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Using the next-day and next-week returns of stocks in the Korean market, we examine the association of option volume ratios – i.e. the option-to-stock (O/S) ratio, which is the total volume of put options and call options scaled by total underlying equity volume, and the put-call (P/C) ratio, which is the put volume scaled by total put and call volume – with future returns. We find that O/S ratios are positively related to future returns, but P/C ratios have no significant association with returns. We calculate individual, institutional, and foreign investors’ option ratios to determine which ratios are significantly related to future returns and find that, for all investors, higher O/S ratios predict higher future returns. The predictability of P/C depends on the investors: institutional and individual investors’ P/C ratios are not related to returns, but foreign P/C predicts negative next-day returns. For net-buying O/S ratios, institutional net-buying put-to-stock ratios consistently predict negative future returns. Institutions’ buying and selling put ratios also predict returns. In short, institutional put-to-share ratios predict future returns when we use various option ratios, but individual option ratios do not.

Previous literature shows that market sentiment and the steepness of index option's implied volatility slope have a negative relation. This paper investigates the relation between firm-specific sentiment and individual option's implied volatility slope both theoretically and empirically.

The authors develop a simple model with option traders' sentiment heterogeneity to show that sentiment and the steepness of individual option's implied volatility slope have a positive relation.

When firm-specific sentiment is higher (more bullish), individual option's implied volatility slope becomes steeper. The positive relation is stronger when option traders' beliefs on risk are more dispersed. Empirical results support the theoretical model predictions.

Although both firm-specific sentiment and individual options implied volatility slope predict future stock returns, there is no research exploring the relation between them. In particular, none of previous studies associates implied volatility slope's stock return predictability to investor behavior such as sentiment. The authors’ findings provide a behavior-based explanation on why steep implied volatility slope negatively predicts cross-sectional stock returns.

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.

Increasingly popular, stock options may reward managers more for investors' expectations of future performance than for current performance.

The purpose of this paper is to investigate the relationship between option’s implied volatility smirk (IVS) and excess returns in the Germany’s leading stock index Deutscher-Aktien Index (DAX) 30.

The study defines the IVS as the difference in implied volatility derived from out-of-the-money put options and at-the-money call options. This study employs the ordinary least square regression with Newey-West correction to analyse the relationship between IVS and excess DAX 30 index returns in Germany.

The authors find that the German market adjusts information in an efficient way. Consequently, there is no information linkage between option volatility smirk and market index returns over the nine years sample period after considering the control variables, global financial crisis dummies, and the subsample test.

This study finds that the option market and the DAX 30 index are informationally efficient. Implications of the findings are that the investors cannot profit from the information contained in the IVS since the information is simultaneously incorporated into option prices and the stock index prices. The findings of this study are applicable to other markets with European options and for market participants who seek to exploit short-term market divergence from efficiency.

The relationship between IVS and stock price changes has not been investigated sufficiently in academic literature. This study looks at this relationship in the context of European options using high-frequency transactions data. Prior studies look at this relationship for only American options using daily data. Pricing efficiency of the European option market using high-frequency data have not been studied in the prior literature. The authors find different results for the German market based on this high-frequency data set.

The challenge facing human resource/compensation professionals in the people‐intensive, high‐technology industry, will be the development of a model and strategy intended to respond to the specific needs of unique professionals engaged in high growth organisations. This article examines the complex purposes of compensation, including the eight factors contributing to the determination of compensation levels, while considering constraints and contingencies. Job‐based evaluation and person‐based systems will be examined together with individual and group incentive plans as they impact upon growth cycles of high‐tech firms. The innovative nature of high‐technology organisations can be directly linked to compensation strategies for management. These high growth firms utilise a most unique compensation approach which is fundamentally different from normative organisations. They: (1) use annual incentives, but emphasise the longer term; (2) emphasise stock rather than long‐term cash plans; (3) use stock options where the manager benefits only if stock prices increase; (4) use a much larger proportion of stock than typical firms provide; and (5) encourage much wider use of stock among a broad employee group. Compensation occupies as significant a niche as articulate strategies and leading edge innovativeness, for high‐technology organisations.

The purpose of this paper is to examine the cross-sectional predictive power and the information content of volatility smirks for future stock returns using single stock options.

The study uses Fama-Macbeth procedure and portfolio approach to investigate the predictability and informativeness in a setup when options settlement style is changed from American to European.

The study reports that the volatility smirk of European style options, unlike American style options, predict the underlying cross-sectional equity returns. Firms with steepest volatility smirk underperform firms with flatter volatility smirks, by an average of 3.28 and 4.01 per cent annually for American and European options, respectively. The results are robust to the control of idiosyncratic and systematic risk factors.

The results confirm that a trader with negative information prefers to trade out-of-the-money put options. The more pronounced results of European options designate the trader’s preference to less risky European style stock options. Results are robust and signify the delay of equity market in incorporating information impounded in the volatility smirk.

Very few studies examine smirk and returns relationship and to the best of the authors’ knowledge, no study exists that examine the unique case of change in options style and its role in affecting relationship between smirk and future returns.

This paper aims to investigate informational efficiency of stock, options and credit default swap (CDS) markets. Previous research suggests that informed traders prefer equity option and CDS markets over stock markets to exploit their informational advantage. As a result, equity and credit derivative markets contribute more to price discovery compared to stock markets.

In this study, the authors investigate the dynamics behind informed investors’ trading decisions in European stock, options and CDS markets. This allows to identify the predictive explanatory power of the unique information contained in each market with respect to future stock, CDS and option market movements.

A lead-lag relation is found between the CDS market and the other markets, in which changes in CDS spreads are able to consistently forecast changes in stock prices and equity options’ implied volatilities, indicating how the fast-growing CDS market seems to play a special role in the price discovery process. Moreover, in contrast to results of US studies, the stock market is found to forecast changes in the other two markets, suggesting that investors also prefer stock market involvement to exploit their information advantages before moving to CDS and option markets. Interestingly, these patterns have only emerged during the recent financial crisis, while before the crisis, the option market was found to be of major importance in the price discovery process.

The authors are the first to study the lead-lag relationship among European stock, option and CDS markets for a large sample period covering the financial crisis.

The purpose of this paper is to test the pricing performance of Black-Scholes (B-S) model, with the volatility of the underlying estimated with the two-scale realised volatility measure (TSRV) proposed by Zhang et al. (2005).

The ex post TSRV is used as the volatility estimator to ensure efficient volatility estimation, without forecasting error. The B-S option prices, thus obtained, are compared with the market prices using four performance measures, for the options on NIFTY index, and three of its constituent stocks. The tick-by-tick data are used in this study for price comparisons.

The B-S model shows significantly negative pricing bias for all the options, which is dependent on the moneyness of the option and the volatility of the underlying.

The negative pricing bias of B-S model, despite the use of the more efficient TSRV estimate, and post facto volatility values, confirms its inadequacy. It also points towards the possible existence of volatility risk premium in the Indian options market.

The use of tick-by-tick data obviates the nonsynchronous error. TSRV, used for estimating the volatility, is a significantly improved estimate (in terms of efficiency and bias), as compared to the estimates based on closing data. The use of ex post realised volatility ensures that the forecasting error does not vitiate the test results. The sample is selected to be large and varied to ensure the robustness of the results.

How do stock prices evolve over time? The standard assumption of geometric Brownian motion, questionable as it has been right along, is even more doubtful in light of the recent stock market crash and the subsequent prices of U.S. index options. With the development of rich and deep markets in these options, it is now possible to use options prices to make inferences about the risk-neutral stochastic process governing the underlying index. We compare the ability of models including Black–Scholes, naïve volatility smile predictions of traders, constant elasticity of variance, displaced diffusion, jump diffusion, stochastic volatility, and implied binomial trees to explain otherwise identical observed option prices that differ by strike prices, times-to-expiration, or times. The latter amounts to examining predictions of future implied volatilities.

Certain naïve predictive models used by traders seem to perform best, although some academic models are not far behind. We find that the better-performing models all incorporate the negative correlation between index level and volatility. Further improvements to the models seem to require predicting the future at-the-money implied volatility. However, an “efficient markets result” makes these forecasts difficult, and improvements to the option-pricing models might then be limited.