Computer Science – Computational Engineering – Finance – and Science
Scientific paper
2000-10-14
Computer Science
Computational Engineering, Finance, and Science
The conference version will appear in SODA 2001
Scientific paper
This paper initiates a study into the century-old issue of market predictability from the perspective of computational complexity. We develop a simple agent-based model for a stock market where the agents are traders equipped with simple trading strategies, and their trades together determine the stock prices. Computer simulations show that a basic case of this model is already capable of generating price graphs which are visually similar to the recent price movements of high tech stocks. In the general model, we prove that if there are a large number of traders but they employ a relatively small number of strategies, then there is a polynomial-time algorithm for predicting future price movements with high accuracy. On the other hand, if the number of strategies is large, market prediction becomes complete in two new computational complexity classes CPP and BCPP, which are between P^NP[O(log n)] and PP. These computational completeness results open up a novel possibility that the price graph of an actual stock could be sufficiently deterministic for various prediction goals but appear random to all polynomial-time prediction algorithms.
Aspnes James
Fischer David F.
Fischer Michael J.
Kao Ming-Yang
Kumar Alok
No associations
LandOfFree
Towards Understanding the Predictability of Stock Markets from the Perspective of Computational Complexity does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Towards Understanding the Predictability of Stock Markets from the Perspective of Computational Complexity, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Towards Understanding the Predictability of Stock Markets from the Perspective of Computational Complexity will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-158314