Kalman Filter For Arbitrage Identification In High Frequency Data
We present a methodology for modelling real world high frequency financial data.The methodology copes with the erratic arrival of data and is robust to additive outliers in the data set. Arbitrage pricing relationships are formulated into a linear state space representation.
Thomas And Patnaik-Serial Correlation In High-Frequency Data And The Link With Liquidity
This paper tests for market efficiency at high-frequencies of the Indian equity markets. Wedo this by testing the behaviour of serial correlation in firm stock prices using the Variance Ratio test on high frequency returns data. We find that at a frequency interval of five minutes,all the stocks show a pattern of mean-reversion. However, different […]