Options Market Research Articles

Sensitivity-based Conditional Value at Risk (SCVaR): An efficient measurement of credit exposure for options

Counterparty Credit Risk (CCR) has received extensive attention in the Over-The-Counter (OTC) derivative markets. This paper proposes a credit risk exposure measurement for European options: Sensitivity-based Conditional Value at Risk (SCVaR), which can cover the future credit risk by a stable sensitivity weight, and improve the accuracy of risk tracking in most cases. Compared with VaR and CVaR, SCVaR has superiority in extensibility, computational efficiency and stability. We further derive the tendency and upper bound of sensitivity weights, consequently obtaining a practical value of price weight for long-term stability. The simulation and empirical analysis in the Chinese options market also show good applicability of SCVaR. The risk exposures are efficiently covered during periods of fluctuation, which alleviates the procyclicality to some extent. These results provide a useful guidance for the development of financial risk management.

Retailer's decoy strategy versus consumers' reference price effect in a retailer-Stackelberg supply chain

Decoy strategy for bundling is an important marketing option because it can reflect the behavior resulting from consumers' reference price effect. This paper develops a game-theoretic model of a dyadic supply chain to study the joint decisions on pricing and decoy strategies in the presence of consumers' reference price effect. The retailer chooses one of the decoy strategies (phantom decoy-mixed bundling, decoy-mixed bundling) and selling prices to maximize her profit. Our study shows that: under both decoy strategies, the retailer and the manufacturer benefit from consumers' low reference price effect; however, the high reference price effect hurts their profits.

An empirical study on the characterization of implied volatility and pricing in the Chinese option market

This study investigates the problem of pricing model selection for SSE 50 ETF options in the Chinese market. Numerous studies identified a volatility smile in the implied volatility of options; thus, the BS model (BS-HV model), based on the assumption of constant volatility, was criticized. Stochastic volatility models, represented by the Heston model, have become popular owing to their ability to reflect non-constant volatility. This ability inspired us to address the controversial BS-HV model issue by combining the BS formulation with the method of generating the implied volatility surface using TPS interpolation (BS-IV model). In this study, we evaluate the pricing ability of the model from three perspectives: pricing error, volatility portrayal, and price trend prediction. We find that though the historical volatility of the BS-HV model cannot reflect the implicit information of the options market price, the longer the interval of its moving average, the smaller the pricing error of the test set. The BS-IV model can accurately predict the price trend but has the largest pricing error. The Heston model demonstrates average capability in the three aspects of volatility. Therefore, the merits of each model should be combined when pricing options, and the long-range BS-HV model should be used as a reference when pursuing small errors. The BS-IV model can be combined with the previous day's options closing price to obtain a reasonable options price if the trend prediction is important.

On the impact of different electricity markets on the operation of a network of microgrids in remote areas

The development of distributed energy generation, often aggregated to form micro- or nano- grids based on power generation from renewable sources, or small-size generators make it easier to electrify remote and isolated areas. In addition to privately owned generation capacities, it could be feasible and profitable to sell/buy the excess energy to/from the closest neighbors, giving rise to “peer-to-peer” forms of energy trades. Despite that peer-to-peer trading has been widely discussed in the literature, the organization of isolated markets with limited small capacities is still a subject of study and discussion in the power community. In this paper, we evaluate the functioning of an alternative shorter market scheme characterized by only one bidding period, closer to the delivery time, which is convenient as it profits from more accurate forecasts. Then, the final balancing is performed internally within the same microgrids. Feasibility and cost-effectiveness of the proposed market is assessed for an isolated cluster of microgrids and compared with the currently operating markets, modelled as a day-ahead and real-time balancing markets. Two-stages stochastic optimization is implemented to compare the two market options. For this purpose, a grid of five villages is considered as a case-study and simulations are performed under two possible sets of installed capacities, including both diesel generators and renewable energy sources, to operate in either a dependent or a self-sufficient regime. Simulation results show that both markets succeed in supplying the required power demand, but the proposed simpler type of market may also be cost effective with a cost reduction up to 20%.

Heterogeneous trading of option implied volatility

ABSTRACT We investigate the equilibrium properties of the implied volatility in the option market within the framework of a dynamic heterogeneous agent model. Fundamentalists and chartists are incorporated into our heterogeneous agent model, and they can change their types based on their previous performance. We show that the stability conditions of the model mainly depend on the relationship between the mean-reverted coefficients of fundamentalists and the extrapolation coefficients of chartists. The empirical results show that the fundamentalists and chartists of volatility coexist in the option market. However, during the market panic, especially before and after the 2008 financial crisis, chartists dominate the market.

Representative Bias and Pairs Trade: Evidence From S&P 500 and Russell 2000 Indexes

This study tests whether pairs trade conditional on representative bias in the options and stock markets leads to abnormal returns. While previous literature on representativeness focuses on a single index, S&P 500 and Russell 2000 indexes are used to examine the extent to which representative bias arises due to a pattern of similar information shock in the three analyzed periods. The empirical results of the options market lend little support to the representativeness anomalies because Russell 2000 index, relative to S&P 500 index, does not adjust to a sequence of information shocks in the 2020 economic downturn inflicted by the coronavirus pandemic, despite the asymmetrical responsiveness to information shock over the sample period of 2004 to 2020, and during the 2008 global financial crisis. However, the empirical findings of the stock market verify, to some degree, the existence of representative bias during the sample period of 2004 to 2020. To examine whether asymmetrical representativeness in the options market or representativeness in the stock market yields abnormal returns, pairs trade is designed to exploit riskless profits via buying S&P 500 index and selling Russell 2000 index. Based on the Fama and French three-factor model, the empirical evidence is in support of market efficiency because the pairs trading strategy cannot generate positive abnormal returns in both options and stock markets.

Assessing options for cannabis law reform: A Multi-Criteria Decision Analysis (MCDA) with stakeholders in New Zealand.

A number of jurisdictions are considering or implementing different options for cannabis law reform, including New Zealand. Multi-Criteria Decision Analysis (MCDA) helps facilitate the resolution of complex policy decisions by breaking them down into key criteria and drawing on the combined knowledge of experts from various backgrounds. To rank cannabis law reform options by facilitating expert stakeholders to express preferences for projected reform outcomes using MCDA. A group of cannabis policy experts projected the outcomes of eight cannabis policy options (i.e., prohibition, decriminalization, social clubs, government monopoly, not-for-profit trusts, strict regulation, light regulation, and unrestricted market) based on five criteria (i.e., health and social harm, illegal market size, arrests, tax income, treatment services). A facilitated workshop of 42 key national stakeholders expressed preferences for different reform outcomes and doing so generated relative weights for each criterion and level. The resulting weights were then used to rank the eight policy options. The relative weighting of the criteria were: "reducing health and social harm" (46%), "reducing arrests" (31%), "reducing the illegal market" (13%), "expanding treatment" (8%) and "earning tax" (2%). The top ranked reform options were: "government monopoly" (81%), "not-for-profit" (73%) and "strict market regulation" (65%). These three received higher scores due to their projected lower impact on health and social harm, medium reduction in arrests, and medium reduction in the illegal market. The "lightly regulated market" option scored lower largely due its projected greater increase in health and social harm. "Prohibition" ranked lowest due to its lack of impact on reducing the number of arrests or size of the illegal market. Strictly regulated legal market options were ranked higher than both the current prohibition, and alternatively, more lightly regulated legal market options, as they were projected to minimize health and social harms while substantially reducing arrests and the illegal market.

Relationship among Covid-19, stock price and green finance markets pragmatic evidence from volatility dynamics

This paper aims to map the effects of the rapid spread of coronavirus (COVID-19) on stock price dynamics and markets selections based on data from March 22, 2021, to September 20, 2021. Options markets from 2020 to 2021, multiple kinds of critical COVID-19 data. The proposed hypothetical modal considers investors' behavior and errors caused by the level of sentiment elicited for stock markets and green categories. This paper another element (1) Covid-19 (2) feeling, and (3) networking websites, for example, Covid-19 influence on the green size, green direction, and impact on securities prices. This paper used google search data work also creates a proxy for emotions dependent on five main categories of Data: (1) Covid-19, pandemic effect (2) markets, (3) lockdown, (4) banking and government aid. Moreover, this paper Use (a) VIX index sentiment, (b) S& The P 500 index is a measure of how well a sentiment (c) Sentiment in the S& amp;P 500 bank index. The Projected to empirical Finding follow First Level during the Covid-19, effect on jump volatility, and variability level in persistence on the green stock market exceeds that on the options market. VIX index green financial level increases with the COVID green financial level increase with the COVID-19 market index, index banking index and lockdown index. Therefore, it concluded the Share market statistic, COVID-19 benchmark, and long-run volatility. The fraction of the leap government assistance reduced. We find that the outbreak of the Pandemic of COVID-19 effects of the S&P 500 Index and S&P 500 Banks Index decrease with highest values (39%) but only after a surge in volatility covid-19 Pandemic. These results comply with our model's expectations.

Performance of a Balanced Portfolio With Active Covered-Call Strategies

This study investigates the performance of local and global investments with and without covered call option strategies over the period from January 2000 to December 2015. The Covered Call Strategy (CCS) is a common return enhancing strategy used in portfolio management. The strategy consists of simultaneously holding a long position in an asset and writing call options on that asset. The local investment are on the top twenty stocks from Australian market while the global investment is an international balanced portfolio. For covered call strategies, market option data from Australian Stock Exchange is used. The results show that under some constraints, using covered call strategies in general improves the risk-adjusted returns.

Implied Volatility Spread and Stock Mispricing

Stocks can be mispriced for at least two reasons: value-relevant information is not timely incorporated or investor sentiment can induce mispricing. Using the mispricing measure proposed by Stambaugh, Yu, and Yuan (2015), we show that informed trading in the options market, proxied by the implied volatility spread, can substantially alleviate stock mispricing. Higher implied volatility spread reliably predicts subsequently lower stock mispricing after controlling for an array of economic variables including firm size, illiquidity, idiosyncratic volatility, institutional ownership, and investor’s divergence of opinions. In addition, this effect is more pronounced when the options trading volume is higher, consistent with the notion that higher options trading volume provides better camouflage for informed trading in the spirit of Kyle (1985). Our findings highlight the importance of information incorporation to reduce asset mispricing. We further show that a self-financing monthly portfolio that goes long on most underpriced stocks and short on most overpriced stocks when the implied volatility spread is the lowest yields statistically and economically significant abnormal returns.

A New Homotopy Transformation Method for Solving the Fuzzy Fractional Black–Scholes European Option Pricing Equations under the Concept of Granular Differentiability

The Black–Scholes option pricing model is one of the most significant achievements in modern investment science. However, many factors are constantly fluctuating in the actual financial market option pricing, such as risk-free interest rate, stock price, option underlying price, and security price volatility may be inaccurate in the real world. Therefore, it is of great practical significance to study the fractional fuzzy option pricing model. In this paper, we proposed a reliable approximation method, the Elzaki transform homotopy perturbation method (ETHPM) based on granular differentiability, to solve the fuzzy time-fractional Black–Scholes European option pricing equations. Firstly, the fuzzy function is converted to a real number function based on the horizontal membership function (HMF). Secondly, the specific steps of the ETHPM are given to solve the fuzzy time-fractional Black–Scholes European option pricing equations. Finally, some examples demonstrate that the new approach is simple, efficient, and accurate. In addition, the fuzzy approximation solutions have been visualized at the end of this paper.

The Generalized Gamma Distribution as a Useful RND under Heston’s Stochastic Volatility Model

We present the Generalized Gamma (GG) distribution as a possible risk neutral distribution (RND) for modeling European options prices under Heston’s stochastic volatility (SV) model. We demonstrate that under a particular reparametrization, this distribution, which is a member of the scale-parameter family of distributions with the mean being the forward spot price, satisfies Heston’s solution and hence could be used for the direct risk-neutral valuation of the option price under Heston’s SV model. Indeed, this distribution is especially useful in situations in which the spot’s price follows a negatively skewed distribution for which Black–Scholes-based (i.e., the log-normal distribution) modeling is largely inapt. We illustrate the applicability of the GG distribution as an RND by modeling market option data on three large market-index exchange-traded funds (ETF), namely the SPY, IWM and QQQ as well as on the TLT (an ETF that tracks an index of long-term US Treasury bonds). As of the writing of this paper (August 2021), the option chain of each of the three market-index ETFs shows a pronounced skew of their volatility ‘smile’, which indicates a likely distortion in the Black–Scholes modeling of such option data. Reflective of entirely different market expectations, this distortion in the volatility ‘smile’ appears not to exist in the TLT option data. We provide a thorough modeling of the option data we have on each ETF (with the 15 October 2021 expiration) based on the GG distribution and compare it to the option pricing and RND modeling obtained directly from a well-calibrated Heston’s SV model (both theoretically and also empirically, using Monte Carlo simulations of the spot’s price). All three market-index ETFs exhibited negatively skewed distributions, which are well-matched with those derived under the GG distribution as RND. The inadequacy of the Black–Scholes modeling in such instances, which involves negatively skewed distribution, is further illustrated by its impact on the hedging factor, delta, and the immediate implications to the retail trader. Similarly, the closely related Inverse Generalized Gamma distribution (IGG) is also proposed as a possible RND for Heston’s SV model in situations involving positively skewed distribution. In all, utilizing the Generalized Gamma distributions as possible RNDs for direct option valuations under the Heston’s SV is seen as particularly useful to the retail traders who do not have the numerical tools or the know-how to fine-calibrate this SV model.

MARKETWIDE LIQUIDITY AND OPTIONS MARKET

In this paper, we study the relationship between marketwide liquidity and options market. Using the Chicago Board Options Exchange (CBOE) Volatility Index, VIX as a measure of overall value of the S&P 500 (SPX) options, and the CBOE SKEW Index as a measure of market crash risk premium in the options market, we study the relation among marketwide liquidity, VIX and SKEW. Empirical results show that higher the marketwide liquidity, less expensive the options and the less likely options traders anticipate a market crash.

Market Manipulation around Seasoned Equity Offerings: Evidence Prior to the Global Financial Crisis of 2007–2009

Since the adoption of the SEC’s Rule 10b-21 in 1988, many researchers have been concerned over the effectiveness of short sales constraints in preventing manipulative trading in the derivatives market. We analyze whether options can be used as synthetic short sale instruments to manipulate stock prices before a seasoned equity offer. Due to the existence of strict short sales constraints in the equity market and market makers’ anticipation of manipulative trading, it would be very costly for a manipulator to drive stock prices down artificially either by short selling in the equity market or by using synthetic short sales in the options market. Using a sample of 237 firms that issued SEOs on the NYSE and had options listed on any U.S. options exchange from April 2002 to December 2004, we show that potential manipulators in the options market tend to use put options as a trading vehicle during the SEO’s pre-offer period. The results of our empirical tests support the predictions of our model.

Delta-hedging demand and intraday momentum: Evidence from China

This paper reveals that the rest-of-day return has positively significant prediction on the last 30-min return in the Chinese SSE 50 exchange-traded fund market. Its predictive power is economically significant and will decay in the next three days. Moreover, it reveals the relationship between intraday return prediction and short gamma hedging demand from option market makers, demonstrating that intraday hedging could be postponed till the end of a trading day. Intraday momentum caused by rebalancing traders and information investors cannot be completely offset by option market makers on days with positive net gamma exposure. Our results are robust to alternative exchange-traded fund index option and its underlying asset.

Informed trading of out‐of‐the‐money options and market efficiency

AbstractWe examine the stock return predictability of out‐of‐the‐money (OTM) put‐to‐call trading volume ratio (OTMPC). Our numerical analysis predicts that in the US equity option market, informed investors rarely write OTM options because the leverage effect is not sufficient to compensate for transaction costs. OTMPC thus captures the informed investors’ OTM put purchase volume relative to their OTM call purchase volume. After controlling for existing empirical proxies for informed option trading, we find that OTMPC predicts future stock returns and corporate news. The return predictability offers implementable stock portfolio strategies. Our findings suggest that market inefficiency can emerge from uninformed investors’ limited knowledge about how transaction costs influence the trading strategies of informed investors.

The information content of ETF options

We examine the information content of China's Shanghai Stock Exchange (SSE) 50 ETF options introduced in 2015. Trading volume and implied volatilities of calls versus puts differ markedly: trading volume is consistently higher for calls, and implied volatility is higher for puts. Put-call volume and implied volatility ratios are not good predictors of future SSE 50 returns. Implied volatility follows a right-skewed smirk across strike prices, indicating a tendency among option traders to turn bullish and expect the stock market to recover from the June 2015 market crash. The options market dominates the price discovery process, with an average information leadership share of 67%. Our price discovery results persist during the COVID outbreak.

Arbitrage Opportunities in the Options Market: A Study of the Indian Index Options

The objective of this paper is to find out whether the put-call parity relationship holds in case of index options in the Indian stock market. The index which has been chosen as the underlying asset is NSE Nifty. This paper further aims at finding out different factors responsible for the violation of put-call parity relationship, if any.

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.