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This paper introduces MarketSenseAI, an innovative framework leveraging GPT-4's advanced reasoning for selecting stocks in financial markets.
Finbert: Financial sentiment analysis with pre-trained language models
Araci, D., 2019 · 1908
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Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
Efron, B., Tibshirani, R., 1986 · 1986
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Momentum and autocorrelation in stock returns
Lewellen, J., 2002 · 2002
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Fluctuations and response in financial markets: the subtle nature ofrandom’price changes
Bouchaud, J.P., Gefen, Y., Potters, M., Wyart, M., 2003 · 2003
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The efficient market hypothesis and its critics
Malkiel, B.G., 2003 · 2003
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More than words: Quantifying language to measure firms’ fundamentals
Tetlock, P.C., Saar-Tsechansky, M., Macskassy, S., 2008 · 2008
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Estimating the impact of good news on stock market volatility
Malik, F., 2011 · 2011
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Passive investing and market liquidity
Goyal, A., He, Z., 2015 · 2015
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Financial institutions, markets, and money
Kidwell, D.S., Blackwell, D.W., Whidbee, D.A., 2016 · 2016
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Behavioral biases in pension fund trustees’ decision making
Weiss-Cohen, L., Ayton, P., Clacher, I., Thoma, V., 2019 · 2019
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Impact of news-based equity market volatility on international stock markets
Alqahtani, A., Wither, M.J., Dong, Z., Goodwin, K.R., 2020 · 2020
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Value investing: from Graham to Buffett and beyond
Greenwald, B.C., Kahn, J., Bellissimo, E., Cooper, M.A., Santos, T., 2020 · 2020
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Mpnet: Masked and permuted pre-training for language understanding
Song, K., Tan, X., Qin, T., Lu, J., Liu, T.Y., 2020 · 2020
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The role of reddit in the gamestop short squeeze
Anand, A., Pathak, J., 2022 · 2022
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A survey for in-context learning
Dong, Q., Li, L., Dai, D., Zheng, C., Wu, Z., Chang, B., Sun, X., Xu, J., Sui, Z., 2022 · 2022
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Drawdown measures: Are they all the same?
Korn, O., Möller, P.M., Schwehm, C., 2022 · 2022
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Deep learning enhancing banking services: a hybrid transaction classification and cash flow prediction approach
Kotios, D., Makridis, G., Fatouros, G., Kyriazis, D., 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q.V., Zhou, D., et al., 2022 · 2022
Cited alongside, same era.
Cognitive network science reveals bias in gpt-3, gpt-3.5 turbo, and gpt-4 mirroring math anxiety in high-school students
Abramski, K., Citraro, S., Lombardi, L., Rossetti, G., Stella, M., 2023 · 2023
Cited alongside, same era.
Harnessing the power of chatgpt for automating systematic review process: Methodology, case study, limitations, and future directions
Alshami, A., Elsayed, M., Ali, E., Eltoukhy, A.E., Zayed, T., 2023 · 2023
Cited alongside, same era.
Cognitive biases in natural language: Automatically detecting, differentiating, and measuring bias in text
Atreides, K., Kelley, D., 2023 · 2023
Gpteval: Nlg evaluation using gpt-4 with better human alignment
Liu, Y., Iter, D., Xu, Y., Wang, S., Xu, R., Zhu, C., 2023 · 2023
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Can chatgpt forecast stock price movements? return predictability and large language models
Lopez-Lira, A., Tang, Y., 2023 · 2023
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Marketdigest
Metaxas, K., 2023 · 2023
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Experimental evidence on the productivity effects of generative artificial intelligence
Noy, S., Zhang, W., 2023 · 2023
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Artificial intelligence, machine learning and big data in finance: Opportunities, challenges, and implications for policy makers
OECD, 2021 · 2023
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Cited alongside, same era.
Market dysfunction and central bank tools
BIS, 2022 · 2023
Cited alongside, same era.
What’s an “algo wheel?” and why should you care? | bloomberg professional services
Bloomberg, 2019 · 2023
Cited alongside, same era.
How does zero-day-to-expiry options trading affect the volatility of underlying assets?
Brogaard, J., Han, J., Won, P.Y., 2023 · 2023
Cited alongside, same era.
Can gpt models be financial analysts? an evaluation of chatgpt and gpt-4 on mock cfa exams
Callanan, E., Mbakwe, A., Papadimitriou, A., Pei, Y., Sibue, M., Zhu, X., Ma, Z., Liu, X., Shah, S., 2023 · 2023
Cited alongside, same era.
Langchain
Chase, H., 2022 · 2023
Cited alongside, same era.
Chatgpt informed graph neural network for stock movement prediction
Chen, Z., Zheng, L.N., Lu, C., Yuan, J., Zhu, D., 2023 · 2023
Cited alongside, same era.
The Economic Potential of Generative AI: The Next Productivity Frontier
Chui, M., Hazan, E., Roberts, R., Singla, A., Smaje, K., Sukharevsky, A., Yee, L., Zemmel, R., 2023 · 2023
Cited alongside, same era.
Shu, L., Wichers, N., Luo, L., Zhu, Y., Liu, Y., Chen, J., Meng, L., 2023 · 2023
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Do llms exhibit human-like response biases? a case study in survey design
Tjuatja, L., Chen, V., Wu, S.T., Talwalkar, A., Neubig, G., 2023 · 2023
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Bloomberggpt: A large language model for finance
Wu, S., Irsoy, O., Lu, S., Dabravolski, V., Dredze, M., Gehrmann, S., Kambadur, P., Rosenberg, D., Mann, G., 2023 · 2023
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Temporal data meets llm–explainable financial time series forecasting
Yu, X., Chen, Z., Ling, Y., Dong, S., Liu, Z., Lu, Y., 2023 · 2023
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Chatgpt: Unlocking the future of nlp in finance
Zaremba, A., Demir, E., 2023 · 2023
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Can anybody beat the market?
Fontinelle, A., 2022 · 2024
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Sentiment trading with large language models
Kirtac, K., Germano, G., 2024 · 2024
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Bondgpt: Introducing ltx’s generative ai application for corporate bond trading
LTXtrading, 2023 · 2024
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Morgan stanley wealth management deploys gpt-4 to organize its vast knowledge base
OpenAI, 2023b · 2024
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Magnificent 7 stocks: What you need to know
Thompson, C., 2023 · 2024
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