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Stock Market Trading Based on Market Sentiments and Reinforcement Learning
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作者 K.M.Ameen Suhail Syam Sankar +5 位作者 Ashok S.Kumar Tsafack Nestor Naglaa F.Soliman Abeer D.Algarni Walid El-Shafai Fathi E.Abd El-Samie 《Computers, Materials & Continua》 SCIE EI 2022年第1期935-950,共16页
Stock market is a place,where shares of different companies are traded.It is a collection of buyers’and sellers’stocks.In this digital era,analysis and prediction in the stock market have gained an essential role in... Stock market is a place,where shares of different companies are traded.It is a collection of buyers’and sellers’stocks.In this digital era,analysis and prediction in the stock market have gained an essential role in shaping today’s economy.Stock market analysis can be either fundamental or technical.Technical analysis can be performed either with technical indicators or through machine learning techniques.In this paper,we report a system that uses a Reinforcement Learning(RL)network and market sentiments to make decisions about stock market trading.The system uses sentiment analysis on daily market news to spot trends in stock prices.The sentiment analysis module generates a unified score as a measure of the daily news about sentiments.This score is then fed into the RL module as one of its inputs.The RL section gives decisions in the form of three actions:buy,sell,or hold.The objective is to maximize long-term future profits.We have used stock data of Apple from 2006 to 2016 to interpret how sentiments affect trading.The stock price of any company rises,when significant positive news become available in the public domain.Our results reveal the influence of market sentiments on forecasting of stock prices. 展开更多
关键词 Deep learning machine learning daily market news reinforcement learning stock market
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Tung Pok Chin: A Paper Son Poet in New York
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作者 LAM Lap 《Frontiers of Literary Studies in China-Selected Publications from Chinese Universities》 2015年第4期635-665,共31页
Classical-style poetry is a neglected genre in the study of Chinese American literature. Except for the Angel Island Poetry and the Songs of Gold Mountain (Jinshan geji 金山歌集), no substantial research has been do... Classical-style poetry is a neglected genre in the study of Chinese American literature. Except for the Angel Island Poetry and the Songs of Gold Mountain (Jinshan geji 金山歌集), no substantial research has been done on the enormous amount of classical-style poems published in San Francisco and New York. This article attempts to explore this uncharted territory by examining the poetry of Tung Pok Chin 陈松柏 (1916-88, aka Lai Bing Chan 黎屏尘) and his story as a Chinese immigrant. Chin moved to the United States in 1934 as a paper son. He joined the American navy during World War II and eventually established his own laundry business in Brooklyn. Since the late 1940s, Chin published a significant amount of his classical-style poetry in the China Daily News (Meizhou huaqiao ribao 美洲华侨日报), a left-wing newspaper operated by the pro-communist Chinese Hand Laundry Alliance. With the help of his daughter, he also wrote a memoir in English narrating his assimilation into American society. His poetry, though not particularly refined, similarly records his experiences and comments regarding American life and politics. Based on the source materials found in the Tung Pok Chin Papers archived in New York University, his memoir, and the poems he published in the China Daily News, herein I illuminate how Chin adopted a traditional form of poetry as his expressive vehicle and, with the narrative power of his English memoir, how he used his poems to construct a social identity. The article also relates Chin's work to the broader context of Asian American studies, as well as the classical poetry community and its development in New York, and ponders his significances in the history of Chinese American literature. 展开更多
关键词 Tung Pok Chin New York Chinatown Chinese American literature paper son Chinese immigrants classical-style poetry China daily news Chinese Hand Laundry Alliance
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