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Existing methods based on iteratively reweighted least squares (IWLS) are not computationally efficient for large\u2010scale sample sizes. To overcome the issue, we develop a direct nonparametric conditional expectile function estimator by inverting the local polynomial estimator of the conditional loss\u2010gain function. The proposed estimator is computationally friendly and stable without using iterative algorithms that require computation with large\u2010scale data in each iteration. We establish the asymptotic distribution of the proposed estimator. We further show that the proposed estimator has a smaller variance than the existing IWLS estimator and a smaller mean square error in various scenarios. Simulations confirm the computational and statistical efficiency of the proposed method. We further apply the proposed methods to an S&amp;P500 data set to illustrate the computational time to estimate the conditional expectile\u2010based value\u2010at\u2010risk (EVaR) and the precision in out\u2010of\u2010sample prediction.<\/jats:p>","DOI":"10.1111\/jtsa.70021","type":"journal-article","created":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:37:53Z","timestamp":1759919873000},"page":"1098-1112","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Nonparametric Inference of Conditional Expectile Functions in Large\u2010Scale Time Series Data With Improved Efficiency"],"prefix":"10.1111","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8110-5837","authenticated-orcid":false,"given":"Feipeng","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Economics and Finance Xi'an Jiaotong University  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8568-3175","authenticated-orcid":false,"given":"Ping\u2010Shou","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Statistics, and Computer Science University of Illinois Chicago  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,10,8]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-73249-3_8"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10463-021-00799-y"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1080\/10485252.2022.2027412"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9965.00068"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/14697688.2014.946955"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/1351847X.2015.1052150"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11009-016-9527-2"},{"key":"e_1_2_11_9_1","volume-title":"Efficient and Adaptive Estimation for Semiparametric Models","author":"Bickel P. 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