1) using Matched Pattern from 2000 stocks in last 5 years, matched the pattern of SPX over last 3 days, found similar patterns.
2) Use all matched patterns and perform Markov Chain Monte Carlo simulation, burning-in of first 1000 simulation to reduce predict errors.
3) APPLIED different weight, most recent data with higher weight and perform Bayesian adjustment.
4) Perform Bootstrap simulation to get p values and prediction confidences.
Knowledge need: Bayesian Analyses, Linear model, Pattern analyses, MCMC simulation, Bootstrap simulation, SAS, JAVA, GRAPH, finance knowledge....
Each run cover 2000 stocks*average 30 matched patterns*10000 MCMC simulations * 10000 Bootstrap simulations.
If you have better suggestion, welcomed to suggest. |