional trade being one of lowest as compared to other regional groups. Results point towards greater need for economic cooperation and integration between SAARC countries. Greater financial integration leads to development of markets and institutions, effective price discovery, higher savings and greater economic progress.

The paper focuses on EMH and risk return relation for SAARC nations.

Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be measured through the generalized autoregressive conditional heteroscedasticity family models and that will give an insight for investment decision-making.

Daily data of the closing value of Bombay Stock Exchange (BSE) (Sensex) and National Stock Exchange (NSE) (Nifty) from April 1, 2011 to March 31, 2017 is collected through the web-portal of BSE (www.bseindia.com) and NSE (www.nseindia.com) for the analysis purpose.

The outcome of the study suggested that P-GARCH model is most suitable to predict and forecast the stock market volatility for both the markets.

Future research can be extended to other stock market segments and sectoral indices to explore and forecast the volatility to establish a trade-off between risk and return.

The results of previous studies available are not conducive to this research, and very limited scholarly work is available in the Indian context, so required to be re-explored to identify the appropriate model to predict market volatility.

The purpose of this paper is to examine the effect of trading volume and open interest on volatility of futures markets. The authors capture the size and change in speculative behaviour in futures markets by examining the role of liquidity variables (trading volume and open interest) in the behaviour of futures prices.

The sample includes daily data covering the period 1996-2014 from 36 international futures markets (including currencies, commodities, stock indices, interest rates and bonds). The authors employ a two-stage estimation methodology: first, the authors employ a E-GARCH model and consider the asymmetric response of volatility to shocks of different sign. Further, the authors consider a regression framework to examine the contemporaneous relationships between volatility, trading volume and open interest. To quantify the percentage of volatility that is caused by liquidity variables, the authors also regress the estimated volatilities on the measures of open interest and trading volume.

The authors find that: market depth has an effect on the volatility of futures markets but the direction of this effect depends on the type of contract, and there is evidence of a positive contemporaneous relationship between trading volume and futures volatility for all futures contracts. Impulse-response functions also show that trading volume has a more relevant role in explaining market volatility than open interest.

These results are recommended to financial managers and analysts dealing with futures markets.

To the best of the authors’ knowledge, no study has yet considered a complete database of futures markets to investigate the empirical relation between price changes (volatility), trading volume and open interest in futures markets.

The purpose of this paper is to estimate time‐varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures.

To estimate the volatility and capture the stylized facts of fat‐tail distribution, volatility clustering, leverage effect, and mean‐reversion in futures returns, appropriate ARMA‐generalized autoregressive conditional heteroscedastic (GARCH) and ARMA‐EGARCH models with generalized error distribution have been used. The ARMA‐EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time‐varying conditional volatility.

The paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish.

Research findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume‐price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions.

Equity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set.

This study is the first to examine the role of idiosyncratic risk in the pricing of European real estate equities. The capital asset pricing model predicts that in equilibrium, investors should hold the market portfolio. As a result, investors should only be rewarded for carrying undiversifiable systematic risk and not for diversifiable idiosyncratic risk. The study is adding to the growing body of countering studies by first examining time trends of idiosyncratic risk and subsequently the pricing of idiosyncratic risk in European real estate equities. The paper aims to discuss these issues.

The study analyses 293 real estate equities from 16 European capital markets over the 1991-2011 period. The framework of Fama and MacBeth is employed. Regressions of the cross-section of expected equity excess returns on idiosyncratic risk and other firm characteristics such as beta, size, book-to-market equity (BE/ME), momentum, liquidity and co-skewness are performed. Due to recent evidence on the conditional pricing of European real estate equities, the pricing is also investigated using the conditional framework of Pettengill et al. Either realised or expected idiosyncratic volatility forecasted using a set of exponential generalized autoregressive conditional heteroskedasticity models are employed.

The initial analysis of time trends in idiosyncratic risk reveals that while the early 1990s are characterised by both high total and idiosyncratic volatility, a strong downward trend emerged in 1992 which was only interrupted by the burst of the dotcom bubble and the 9/11 attacks along with the global financial and economic crisis. The largest part of total volatility is idiosyncratic and therefore firm-specific in nature. Simple cross-correlations indicate that high beta, small size, high BE/ME, low momentum, low liquidity and high co-skewness equities have higher idiosyncratic risk. While size and BE/ME are priced unconditionally from 1991 to 2011, both measures of idiosyncratic risk fail to achieve significance at reasonable levels. However, once conditioned on the general equity market or real estate equity market, a strong positive relationship between idiosyncratic risk and expected returns emerges in up-markets, while the opposite relationship exists in down-markets. The relationship is robust to firm-specific factors and a series of robustness checks.

The results show that ignoring the conditional relationship between idiosyncratic risk and returns might result in the false realisation that idiosyncratic risk does not matter in the pricing of risky (real estate) assets.

This study is the first to examine the role of idiosyncratic risk in the pricing of European real estate equities. The study reveals differences in the pricing of European real estate equities and US REITs. The study highlights that ignoring the conditional relationship between idiosyncratic risk and returns might result in the false realisation that idiosyncratic risk does not matter in the pricing of risky assets.

The purpose of this paper is to examine whether firms manage the total value of stock option grants downward after the implementation of Statement of Financial Accounting Standards (SFAS) 123R to reduce their reported option expenses.

All Standard & Poor’s (S&P) 1500 firms with available stock option data in 2004 and 2006 are included in the analysis. The authors analyze if the total value of options granted, the per share fair value of options granted, the number of options granted as well as each individual input assumption have changed from the pre-SFAS 123R (i.e. 2004) to the post-SFAS 123R (i.e. 2006) period. We compare post-SFAS123R option pricing assumptions and per share fair value of options granted with their respective expected values to verify the results. We also analyze whether SFAS 123R has differential effects on firms which chose to disclose option expense only in footnotes (“disclosing firms”) versus firms which voluntarily recognized option expense (“recognizing firms”) prior to SFAS 123R.

The results show that after SFAS 123R, the total fair value of stock options granted for disclosing firms declined significantly. The decrease appears to result from managerial discretion over volatility and dividend yield assumptions as well as the reduction in the number of options granted. The evidence suggests that firms engage in not only assumption-based manipulations but also real activities to lower reported stock option expenses. It was also found that disclosing firms lower the total fair value of stock options granted to a greater extent than recognizing firms.

This study adds to prior literature that examines the opportunistic incentives for managers to use discretion in reporting stock option expenses. This study contributes to the earnings management literature by providing another example of manipulating earnings through real activities. Finally, our study should be of interest to regulators and investors.

The purpose of this paper is to test whether the 2007 identification of commonality in liquidity by Galariotis and Giouvris for the UK is robust to different methodological approaches; to find whether commonality is priced; and to identify how changes in trading regimes, hence liquidity provision, affect the relationship between commonality and excess returns.

The paper builds on the 2001 methodology of Huberman and Halka. In addition it extracts common factors using principal component analysis to test the effect of commonality on excess returns.

The findings of this paper confirm the presence of a systematic time‐varying component in UK spreads (under a different approach) even after controlling for well‐known spread determining variables.

The paper provides original evidence on the presence and the effect of systematic liquidity on asset pricing in the UK, showing that it is sensitive to the nature of trading regimes. It is concluded that in order‐driven regimes the effect of commonality on asset pricing is reduced, hence policy makers should consider this when deciding on trading systems