Treasury Bill Futures as a Hedging Tool: A Risk‐return Approach

Howard, C. Thomas; D'Antonio, Louis J.

doi:10.1111/j.1475-6803.1986.tb00433.x

Cited by 13 publications

(8 citation statements)

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“…Finally, in most cases, the ex post risk-return effectiveness for the risk-minimization ratios is greater than the risk-return ratios. This result is comparable to the finding by Howard and D'Antonio (1986) that, ex post, the risk-return approach may not provide the highest performance. Thus, although the risk-return hedge approach would have improved the risk-return performance of the hedger's portfolio, the performance would have been even better by following a risk minimization approach.…”

Section: Risk-return Hedging Effectivenese-risk-minimization Vereus Rsupporting

confidence: 83%

“…However, unlike the risk minimization horizon results (but similar to the results presented in Howard and D'Antonio, 1986), not$ll of the risk-return h+edge ratios are negative. If 1hp > 0 (Equation (4)), then b > 0 when h > p and b < 0 when %ach regression was also estimated via the random coefficient approach (Grammatikos and Saunders.…”

Section: Risk-return Hedging Reeultssupporting

confidence: 75%

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Oil Prices and Energy Futures

Chen

Sears

Tzang

1987

The Financial Review

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Section: Risk-return Hedging Effectivenese-risk-minimization Vereus Rsupporting

confidence: 83%

Section: Risk-return Hedging Reeultssupporting

confidence: 75%

Oil Prices and Energy Futures

Chen

Sears

Tzang

1987

The Financial Review

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“…and Ross (1981). Richard and Sundaresan (1981), Capozza and Cornell (1979), Howard and D'Antonio (1986). and Monroe and Cohn (1986).…”

Section: B Short Cash Position-long Futures Positionmentioning

confidence: 99%

Cash‐futures arbitrage and forward‐futures spreads in the treasury bill market

Allen

Thurston

1988

Journal of Futures Markets

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ersistent discrepancies between implied forward rates on the yield curve P and corresponding futures rates have been widely observed. For instance, in one of our samples, eight week-ahead forward-future spreads averaged nearly 70 discount basis points before 1982 and have since averaged about 30 basis points (see Figure 1). Spreads of these magnitudes are usually rationalized as manifestations of market inefficiencies or transactions cost. However, the observation that the spreads are at least predominantly positive' suggests something more is at work.The observations above appear curious given the presence of leveraged investors (such as securities dealers). securities dealers who seem unlikely to behave inefficiently, are subject to low transactions cost. Assuming they act efficiently, the explanation for substantial forward-futures spreads must be found in the terms at which securities dealers can borrow and lend in order to set up arbitrage positions.As we shall demonstrate, it is these terms which appear to "drive" (i.e., explain the existence and magnitude of) forward-futures spreads. The market requires there be a positive spread between the dealer rep0 rate over the riskfree Treasury bill rate for the same term (the financing cost spread). Further, this spread will systematically determine the size of the forward-futures spread. We find that the predictive power of the financing cost spread is substantial, despite deficiencies in our database which consists of daily averages for repos and Treasury bills and closing prices for futures. This database is, in part, inferior to those using intra-day prices (notably that of Elton, Gruber, and Rentzler (1984)* but has an advantage over this and other studies in that it 'In the case of the spreads calculated for Figure 1, and for those appearing later in this paper, a total of 100 calculated forward minus futures spreads, there are only eight negative ones, whose maximum absolute value is eight discount basis points (see Table 1).

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“…A second measure pioneered by Howard and D'Antonio (HD) (1984, 1987), and Chang and Shanker (CS) (1987) has the objective of maximizing a hedger's risk-return tradeoff, which is proper when both risk and return are important.' These two measures have been tested empirically by Chang and Shanker (1986), Chen, Sears, and Tzang (1987), Howard and D'Antonio (1986), and Overdahl and Starleaf (1986.These hedging effectiveness measures suffer from a major deficiency: they are derived in a one-period setting. This setting imposes rather restrictive conditions on a hedger's behavior.…”

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confidence: 99%

An intertemporal measure of hedging effectiveness

Chang

Fang

1990

Journal of Futures Markets

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Hsing Fangedging effectiveness is measured to determine the effectiveness of adding a given H futures contract to a hedger's cash portfolio. It is determined by comparing the combined futures-cash position with the cash position alone according to certain criteria. The traditional measure developed by Johnson (1960) and Ederington (1979) has the single objective of minimizing a hedger's risk, which is proper when risk-reduction is his only concern. A second measure pioneered by Howard and D'Antonio (HD) (1984, 1987), and Chang and Shanker (CS) (1987) has the objective of maximizing a hedger's risk-return tradeoff, which is proper when both risk and return are important.' These two measures have been tested empirically by Shanker (1986), Chen, Sears, andTzang (1987), D'Antonio (1986), and Overdahl and Starleaf (1986).These hedging effectiveness measures suffer from a major deficiency: they are derived in a one-period setting. This setting imposes rather restrictive conditions on a hedger's behavior. For example, a hedger is assumed to ignore any new information and, therefore, adjusts neither consumption behavior nor hedging positions to his changing consumptiodinvestment opportunity set during the hedge period. This is inconsistent with evidence in the literature which suggests that an optimum hedge ratio should be time-varying, and tends to be unstable when the market is volatile.' These hedging effectiveness measures are accurate only when the market is stable and tend to be noticeably biased when applied to recent market data. This bias problem, however, can be corrected using an intertemporal measure of hedging effectiveness.The authors would like to thank two anonymous reviewers of the journal and the editor, Mark J. Powers, for very constructive comments.'Strictly speaking, the HDICS measures assume a given long-spot position. In contrast, Levy (1987) derives an alternative measure with a variable spot position. However, as shown in Chang and Shanker (1986). the HDlCS measures can be easily modified to a variable spot position with short-sale constraints, margin requirements, and other transaction costs. Gjerde (1987) also has derived alternative risk-return hedging effectiveness measures that assume a hedger's loss function is based upon dollar-return but not percentage returns. For a discussion of alternative performance models, see Yau, Savanayana, and Schneeweis (1988).'For empirical investigations of the properties of the time-varying hedge ratio, see Lee, Bubnys, andLin (1986), andGrammatikos andSaunders (1983). For the derivation of a stochastic hedge ratio, see Geske and Pieptea (1987). Evidence of this is also seen in the daily movements of trading volume. Initial low volume of a futures contract tends to rise over time, reaches a peak near the contract's termination, and drops off as its maturity nears. 'Fortin and Khoury (1988) derived an intertemporal measure of hedging effectiveness based upon a constant consumptionlinvestment opportunity set. Thus, their measure suffers from the bias prob...

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Treasury Bill Futures as a Hedging Tool: A Risk‐return Approach

Cited by 13 publications

References 20 publications

Oil Prices and Energy Futures

Oil Prices and Energy Futures

Cash‐futures arbitrage and forward‐futures spreads in the treasury bill market

An intertemporal measure of hedging effectiveness

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