We　propose　a　three-state　microscopic　opinion　formation　model　for　the　purpose　of　simulating　the　dynamics　of　financial　markets.　In　order　to　mimic　the　heterogeneous　composition　of　the　mass　of　investors　in　a　market,　the　agent-based　model　considers　two　different　types　of　traders:　noise　traders　and　noise　contrarians.　Agents　are　represented　as　nodes　in　a　network　of　interactions　and　they　can　assume　any　of　three　distinct　possible　states.　The　time　evolution　of　the　state　of　an　agent　is　dictated　by　probabilistic　dynamics　that　include　both　local　and　global　influences.　A　noise　trader　is　subject　to　local　interactions,　tending　to　assume　the　majority　state　of　its　nearest　neighbors,　whilst　a　noise　contrarian　is　subject　to　a　global　interaction　with　the　behavior　of　the　market　as　a　whole,　tending　to　assume　the　state　of　the　global　minority　of　the　market.　The　model　exhibits　the　typical　qualitative　and　quantitative　features　of　real　financial　time　series,　including　distributions　of　returns　with　heavy　tails,　volatility　clustering　and　long-time　memory　for　the　absolute　values　of　the　returns.　The　distributions　of　returns　are　fitted　by　means　of　coupled　Gaussian　distributions,　quantitatively　revealing　transitions　between　leptokurtic,　mesokurtic　and　platykurtic　regimes　in　terms　of　a　non-linear　statistical　coupling　which　describes　the　complexity　of　the　system.　(C)　2021　Elsevier　B.V.　All　rights　reserved.