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We investigate the difference in pricing performance between tradable and nontradable factors in terms of explaining cross-sectional portfolio returns by comparing the Hansen-Jagannathan (HJ) distance misspecification measures. By constructing nontradable factors mimicking portfolios and incorporating them into the least misspecified tradable stochastic discount factor (SDF), we provide cross-country empirical evidence that this single proxy SDF dominates others to price crosssectional risky assets. Since nontradable factors mimicking portfolios (FMPs) are functions of current risky factors information about the economic state, therefore FMPs "hedge" the state variable risks and FMPs' returns describe the risk premiums.

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This paper aims to establish the strategy of the large-scale consumer for maximizing the total benefits under the circumstance of the day-ahead (DA) and realtime (RT) coupling market. Among the various possible bidding behaviors in demand side, three typical bidding modes are concluded and four typical trade scenes are further formulated. Moreover, a unified general function for trades has been constructed and the corresponding solutions have been discussed. Furthermore, an optimal bidding model is proposed for the large-scale consumer and the corresponding assessment indices have been utilized to quantify the effectiveness of the proposed method. A case study based on the data from a provincial power market is carried out, which demonstrates that the reasonable power portfolios between the DA and RT market can decrease the purchase costs of the largescale consumer.