چولگی شرکت و درجه اوج در نمودار آماری شرکت در بازارهای آتی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|14190||2001||27 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Empirical Finance, Volume 8, Issue 1, March 2001, Pages 55–81
The contribution of the third and fourth moments in explaining the return-generating process in futures markets remains unresolved. This study attempts to resolve this issue by using a four-moment model and by sampling 28 futures contracts and nine market proxies. Such sampling provides wide representation of futures markets and lends a high degree of robustness to the results. Our results show that the second, third and fourth moments are all important in explaining futures returns. Evidence from regression tests show increases in explanatory power as the third and fourth moments are included. The results are robust to the market proxy used.
The nature of the return-generating process in futures markets remains an unresolved issue. Although the distribution of futures returns is well known, empirical tests that examine risk premia in futures markets yield conflicting results. Many studies in the past fail to detect evidence of risk premia in futures markets. For instance, studies that employ a traditional Capital Asset Pricing Model (CAPM) or an Arbitrage Pricing Framework (APT), often fail to detect significant risk premia in futures prices (see, e.g., Dusak, 1973, Baxter et al., 1985 and Ehrardt et al., 1987), and those that use a pricing framework that departs from traditional models provide mixed results. For example, Raynauld and Tessier (1984) and Chang (1985) detect significant risk premia while Junkus (1991) does not. To shed new evidence on the return-generating process in futures markets, we examine 28 futures contracts and use nine different proxies for the market. The wide sampling of futures contracts ensures comprehensive representation of all futures markets, while the use of different market proxies ensures the results are robust. Early tests of the return-generating process were mainly confined to equity markets. Such tests followed the development of the widely accepted two-moment CAPM, developed by Sharpe (1964), Lintner (1965), Mossin (1966), and later Black (1972). Tests of the CAPM are conducted by Friend and Blume (1970), Black et al. (1972), and Basu (1977), among others. These tests provide much insight into the functioning of financial markets. However, violations of the linear pricing kernel proposed by the CAPM found by some (see, e.g., Chen et al., 1986, Fama and French, 1992 and Fama and French, 1993), prompted the search for alternative pricing models. Suggestions included modifications to the CAPM, such as the addition of higher moments (e.g., Arditti and Levy, 1975). This study provides a four-moment extension to the two-moment CAPM, much in the spirit of Kraus and Litzenberger's (1976) three-moment extension to the standard CAPM. Fang and Lai (1997) and Dittmar (1999) present four-moment extensions in other contexts. The basic inferences of our model are consistent with these models.
نتیجه گیری انگلیسی
In this study we examine the importance of coskewness and cokurtosis in explaining futures returns. Studies in futures markets that examine risk premia using the traditional CAPM framework often fail to detect significant risk premia in futures prices. Research that relies on models that depart from a traditional framework find mixed results. Given the current state of the literature, we attempt to provide insight into the return-generating process in futures markets by using a four-moment CAPM model. Although it is almost impossible to know the exact form of the return generating relationship, the preponderance of the evidence from this study provides strong support for the inclusion of terms that represent coskewness and cokurtosis. In the regressions where the excess return on the future is employed as the dependent variable and regressed against the proxies for the second, third, and fourth moments, we find that the explanatory power increases as terms for coskewness and cokurtosis are included. To illustrate, when we employ S&P 500 index futures as the market proxy with the full sample of 28 futures, the average R2 values increase from 0.07 for the two-moment regression to 0.13 for the three-moment regression and to 0.22 for the four-moment regression. Dispute over the appropriate market proxy for futures prompts us to use nine different market proxies, from weighted to nonweighted futures indexes. Additionally, we also employ an all-equity index as a market proxy. The results are robust to the market proxy used. Criticisms of the two-pass methodology are addressed by using corrective techniques. The corrections applied do not change the results. We also check the specification of the model and find the model to be well specified. The overall results confirm that coskewness and cokurtosis are important in explaining the return-generating process in futures markets. Of practical importance is the implication for risk computation on futures instruments. These calculations must account for the pricing of coskewness and cokurtosis.