Information arrival as price jumps

We propose two new risk measures (i-beta and i-gamma) for a stock, which aim to distinguish between noise and information. Noise allows the stock price evolution to happen along a continuous path. Market wide economic information is transmitted via price jumps. Noise is idiosyncratic and does not propagate across securities. The main contribution is the development of an exact closed-form non-parametric jump risk estimator that boosts the 'signal-to-noise' ratio by utilizing co-skew moments. Empirically, the procedure is used to extract the i-beta and i-gamma for Google and Yahoo on NASDAQ, and provide a possible explanation of their seemingly low Sharpe ratio during the 2006-2008 period based on their asymmetrically high i-beta value.