The price-volume relationship is one of the most studied in the field of finance when studying price dynamics. One of the oldest models used to study price-volume relationship is the model of Osborne (1959) who models the price as a diffusion process with its variance dependent on the quantity of transaction at that particular moment. Subsequent relevant work can be found in Karpoff (1987), Gallant et al. (1992), Bollerslev and Jubinski (1999), Lo and Wang (2002), and Sun (2003). In general this line of research studies the relationship between volume and some measure of variability of the stock price (e. g., the absolute deviation, the volatility, etc.). Most of these works use models in time, they are tested with low frequency data and the main conclusion is that the price of a specific equity exhibits larger variability in response to increased volume of trades. Engle and Russell (1998) use the Autoregressive Conditional Duration (ACD) model which considers the time between trades as a variable related to both price and volume. Bozdog et al. (2011) study the exception of the conclusion presented in the earlier literature, they do not consider models in time but rather make the change in price dependent on the volume directly. Authors present a methodology of detecting and evaluating unusual price movements defined as large change in price corresponding to small volume of trades. They classify these events as “rare” and show that the behavior of the equity price in the neighborhood of a rare event exhibits an increase in the probability of price recovery. The use of an arbitrary trading rule designed to take advantage of this observation indicates that the returns associated with such movements are significant. Bozdog et al. confirm the old Wall Street adage that “it takes volume to move prices” even in the presence of high frequency trading.