Monotone Regression and Covariance Structure

Shea, Gerald

doi:10.1214/aos/1176344794

Cited by 13 publications

(7 citation statements)

References 7 publications

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“…The positive regression dependence has the intuition that P and Z tend to move together. As shown by Shea (1979), it follows from Chebyshev inequality and Definition 1 that Cov(P, Z ) 30. It is noteworthy that [Z, 21).…”

Section: The Effect Of Adding a Background Risk On Productionmentioning

confidence: 96%

Background Risk and the Theory of the Competitive Firm Under Uncertainty*

Wong

1996

Bulletin of Econ Res

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This paper examines the optimal production decision of a firm under output price risk h la Sandmo when the firm also faces a dependent background risk. It is shown that standard risk aversion plus a non-negative association between the output price risk and the background risk are sufficient to ensure a reduction in the firm's optimal output upon introduction of the background risk. The paper investigates the impact of a deterministic transformation of the background risk on the firm's optimal production decision. It is shown that decreasing absolute risk aversion in Ross' sense is among the sufficient conditions that generate an unambiguous negative comparative static result.

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Section: The Effect Of Adding a Background Risk On Productionmentioning

confidence: 96%

Background Risk and the Theory of the Competitive Firm Under Uncertainty*

Wong

1996

Bulletin of Econ Res

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“…Using a similar method to that in the proof of Proposition I, may not be linearly related [see Shea (1979)].…”

Section: Discussionmentioning

confidence: 99%

The Role of Capital Adequacy Regulation in the Hedging Decisions of Financial Intermediaries

Morgan

Smith

1987

J of Financial Research

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This paper identifies the effect of capital adequacy requirements, which have been ignored to date in the hedging literature, on the forward hedging decisions of financial intermediaries. Using a more general framework than has been used in the literature on intermediary behavior in forward markets, cases are developed where capital and forward contracting are substitutes as well as where increasing the capital requirement increases the volume of desired forward contracting. The model shows that the most important factors in determining the equilibrium rate and the equilibrium position of intermediaries are the statistical association between the level of the forward rate and the spread between interest rates, the level of the capital-to-assets ratio, and the degree of risk aversion of intermediaries and other participants in the forward market. To characterize whether the intermediary's optimal forward position is long or short, one must have knowledge of at least the sign of the association between the level and spread for the particular intermediary, the intermediary's capital position, and whether the forward market equilibrium corresponds to a positive or negative premium. The model also demonstrates that a full hedge of assets is always sub-optimal, and a universally applicable expression for the optimal hedge ratio when hedging is costless is derived.

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“…Lemma 6 A version of Chebyshev's inequality (See Shea (1979)). Let u( x ) and v ( x ) be functions and W be a random variable such that E{u( W ) }, E{v ( W ) }, and E{u ( W ) v ( W )} exist.…”

Section: A1 Lead-timementioning

confidence: 99%

Correcting the Results of the Wrong Model: Treatment Effects Under Early Detection of Cancer

Lee

Tsodikov

2013

Journal of Statistical Theory and Practice

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Early detection of cancer leads to variability of the point of diagnosis advanced by the amount of the so-called lead time, a random variable. Estimated treatment effects by the proportional hazards (PH) model may be biased if this variability is ignored. We study how true and PH-estimated treatment effects differ in screened vs. unscreened populations and offer an approximate correction for the reported PH-based estimate that does not require raw data, targeting a meta-analysis-type application. We rely on a joint cancer incidence and survival model of prostate cancer to furnish key information for the correction. The procedure is applied to a series of prostate cancer data analyses using the PH models reported in the literature. Simulations are used for assessing the quality of the method and sensitivity analyses.

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Monotone Regression and Covariance Structure

Cited by 13 publications

References 7 publications

Background Risk and the Theory of the Competitive Firm Under Uncertainty*

Background Risk and the Theory of the Competitive Firm Under Uncertainty*

The Role of Capital Adequacy Regulation in the Hedging Decisions of Financial Intermediaries

Correcting the Results of the Wrong Model: Treatment Effects Under Early Detection of Cancer

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