Name
Abstract | ||
|---|---|---|
Price manipulation refers to the act of using illegal trading behaviour to manually change an equity price with the aim of making profits. With increasing volumes of trading, price manipulation can be extremely damaging to the proper functioning and integrity of capital markets. Effective approaches for analysing and real-time detection of price manipulation are yet to be developed. This paper proposes a novel approach, called Hidden Markov Model with Abnormal States (HMMAS), which models and detects price manipulation activities. Together with the wavelet decomposition for features extraction and Gaussian Mixture Model for Probability Density Function (PDF) construction, the HMMAS model detects price manipulation and identifies the type of the detected manipulation. Evaluation experiments of the model were conducted on six stock tick data from NASDAQ and London Stock Exchange (LSE). The results showed that the proposed HMMAS model can effectively detect price manipulation patterns. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SMC.2013.514 | SMC |
Keywords | Field | DocType |
gaussian mixture model,detects price manipulation activity,detecting stock price manipulation,price manipulation,proposed hmmas model,hmmas model detects price,abnormal states,hidden markov model,equity price,illegal trading behaviour,price manipulation pattern,pricing,gaussian processes,wavelet transforms,hidden markov models,probability | Econometrics,Anomaly detection,Actuarial science,Capital market,Computer science,Stock exchange,Artificial intelligence,Hidden semi-Markov model,Markov model,Equity (finance),Hidden Markov model,Machine learning,Mixture model | Conference |
ISSN | Citations | PageRank |
1062-922X | 4 | 0.50 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yi Cao | 1 | 48 | 9.30 |
| Yuhua Li | 2 | 1113 | 53.63 |
| Sonya Coleman | 3 | 11 | 2.12 |
| Ammar Belatreche | 4 | 256 | 23.11 |
| T. Martin Mcginnity | 5 | 518 | 66.30 |