As the world move towards knowledge based economy, it becomes increasingly important to understand and value intangible assets of a firm. In order to understand these intangible assets, it is important to understand their value generation ability. In other words, one way to know these intangible assets of a firm is to understand their efficiency in value creation. A. Pulic, devised an firm efficiency measurement called value added intellectual coefficient (VAIC). This index looks beyond the traditional accounting method and calculates overall resource utilization efficiency of a firm. This efficiency index in turn, reflects on the intellectual capital of a firm. VAIC as described by A. Pulic, is made on three efficiency components human capital efficiency (HCE), structural capital efficiency (SCE) and capital employed efficiency (CEE). Since the publication of VAIC methodology, researchers have tried to understand whether this efficiency index of VAIC correlates with traditional firm performance like its market valuation (M/B) and return on equity (ROE). A good correlation between VAIC and dependent variables like M/B and ROE will help investors (stakeholders) to understand intellectual capital of a firm. This understanding of firm efficiency can help an investment firm or an investor to make better investment decision. In this thesis, a multilinear regression approach was adopted to investigate correlation between independent variables like (VAIC,HCE, SCE and CEE) and dependent variables like market valuation (M/B) and return on equity (ROE). In addition, two moderating variables (age of firm and size of firm) were also explored. These variables were selected because of learning effect theory ; as firm grows old (age of a firm) or increase in size (market valuation) they undergo learning effect, which should be reflected in their efficiency. In order to empirically investigate, one needs to define the scope of the research to a specific industry and country. The main research question of thesis is " In the context of US biotech firms, what is the relationship between firm value efficiency and traditional financial parameters ?" VAIC, M/B and ROE data from 53 biotech companies was collected for 2011, 2012 and 2013. Results of linear regression analysis did not indicate any relationship between VAIC and M/B. However, it exhibited moderately positive relationship between VAIC and ROE (for year 2011 and 2012). A multilinear regression analysis between components of VAIC (HCE, SCE and CEE) and dependent variables was conducted. Here, only HCE exhibited moderately positive relationship with ROE, while M/B did not exhibit significant relationship with any of the VAIC components. Low positive correlation between ROE and VAIC was due to extreme negative data points which distorted the relationship. Hence, for future research it is important to screen the firms in detail and only include the firms that are beyond start up and development phase. In other words, include firms that have at least one product in the market. Practical relevance of this research is to leverage the knowledge of correlations discovered in this research . A software or mobile app can be designed by using the results discussed in this research to screen and shortlist equities for investment. Hence, an application/software like this can guide people without financial background to make investment decisions.