This paper investigates the information role of algorithmic traders (AT) in the Nifty index option market. I analyse a unique dataset to test for information-based trading by looking at the effect of net buying pressure of options on implied volatilities. According to the direction- learning hypothesis, (directional) informed investors’ net buying pressure of calls (puts) raises the implied volatilities of calls (puts) and lowers the implied volatilities of puts (calls). In addition, their net buying pressure can also predict future index returns. According to the volatility-learning hypothesis, (volatility) informed investors’ net buying pressure is always positively related to implied volatilities. I find that these relations do not hold for AT and, therefore, infer absence of information-based trading by AT. On the contrary, I find the direction-learning hypothesis to hold for non-AT who, in this market, are primarily individual investors.

Citation: The informational role of algorithmic traders in the option market, Rohini Grover. IGIDR Working Paper WP-2015-012 , May 2015.