The emotional cost-of-carry: Chinese investor sentiment and equity index futures basis

PurposeWhile 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.Design/methodology/approachUsing 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.FindingsThe 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.Originality/valueThis 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.

On Pricing Unconventional Prepaid Forward Contracts: Evidence from en primeur Fine Wine

An en primeur agreement is an unconventional forward contract. In this article, we provide a new conceptual framework for analyzing the properties of en primeur prices based on the cost of carry approach. The results, based upon Bayesian modeling, indicate that the cost of carry increases up to 0.9598 when en primeur and bottled wines are traded in parallel. Moreover, our findings confirm that price dispersion around the mean value is greater for en primeur wines (22.42%) than for standard bottled wines (8.2%) traded after the sale of en primeur wines has ended. (JEL Classifications: G12, G15, L66, Q02)

Valuing and Analyzing Fixed Income Derivatives

Derivatives valuation is based on the key principle of no-arbitrage pricing. This chapter presents valuation models for various types of fixed income derivatives, including forward rate agreements (FRAs), interest rate swaps, Eurodollar and Treasury bond futures, bond options, caps and floors, swaptions, and options on interest rate futures. Following the financial crisis that began in the summer of 2007, major changes occurred in the practice of fixed income derivatives valuation, particularly regarding the adoption of overnight indexed swaps (OIS) as a source of the risk-free rate. This chapter shows how OIS discounting is implemented in FRA pricing and swap valuation. Traditional approaches such as cost of carry valuation in futures pricing are illustrated. With respect to option valuation, this chapter explains the risk-neutral pricing approach as well as closed-form solutions such as the Black model. The chapter also provides numeric examples to illustrate the practical use of the presented models and formulas.

Analyzing the Arbitrage Opportunities and their Determinants in Deliverable Future Contracts: Evidence from Pakistan

This study explores the arbitrage opportunities in Deliverable Future Contracts (DFC) due to mispricing and the factors affecting it. We use the cost of carry model to calculate the fair prices of futures. We use mispricing as a direct measure of arbitrage opportunities. With one-year daily data collected from the data portal of Pakistan Stock Exchange, we calculate mispricing for twenty-two stock futures. Summary statistics of mispricing confirm the presence of arbitrage opportunities in this market. We also examine the relationship of mispricing with the time to contract expiry, stock return volatility, the trading volume of ready and future market, and open interest. Tobit regression results indicate that apart from open interest, all other factors possess significant explanatory power for mispricing.