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This paper studies the performance of commonly employed stochastic volatility and jump models in the consistent pricing of The CBOE Volatility Index (VIX) and The S&P 500 Index (SPX) options. With the existence of active markets for volatility derivatives and options on the underlying instrument, the need for models that are able to price these markets consistently has increased. Although pricing formulas for VIX and vanilla options are now available for commonly used models exhibiting stochastic volatility and/or jumps, it remains to be shown whether these are able to price both markets consistently. This paper fills this vacuum.

In particular, the Heston model, the Heston model with jumps in returns and the Heston model with simultaneous jumps in returns and variance (SVJJ) are jointly calibrated to market quotes on SPX and VIX options together with VIX futures.

The full flexibility of having jumps in both returns and volatility added to a stochastic volatility model is essential. Moreover, we find that the SVJJ model with the Feller condition imposed and calibrated jointly to SPX and VIX options fits both markets poorly. Relaxing the Feller condition in the calibration improves the performance considerably. Still, the fit is not satisfactory, and we conclude that one needs more flexibility in the model to jointly fit both option markets.

Compared to existing literature, we derive numerically simpler VIX option and futures pricing formulas in the case of the SVJ model. Moreover, the paper is the first to study the pricing performance of three widely used models to SPX options and VIX derivatives.

There is a distinct separation of price discovery from pricing power in China's sugar spot and futures markets. The purpose of this paper is to identify the reasons and provide plausible explanations for this stylized phenomenon. Therefore, the research may deepen the understandings of the operational mechanisms and internal efficiency of China's sugar spot and futures markets.

The authors analyze the historical spot and futures price time series from China's sugar spot market and China's Zhengzhou Commodity Exchange (CZCE) within a co‐integration framework.

It is found that China's sugar spot market has the pricing power, even though the futures market leads the spot market in price discovery. The phenomenon of observed separation of price discovery in spot market from pricing power in futures market may be caused by: irrational speculation in CZCE sugar futures market; oligopoly and local government politics; or the operational efficiency of the wholesale spot market, especially for its comparative advantages of information accessibility in the sugar producing areas. The results are compared with other empirical findings in many other commodities markets to obtain deeper understandings.

The paper uncovers and provides the earliest econometric evidence of the observed stylized phenomenon and also provides plausible explanations for this phenomenon.

This paper shows the limitation of the cost-of-carry model which is used for pricing the theoretical value of the KTB futures, and proposes an alternative pricing model based on the term structure of interest rates. Under the assumption of 1-factor term structure, this paper treats the theoretical price of KTB futures price as a risk-neutral expectation of payoff function at maturity and derives the approximated formula for pricing the KTB futures. As compared with our price of KTB futures using the term structure of interest rates, the conventional KOFEX price based on the cost-of-carry model tends to be overvalued as the time to maturity increases. This result is due to the difference between the futures and forward prices which is caused by treating the futures contract as the forward contract in the conventional KOFEX pricing model. In particular, this discrepancy becomes more significant when the price of underlying asset and the interest rates are negatively correlated and the time to maturity is longer. The bond futures contract is a typical example of financial instrument whose price has a negative correlation with interest rates

The purpose of this paper is to examine the pricing efficiency of the Malaysian crude palm oil (CPO) market before and after the structural break. This study uses the daily closing price of CPO and CPO futures (CPO-F) for the period ranging from June 2009 to August 2016 while taking structural breaks into account.

In this study, symmetric and asymmetric long-run relationship model are employed, such as the Johansen cointegration, VECM, TAR and M-TAR models, to examine the impact of structural breaks on the pricing efficiency of the Malaysian CPO market.

This finding establish that Malaysian CPO price is efficient before and after the structural break. The consistent efficiency of the Malaysian CPO market supports the trading of the CPO-F in Globex and the use of Malaysian CPO pricing as the reference price. This study establishes that a structural break in the Malaysian CPO price series does not affect the pricing efficiency of the market.

This study shows that using Malaysian CPO price as a reference price is sustainable even in the event of a structural break. Therefore, market participants in the Malaysian CPO market have less to worry about the CPO price as it supports the weak form of efficiency. Price deviation in the short run may not lead to arbitrage profit as transaction cost may not be covered.

This study implies that if there is distortion in the price due to shocks, both manufacturers and producers need to hedge their positions in the futures market (subject to their positions in the underlying market). By entering into the futures market, pricing is locked in advance; hence, price risk is eliminated. Such a distortion could also affect the efficiency of the CPO price, therefore this study also addresses the issue of efficiency of the local CPO market.

Previous studies on Malaysian CPO pricing efficiency did not take the effect of structural break into consideration, making it difficult for these studies to show consistency in the efficiency of the Malaysian CPO market.

Reference price is a key input in deciding product/service prices by organizations and has a significant influence on consumer purchase decisions. This study aims to provide a deeper understanding of reference pricing literature using bibliometric analysis and offers specific research questions for future research in this domain.

Using a sample of 309 articles published between 1977 and 2021, the study conducts bibliographic coupling, citation analysis, cluster analysis, content analysis, keyword analysis and a three-field plot to map the intellectual structure of reference price.

The content analysis gave seven research clusters: (1) modeling reference price, (2) consumer perceptions of price (un)fairness, (3) price framing, (4) comparative price-based promotion, (5) reference price formulation, (6) pay-what-you-want (PWYW) pricing and (7) range theory and price perceptions. The study also delineates reference price literature across several parameters like authorship, highest cited paper, most popular journal, institutions, region-wise publication trend and author-networks. The emerging research themes for future scholars working in this domain have also been highlighted.

This is the first comprehensive study to explore reference price from a bibliometric lens. The study highlights and discusses the recent themes on reference price, from both academic and managerial perspectives.

The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market.

Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market.

The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks.

This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.

Real estate developers often operate in oligopolistic environments. Pricing strategies must be made in an interactive framework that makes empirical evaluation difficult. This study appeals to economic experiments to examine how developers price their properties, especially when there is an option to market pre‐completed units. In addition, the interaction between bidding for land and pricing the end product is examined. The results indicate that competitor actions are important considerations in pricing decisions. In particular, the profit maximizing pricing strategy depends critically on being competitive, not necessarily being the most aggressive. Interestingly, pre‐completed units sell only at prices that incorporate future price expectations, and successful bids tend to precipitate more aggressive pricing. Finally, competitive bidding and pricing strategies appear to the best profit maximizing strategy.

Recent years have seen explosive growth in the use of enterprise pricing software. Pricing software contributes to business returns by improving pricing decision-making, and by providing monitoring and process control for pricing processes across the corporation. This software has developed in a number of significant ways over the past decade and continues to evolve in terms of sophistication and ability to contribute to both top- and bottom-line growth. In this paper, the authors present a brief historical context for the role that pricing software fulfills in a typical B2B corporation, and a set of predictions of future capabilities based on emerging trends.

While the classic futures pricing tool works well for capital markets that are less affected by sentiment, it needs further modification in China's case as retail investors constitute a large portion of the Chinese stock market participants. Their expectations of the rate of return are prone to emotional swings. This paper, therefore, explores the role of investor sentiment in explaining futures basis changes via the channel of implied discount rates.

Using Chinese equity market data from 2010 to 2019, the authors augment the cost-of-carry model for pricing stock index futures by incorporating the investor sentiment factor. This design allows us to estimate the basis in a better way that reflects the relationship between the underlying index price and its futures price.

The authors find strong evidence that the measure of Chinese investor sentiment drives the abnormal fluctuations in the basis of China's stock index futures. Moreover, this driving force turns out to be much less prominent for large-cap stocks, liquid contracting frequencies, regulatory loosening periods and mature markets, further verifying the sentiment argument for basis mispricing.

This study contributes to the literature by relying on investor sentiment measures to explain the persistent discount anomaly of index futures basis in China. This finding is of great importance for Chinese investors with the intention to implement arbitrage, hedging and speculation strategies.

Real estate is the last major asset class without liquid derivatives markets. The reasons for that are not fully known or understood. Therefore, the purpose of this paper is to better understand the main factors that influence the propensity of commercial real estate investors in the UK to employ property derivatives.

The research methodology that was chosen for this research is grounded theory which, in its original form, goes back to Glaser and Strauss (1967). A total of 43 interviews were conducted with 46 real estate professionals in the UK from property investment management firms (investing directly or indirectly in real estate), multi-asset management firms, real estate investment trusts, banks, and brokerage and advisory firms, among others.

The research results show 29 factors that influence the propensity of direct and indirect real estate investors in the UK to employ property derivatives. Out of the 29 factors, the current research identified 12 factors with high-explanatory power, 6 with a contributing role and 11 with low explanatory power. Moreover, factors previously discussed in the literature are tested and assessed as to their explanatory power. The focus of this paper is on those factors with high-explanatory power. From the research data, three main reasons have been identified as the sources of investor reluctance to trade in property derivatives. The first and main reason is related to a mismatch between motivations of property investment managers and what can be achieved with the instruments. The second reason, which ties in with the first one, is a general misunderstanding as to the right pricing technique of property derivatives. Finally, the third reason is a general lack of hedging demand from the investor base owing to the long investment horizons through market cycles.

The research contributes to the literature on property derivatives in various ways. First, it extends the literature on market hurdles in property derivatives markets by testing and extending the hurdles that were proposed previously. Second, the research shows that the existing pricing models need to be extended in order to account for the risk perception of practitioners and their concerns with regard to liquidity levels.

For both theory and practice, the research has shown some limitations in using property derivatives for purposes such as creating index exposure or hedging. Another contribution, in this case to practice, is that this study provides a clearer picture as to the reasons that keep property investment managers away from using property derivatives.

The research results indicate that liquidity per se is not a universal remedy for the problems in the market. In addition to the need for improving the understanding of the pricing mechanism, practitioners should give more thought to the notion of real estate market risk and the commensurate returns that can reasonably be expected when they take or reduce it. This implies that property index futures currently do not price like those on any other investable asset class.