What is the Howard-D'Antonio Strategy
The Howard D’Antonio Strategy provides investors an algorithm for calculating the most efficient hedge position using risk-return metrics.
BREAKING DOWN Howard-D'Antonio Strategy
The Howard D’Antonio Strategy describes a solution for an optimal hedging strategy by developing a set of relationships between the risk and return embedded in each of three elements an investor could use to hedge a position: short futures positions, long futures positions or positions without any futures. Charles T. Howard and Louis J. D’Antonio developed the algorithm in a paper titled “A Risk-Return Measure of Hedging Effectiveness,” published in 1984.
The formula’s inputs depend upon three variables:
- The expected return on an investment given the spot rate for its underlying commodity. In other words, the return available for an investment whose underlying asset settled immediately.
- The expected returns on investments holding futures positions in an underlying commodity.
- The risk-free rate of return, which provides a theoretical interest rate for an investment with zero risk. This represents an investor’s expected minimum return on a given investment.
Hedgers plug these inputs into the complex algorithm described by the strategy to determine the mix of positions they should take to generate the most effective available hedge.
Optimal Hedging Strategies
Hedging strategies provide investors some degree of protection on investment risks. Investors typically hedge investments by taking up secondary positions in additional investments that they expect to move in the opposite direction of the original investment. Hedge positions usually involve either derivatives, typically futures or options, or entirely different assets with price characteristics that mirror those of the commodity the investor seeks to hedge. Hedge positions can limit losses when markets move against an investor’s expectations. In some scenarios, hedges can also lock in a minimum amount of profit on an investment.
A perfect hedge minimizes the risk inherent in a position, but it does so at the cost of any return since the price of the hedge position exactly mirrors movements in the price of the hedged investment. For any hedge position between an unhedged position and a perfect hedge, an investor receives some balance between reduced risk from the hedge and potential profit depending on the investment’s performance. At some point along that line, the investor will encounter the most efficient mix of the two variables, where a hedge position offers the maximum reduction in risk for the minimum cost to upside potential. Algorithms such as the one developed by Howard and D’Antonio attempt to locate that position by accounting for changes to the risk-reward calculation for a range of potential hedge positions.