Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power

Abstract

Since the future output of wind power generation is uncertain due to weather conditions, there is an increasing need to manage the risks associated with wind power businesses, which have been increasingly implemented in recent years. This study introduces multiple weather derivatives of wind speed and temperature and examines their effectiveness in reducing (hedging) the fluctuation risk of future cash flows attributed to wind power generation. Given the diversification of hedgers and hedging needs, we propose new standardized derivatives with higher-order monomial payoff functions, such as “wind speed cubic derivatives” and “wind speed and temperature cross-derivatives,” to minimize the cash flow variance and develop a market-trading scheme to practically use these derivatives in wind power businesses. In particular, while demonstrating the importance of standardizing weather derivatives regarding market liquidity and efficiency, we propose a strategy to narrow down the required number (or volume) of traded instruments and improve trading efficiency by utilizing the least absolute shrinkage and selection operator (LASSO) regression. Empirical analysis reveals that higher-order, multivariate standardized derivatives can not only enhance the out-of-sample hedge effect but also help reduce trading volume. The results suggest that diversification of hedging instruments increases transaction flexibility and helps wind power generators find more efficient portfolios, which can be generalized to risk management practices in other businesses.

Construction of Mixed Derivatives Strategy for Wind Power Producers

“…Note that this paper provides a new perspective on the simultaneous price and volume hedging problem by constructing derivative portfolios of multiple underlying assets and by elaborately modeling the nonlinear relationships among variables, which is distinct from our previous studies that have only dealt with volume risk [33,37]. Other related studies dealing with simultaneous price and volume hedging problems have been conducted for retailers [29][30][31]38], solar power producers [39], wind power producers [40], etc., but all of them deal with derivatives having a single underlying asset (e.g., electricity prices or temperatures).…”

“…A common feature of these studies is to use nonparametric regression techniques and to seek derivatives with arbitrarily nonlinear payoffs (nonparametric derivatives) for optimal hedging. Note that another approach to hedging that replicates arbitrarily nonlinear payoffs has recently been proposed in [37] based on the standardized derivatives, which were shown to be superior to nonparametric derivatives in terms of market transactions at the expense of hedging effect. Thus, nonparametric derivatives have proven to be flexible and advantageous in terms of both hedge effect and contracting procedures efficiency.…”