Abstract Purpose – The purpose of this paper is to test an augmented technology acceptance model (TAM) in the online financial trading context. This research aims to investigate how e‐investors are influenced by perceived trust, security, and privacy jointly with traditional TAM constructs. Design/methodology/approach – The research examines e‐investors' behavioral intention to use online dealers' and stockbrokers' services. The model suggests that perceived trust jointly with perceived usefulness and perceived ease of use are important antecedents of intentions; the hypotheses are statistically tested using structural modeling. Findings – The results from this study suggest that perceived trust, usefulness and ease of use are important issues in online trading systems. The findings suggest that online financial dealers and stockbrokers must improve the security of the online system since e‐investors form perceptions about its perceived security and when these perceptions are confirmed, their trust is enhanced and consequently they are more likely to use these online services particularly if the financial information is useful for their purposes. Research limitations/implications – The findings of the present study have various implications for research as well as practice. First, perceived trust, perceived usefulness and perceived ease of use are critical to the success of an online trading system. Second, perceived privacy did not influence users' beliefs in trust. Since perceived trust and perceived usefulness are the most important antecedents of behavioral intention, managers can increase e‐investors' usage intention by improving their beliefs in how the online trading system can enhance their performance and effectiveness using a system with enough security mechanisms. The major limitation is that trust is examined as a single‐dimension construct. Originality/value – This paper is one of the first that has empirically tested the link between trust, security, privacy, usefulness, ease of use and behavioral intention in the online trading context.