GMM and present value tests of the C-CAPM: evidence from the Danish, German, Swedish and UK stock markets

Lund, Jesper; Engsted, Tom

doi:10.1016/0261-5606(96)00018-6

Cited by 62 publications

(45 citation statements)

References 33 publications

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“…Indeed, the probability that the J-statistic exceeds the calculated value is always well above the 5% level. Lund and Engsted (1996) put also in evidence these aberrations. The fact that the test is biased in favor of accepting the model may be due to the use of the lagged values of the consumption growth rate and return.…”

Section: Resultsmentioning

confidence: 95%

Utility-based pricing of weather derivatives

Hamisultane

2010

The European Journal of Finance

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Since the underlying of the weather derivatives is not a traded asset, these contracts cannot be evaluated by the traditional financial theory. Cao and Wei (2004) price them by using the consumption-based asset pricing model of Lucas (1978) and by assuming different values for the constant relative risk aversion coefficient. Instead of taking this coefficient as given, we suggest in this paper to estimate it by using the consumption data and the quotations of one of the most transacted weather contracts which is the New York weather futures on the Chicago Mercantile Exchange (CME). We apply the well-known generalized method of moments (GMM) introduced by Hansen (1982) to estimate it as well as the simulated method of moments (SMM) attributed to Lee and Ingram (1991) and Duffie and Singleton (1993). This last method is studied since it is presumed to give satisfactory results in the case of the weather derivatives for which the prices are simulated. We find that the estimated coefficient from the SMM approach must have improbably high values in order to have the calculated weather futures prices matching the observations.

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Section: Resultsmentioning

confidence: 95%

Utility-based pricing of weather derivatives

Hamisultane

2010

The European Journal of Finance

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“…Lund and Engsted (1996) contains a detailed description of the data from where we have taken the following quote: "A nominal stock index and accompanying dividend series was constructed from the original price quotation sheets from the Copenhagen Stock Exchange. In order to avoid a possible taxinduced distortion due to the well known January effect, the stock index at the end of the year t is defined as the value in (mid) February of year t + 1.…”

Section: The Data and Our Definition Of Predictionmentioning

confidence: 99%

“…In this paper we use the annual Danish stock market data from Lund and Engsted (1996), respectively the extended sample period 1922-1996 from Engsted and Tanggård (2000). Lund and Engsted (1996) contains a detailed description of the data from where we have taken the following quote: "A nominal stock index and accompanying dividend series was constructed from the original price quotation sheets from the Copenhagen Stock Exchange.…”

Section: The Data and Our Definition Of Predictionmentioning

confidence: 99%

“…The composition of the stock index is changed about every 10 years, and the weights for the individual stocks are only adjusted in connection with changes in the composition of the stock index." We have updated the data set of Lund and Engsted (1996) following their original approach. The leading Danish stock index, the KFX, index has been used for this purpose.…”

Section: The Data and Our Definition Of Predictionmentioning

confidence: 99%

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Prediction of Stock Returns: A New Way to Look at It

Nielsen¹,

Sperlich²

2003

ASTIN Bull.

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While the traditional R 2 value is useful to evaluate the quality of a fit, it does not work when it comes to evaluating the predictive power of estimated financial models in finite samples. In this paper we introduce a validated R 2 V value useful for prediction. Based on data from the Danish stock market, using this measure we find that the dividend-price ratio has predictive power. The best horizon for prediction seems to be four years. On a one year horizon, we find that while inflation and interest rate do not add to the predictive power of the dividend-price ratio then last years excess stock return does.

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“…An exception is the work of Gao and Huang (2004), who use UK value and size portfolios, whereas other papers such as Hyde and Sherif (2005a,b) for the UK and Lund and Engsted (1996) for Germany estimate consumption-based models separately for each industry sector or market index.…”

mentioning

confidence: 99%

Long-Horizon Consumption Risk and the Cross-Section of Returns: New Tests and International Evidence

2009

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This paper investigates whether measuring consumption risk over long horizons can improve the empirical performance of the Consumption CAPM for size and value premia in international stock markets (US, UK, and Germany). We modify the estimation approach of Parker and Julliard (2005) taking commonalities in size and book-to-market sorted portfolios into account. Our results show that, contrary to the findings of Parker and Julliard, the model falls short of providing an accurate description of the cross-section of returns under our modified empirical approach. At the same time, however, measuring consumption risk over longer horizons typically yields lower risk-aversion estimates. Thus, our results suggest that more plausible parameter estimates -as opposed to lower pricing errors -can be regarded as the main achievement of the long-horizon Consumption CAPM. JEL Classification: G12, G15

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GMM and present value tests of the C-CAPM: evidence from the Danish, German, Swedish and UK stock markets

Cited by 62 publications

References 33 publications

Utility-based pricing of weather derivatives

Utility-based pricing of weather derivatives

Prediction of Stock Returns: A New Way to Look at It

Long-Horizon Consumption Risk and the Cross-Section of Returns: New Tests and International Evidence

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