FinGPT-Open-Source-Financial-Large-Language-Models

Company filings and announcements are official docu-High dynamism:The financial landscape is perpetuallyments that corporations submit to regulatory bodies,provid-evolving,with a daily influx of news,social media posts,ing insight into a company's financial health and strategic di-and other market-related information.It's impractical andrection.They feature:cost-prohibitive to retrain models frequently to cope withGranularity:These documents offer granular informationthese changes.about a company's financial status,including assets,liabil-.Low signal-to-noise ratio(SNR):Financial data often ex-ities,revenue,and profitability.hibit a low signal-to-noise ratio [Liu et al.,2022.meaningReliability:Company fillings contain reliable and verifiedthat the useful information is usually dwarfed by a substan-data vetted by regulatory bodiestial amount of irrelevant or noisy data.Extracting valuableinsights from this sea of information necessitates sophisti-Periodicity:Company fillings are periodic,usually sub-cated techniquesmitted on a quarterly or annual basis,offering regular snap-shots of a company's financial situation.Addressing these challenges is critical for the effective uti-Impactfulness:Company announcements often have sub-lization of financial data and maximizing the potential of Fin-stantial impacts on the market,influencing stock prices andLLMs.As we navigate these challenges,we propose an open-source framework FinGPT.investor sentiment.Social media discussions related to finance can reflect4public sentiment towards specific stocks,sectors,or the over-Overview of FinGPT:An Open-Sourceall market.These discussions tend to exhibit:Framework for FinLLMsVariability:Social media discussions vary widely in tone,FinGPT represents an innovative open-source frameworkcontent,and quality,making them rich,albeit complex,designed specifically for applying large language modelssources of infommation.(LLMs)within the financial domain.As delineated in Fig.Real-time sentiment:These platforms often capture real-1,FinGPT consists of four fundamental components:Datatime market sentiment,enabling the detection of trends andSource,Data Engineering,LLMs,and Applications.Each ofshifts in public opinionthese components plays a crucial role in maintaining the func-tionality and adaptability of FinGPT in addressing dynamicVolatility:Sentiments expressed on social media can befinancial data and market conditions.highly volatile,changing rapidly in response to news eventsor market movements.Data source layer:The starting point of the FinGPTTrends.often observable through websites like Seekingpipeline is the Data Source Layer,which orchestrates theAlpha,Google Trends,and other finance-oriented blogs andacquisition of extensive financial data from a wide arrayof online sources.This layer ensures comprehensive mar-forums,offer critical insights into market movements and in-vestment strategies.They feature:ket coverage by integrating data from news websites,socialmedia platfo