Intangible assets and innovation have been a topic with increased importance during the last decades. Despite of this, common stock valuation methods only use financial data and ignore the intangible assets in valuation process. This thesis examines how intangibles can improve valuation accuracy by using a two stage-process where we start with share price valuation of five different companies through Free-Cash-Flow (FCF) model and an alternative Dividend Discount Model (DDM) with financial data input from the last ten years, followed by sensitivity analysis. In second stage we add innovation parameters in valuation process to see if the FCF-model can be improved or adjusted. These innovation parameters are: (1) R&D spending, (2) Patent applications, and (3) New product releases. Both FCF- and DDM-models are very sensitive to the input variable assumptions made regarding future growth rates and weighted average cost of capital for instance. Even the smallest change in these variables in a sensitivity analysis can easily double or half the output; share price. There is also very difficult to handle stochastic macro-economy disturbances like the financial crisis in recent years (2007-2010). These models could therefore only be used as a rough estimation of stock price levels and the fine tuning with innovation variables becomes irrelevant. Four out of five companies studied fall short compared to actual share price level, however, the two that comes closest to our valuation are also those with highest R&D spending in absolute values. It also seems that the company with highest deviation from our valuation has recently made a strategic redirection of R&D spending. Both these findings indicate that further research of R&D spending in relation to company value might be an interesting topic to explore. Patent applications and new product releases are difficult to interpret because possible contribution to future company profit can vary tremendously between each new patent and product. Nevertheless, there is a clear sign of change in patent application behavior by some of the companies. Reason for this is not explored and could be studied further. Analysis of new product releases could not be performed since reliable and structured data was not found.