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Journal of Medicine and Pharmacy","Tạp chí Y Dược học Cần Thơ",{"EN":487,"VI":488},"\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">04\u002F10\u002F2015 Ministry of Information and Communications allowed Can Tho journal of medicine and pharmacy to operate (102 \u002FGP-BTTTT)\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">07\u002F16\u002F2015 Can Tho journal of medicine and pharmacy is internationally recognized: ISSN 2354-1210\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">In 2016, The journal has been included in the list of medical science journals by The State Council for professorship which is awarded a work score of 0-0.5 points for a published article.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Can Tho Journal of Medicine and Pharmacy welcome original works that haven’t been submitted or published in other medical journals. Posts must contain content related to one of the journal’s categories.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The content published\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The journal is divided into 3 categories:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Scientific research article: are valuable scientific works, which have been researched and accepted.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Overview of medicine, biology and pharmacy: serving the objective of continuing training in the fields of medicine, biology and pharmacy; to systematize classical and modern knowledge.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Update information on new knowledge about medicine, biology, pharmacy in the country and in the world.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Scope\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Publication and introduction of scientific research in the fields:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Medicine (internal medicine, surgery, pediatrics, obstetrics and gynecology, odonto-stomatology, laboratory, oncology, traditional medicine, nursing).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Biology (genetics, biotechnology).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Pharmacology (pharmaceutics, drug quality analysis-control, synthetic pharmaceutical chemistry, biochemistry, pharmacognosy, botany, clinical pharmacy).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- To enhance the quality of undergraduate, postgraduate education, scientifically researching and meet the necessary treatment in hospital.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Introducing the updated domestic and oversea information about science technology to promote scientific research and exchanging technology in local, other universities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Exchanging pharmaceutical and medical information for social health developing in the Mekong Delta and Vietnam.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The object\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Postgraduate students, student of Can Tho University of Medicine and Pharmacy, scientists from schools, research institutes, hospitals, health centers, pharmaceutical companies of the Mekong Delta; other provinces and regions in Vietnam and other country.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Address\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Headquarters of Can Tho Journal of Medicine and Pharmacy, located Scientific Research and International Cooperation Office: 179 Nguyen Van Cu Street, An Khanh Ward, Ninh Kieu District, Can Tho City, Vietnam.\u003C\u002Fspan>\u003C\u002Fp>","\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Ngày 16\u002F7\u002F2015, Tạp chí Y Dược học Cần Thơ được cấp chỉ số quốc tế: ISSN 2354-1210.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Từ tháng 4\u002F2016, Tạp chí đã được Hội đồng Giáo sư ngành Y đưa vào danh sách các tạp chí khoa học Y học được tính điểm công trình 0-0,5 điểm cho một bài báo đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Năm 2020 Tạp chí Y Dược học Cần Thơ đã được phê duyệt vào danh mục của các Hội đồng Giáo sư ngành Dược học được tính điểm công trình 0-0,5 điểm cho một bài báo đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ ra 12 số\u002Fnăm, 180-200 trang\u002Fsố.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Từ tháng 12\u002F2022 Tạp chí Y Dược học Cần Thơ là thành viên của hệ thống Crossref và từ tháng 01\u002F2023 tạp chí thực hiện bình duyệt online kín 2 chiều nhằm tăng tính minh bạch, tin cậy của các công trình nghiên cứu khoa học và đảm bảo tốt nhất chất lượng khoa học của bài viết.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tôn chỉ, mục đích và phạm vi của tạp chí\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tôn chỉ và mục đích hoạt động của tạp chí: xuất bản nhằm mục đích phổ biến kết quả từ các đề tài nghiên cứu khoa học; giao lưu trao đổi khoa học, chia sẻ kinh nghiệm, học tập, đồng thời cập nhật thông tin khoa học mới trong các lĩnh vực y, sinh, dược học trong và ngoài nước.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Phạm vi của tạp chí: Tạp chí xuất bản được chia thành 3 chuyên mục: (i) Bài báo nghiên cứu khoa học là kết quả công trình nghiên cứu khoa học có giá trị đã được triển khai nghiên cứu, (ii) Bài tổng quan y, sinh, dược học: phục vụ mục tiêu đào tạo liên tục trong lĩnh vực y, sinh, dược học; nhằm hệ thống hóa những kiến thức kinh điển và hiện đại; (iii) Thông tin cập nhật kiến thức mới về y, sinh, dược học trong nước và trên thế giới.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Chính sách truy cập mở\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ áp dụng chính sách truy cập mở đối với các bài báo đã xuất bản đến với độc giả, nhằm mở rộng cơ hội tiếp cận các kết quả nghiên cứu chất lượng cao và tăng cường trao đổi kiến thức. Tạp chí đăng tải trực tuyến (miễn phí) toàn văn các bài báo được công bố trên website của Tạp chí (https:\u002F\u002Ftapchi.ctump.edu.vn).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đạo đức xuất bản\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ cam kết tuân thủ đạo đức xuất bản phù hợp với các hướng dẫn và tiêu chuẩn của the Committee on Publication Ethics (COPE), tuân thủ các nguyên tắc của COPE’s Core Practices, Best Practices Guidelines for Journal Editors và Guidelines on Good Publication Practices.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Bản thảo bài báo chỉ được chấp nhận khi được tác giả chịu trách nhiệm chính cam kết các nội dung sau: Các nội dung của bản thảo chưa được đăng tải toàn bộ hoặc một phần ở các tạp chí khác; Tất cả các tác giả đều có đóng góp một cách đáng kể vào quá trình nghiên cứu hoặc chuẩn bị bản thảo và cùng chịu trách nhiệm về các nội dung của bản thảo; Tuân thủ các biện pháp đảm bảo đạo đức nghiên cứu (ví dụ thỏa thuận đồng ý tham gia nghiên cứu).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Cam kết bảo mật\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí cam kết thực hiện và tuân thủ các quy định của luật và các văn bản hướng dẫn liên quan đến bảo mật thông tin cá nhân trên không gian mạng. Các thông tin mà người dùng (tác giả, độc giả, biên tập viên, người phản biện) nhập vào các biểu mẫu trên Hệ thống Quản lý xuất bản trực tuyến của tạp chí chỉ được sử dụng vào các mục đích đã được tuyên bố rõ ràng và sẽ không được cung cấp cho bất kỳ bên thứ ba nào khác, hay dùng vào bất kỳ mục đích nào khác.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Phí gửi bài\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Lệ phí gửi đăng bài: 1.000.000đ\u002Fbài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Lệ phí gửi đăng nhanh: 1.500.000đ\u002Fbài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đối với tác giả là cán bộ viên chức thuộc Trường Đại học Y Dược Cần Thơ thì được hỗ trợ 50% lệ phí gửi đăng bài.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đối với sinh viên thực hiện đề tài nghiên cứu khoa học cấp trường được hỗ trợ 100% lệ phí đăng bài ( Tác giả gửi đính kèm “ Quyết định về việc giao tổ chức thực hiện đề tài nghiên cứu khoa học cấp Trường của sinh viên”).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Hình thức nộp lệ phí:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Tiền mặt:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Nộp trực tiếp tại Phòng Tài chính - Kế toán, Trường Đại học Y Dược Cần Thơ, số 179 Nguyễn Văn Cừ, P. An Khánh, Q. Ninh Kiều, thành phố Cần Thơ.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Chuyển khoản:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tên Tài khoản: Trường ĐHYD Cần Thơ, Số TK: 0111000115668, tại ngân hàng Vietcombank chi nhánh Cần Thơ.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Thời gian: Áp dụng từ ngày 01\u002F02\u002F2023.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">* Phí gửi bài không được hoàn trả khi bài viết bị từ chối hoặc tác giả xin rút bài viết.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Quy trình phản biện bài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ thực hiện quy trình phản biện kín hai chiều nghiêm ngặt. Danh tính của những người phản biện không được tiết lộ cho các tác giả và ngược lại. Quy trình thẩm định bài báo đăng gồm các bước sau:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tiếp nhận bản thảo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tác giả liên hệ gửi bản thảo đến Tạp chí qua hệ thống trực tuyến tại website: https:\u002F\u002Ftapchi.ctump.edu.vn. Hướng dẫn về cách đăng ký, gửi bài và chuẩn bị bản thảo được cung cấp trên website của Tạp chí.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Sàng lọc sơ bộ\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Sau khi Tòa soạn nhận được bài báo của tác giả, Ban Thư ký sẽ tiến hành kiểm tra sơ bộ bài báo (các yêu cầu về nội dung và hình thức). Những bài báo không đúng quy cách hoặc có nội dung không phù hợp hoặc vi phạm bản quyền sẽ bị từ chối (Ban Thư ký thông báo phản hồi đến tác giả trong vòng 1 tuần). Những bài báo đủ điều kiện, được Ban Thư ký tòa soạn chuyển đến Ban Biên tập có cùng chuyên môn với nội dung bài báo để đề xuất người phản biện. Thời gian kể từ khi Ban Biên tập nhận bài báo đến khi đề xuất người phản biện bài báo chậm nhất là 5 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Vòng phản biện\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Ban Thư ký gửi bài và yêu cầu phản biện đến 02 phản biện độc lập.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Các phản biện gởi nhận xét cho Ban Thư ký. Thời gian từ khi gửi bài cho phản biện đến khi nhận ý kiến của phản biện tối đa là 20 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Xử ký kết quả phản biện\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Nếu ý kiến đồng ý cho đăng và không cần chỉnh sửa, Ban Thư ký tiếp tục đăng bài theo qui trình.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Nếu ý kiến đồng ý đăng và cần chỉnh sửa, Ban Thư ký sẽ thông tin đến tác giả chỉnh sửa theo yêu cầu của người phản biện. Thời gian chỉnh sửa và gửi lại kéo dài không quá 2 tuần, từ khi tác giả bài báo nhận được thông tin (Quá trình này có thể lặp lại tối đa 2 lần\u002F1 bài báo). Khi có sự thống nhất, đồng ý của người phản biện; bài báo được tiếp tục đăng theo qui trình.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">3. Những bài báo có chất lượng không đạt yêu cầu, cả 2 phản biện không đồng ý cho đăng sẽ bị Tòa soạn từ chối đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Xuất bản\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Ban Thư ký tổng hợp các bản thảo đã được tác giả hoàn thiện sau thẩm định trình Ban Biên tập xem xét, Tổng Biên tập phê duyệt, quyết định bài đăng theo các tiêu chí: sự phù hợp nội dung với tôn chỉ và mục đích, thể loại bài viết (ưu tiên các bài có bài có nghiên cứu chuyên sâu, hàm lượng khoa học cao), đóng góp mới bài báo, bài báo được ưu tiên đăng trong số gần nhất của Tạp chí theo thứ tự: tính thời sự, chất lượng bài báo và thời gian gửi bài.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Ban Biên tập và Ban Thư ký biên tập bản thảo, chế bản, đọc rà soát lỗi. Thời gian hoàn thành từ 10-15 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">3. Ban Thư ký có trách nhiệm thông báo cho tác giả bài báo (bằng e-mail) về tình hình phê duyệt bài báo, thời gian, số kỳ, tập xuất bản bài báo theo qui định.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">4. Danh sách bài báo theo số Tạp chí được in ấn và phát hành trong năm định kỳ được công bố chính thức trên website: https:\u002F\u002Ftapchi.ctump.edu.vn\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>",{"VOID":490},"wcQ1uqwAAAAJ","2023-05-30T08:17:21.868+00:00",[],[494],{"id":495,"createTime":28,"updateTime":28,"relativeEntities":496,"slug":28,"properties":497,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":507,"parentIds":508,"statistic":28},"6413896b-eca9-442b-a73f-182a58a0ce40",[],{"title":498,"address":501,"country":504,"abbreviation":505},{"EN":499,"VI":500},"Can Tho University of Medicine and Pharmacy","Trường Đại học Y Dược Cần Thơ",{"EN":502,"VI":503},"No 179, Nguyen Van Cu street, An Khanh ward, Ninh Kieu district, Can Tho city, Vietnam","Số 179, đường Nguyễn Văn Cừ, phường An Khánh, quận Ninh Kiều, thành phố Cần Thơ, Việt Nam",{"VOID":15},{"VOID":506},"ctump","http:\u002F\u002Fwww.ctump.edu.vn\u002F",[],[],"https:\u002F\u002Ftapchi.ctump.edu.vn\u002Findex.php\u002Fctump",{"impactFactor":32,"impactFactorByYear":512,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":514,"totalPublicationByYear":515,"totalCitation":520,"totalCitationByYear":521,"totalCitationPerPublication":108,"totalCitationPerPublicationByYear":523,"hindexLast5Year":45,"hindex":45},{"2022":513,"2023":111,"2024":106},0.01,1556,{"2020":47,"2021":516,"2022":517,"2023":518,"2024":519,"2025":122},57,306,801,358,161,{"2021":146,"2022":280,"2023":522},99,{"2021":524,"2022":318,"2023":104},0.23,{"impactFactor":28,"impactFactorByYear":28,"i10Index":123,"i10IndexLast5Year":123,"totalPublication":526,"totalPublicationByYear":527,"totalCitation":526,"totalCitationByYear":528,"totalCitationPerPublication":40,"totalCitationPerPublicationByYear":531,"hindexLast5Year":49,"hindex":49},476,{"0":205,"2019":123,"2021":139,"2022":459,"2023":451,"2024":357,"2025":49,"2026":48},{"2021":42,"2022":123,"2023":161,"2024":529,"2025":360,"2026":530},136,83,{"2021":105,"2022":513,"2023":532,"2024":127,"2025":533,"2026":534},0.62,25.43,13.83,{"id":536,"createTime":537,"updateTime":382,"relativeEntities":538,"slug":539,"properties":540,"entityType":25,"verifyStatus":26,"verifyTime":28,"verifyNote":28,"languages":552,"translateLanguages":28,"viewCount":133,"subjectFields":553,"manageAffiliations":554,"indexDatabases":555,"url":556,"thumbnailPath":557,"statistic":558,"gsStatistic":594,"type":55,"analyzePriority":28},"6984a56a-db70-403b-9cc4-4013e1ceaffa","2023-05-09T06:47:40.346+00:00",[],"T%E1%BA%A1p%20ch%C3%AD%20Nghi%C3%AAn%20c%E1%BB%A9u%20n%C6%B0%E1%BB%9Bc%20ngo%C3%A0i",{"country":541,"issn":542,"title":544,"introduce":547,"gsId":550},{"VOID":15},{"VOID":543},"25252445",{"EN":545,"VI":546},"VNU Journal of Foreign Studies","Tạp chí Nghiên cứu nước ngoài",{"EN":548,"VI":549},"{\"ops\":[{\"insert\":\"\\n\\nThe \\n\"},{\"attributes\":{\"italic\":true},\"insert\":\"VNU Journal of Science\"},{\"insert\":\"\\n was established in 1985 for the publication of national and international research papers in all fields of natural sciences and technology, social sciences and humanities. 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SSCI","ssci",[933,813],"SSCI","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002Fnull",[936,937],"0b8e62b2-c9d1-413b-84bb-3d9515d04f0d","4b168529-40aa-4c68-81bf-b698a674114b","https:\u002F\u002Flink.springer.com\u002Fjournal\u002F40854",{"impactFactor":32,"impactFactorByYear":940,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":123,"totalPublicationByYear":941,"totalCitation":32,"totalCitationByYear":942,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":943,"hindexLast5Year":32,"hindex":32},{},{"2021":40,"2024":40},{},{},{"meta":945,"data":947},{"total":946},"410",[948,1059,1167,1249,1348,1459,1539,1677,1761,1886],{"id":949,"createTime":950,"updateTime":951,"relativeEntities":952,"slug":953,"properties":954,"entityType":965,"verifyStatus":26,"verifyTime":951,"verifyNote":966,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":967,"fullTextUrl":28,"authors":968,"publicationType":1008,"publisherRelationship":1009,"citationCount":28,"citationInfo":28,"publishDate":1055,"publishYear":1056,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":1057,"openAccess":28,"references":28,"isForceReanalyzing":1058},"00103ad9-fc5e-47f1-a1a4-5d9b858c14e1","2024-04-06T17:14:50.099+00:00","2025-01-25T06:18:55.812+00:00",[],"Pattern-and-determinants-of-tail-risk-transmission-between-cryptocurrency-markets-new-evidence-from-recent-crisis-episodes",{"abstract":955,"title":957,"keywords":959,"references":961,"doi":963},{"EN":956},"The main objective of this study is to investigate tail risk connectedness among six major cryptocurrency markets and determine the extent to which investor sentiment, economic conditions, and economic uncertainty can predict tail risk interconnectedness. Combining the Conditional Autoregressive Value-at-Risk (CAViaR) model with the time-varying parameter vector autoregressive (TVP-VAR) approach shows that the transmission of tail risks among cryptocurrencies changes dynamically over time. During crises and significant events, transmission bursts and tail risks change. Based on both in- and out-of-sample forecasts, we find that the information contained in investor sentiment, economic conditions, and uncertainty includes significant predictive content about the tail risk connectedness of cryptocurrencies.",{"EN":958},"Pattern and determinants of tail-risk transmission between cryptocurrency markets: new evidence from recent crisis episodes",{"EN":960},"",{"VOID":962},"Adrian T, Brunnermeier MK (2016) CoVaR. Am Econ Rev 106(7):1705–1741\nAl-Shboul M, Assaf A, Mokni K (2022) When bitcoin lost its position: cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic. 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Int Rev Financ Anal 60:98–114",{"VOID":964},"10.1186\u002Fs40854-023-00592-1","PUBLICATION","Auto Verify","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-023-00592-1",[969,985],{"id":970,"sortIndex":32,"researcher":28,"roles":971,"affiliations":973,"properties":982,"displayName":984,"givenName":28,"familyName":28},"c824fea1-5026-4ed8-ab73-409cbac80990",[972],"AUTHOR",[974],{"id":975,"sortIndex":32,"affiliation":976,"properties":28},"7d7ccd89-a270-451b-b650-5e381b482dec",{"id":975,"createTime":28,"updateTime":28,"relativeEntities":977,"slug":28,"properties":978,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":981,"statistic":28},[],{"title":979},{"VI":980},"Department of Accounting and Finance, United Arab Emirates University, Al Ain, United Arab Emirates",[],{"title":983},{"VI":984},"Aktham 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UK",[],{"id":998,"sortIndex":32,"affiliation":999,"properties":28},"9ac51954-dc66-480a-8054-12c597dcb8c5",{"id":998,"createTime":28,"updateTime":28,"relativeEntities":1000,"slug":28,"properties":1001,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1004,"statistic":28},[],{"title":1002},{"VI":1003},"Faculty of Business, Al-Ahliyya Amman University Jordan, Amman, Jordan",[],{"title":1006},{"VI":1007},"Salem Adel Ziadat","ARTICLE",{"url":28,"publisher":1010,"properties":28},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":1011,"slug":872,"properties":1012,"entityType":25,"verifyStatus":878,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":1015,"manageAffiliations":1024,"indexDatabases":1035,"url":938,"thumbnailPath":28,"statistic":1050,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":1013,"title":1014},{"VOID":875},{"EN":877},[1016,1020],{"id":881,"createTime":28,"updateTime":28,"relativeEntities":1017,"label":1018,"description":1019,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":884},{},{"id":887,"createTime":28,"updateTime":28,"relativeEntities":1021,"label":1022,"description":1023,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":890},{},[1025,1030],{"id":894,"createTime":28,"updateTime":28,"relativeEntities":1026,"slug":28,"properties":1027,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1029,"statistic":28},[],{"title":1028},{"EN":898},[],{"id":901,"createTime":28,"updateTime":28,"relativeEntities":1031,"slug":28,"properties":1032,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1034,"statistic":28},[],{"title":1033},{"EN":905},[],[1036,1043],{"id":909,"indexDatabase":1037,"url":915,"indexYears":916,"academicFieldIds":1042,"indexDatabaseRanking":920},{"id":786,"createTime":28,"updateTime":28,"relativeEntities":1038,"label":1039,"description":1040,"key":792,"publicationTags":1041,"standard":28},[],{"EN":789,"VI":789},{"EN":789,"VI":791},[794],[918,919],{"id":922,"indexDatabase":1044,"url":934,"indexYears":28,"academicFieldIds":1049,"indexDatabaseRanking":28},{"id":924,"createTime":28,"updateTime":28,"relativeEntities":1045,"label":1046,"description":1047,"key":931,"publicationTags":1048,"standard":28},[],{"EN":927,"VI":927},{"EN":929,"VI":930},[933,813],[936,937],{"impactFactor":32,"impactFactorByYear":1051,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":123,"totalPublicationByYear":1052,"totalCitation":32,"totalCitationByYear":1053,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":1054,"hindexLast5Year":32,"hindex":32},{},{"2021":40,"2024":40},{},{},"2024-03-01",2024,[933,920],false,{"id":1060,"createTime":1061,"updateTime":1062,"relativeEntities":1063,"slug":1064,"properties":1065,"entityType":965,"verifyStatus":26,"verifyTime":1062,"verifyNote":966,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":1074,"fullTextUrl":28,"authors":1075,"publicationType":1008,"publisherRelationship":1113,"citationCount":28,"citationInfo":28,"publishDate":1164,"publishYear":1165,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":1166,"openAccess":28,"references":28,"isForceReanalyzing":1058},"015be1b0-d222-4142-9b43-366a50c75c7b","2024-02-13T09:05:47.890+00:00","2025-01-14T14:59:38.719+00:00",[],"Impact-of-trading-hours-extensions-on-foreign-exchange-volatility-intraday-evidence-from-the-Moscow-exchange",{"abstract":1066,"title":1068,"references":1070,"doi":1072},{"EN":1067},"Using transaction-level tick-by-tick data of same- and next-day settlement of the Russian Ruble versus the US Dollar exchange rate (RUB\u002FUSD) traded on the Moscow Exchange Market during the period 2005–2013, we analyze the impact of trading hours extensions on volatility. During the sample period, the Moscow Exchange extended trading hours three times for the same-day settlement and two times for the next-day settlement of the RUB\u002FUSD rate. To analyze the effect of the implementations, various measures of historical and realized volatility are calculated for 5- and 15-min intraday intervals spanning a period of three months both prior to and following trading hours extensions. Besides historical volatility measures, we also examine volume and spread. We apply an autoregressive moving average-autoregressive conditional heteroscedasticity (ARMA-GARCH) model utilizing realized volatility and a trade classification rule to estimate the probability of informed trading. The extensions of trading hours cause a significant increase in both volatility and volume for further analyzing the reasons behind volatility changes. Volatility changes mostly occur after the opening of the market. The length of the extension has a significant positive effect on realized volatility. The results indicate that informed trading increased substantially after the opening for the rate of same-day settlement, whereas this is not observed for next-day settlement. Although trading hours extensions raise opportunities for more transactions and liquidity in foreign exchange markets, they may also lead to higher volatility in the market. Furthermore, this distortion is more significant at opening and midday. A potential explanation for the increased volatility mostly at the opening is that the trading hours extension attracts informed traders rather than liquidity providers.",{"EN":1069},"Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange",{"VOID":1071},"Abdullah SM, Siddiqua S, Siddiquee MSH, Hossain N (2017) Modeling and forecasting exchange rate volatility in Bangladesh using Garch models: a comparison based on normal and student’s T-error distribution. Financ Innov 3(1):18. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40854-017-0071-z\nAdmati AR, Pfleiderer P (1988) A theory of intraday patterns: volume and price variability. Rev Financ Stud 1(1):3–40. https:\u002F\u002Fdoi.org\u002F10.1093\u002Frfs\u002F1.1.3\nAgarwalla SK, Jacob J, Pandey A (2015) Impact of the introduction of call auction on price discovery: evidence from the Indian stock market using high-frequency data. 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paper derives a new method for comparing the weak-form efficiency of markets. The author derives the formula of the Sharpe ratio from the ARMA-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH process. For empirical purposes, the Sharpe ratio can be formulated with a monotonic increasing function of R-squared if the sample size is large enough. One can utilize the Sharpe ratio to compare weak-form efficiency among different markets. The results of stochastic simulation demonstrate the validity of the proposed method. The author also constructs empirical AR-GARCH models and computes the Sharpe ratio for S&P 500 Index and the SSE Composite Index.",{"EN":1259},"How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast",{"VOID":1261},"Box G, Jenkins GM, Reinsel GC (2008) Time series analysis. Wiley, NJ\nBox G, Pierce D (1970) Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. J Am Stat Assoc 65:1509–1526\nCampbell JY, Lo AW, MacKinlay AC (1997) The econometrics of financial markets. Princeton University Press, Princeton\nCochrane JH (1999) Portfolio advice for a multifactor world. Econ Perspect 23:59–78\nFama EF (1970) Efficient capital markets: a review of theory and empirical work. J Financ 25:383–417\nFang Y, Xu D (2003) The predictability of asset returns: an approach combining technical analysis and time series forecasts. Int J Forecast 19:369–385\nGriffin JM, Kelly PJ, Nardari F (2010) Do market efficiency measures yield correct inferences? A Comparison of Developed and Emerging Markets. Rev Financ Stud 23:3225–3277\nHamilton JD (1994) Time series analysis. Princeton University Press, Princeton\nHan CY, Wang YM, Ning Y (2019) Analysis and comparison of the Multifractality and efficiency of Chinese stock market: evidence from dynamics of major indexes in different boards. Phys A 528:121305\nHou K, Moskowitz TJ (2005) Market frictions, Price delay, and the cross-section of expected returns. Rev Financ Stud 18:981–1020\nHuang D, Zhou GF (2017) Upper bounds on return predictability. J Financ Quant Anal 52:401–425\nKirby C (1998) The restrictions on predictability implied by rational asset pricing models. Rev Financ Stud 11:343–382\nLevich RM, Potì V (2015) Predictability and ‘good deals’ in currency markets. Int J Forecast 31:454–472\nLiu J, Cheng C, Yang XL, Yan LZ, Lai YZ (1999) Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent. Phys A 534:122035\nLo AW, Mackinlay AC (1988) Stock market prices do not follow random walks: evidence from a simple specification test. Rev Financ Stud 1:41–66\nLu M (1999) Advanced time series econometrics. Shanghai People’s Publishing House, Shanghai\nMalkiel B (1992) Efficient market hypothesis. In: Newman P, Milgate M, Eatwell J (eds) New Palgrave dictionary of money and finance. London, Macmillan\nMech T (1993) Portfolio return autocorrelation. J Financ Econ 34:307–344\nMoradi M, Nooghabi MJ, Rounaghi MM (2019) Investigation of Fractal Market Hypothesis and Forecasting Time Series Stock Returns for Tehran Stock Exchange and London Stock Exchange. Int J Financ Econ 11:1002\u002FIJFE.1809\nOla MR, Nooghabi MJ, Rounaghi MM (2014) Chaos process testing (using local polynomial approximation model) in predicting stock returns in Tehran stock exchange. Asian J Res Bank Financ 4:100–109\nPotì V (2018) A new tight and general bound on return predictability. Econ Lett 162:140–145\nRoss SA (2005) Neoclassical Finance. Princeton: Princton University Press\nSharpe WF (1966) Mutual Fund Performance. J Bus 39:119–138\nWen FH, Xu LH, Ouyang GD, Kou G (2019) Retail investor attention and stock Price crash risk: evidence from China. Int Rev Financ Anal 65:101376\nZhang Y (1999) Toward a theory of marginally efficient markets. Phys A 269:30–40",{"VOID":1263},"10.1186\u002Fs40854-020-00200-6","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-020-00200-6",[1266,1281],{"id":1267,"sortIndex":32,"researcher":28,"roles":1268,"affiliations":1269,"properties":1278,"displayName":1280,"givenName":28,"familyName":28},"5cc6669c-fb2f-45f2-bd61-3b19229389ed",[972],[1270],{"id":1271,"sortIndex":32,"affiliation":1272,"properties":28},"1fb8787c-89d9-40ec-9d9c-deaf52d78082",{"id":1271,"createTime":28,"updateTime":28,"relativeEntities":1273,"slug":28,"properties":1274,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1277,"statistic":28},[],{"title":1275},{"VI":1276},"Peking University, Beijing, China",[],{"title":1279},{"VI":1280},"Lin Liu",{"id":1282,"sortIndex":40,"researcher":28,"roles":1283,"affiliations":1284,"properties":1291,"displayName":1293,"givenName":28,"familyName":28},"6bb7ba14-60c1-4f14-9417-b3fc412d8706",[972],[1285],{"id":1271,"sortIndex":32,"affiliation":1286,"properties":28},{"id":1271,"createTime":28,"updateTime":28,"relativeEntities":1287,"slug":28,"properties":1288,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1290,"statistic":28},[],{"title":1289},{"VI":1276},[],{"title":1292},{"VI":1293},"Qiguang Chen",{"url":1264,"publisher":1295,"properties":1340},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":1296,"slug":872,"properties":1297,"entityType":25,"verifyStatus":878,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":1300,"manageAffiliations":1309,"indexDatabases":1320,"url":938,"thumbnailPath":28,"statistic":1335,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":1298,"title":1299},{"VOID":875},{"EN":877},[1301,1305],{"id":881,"createTime":28,"updateTime":28,"relativeEntities":1302,"label":1303,"description":1304,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":884},{},{"id":887,"createTime":28,"updateTime":28,"relativeEntities":1306,"label":1307,"description":1308,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":890},{},[1310,1315],{"id":894,"createTime":28,"updateTime":28,"relativeEntities":1311,"slug":28,"properties":1312,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1314,"statistic":28},[],{"title":1313},{"EN":898},[],{"id":901,"createTime":28,"updateTime":28,"relativeEntities":1316,"slug":28,"properties":1317,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1319,"statistic":28},[],{"title":1318},{"EN":905},[],[1321,1328],{"id":909,"indexDatabase":1322,"url":915,"indexYears":916,"academicFieldIds":1327,"indexDatabaseRanking":920},{"id":786,"createTime":28,"updateTime":28,"relativeEntities":1323,"label":1324,"description":1325,"key":792,"publicationTags":1326,"standard":28},[],{"EN":789,"VI":789},{"EN":789,"VI":791},[794],[918,919],{"id":922,"indexDatabase":1329,"url":934,"indexYears":28,"academicFieldIds":1334,"indexDatabaseRanking":28},{"id":924,"createTime":28,"updateTime":28,"relativeEntities":1330,"label":1331,"description":1332,"key":931,"publicationTags":1333,"standard":28},[],{"EN":927,"VI":927},{"EN":929,"VI":930},[933,813],[936,937],{"impactFactor":32,"impactFactorByYear":1336,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":123,"totalPublicationByYear":1337,"totalCitation":32,"totalCitationByYear":1338,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":1339,"hindexLast5Year":32,"hindex":32},{},{"2021":40,"2024":40},{},{},{"pages":1341,"volume":1343},{"VOID":1342},"1-21",{"VOID":1344},"6","2020-10-15",2020,[933,920],{"id":1349,"createTime":1350,"updateTime":1351,"relativeEntities":1352,"slug":1353,"properties":1354,"entityType":965,"verifyStatus":26,"verifyTime":1351,"verifyNote":966,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":1363,"fullTextUrl":28,"authors":1364,"publicationType":1008,"publisherRelationship":1406,"citationCount":28,"citationInfo":28,"publishDate":1457,"publishYear":1056,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":1458,"openAccess":28,"references":28,"isForceReanalyzing":1058},"0430b400-dfa8-48e9-8d47-02304cd2d247","2024-01-19T03:44:21.362+00:00","2024-12-22T07:19:03.249+00:00",[],"Unsupervised-clustering-of-bitcoin-transactions",{"abstract":1355,"title":1357,"references":1359,"doi":1361},{"EN":1356},"Since its inception in 2009, Bitcoin has become and is currently the most successful and widely used cryptocurrency. It introduced blockchain technology, which allows transactions that transfer funds between users to take place online, in an immutable manner. No real-world identities are needed or stored in the blockchain. At the same time, all transactions are publicly available and auditable, making Bitcoin a pseudo-anonymous ledger of transactions. The volume of transactions that are broadcast on a daily basis is considerably large. We propose a set of features that can be extracted from transaction data. Using this, we apply a data processing pipeline to ultimately cluster transactions via a k-means clustering algorithm, according to the transaction properties. Finally, according to these properties, we are able to characterize these clusters and the transactions they include. Our work mainly differentiates from previous studies in that it applies an unsupervised learning method to cluster transactions instead of addresses. Using the novel features we introduce, our work classifies transactions in multiple clusters, while previous studies only attempt binary classification. Results indicate that most transactions fall into a cluster that can be described as common user transactions. Other clusters include transactions made by online exchanges and lending services, those relating to mining activities as well as smaller clusters, one of which contains possibly illicit or fraudulent transactions. We evaluated our results against an online database of addresses that belong to known actors, such as online exchanges, and found that our results generally agree with them, which enhances the validity of our methods.",{"EN":1358},"Unsupervised clustering of bitcoin transactions",{"VOID":1360},"Alqassem I, Rahwan I, Svetinovic D (2020) The anti-social system properties: Bitcoin network data analysis. IEEE Trans Syst Man Cybern Syst 50(1):21–31\nAndroulaki E et al (2013) Evaluating user privacy in bitcoin. In: International conference on financial cryptography and data security. Springer, pp 34–51\nArbelaitz O, Gurrutxaga I, Muguerza J, Pérez JM, Perona I (2013) An extensive comparative study of cluster validity indices. Patt Recogn 46(1):243–256\nBallis A, Drakos K (2021) The explosion in cryptocurrencies: a black hole analogy. Financ Innov 7(1):8. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40854-020-00222-0\nBartoletti M et al (2018) Data mining for detecting bitcoin ponzi schemes. In: 2018 crypto valley conference on blockchain technology (CVCBT), pp 75–84. https:\u002F\u002Fdoi.org\u002F10.1109\u002FCVCBT.2018.00014\nBistarelli S, Mercanti I, Santini F (2019) An analysis of non-standard transactions. Front Blockchain 2:7\nBitcoin wiki (2021) Bitcoin core. Accessed 28 Feb from https:\u002F\u002Fen.bitcoin.it\u002Fwiki\u002FBitcoin_Core\nBitcoin wiki (2021) Deterministic wallet. Accessed 28 Feb from https:\u002F\u002Fen.bitcoin.it\u002Fwiki\u002FDeterministic_wallet\nBitcoin wiki (2021a) Op_return. Accessed 28 Feb from https:\u002F\u002Fen.bitcoin.it\u002Fwiki\u002FOP_RETURN\nBitcoin wiki (2021b) Segregated witness. Accessed 28 Feb from https:\u002F\u002Fen.bitcoin.it\u002Fwiki\u002FSegregated_Witness\nBlockchain charts (2021) Unique addresses used. Accessed 28 Feb from https:\u002F\u002Fwww.blockchain.com\u002Fcharts\u002Fn-unique-addresses\nBonneau J, Miller A, Clark J, Narayanan A, Kroll J A, Felten EW (May 2015) Sok: research perspectives and challenges for bitcoin and cryptocurrencies. In: 2015 IEEE symposium on security and privacy, pp 104–121. https:\u002F\u002Fdoi.org\u002F10.1109\u002FSP.2015.14\nButerin V (2021) Ethereum whitepaper, Accessed 14 Jan 2013 from https:\u002F\u002Fethereum.org\u002Fen\u002Fwhitepaper\u002F\nCaprolu M et al (2021) Analysis and patterns of unknown transactions in bitcoin. In: 2021 IEEE international conference on blockchain (Blockchain)\nChen T, Tsourakakis C (2022) Antibenford subgraphs: unsupervised anomaly detection in financial networks. In: Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining, KDD ’22. Association for Computing Machinery, New York, pp 2762–2770. https:\u002F\u002Fdoi.org\u002F10.1145\u002F3534678.3539100\nConlon T, McGee RJ (2020) Betting on bitcoin: does gambling volume on the blockchain explain bitcoin price changes? Econ Lett 191:108727\nCost of a 51% attack for different cryptocurrencies (2021). Accessed 27 Dec 2021 from https:\u002F\u002Fwww.crypto51.app\u002F\nCuesta-Albertos J, Gordaliza A, Matrán C (1997) Trimmed k-means: an attempt to robustify quantizers. Annal Stat 25:553–576\nDanovitch JH, Keil FC (2004) Should you ask a fisherman or a biologist?: Developmental shifts in ways of clustering knowledge. Child Devel 75(3):918–931\nDing C, He X (2004) K-means clustering via principal component analysis. In: Proceedings of the twenty-first international conference on Machine learning, p 29\nDouglas S (2006) K-means clustering: a half-century synthesis. Br J Math Stat Psychol 59(1):1–34\nDunteman GH (1989) Principal components analysis\nFoley S, Karlsen JR, Putniņš TJ (2019) Sex, drugs, and bitcoin: how much illegal activity is financed through cryptocurrencies? Rev Financ Stud 32(5):1798–1853\nHan W et al (2020) Darknet and bitcoin de-anonymization: Emerging development. In: 2020 zooming innovation in consumer technologies conference (ZINC), pp 222–226\nHarlev MA et al (2018) Breaking bad: de-anonymising entity types on the bitcoin blockchain using supervised machine learning. In: Proceedings of the 51st Hawaii international conference on system sciences\nHarrigan M, Fretter C (2016) The unreasonable effectiveness of address clustering. In: 2016 Intl IEEE conferences on ubiquitous intelligence computing, advanced and trusted computing, scalable computing and communications, cloud and big data computing, internet of people, and smart world congress (UIC\u002FATC\u002FScalCom\u002FCBDCom\u002FIoP\u002FSmartWorld), pp 368–373\nHerrera-Joancomartí J (2014) Research and challenges on bitcoin anonymity. In: Data privacy management, autonomous spontaneous security, and security assurance. Springer, pp 3–16\nHinton GE et al (1999) Unsupervised learning: foundations of neural computation\nHirshman J, Huang Y, Macke S (2013) Unsupervised approaches to detecting anomalous behavior in the bitcoin transaction network. In: Technical report, 3rd edn. Stanford University\nJanda A (2022) Bitcoin block explorer with address grouping and wallet labeling. Accessed 30 Dec 2022. https:\u002F\u002Fwww.walletexplorer.com\u002F\nJolliffe IT (2002) Springer series in statistics. Princ Comp Anal 29:1403\nJourdan M et al (2018) Characterizing entities in the bitcoin blockchain. In: 2018 IEEE international conference on data mining workshops (ICDMW), pp 55–62. https:\u002F\u002Fdoi.org\u002F10.1109\u002FICDMW.2018.00016\nKang C et al (2020) De-anonymization of the bitcoin network using address clustering. In: Zibin Z et al (eds) Blockchain and trustworthy systems. Springer, Singapore, pp 489–501\nKou G et al (2014) Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Inf Sci 275:1–12\nKou G et al (2021) Bankruptcy prediction for SMES using transactional data and two-stage multiobjective feature selection. Decis Supp Syst 140:113429\nLangley P et al (1994) Selection of relevant features in machine learning. Proc AAAI Fall Symp Relev 184:245–271\nLee C et al (2020) Toward detecting illegal transactions on bitcoin using machine-learning methods. In: Zibin Z et al (eds) Blockchain and trustworthy systems. 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China",[],{"title":1485},{"VI":1194},{"url":1470,"publisher":1487,"properties":1532},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":1488,"slug":872,"properties":1489,"entityType":25,"verifyStatus":878,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":1492,"manageAffiliations":1501,"indexDatabases":1512,"url":938,"thumbnailPath":28,"statistic":1527,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":1490,"title":1491},{"VOID":875},{"EN":877},[1493,1497],{"id":881,"createTime":28,"updateTime":28,"relativeEntities":1494,"label":1495,"description":1496,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":884},{},{"id":887,"createTime":28,"updateTime":28,"relativeEntities":1498,"label":1499,"description":1500,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":890},{},[1502,1507],{"id":894,"createTime":28,"updateTime":28,"relativeEntities":1503,"slug":28,"properties":1504,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1506,"statistic":28},[],{"title":1505},{"EN":898},[],{"id":901,"createTime":28,"updateTime":28,"relativeEntities":1508,"slug":28,"properties":1509,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1511,"statistic":28},[],{"title":1510},{"EN":905},[],[1513,1520],{"id":909,"indexDatabase":1514,"url":915,"indexYears":916,"academicFieldIds":1519,"indexDatabaseRanking":920},{"id":786,"createTime":28,"updateTime":28,"relativeEntities":1515,"label":1516,"description":1517,"key":792,"publicationTags":1518,"standard":28},[],{"EN":789,"VI":789},{"EN":789,"VI":791},[794],[918,919],{"id":922,"indexDatabase":1521,"url":934,"indexYears":28,"academicFieldIds":1526,"indexDatabaseRanking":28},{"id":924,"createTime":28,"updateTime":28,"relativeEntities":1522,"label":1523,"description":1524,"key":931,"publicationTags":1525,"standard":28},[],{"EN":927,"VI":927},{"EN":929,"VI":930},[933,813],[936,937],{"impactFactor":32,"impactFactorByYear":1528,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":123,"totalPublicationByYear":1529,"totalCitation":32,"totalCitationByYear":1530,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":1531,"hindexLast5Year":32,"hindex":32},{},{"2021":40,"2024":40},{},{},{"pages":1533,"volume":1534},{"VOID":1243},{"VOID":1535},"3","2017-09-21",2017,[933,920],{"id":1540,"createTime":1541,"updateTime":1542,"relativeEntities":1543,"slug":1544,"properties":1545,"entityType":965,"verifyStatus":26,"verifyTime":1542,"verifyNote":966,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":1554,"fullTextUrl":28,"authors":1555,"publicationType":1008,"publisherRelationship":1623,"citationCount":28,"citationInfo":28,"publishDate":1674,"publishYear":1675,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":1676,"openAccess":28,"references":28,"isForceReanalyzing":1058},"04dd59da-0f2f-4aab-891b-8cbcc7573cb2","2023-12-06T19:31:40.474+00:00","2024-12-15T09:20:40.507+00:00",[],"A-literature-review-and-integrated-framework-for-the-determinants-of-crowdfunding-success",{"abstract":1546,"title":1548,"references":1550,"doi":1552},{"EN":1547},"Crowdfunding is an innovative strategy for financing a new business venture from the general public instead of seeking funds in traditional ways, such as issuing bonds or bank lending. This study aims to identify the determinants affecting the success of a crowdfunding campaign and how different measurements for crowdfunding success, different crowdfunding models, and the selection of subdivided determinants influence the determinants’ impacts on crowdfunding success. We set the disciplines in the search strategy to select studies related to crowdfunding success. Ultimately, 94 empirical papers are selected to reveal the different findings for the determinants of crowdfunding success; based on this information, we construct an integrated framework for future research. There has been much research on project- and creator-related factors; however, many of these factors have inconsistent relationships with crowdfunding success due to varying measurements of success. In particular, different measurements used within the same study for determinants or crowdfunding success may also produce inconsistent results. In addition, different crowdfunding models of a project have been found to induce additional findings. Our review of the determinants of crowdfunding success and the definitions of the determinants, as well as the proposed integrated framework, can help focus future work on relatively new or unique determinants rarely addressed in the existing literature. This work provides practical implications for both theory and practice, and directions for future research.",{"EN":1549},"A literature review and integrated framework for the determinants of crowdfunding success",{"VOID":1551},"Agrawal AK, Catalini C, Goldfarb A (2011) The geography of crowdfunding. In: Working paper. w16820, N.B.O.E. Research\nAhlers GKC, Cumming DJ, Günther C, Schweizer D (2015) Signaling in equity crowdfunding. Entrep Theory Pract 39(4):955–980. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fetap.12157\nAllison TH, Davis BC, Short JC, Webb JW (2015) Crowdfunding in a prosocial microlending environment: examining the role of intrinsic versus extrinsic cues. Entrep Theory Pract 39(1):53–73. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fetap.12108\nAllison TH, Davis BC, Webb JW, Short JC (2017) Persuasion in crowdfunding: an elaboration likelihood model of crowdfunding performance. J Bus Ventur 32(6):707–725. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusvent.2017.09.002\nAnglin AH, Short JC, Drover W, Stevenson RM, McKenny AF, Allison TH (2018a) The power of positivity? The influence of positive psychological capital language on crowdfunding performance. J Bus Ventur 33(4):470–492. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusvent.2018.03.003\nAnglin AH, Wolfe MT, Short JC, McKenny AF, Pidduck RJ (2018b) Narcissistic rhetoric and crowdfunding performance: a social role theory perspective. J Bus Ventur 33(6):780–812. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusvent.2018.04.004\nBeier M, Wagner K (2015) Crowdfunding success: a perspective from social media and e-commerce. In: Thirty sixth international conference on information systems (ICIS), Fort Worth, Twxas.\nBelleflamme P, Lambert T, Schwienbacher A (2014) Crowdfunding: tapping the right crowd. J Bus Ventur 29(5):585–609. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusvent.2013.07.003\nBelleflamme P, Omrani N, Peitz M (2015) The economics of crowdfunding platforms. Inf Econ Policy 33:11–28. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.infoecopol.2015.08.003\nBengtson B (2019) A comparative study on the effect of environmental social value statements on crowdfunding success across various crowdfunding platforms. In: Working paper\nBoeuf B, Darveau J, Legoux R (2014) Financing creativity: crowdfunding as a new approach for theatre projects. Int J Arts Manag 16(3):33–48\nBorrero-Domínguez C, Cordón-Lagares E, Hernández-Garrido R (2020) Sustainability and real estate crowdfunding: success factors. Sustainability 12(12):5136. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu12125136\nBurtch G, Ghose A, Wattal S (2013) An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets. Inf Syst Res 24(3):499–519. https:\u002F\u002Fdoi.org\u002F10.1287\u002Fisre.1120.0468\nBurtch G, Ghose A, Wattal S (2014) Cultural differences and geography as determinants of online prosocial lending. MIS Q 38(3):773–794\nBurtch G, Ghose A, Wattal S (2016) Secret admirers: an empirical examination of information hiding and contribution dynamics in online crowdfunding. Inf Syst Res 27(3):478–496. https:\u002F\u002Fdoi.org\u002F10.1287\u002Fisre.2016.0642\nButticè V, Colombo MG, Wright M (2017) Serial crowdfunding, social capital, and project success. Entrep Theory Pract 41(2):183–207. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fetap.12271\nCappa F, Pinelli M, Maiolini R, Leone MI (2021) “Pledge” me your ears! The role of narratives and narrator experience in explaining crowdfunding success. Small Bus Econ 57(2):953–973. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11187-020-00334-y\nChan CSR, Parhankangas A (2017) Crowdfunding innovative ideas: how incremental and radical innovativeness influence funding outcomes. Entrep Theory Pract 41(2):237–263. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fetap.12268\nChan HF, Moy N, Schaffner M, Torgler B (2021) The effects of money saliency and sustainability orientation on reward based crowdfunding success. J Bus Res 125:443–455. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusres.2019.07.037\nChaney D (2019) A principal–agent perspective on consumer co-production: crowdfunding and the redefinition of consumer power. Technol Forecast Soc Chang 141:74–84. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.techfore.2018.06.013\nColombo MG, Franzoni C, Rossi-Lamastra C (2015) Internal social capital and the attraction of early contributions in crowdfunding. Entrep Theory Pract 39(1):75–100. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fetap.12118\nCordova A, Dolci J, Gianfrate G (2015) The determinants of crowdfunding success: evidence from technology projects. Procedia Soc Behav Sci 181:115–124. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.sbspro.2015.04.872\nCourtney C, Dutta S, Li Y (2017) Resolving information asymmetry: signaling, endorsement, and crowdfunding success. Entrep Theory Pract 41(2):265–290. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fetap.12267\nCrosetto P, Regner T (2014) Crowdfunding: determinants of success and funding dynamics. In: Working paper. 2014–035, M.P.I.O. Economics\nCumming DJ, Leboeuf Gl, Schwienbacher A (2015) Crowdfunding models: Keep-it-all vs. all-or-nothing. In: Working paper\nDa Cruz JV (2018) Beyond financing: crowdfunding as an informational mechanism. J Bus Ventur 33(3):371–393. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusvent.2018.02.001\nDavis BC, Hmieleski KM, Webb JW, Coombs JE (2017) Funders’ positive affective reactions to entrepreneurs’ crowdfunding pitches: the influence of perceived product creativity and entrepreneurial passion. J Bus Ventur 32(1):90–106. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jbusvent.2016.10.006\nDu Q, Fan W, Qiao Z, Wang G, Zhang X, Zhou M (2015) Money talks: A predictive model on crowdfunding success using project description. In: Twenty-first Americas Conference on Information Systems (AMCIS), Puerto Rico.\nDuan Y, Hsieh T-S, Wang RR, Wang Z (2020) Entrepreneurs’ facial trustworthiness, gender, and crowdfunding success. 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research seeks to contribute to Bitcoin pricing analysis based on the dynamics between variables of attractiveness and the value of the digital currency. Using the error correction model, the relationship between the price of the virtual currency, Bitcoin, and the number of Google searches that used the terms bitcoin, bitcoin crash and crisis between December 2012 and February 2018 is analyzed. The study also applied the same analysis to prices of Bitcoin denominated in different sovereign currencies traded during the same period. The Johansen (J Econ Dyn Control 12:231-254, 1988) test demonstrates that the price and number of searches on Google for the first two terms are cointegrated. This research indicates that there are strong short-term and long-term dynamics among attractiveness factors, suggesting that an increase in worldwide interest in Bitcoin is usually preceded by a price increase. In contrast, an increase in market mistrust over a collapse of the currency, as measured by the term bitcoin crash, is followed by a fall in price. Intense world economic crisis events appear to have a strong impact on interest in the virtual currency. This study demonstrates that during a worldwide crisis Bitcoin becomes an alternative investment, increasing its price. Based on it, bitcoin may be used as a safe haven by the financial market and its intrinsic characteristics might help the investors and governments to find new mechanisms to deal with monetary transactions.",{"EN":1687},"Bitcoin pricing: impact of attractiveness variables",{"VOID":1689},"Akaike H (1969) Fitting autoregressive models for prediction. Ann Inst Stat Math 21:243–247\nAl-Khazali O, Bouri E, Roubaud D (2018) The impact of positive and negative macroeconomic news surprises: gold versus Bitcoin. Econ Bull, AccessEcon 38:373–382\nBacen. Comunicado n° 31.379, de 16 de novembro de 2017. 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Financ Innov",{"VOID":1691},"10.1186\u002Fs40854-020-00176-3","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-020-00176-3",[1694],{"id":1695,"sortIndex":32,"researcher":28,"roles":1696,"affiliations":1697,"properties":1706,"displayName":1708,"givenName":28,"familyName":28},"c513479d-728f-44ed-b26e-a30a726a49e8",[972],[1698],{"id":1699,"sortIndex":32,"affiliation":1700,"properties":28},"128020c4-4b29-46cf-9ebe-13aebf436ed2",{"id":1699,"createTime":28,"updateTime":28,"relativeEntities":1701,"slug":28,"properties":1702,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1705,"statistic":28},[],{"title":1703},{"VI":1704},"Sao Paulo School Of Economics (FGV), Sao Paulo, Brazil",[],{"title":1707},{"VI":1708},"Rodrigo Hakim das Neves",{"url":1692,"publisher":1710,"properties":1755},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":1711,"slug":872,"properties":1712,"entityType":25,"verifyStatus":878,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":1715,"manageAffiliations":1724,"indexDatabases":1735,"url":938,"thumbnailPath":28,"statistic":1750,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":1713,"title":1714},{"VOID":875},{"EN":877},[1716,1720],{"id":881,"createTime":28,"updateTime":28,"relativeEntities":1717,"label":1718,"description":1719,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":884},{},{"id":887,"createTime":28,"updateTime":28,"relativeEntities":1721,"label":1722,"description":1723,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":890},{},[1725,1730],{"id":894,"createTime":28,"updateTime":28,"relativeEntities":1726,"slug":28,"properties":1727,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1729,"statistic":28},[],{"title":1728},{"EN":898},[],{"id":901,"createTime":28,"updateTime":28,"relativeEntities":1731,"slug":28,"properties":1732,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1734,"statistic":28},[],{"title":1733},{"EN":905},[],[1736,1743],{"id":909,"indexDatabase":1737,"url":915,"indexYears":916,"academicFieldIds":1742,"indexDatabaseRanking":920},{"id":786,"createTime":28,"updateTime":28,"relativeEntities":1738,"label":1739,"description":1740,"key":792,"publicationTags":1741,"standard":28},[],{"EN":789,"VI":789},{"EN":789,"VI":791},[794],[918,919],{"id":922,"indexDatabase":1744,"url":934,"indexYears":28,"academicFieldIds":1749,"indexDatabaseRanking":28},{"id":924,"createTime":28,"updateTime":28,"relativeEntities":1745,"label":1746,"description":1747,"key":931,"publicationTags":1748,"standard":28},[],{"EN":927,"VI":927},{"EN":929,"VI":930},[933,813],[936,937],{"impactFactor":32,"impactFactorByYear":1751,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":123,"totalPublicationByYear":1752,"totalCitation":32,"totalCitationByYear":1753,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":1754,"hindexLast5Year":32,"hindex":32},{},{"2021":40,"2024":40},{},{},{"pages":1756,"volume":1758},{"VOID":1757},"1-18",{"VOID":1344},"2020-04-13",[933,920],{"id":1762,"createTime":1763,"updateTime":1764,"relativeEntities":1765,"slug":1766,"properties":1767,"entityType":965,"verifyStatus":26,"verifyTime":1764,"verifyNote":966,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":1776,"fullTextUrl":28,"authors":1777,"publicationType":1008,"publisherRelationship":1834,"citationCount":28,"citationInfo":28,"publishDate":1884,"publishYear":1675,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":1885,"openAccess":28,"references":28,"isForceReanalyzing":1058},"05878ca7-fe3e-4dc5-967d-66a91155eaf2","2024-01-04T09:39:01.616+00:00","2025-01-06T15:36:51.207+00:00",[],"Hybrid-data-decomposition-based-deep-learning-for-Bitcoin-prediction-and-algorithm-trading",{"abstract":1768,"title":1770,"references":1772,"doi":1774},{"EN":1769},"In recent years, Bitcoin has received substantial attention as potentially high-earning investment. However, its volatile price movement exhibits great financial risks. Therefore, how to accurately predict and capture changing trends in the Bitcoin market is of substantial importance to investors and policy makers. However, empirical works in the Bitcoin forecasting and trading support systems are at an early stage. To fill this void, this study proposes a novel data decomposition-based hybrid bidirectional deep-learning model in forecasting the daily price change in the Bitcoin market and conducting algorithmic trading on the market. Two primary steps are involved in our methodology framework, namely, data decomposition for inner factors extraction and bidirectional deep learning for forecasting the Bitcoin price. Results demonstrate that the proposed model outperforms other benchmark models, including econometric models, machine-learning models, and deep-learning models. Furthermore, the proposed model achieved higher investment returns than all benchmark models and the buy-and-hold strategy in a trading simulation. The robustness of the model is verified through multiple forecasting periods and testing intervals.",{"EN":1771},"Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading",{"VOID":1773},"Altan A, Karasu S, Bekiros S (2019) Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques. Chaos Soliton Fract 126:325–336\nAtsalakis GS, Atsalaki IG, Pasiouras F, Zopounidis C (2019) Bitcoin price forecasting with neuro-fuzzy techniques. Eur J Oper Res 276(2):770–780\nBaur DG, Dimpfl T (2019) Price discovery in bitcoin spot or futures? J Futures Mark 39(3):803–817\nBöhme R, Christin N, Edelman B, Moore T (2015) Bitcoin: Economics, technology, and governance. 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Appl Soft Comput 84:105739",{"VOID":1775},"10.1186\u002Fs40854-022-00336-7","https:\u002F\u002Fjfin-swufe.springeropen.com\u002Farticles\u002F10.1186\u002Fs40854-022-00336-7",[1778,1793,1808,1821],{"id":1779,"sortIndex":32,"researcher":28,"roles":1780,"affiliations":1781,"properties":1790,"displayName":1792,"givenName":28,"familyName":28},"05a53550-1148-4953-bb73-86031f1f4da8",[972],[1782],{"id":1783,"sortIndex":32,"affiliation":1784,"properties":28},"0ad8f483-0b1f-465f-9231-61757f9ca2ea",{"id":1783,"createTime":28,"updateTime":28,"relativeEntities":1785,"slug":28,"properties":1786,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1789,"statistic":28},[],{"title":1787},{"VI":1788},"Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China",[],{"title":1791},{"VI":1792},"Yuze 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government intervention is a striking characteristic of the Chinese stock market. This study develops a behavioral heterogeneous agent model (HAM) comprising fundamentalists, chartists, and stabilizers to investigate investors’ dynamic switching mechanisms under government intervention. The model introduces a new player, the stabilizer, into the HAM as a proxy for the government. We use the model to examine government programs during the 2015 China stock market crash and find that it can replicate the dynamics of investor sentiment and asset prices. In addition, our analysis of two simulations, specifically the data-generating processes and shock response analysis, further corroborates the key conclusion that our intervention model not only maintains market stability but also promotes the return of risk asset prices to their fundamental values. The study concludes that government interventions guided by the new HAM can alleviate the dilemma between reducing price volatility and improving price efficiency in future intervention programs.",{"EN":1896},"Government intervention model based on behavioral heterogeneity for China’s stock market",{"VOID":1898},"Akerlof GA, Shiller RJ (2009) Animal spirits: how human psychology drives the economy, and why it matters for global capitalism. Princeton University Press, Princeton\nBhanot K, Kadapakkam P (2006) Anatomy of a government intervention in index stocks: Price pressure or information effects? J Bus 79(2):963–986\nBoswijk HP, Hommes CH, Manzan S (2007) Behavioral heterogeneity in stock prices. J Econ Dyn Control 31(6):1938–1970\nBrock WA, Hommes CH (1997) A rational route to randomness. Econometrica 65(5):1059–1095\nBrock WA, Hommes CH (1998) Heterogeneous beliefs and routes to chaos in a simple asset pricing model. J Econ Dyn Control 22(8–9):1235–1274\nBrunnermeier MK, Sockin M, Xiong W (2021) China’s model of managing the financial system. Rev Econ Stud 89(6):3115–3153\nCampbell JY, Shiller RJ (1988) The dividend-price ratio and expectations of future dividends and discount factors. Rev Financ Stud 1(3):195–228\nChavas J-P (2000) On information and market dynamics: the case of the U.S. beef market. J Econ Dyn Control 24:833–853\nChen S-H, Chang C-L, Du Y-R (2012) Agent-based economic models and econometrics. Knowl Eng Rev 27(2):187–219\nChiarella C, He X-Z, Huang W, Zheng H (2012) Estimating behavioural heterogeneity under regime switching. J Econ Behav Organ 83(3):446–460\nChiarella C, He X-Z, Zwinkels RC (2014) Heterogeneous expectations in asset pricing: empirical evidence from the S&P500. J Econ Behav Organ 105:1–16\nChiarella C, ter Ellen S, He X-Z, Wu E (2015) Fear or fundamentals? Heterogeneous beliefs in the European sovereign CDS market. J Empir Financ 32:19–34\nDe Grauwe P (2012) Booms and busts in economic activity: a behavioral explanation. J Econ Behav Organ 83(3):484–501\nde Jong E, Verschoor WF, Zwinkels RC (2009) Behavioural heterogeneity and shift-contagion: evidence from the Asian crisis. J Econ Dyn Control 33(11):1929–1944\nde Jong E, Verschoor WF, Zwinkels RC (2010) Heterogeneity of agents and exchange rate dynamics: evidence from the EMS. J Int Money Financ 29(8):1652–1669\nDieci R, He X-Z (2018) Heterogeneous agent models in finance. In: Hommes C, LeBaron B (eds) Handbook of computational economics, vol 4. Elsevier, pp 257–328\nFama EF, French KR (2002) The equity premium. J Financ 57(2):637–659\nFranke R, Westerhoff F (2012) Structural stochastic volatility in asset pricing dynamics: estimation and model contest. J Econ Dyn Control 36(8):1193–1211\nFrijns B, Lehnert T, Zwinkels RC (2010) Behavioral heterogeneity in the option market. J Econ Dyn Control 34(11):2273–2287\nGrace MF, Rauch J, Wende S (2017) The effect of monetary policy announcements and government interventions on the US insurance industry during the 2007–2009 crisis. J Risk Financ 18(5):500–522\nHaritha PH, Rishad A (2020) An empirical examination of investor sentiment and stock market volatility: evidence from India. Financ Innov 6(1):34\nHe X-Z, Li K (2012) Heterogeneous beliefs and adaptive behaviour in a continuous-time asset price model. J Econ Dyn Control 36(7):973–987\nHe X-Z, Li K (2015) Profitability of time series momentum. J Bank Financ 53:140–157\nHe X-Z, Li Y (2015) Testing of a market fraction model and power-law behaviour in the dax 30. J Empir Financ 31:1–17\nHeemeijer P, Hommes C, Sonnemans J, Tuinstra J (2009) Price stability and volatility in markets with positive and negative expectations feedback: an experimental investigation. J Econ Dyn Control 33(5):1052–1072\nHommes C (2017) Booms, busts and behavioural heterogeneity in stock prices. J Econ Dyn Control 80:101–124\nHommes C, Sonnemans J, Tuinstra J, van de Velden H (2005) Coordination of expectations in asset pricing experiments. Rev Financ Stud 18(3):955–980\nHommes CH (2006) Heterogeneous agent models in economics and finance. in: Tesfatsion L, Judd KL (Eds), Handbook of computational economics. vol. 2. Elsevier, pp. 1109–1186\nHommes CH (2013) Behavioral rationality and heterogeneous expectations in complex economic systems. Cambridge University Press, Cambridge\nHu GX, Pan J, Wang J (2018) Chinese capital market: an empirical overview. National Bureau of Economic Research, Cambridge\nHuang Y, Miao J, Wang P (2019) Saving China’s stock market? IMF Econ Rev 67(2):349–394\nKeynes JM (1936) The general theory of employment, interest and money. Macmillan and Co, London\nLi Z, Jin L (2019) The “National Team” bailout, stock price volatility and idiosyncratic risk. J Manag Sci China 22(9):67–81\nLi Z, Jin L, Zhang Z (2019) Direct government intervention and systemic tail risk: evidence from the “National Team” stock rescue during the 2015 crash. Econ Res J 4:67–83\nLof M (2015) Rational speculators, contrarians, and excess volatility. Manag Sci 61(8):1889–1901\nLux T (2009) Stochastic behavioral asset-pricing models and the stylized facts. in: Hens T, SchenkHoppe KR (Eds), Handbook of financial markets: dynamics and evolution. Elsevier, pp. 161–215\nLux T (2012) Estimation of an agent-based model of investor sentiment formation in financial markets. J Econ Dyn Control 36(8):1284–1302\nMenkhoff L (2010) The use of technical analysis by fund managers: international evidence. J Bank Financ 34(11):2573–2586\nMenkhoff L, Taylor MP (2007) The obstinate passion of foreign exchange professionals: technical analysis. J Econ Lit 45(4):936–972\nSu Y, Yip Y, Wong RW (2002) The impact of government intervention on stock returns. Int Rev Econ Financ 11(3):277–297\nter Ellen S, Verschoor WF, Zwinkels RC (2013) Dynamic expectation formation in the foreign exchange market. J Int Money Financ 37:75–97\nter Ellen S, Zwinkels RC (2010) Oil price dynamics: a behavioral finance approach with heterogeneous agents. Energy Econ 32(6):1427–1434\nZeeman EC (1974) On the unstable behaviour of stock exchanges. J Math Econ 1(1):39–49\nZhang W, Yan K, Shen D (2021) Can the Baidu index predict realized volatility in the Chinese stock market? Financ Innov 7(1):7\nZhang W, Zhou Z-Q, Xiong X (2019) Behavioral heterogeneity and excess stock price volatility in China. 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