FinLlama: Financial Sentiment Classification for Algorithmic Trading Applications

arXiv:2403.12285v1 Announce Type: cross
Abstract: There are multiple sources of financial news online which influence market movements and trader's decisions. This highlights the need for accurate sentiment analysis, in addition to having appropriate algorithmic trading techniques, to arrive at better informed trading decisions. Standard lexicon based sentiment approaches have demonstrated their power in aiding financial decisions. However, they are known to suffer from issues related to context sensitivity and word ordering. Large Language Models (LLMs) can also be used in …

abstract analysis applications arxiv classification cs.cl cs.lg decisions financial highlights influence market movements multiple power q-fin.st q-fin.tr sentiment sentiment analysis standard trading type