Options Market Research Articles

The volatility risk premium in the oil market

This article provides a comprehensive analysis of the volatility risk premium (VRP) in the oil market. We approach the problem from the practitioner’s perspective as an investment strategy that sells and delta-hedges oil options, paying particular attention to the strategy’s risk-adjusted returns and its drawdown characteristics. The results are differentiated across options with different moneyness and expirations and presented in the form of VRP smile and VRP term structure. Strategy results are analyzed using alternative delta-hedging techniques that vary hedging frequencies, hedging thresholds, and volatilities used to calculate options’ delta. We discuss the performance under different regimes and highlight the structural break driven by the changing behavior among main participants in the oil options market.

Trading restriction and the choice for derivatives

In this paper, we explore how trading restriction in terms of significantly increased cost for futures contracts impacts trading activities of futures and options written on the same underlying asset. In particular, we are interested in examining whether the two derivatives markets complement each other or are substitutes. Using daily data of futures and options written on the Shanghai Stock Exchange 50 Exchange Traded Open-end index from April 2015 to October 2019, we show that the regulatory trading restriction substantially reduces the trading volume and open interest in the futures market and increases those in the options market. Furthermore, the gradual relaxation of the restriction pushes up trading activities in the futures market, but does not necessarily reduce those in the options market. Hence, our results suggest that the two derivatives markets complement each other, which advance our understanding of investor behaviour and shed new light on how best policies can be designed to improve market quality.

Market Options for Energy-flexible Industrial Consumers

It is widely accepted that industrial consumers can contribute to the goal of a cost-efficient energy sector by offering energy flexibility. The concrete and conscious actions on industrial processes ending up in a variety of consumption are named in literature “energy flexibility measures”. From the consumers’ point of view, the question is where the locally realizable energy flexibility measures can be offered with the highest cost reduction or profit. The identification of the most promising market segments or tariff schemes for the commercialization of energy flexibility measures, defined as “market options”, is not a trivial activity due to the complex regulatory framework that characterizes the energy market. This paper aims at introducing a standard definition of market options that supports the energy-flexible customer to evaluate where the energy flexibility can be commercialized without specific knowledge of the energy market regulation. The definition is applied to the German energy market and the market options are identified. Through a price trend analysis, the market options with the highest potential for cost reduction or profit are investigated. The results show that in the German market consumers have the highest chances to reduce their energy supply costs through the market options related to network charges and energy-only market.

Implied Volatility Changes and Corporate Bond Returns

Corporate bonds with large increases in implied volatility over the past month underperform those with large decreases in implied volatility by 0.6% per month. In contrast to existing studies that show implied volatility changes carry information about fundamental news, our evidence suggests that implied volatility changes contain information about uncertainty shocks to the firm. Our results are consistent with the notion that informed traders with new information about firm risk prefer to trade in the option market and the corporate bond market underreacts to this information. This paper was accepted by Haoxiang Zhu, finance. Funding: We thank the Canadian Derivatives Institute for financial support. J. Cao and X. Zhan acknowledge generous financial support of the Research Grant Council of the Hong Kong Special Administrative Region, China [Grants GRF 14501720, 14500919]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4379 .

Why are the prices of European‐style derivatives greater than the prices of American‐style derivatives?

AbstractThe prices of European‐style derivative warrants in Hong Kong are generally higher than those of identical American‐style options. We show that liquidity differences have strong explanatory power for this overpricing behavior, especially for low moneyness and long‐term derivatives. Other causative factors include counterparty credit risk, investor preference, information asymmetry, volatility discovery, exercise style, market makers' behavior, and investor sentiment. We also find a big gap in market‐wide liquidity between the two markets. Specifically, lower liquidity results in the weaker efficiency of the options market compared with the derivative warrants market.

Options trading prior to takeover rumors

Purpose In this paper, the authors examine options trading in firms that soon become rumored takeover targets. This study also examines whether measures of informed trading can predict target returns (upon rumor announcement and over the post-rumor period) and/or predict which rumors lead to bids. The authors further assess whether the informed trading they observe is more prevalent in the options market or the equity market.Design/methodology/approach This study calculates abnormal options volume using a market-model approach that accounts for different attributes of options trading. The authors construct a control sample and compare equity options trading of firms in their sample with that of the control sample. In addition, the authors fit a series of regressions to examine whether pre-rumor abnormal options trading can predict rumor accuracy in a multivariate setting.Findings The authors find that the volume of options traded is abnormally high over the pre-rumor period while the direction of option trades (abnormal call volume minus abnormal put volume) prior to takeover rumors predicts forthcoming takeover announcements, rumor date target firm returns and post-rumor target firm returns. The results are robust when controlling for publicly available information, when using a control sample, and when using alternative measures of informed trading.Originality/value This study is the first to provide evidence of informed options trading prior to a broad sample of takeover rumors. In addition, this study contributes to the literature on takeover predictability and profitability by showing that various pre-rumor measures of informed options trading significantly predict bid announcements. The authors also contributes to the literature on price discovery by providing evidence that informed investors are more likely to trade in the options market than in the equity market during the pre-event period.

Process-to-market matrix mapping: A multi-criteria evaluation framework for industrial processes’ electricity market participation feasibility

Industrial consumers have a high potential to directly participate in short-term electricity markets to provide flexibility to the electricity system, particularly due to their large electricity consumption and accurate control of electricity-consuming processes. However, the different market participation options available in a deregulated electricity market context make participation feasibility unclear, as each (sub)market option has different market regulations. To address this issue, this paper proposes a process-to-market matrix mapping framework to evaluate the most feasible electricity (sub)markets for a given industrial process based on a set of techno-regulatory criteria. There are three stages in this framework: at stage 1, the properties of the industrial consumer and the market options are described in terms of standardised criteria; at stage 2, a matrix is developed to link consumer flexibility criteria (horizontal dimension of the matrix) to the relevant market criteria (vertical dimension); at stage 3, a scoring system is applied to evaluate the participation barrier level for each criterion link in the matrix. This paper uses the Danish electricity (sub)markets to illustrate the evaluation framework, and takes an industrial greenhouse, a cement mill and a cooling house as industrial process case studies to implement the developed method. Results show the main participation barriers, both from a market regulation and an industrial consumer perspective. From these, it appears that the type of industrial process significantly influences the choice of (sub)market to participate in. Barriers can be minimised by choosing market options with regulations better aligned with the consumer’s flexibility criteria. The importance of flexibility at the organisational level for market participation feasibility is also underlined. The developed framework provides a systematic method to evaluate the market participation feasibility, which can be used as a decision support tool for market participation and to overcome identified techno-regulatory barriers.

Design and Application of Financial Market Option Pricing System Based on High-Performance Computing and Deep Reinforcement Learning

The option pricing estimation of financial market can be transformed into the calculation of high-dimensional integrals. In order to obtain the actual price, option pricing system can only rely on modern numerical methods; on the other hand, the improvement of calculation methods and technologies has also shifted the focus of design and application of option pricing system from a strict closed model to a less advanced but computationally intensive calculation. High-performance computing can establish a reasonable analysis model, realistically simulate the effects of various designed performance and parameters, and provide technical support for a large number of fast numerical calculations and simulations. Deep reinforcement learning can obtain a description of empirical knowledge through the learning of historical information and use the acquired experience to deal with future problems, which can well solve classification problems, regression problems, and optimization problems. Therefore, based on summarizing and analyzing previous research results, this paper expounds the current research status and significance of the design and application of financial market option pricing systems, elaborates the development background, current status, and future challenges of high-performance computing and deep reinforcement learning, introduces the methods and principles of high-performance computing platform and deep reinforcement learning algorithm, conducts no-arbitrage pricing model design, performs risk-neutral pricing model design, discusses the design of finance market option pricing system based on high-performance computing and deep reinforcement learning, analyzes the financial market option pricing considering random interest rates, implements financial market option pricing considering transaction costs, explores the application of financial market option pricing system based on high-performance computing and deep reinforcement learning, and finally carries out empirical experiment and its result analysis. The study results show that the financial market option pricing system based on high-performance computing and deep reinforcement learning records the basic information of high-performance computer system users and option pricing information in the form of relational data in a relational database. The financial market option pricing system describes the state of the controller and the upcoming option pricing situation. The system’s initialization uses multiple arrays from a stochastic strategy to initialize option pricing and evaluation buffers, which uniformly selects an option pricing from the initial option pricing set in each cycle. The study results of this paper provide a reference for further researches on the design and application of financial market option pricing system based on high-performance computing and deep reinforcement learning.

The impact of option hedging on the spot market volatility

We theoretically model and empirically quantify the feedback effect of delta hedging for the spot market volatility of the forex market. We start from an economy with two types of traders, an aggregated option market maker (OMM) and an aggregated option market taker (OMT), whose exposures reflect the total outstanding positions of all option traders in the market. A different hedge ratio of the OMM and OMT leads to a net delta hedge activity, which introduces market friction. We represent this friction by a simple linear permanent impact model. This approach allows us to derive the dependence of the spot market volatility on the gamma exposure of the traders. Our theoretical model shows that the spot market volatility is increased (decreased) by a negative (positive) gamma exposure of the OMM, whereby the amount of the increase depends on the net delta hedge amount executed in the spot market. To empirically test this model, we first reconstruct the aggregated OMM’s gamma exposure by using trade repository data and find that it is negative. The empirical analysis performed over the period from 21st October 2017 to 30th June 2018 using our reconstructed OMM data then strongly supports our theoretical model: The gamma exposure of the OMM turns out to be highly significant for the spot market volatility and, as expected, the spot market volatility is increased with the OMM’s short gamma exposure. Quantitatively, a negative gamma exposure of the OMM of approximately −1000 billion USD (which is around what we observe from our reconstructed OMM data) leads to an absolute increase in volatility of 0.7% in EURUSD and 0.9% in USDJPY.

Are price limits cooling off agricultural futures markets?

AbstractIn the past few years, the lean hog and live cattle futures markets have experienced significantly heightened volatility and frequent limit moves. In this paper, we study whether price limits help resolve uncertainty and facilitate liquidity provision in the two markets and how they affect trading in the limit‐free options market. In contrast to previous literature that is based on daily data, we use intraday futures and options data from 2014 to 2019 that allows for a better characterization of market behavior around limit moves. Consistent with microstructure theories, we find that price limits neither reduce volatility nor improve liquidity. Instead, they add to the high uncertainty that precedes the limit move, leading to significantly higher volatility and lower liquidity when trading resumes. Further, contrary to the notion that trading migrates to the limit‐free options market, options volume drops and liquidity drains during limit moves. The options‐implied futures price is only a biased, inefficient, and highly noisy estimate of the equilibrium futures price on locked‐limit days. Overall, the findings suggest that rather than allowing the markets to cool off, price limits adversely affect market quality in presence of large price movements.

Investment horizon and option market activity

AbstractThis paper uses a unique data set of institutional investors’ equity and equity option holdings to investigate how their investment horizons are associated with option trading and its information content. Firms with more short‐term investors have more active option markets relative to stock markets. Also, they have a greater proportion of option trading volume ascribed to high‐leveraged contracts. Furthermore, both abnormal option trading before earnings announcements and informativeness of option market statistics are more pronounced when short‐term investors predominate. These findings suggest that short‐term institutions trade leveraged contracts actively to exploit information, thus effecting price discovery in option markets.

On the utility maximization of the discrepancy between a perceived and market implied risk neutral distribution

A method is developed to determine the portfolio that maximizes the expected utility of an agent that trades the difference between a perceived future price distribution of an asset and the associated market implied risk neutral density. Exact results to construct and price such a portfolio are presented under the assumption that the underlying asset price evolves according to a geometric Brownian motion. Integer programming optimization techniques are applied to the general case where one first calibrates the asset price risk neutral density directly from option market data using Gatheral’s SVI parameterization. Several numerical examples approximating the optimal payoff function with liquid securities are given.

The Correlation Risk Premium: International Evidence

In this paper we carry out a cross-country analysis of the correlation risk premium. We examine the statistical properties of the implied and realized correlation in European equity markets and relate the resulting premium to US equity market correlation risk and a global correlation risk premium. We find evidence of strong co-movement of correlation risk premiums in European and US equity markets. Our results support the existence of a strong empirical relationship between the global correlation risk premium and international equity market option returns. We document the dependence of the correlation risk premium on macroeconomic uncertainty and related variables.

Net Buying Pressure and Informed Trading in the Options Market: Evidence from Earnings Announcements

By employing the modified net buying pressure as a measure of informed option trading, this study tested whether option trading around quarterly earnings announcements is either directionally motivated and/or volatility motivated. We found evidence that is consistent with the idea that option investors have private information prior to positive earnings announcements and use at-the-money options to exploit their informational advantage. In the post-event period, however, informed option investors trade by using deep-out-of-the-money and out-of-the-money options. We documented limited evidence on the volatility-motivated option trading, and our results suggest that this type of option trading could be motivated by hedging purposes only.

Volatility and Asymmetric Effect of Crude Oil Options on Crude Oil Market: Empirical Evidence from China

Based on daily data, this paper uses the GARCH model family to empirically study the impact of crude oil option launch on the volatility and asymmetric leverage effect of crude oil futures market variables (futures price, trading volume, open interest, inventory).The conclusion is as follows: Regardless of the impact of the COVID-19, the launch of crude oil options has a long-term volatility impact on price, open interest and inventory volatility in addition to trading volume, and only has a long-term volatility impact on prices under the influence of COVID-19.Regardless of whether the impact of COVID-19 is considered, the launch of crude oil options has intensified the volatility of price yield, reduced the volatility of trading volume, open interest and inventory, and Considering COVID-19 influence, the volatility of crude oil futures prices yield has weakened, and the degree of weakening of trading volume fluctuations has decreased. Regardless of the impact of COVID-19, crude oil futures prices, trading volume, open interest, and inventory volatility all have negative asymmetric leverage effects, and the impact of bearish news is greater than the impact of bullish news. Considering the introduction of crude oil options under the influence of COVID-19: the fluctuation of crude oil futures prices yield has changed from negative asymmetry to positive asymmetric leverage effect. The asymmetric leverage effect of negative fluctuations in crude oil futures trading volume becomes smaller and decreases less than the leverage effect without considering the impact of COVID-19 after the listing of crude oil options. Fluctuations in open interest and inventory have weakened the negative asymmetric leverage effect after the launch of crude oil options. Finally, relevant policy suggestions are given for the construction of the domestic options market.

Is Risk-Neutral Skewness an Indicator of Downside Risk? Evidence from Tail Risk Taking of Hedge Funds

Research suggests that systematic tail risk affects the cross-sectional variation in hedge fund returns. High tail risk hedge funds are known to be exposed to higher-moment risks; they sell market volatility risk and buy market skewness risk. The relationship between a tail risk strategy and a market skewness factor is expected to be positive, but I find it to be negative. Using equity-oriented hedge fund return data, I find that equity market skewness risk explains a major part of variation in hedge funds’ tail risk. My results suggest that the observed negative relationship relates to the problem of price pressure associated with “crowded trades” of mutual funds. In particular, in times when investors shift their funds from bond to equity mutual funds, short selling in the index options market induces a negative relationship between risk-neutral market skewness and returns. Accordingly, the long leg of the tail risk strategy appears to be negatively exposed to market skewness risk, which is in contrast to the usual interpretation of option-implied skewness as an indicator of downside risk.

How Do Options Add Value? Evidence from the Convertible Bond Market

Abstract This paper studies the value relevance of the options market by focusing on convertible bond pricing. Pricing convertible bonds requires essentially the same set of information necessary to price options. Using a regression discontinuity design based on minimum stock price requirements for option listings, we find that the availability of stock options helps issuers attract more convertible bond buyers and reduces convertible issuers’ cost of financing. Our results highlight that the availability of individual stock options can add value to security issuers.

The price of COVID-19-induced uncertainty in the options market

This paper investigates the pricing of uncertainty associated with the COVID-19 responses for 28 countries/regions in 2020. We find that such uncertainty is priced in the equity options market. Specifically, there is a price premium for options that provide protection to hedge against price risk, variance risk, and tail risk caused by a variety of World Health Organization (WHO) announcements and the lockdown announcements from governments on COVID-19. Moreover, such options tend to be more expensive when the governments place stricter restrictions.

Improved Dividend Estimation from Intraday Quotes.

Liquid financial markets, such as the options market of the S&P 500 index, create vast amounts of data every day, i.e., so-called intraday data. However, this highly granular data is often reduced to single-time when used to estimate financial quantities. This under-utilization of the data may reduce the quality of the estimates. In this paper, we study the impacts on estimation quality when using intraday data to estimate dividends. The methodology is based on earlier linear regression (ordinary least squares) estimates, which have been adapted to intraday data. Further, the method is also generalized in two aspects. First, the dividends are expressed as present values of future dividends rather than dividend yields. Second, to account for heteroscedasticity, the estimation methodology was formulated as a weighted least squares, where the weights are determined from the market data. This method is compared with a traditional method on out-of-sample S&P 500 European options market data. The results show that estimations based on intraday data have, with statistical significance, a higher quality than the corresponding single-times estimates. Additionally, the two generalizations of the methodology are shown to improve the estimation quality further.

Information contents of intraday SSE 50 ETF options trades

AbstractWe examine the intraday price discovery role of the Shanghai Stock Exchange 50 exchange‐traded fund options using transaction‐level data. Contemporaneous options trading volumes have significant and permanent price impacts on futures returns, implying that some options traders are informed. The permanent price impacts of large options trades are much greater than those of small trades. We also find that liquidity changes due to regulatory policies affect the options market's informational role. Transactions generally convey less information during special trading sessions, including post‐break and closing sessions, perhaps because informed investors prefer to hide behind high liquidity.