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This paper aims to examine the complex issue of the social cost of carbon. The authors review the existing literature and the strengths and deficiencies of existing approaches. They introduce a simple methodology that estimates the amount of “legal looting” in the fossil fuel industry as an alternative approach to calculate an unpaid social cost of carbon. The “looting amount” can be defined as society’s failure to charge fossil fuel firms for the damage that their activities cause represents an implied subsidy.

The methodology used in this paper combines decisions in the form of policymakers setting carbon taxes and rational investors investing in carbon emission markets.

The authors show that the unpaid social cost of carbon in the fossil fuel industry was US$12.7tn over 1995-2013, but may be as high as US$115.5tn.

Over the same period, the sum of industry profits, emission trading scheme carbon permit and carbon tax revenue totalled US$7tn, indicating the industry would not be viable if it was made to pay for damages to society.

Previous studies have shown the VIX futures tend to roll-down the term structure and converge towards the spot as they grow closer to maturity. The purpose of this paper is to propose an approach to improve the volatility index fear factor-level (VIX-level) prediction.

First, the authors use a forward-looking technique, the Heath–Jarrow–Morton (HJM) no-arbitrage framework to capture the convergence of the futures contract towards the spot. Second, the authors use principal component analysis (PCA) to reduce dimensionality and save substantial computational time. Third, the authors validate the model with selected VIX futures maturities and test on value-at-risk (VAR) computations.

The authors show that the use of multiple factors has a significant impact on the simulated VIX futures distribution, as well as the computations of their VAR (gain in accuracy and computing time). This impact becomes much more compelling when analysing a portfolio of VIX futures of multiple maturities.

The authors’ approach assumes the variance to be stationary and ignores the volatility smile. Nevertheless, they offer suggestions for future research.

The VIX-level prediction (the fear factor) is of paramount importance for market makers and participants, as there is no way to replicate the underlying asset of VIX futures. The authors propose a procedure that provides efficiency to both pricing and risk management.

This paper is the first to apply a forward-looking method by way of a HJM framework combined with PCA to VIX-level prediction in a portfolio context.

We examine tick sizes, stock prices, and share turnover in eighteen stock markets in developed countries and find that differences in mandatory tick sizes explain a significant proportion of the variation in stock prices among markets, and that lower percentage tick sizes are not associated with higher turnover. We consider the implications of these findings for the recent decimalization of stock trading in the United States, and conclude that decimal trading is likely to result in lower stock prices (due to stock splits) with no substantial change in dollar trading volume.

This paper examines and updates an earlier study of the liquidity of an extensive array of common stocks traded on NYSE/ASE/NML‐NASDAQ. It reports apparent variances in liquidity due to trading location and other variables. The paper suggests causes for these differences.

In this time of rapidly increasing journal subscription costs and shrinking (or stable) acquisition budgets, it is imperative to acquire materials as effectively as possible. One method of doing this is to use citation analysis of the scholarly literature as a guideline. Citation analysis is the analysis of the references from a set of documents (such as an analysis of all of the citations from five years of College & Research Libraries or of all citations from geology dissertations at a university). Information received from the analysis includes: languages of items cited, age of items cited (to calculate a half‐life for the field), and rate of self‐citations. Broadus reviewed citation analysis, its use, validity, and reliability. In the past, citation analysis has been used in collection development to decide on the suitability of specific items (both journals and monographs), such as mentioned in Buzzard and Whaley. The method introduced here is to use the percentage of publication formats cited in the research literature to serve as a guideline for acquisitions budget breakdowns, i.e., percentages allocated to monographs versus that allocated to other formats, for each discipline. The reasoning behind this is that an effective method of acquiring materials is to purchase the materials that the library's clients will use in the formats in which they will use them. The key assumption is that the citations in a scholar's paper reflect the literature the scholar used.

This study aims to examine the cross-market efficiency of the FTSE/MIB index options contracts traded on the Italian derivatives market (IDEM) during a period including the financial crisis between 1st October 2007 and 31st December 2012 using daily option prices.

Two fundamental no-arbitrage conditions were tested: the lower boundary condition (LBC) and the put–call parity (PCP) condition while taking into account the role of transaction costs in mitigating the number of violations reported. Ex post tests of LBC and PCP revealed a low incidence of mispricing in this market. Furthermore, to check the robustness of the results obtained by the ex post tests, ex ante tests were applied to PCP violations occurring within a one-day lag.

The results showed a significant drop in the number of profitable arbitrage strategies. The findings obtained from all these tests generally support the cross-market efficiency of the Italian index options market during the sample period, though some violations were occasionally reported. Overall, the number and monetary value of the violations reported declined during the post-financial crisis period compared to those during the financial crisis period.

This study can be extended to test the relationships between arbitrage profitability and other factors such as the moneyness (in the money, out of the money, at the money) of options and the maturity of options. Options market efficiency tests can be conducted such as call and put spreads, box spreads and put/call convexities (butterfly spreads).

There are several factors that influenced the decision to test the Italian index options market. First, the limited number of studies conducted on this market. Second, the fact that the two main studies on this market are relatively old, which makes it interesting to test the efficiency of this market with respect to a new set of data, taking into account the introduction of the Euro and the impact of the recent financial crisis on this market and whether the market efficiency hypothesis holds during the period of crisis. Third, it is important to consider the effect of the new rules applied to this market.

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.

Food—national dietary standards—is a sensitive index of socio‐economic conditions generally; there are others, reflecting different aspects, but none more sensitive. A country that eats well has healthy, robust people; the housewife who cooks hearty, nourishing meals has a lusty, virile family. It is not surprising, therefore, that all governments of the world have a food policy, ranking high in its priorities and are usually prepared to sacrifice other national policies to preserve it. Before the last war, when food was much less of an instrument of government policy than now—there were not the shortages or the price vagaries—in France, any government, whatever its colour, which could not keep down the price of food so that the poor man ate his fill, never survived long; it was—to make use of the call sign of those untidy, shambling columns from our streets which seem to monopolize the television news screens—“out!” Lovers of the Old France would say that the country had been without stable government since 1870, but the explanation for the many changes in power in France in those pre‐war days could be expressed in one word—food!

This study aims to look into how volatility significantly impacts the tracking error for daily-rebalanced leveraged bull and bear ETFs.

Using Morningstar return data and Chicago Board Options Exchange (CBOE) volatility index (VIX) data, the paper examines the daily tracking error for leveraged bull and bear ETFs. Tracking error is defined as the difference between the daily returns for a leveraged bull or bear ETF and the multiple of the daily return for that ETF's respective underlying benchmark index.

Changes in the market VIX of the CBOE have a significant and opposite effect on the daily returns for both leveraged bull and bear ETFs. Furthermore, these effects are more pronounced for bear ETFs than similarly leveraged bull ETFs.

The sample period (June 19, 2006 to September 22, 2009) contains periods of extraordinarily high volatility. Considering that the VIX reached an all-time high during this period, the results may be time-period specific and may not translate to other time periods.

The implication is that market timing may be feasible for enhancing daily returns for both leveraged bull and bear ETFs. However, any specific timing strategies go beyond the scope of this paper.

In this study, the paper examined the effects of expected market volatility on the daily tracking error of leveraged bull and bear ETFs. Specifically, the paper performed multiple linear regression analysis using Morningstar return data for the ETFs and their underlying benchmark and CBOE VIX data. The findings suggest that market timing could be beneficial for increasing daily yields for leveraged and inverse ETFs.

The purpose of this paper is to study short sales trading as part of the New York Stock Exchange (NYSE) batch open and National Association of Securities Dealers Automated Quotations (NASDAQ) opening cross. The paper examines whether short transactions at the open can predict future returns.

The study tests to see if short transactions in the NYSE opening batch trade and NASDAQ opening cross are informative of future returns.

It is found that a stock's opening‐trade short volume is predictive of its short volume for the rest of trading day, positively related to its previous‐day price change, and positively related to its overnight price change at the opening trade on option‐expiration Fridays when the stock is part of the Standard and Poor (S and P) 500 index.

While previous research shows that intraday short sale trades are informative, this is the first paper to examine the opening trade of the day, and whether these short sales are informative.