In this thesis we examine the ability of the log-periodic power law model to accurately predict the end of speculative bubbles on financial markets through modeling of asset price dynamics on a selection of historical bubbles. The methods we use are based on a nonlinear least squares estimation which yields predictions of when the bubble will change regime.We find evidence which support the occurrence of LPPL-patterns leading up to the change in regime; asset prices during bubble periods seem to oscillate around a faster-than-exponential growth. In most cases the estimation yields accurate predictions, although we conclude that the predictions are quite dependent on at which point in time the prediction is conducted. We also find that the end of a speculative bubble seems to be influenced by both endogenous speculative growth and exogenous factors. For this reason we propose a new way of interpreting the predictions of the model, where the end dates should be interpreted as the start of a time period where the asset prices are especially sensitive to exogenous events. We propose that negative news during this time period results in a regime shift of the bubble. This study is the first to address both the possibilities and the limitations of the LPPL-model, and should therefore be considered as a contribution to the academia.

In this paper, the price fluctuations of Bitcoin under speculative environment is studied. It has been seen that the market trend points out an existence of a speculative bubble. Over the course of the period from 2014 to 2018, the trend in price movements of bitcoin has proved to be strongly speculative. In that regard, investors might be curious about what drivers might be instrumental in these speculative price changes.  After reviewing of NPV, it was seen that NPV is not applicable to the case of cryptocurrencies due to their nature and lack of free cash flows to base the asset valuation to some fundamental facts. Later, LPPL model is reviewed, however, that also proved to be insufficient since it does not reflect the investor speculations and inform much about price dynamics regarding behavioral finance principles. Then, some papers from the past price fluctuations of bitcoin (for the period from 2010 to 2013) was reviewed and three key variables were determined which might explain price movements. Public interest towards Bitcoin as interest-driven, regulatory and political news about cryptocurrencies as event-driven and VIX as overall investor approach to Bitcoin market have been taken. After running regressions, the only significant variable happened to be public interest and popularity of Bitcoin. Although, for some cases, VIX variable also explain price fluctuations for some intervals, in none of the cases event-driven variable has long- terms effect on price fluctuations under speculative environment. Lastly, a robustness test is also handled considering the “weekend effect” and it has been seen public interest variable again proved to be a significant price determinant.