This paper presents a detailed analysis of the application of Hardware Transactional Memory (HTM) support for loop parallelization with Thread-Level Speculation (TLS). As a result it provides three contributions: (a) it shows that performance issues well-known to loop parallelism (e.g. false sharing) are exacerbated in the presence of HTM, and that capacity aborts can increase when one tries to overcome them, (b) it reveals that, although modern HTM extensions can provide support for TLS, they are not powerful enough to fully implement TLS, (c) it shows that simple code transformations, such as judicious strip mining and privatization techniques, can overcome such shortcomings, delivering speed-ups for programs that contain loop-carried dependencies. Experimental results reveal that, when these code transformations are used, speed-ups of up to 30% can be achieved for some loops for which previous research had reported slowdowns.