International Journal of Theoretical and Applied Finance

To respond to financial compound risk of farmers, two multiplicative derivative contracts, called respectively revenue futures contract and revenue put option, are proposed. The paper presents the theoretical management strategy of such a contract under the constraint that price and crop yield futures contracts are quoted.

A financial intermediary can thus develop a risk-free management strategy to build a revenue futures contract. This paper opens perspectives on risk management for farmers, on completeness of markets and on new financial intermediation.

Spot prices of electricity and other energy commodities are often modeled by multifactor stochastic processes. This poses a problem of estimating models' parameters based on historical data, i.e. calibrating them to markets. Here we show how a traditional tool of Kalman Filters can be successfuly applied to do this task. We study two mean-reverting log-spot price models and the Pilipovic model using correspondingly Kalman Filter the extended Kalman Filter. The results of applying this method to market data from several power exchanges are discussed.

For a sample of 94 firms, using data up to 1999, we find that retentions are more significant than dividends in determining prices of shares that are actively traded on the Egyptian stock market. However, for non-actively traded shares, the accounting book value is the most important determinant. Reductions in dividends are associated with a lack of liquidity and profitability. Dividend increases are linked to higher pre-tax operating profit effects, which outweighed post-tax effects. As to aspects that influence dividend payout ratios of actively traded firms, important factors are gearing and the market to book value, the latter a surrogate for investment opportunities. For non-actively traded firms, a more complex pattern emerges.

In this paper, we test for causal relationship between China's stock markets by using returns and a measure of volatility for the Shanghai Composite index, the Shenzhen Composite Subindex, and the Hong Kong Hang Seng Index. We also show that the stock index series are nonstationary and that cointegrating vectors and error correction models do not exist for the series.

Based on these tests, for the return series, we conclude that Shenzhen Granger caused Shanghai before 1994. For the volatility data, we find that there exists a positive feedback relationship between Shanghai and Shenzhen stock markets, and that Hong Kong volatility Granger causes Shanghai volatility, but not vice versa.

We derive explicit formulas for pricing double (single) barrier and touch options with time-dependent rebates assuming that the asset price follows a double-exponential jump diffusion process. We also consider incorporating time-dependent volatility.

Assuming risk-neutrality, the value of a barrier option satisfies the generalized Black–Scholes equation with the appropriate boundary conditions. We take the Laplace transform of this equation in time and solve it explicitly. Option price and risk parameters are computed via the numerical inversion of the corresponding solution. Numerical examples reveal that the pricing formulas are easy to implement and they result in accurate prices and risk parameters.

Proposed formulas allow fast computing of smile-consistent prices of barrier and touch options.

We model spot prices in energy markets with exponential non-Gaussian Ornstein–Uhlenbeck processes. We generalize the classical geometric Brownian motion and Schwartz' mean-reversion model by introducing Lévy processes as the driving noise rather than Brownian motion. Instead of modelling the spot price dynamics as the solution of a stochastic differential equation with jumps, it is advantageous from a statistical point of view to model the price process directly. Imposing the normal inverse Gaussian distribution as the statistical model for the Lévy increments, we obtain a superior fit compared to the Gaussian model when applied to spot price data from the oil and gas markets. We also discuss the problem of pricing forwards and options and outline how to find the market price of risk in an incomplete market.