Name
Title | ||
|---|---|---|
Volatility Trading ia Temporal Pattern Recognition in Quantised Financial Time Series |
Abstract | ||
|---|---|---|
We investigate the potential of the analysis of noisy non-stationary time series by quantizing it into streams of discrete symbols and applying finite-memory symbolic predictors. Careful quantization can reduce the noise in the time series to make model estimation more amenable. We apply the quantization strategy in a realistic setting involving financial forecasting and trading. In particular, using historical data, we simulate the trading of straddles on the financial indexes DAX and FTSE 100 ... |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/PL00010989 | Pattern Anal. Appl. |
Keywords | Field | DocType |
Keywords:Fractal geometry,Markov models,Options,Prediction suffix trees,Straddle,Volatility | Econometrics,Categorical variable,Artificial intelligence,Artificial neural network,Volatility (finance),Pattern recognition,Markov model,Fractal,Parametric statistics,Straddle,Autoregressive conditional heteroskedasticity,Finance,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
4 | 4 | 1433-7541 |
Citations | PageRank | References |
5 | 0.79 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tino P. | 1 | 1606 | 155.22 |
| Christian Schittenkopf | 2 | 55 | 6.95 |
| Georg Dorffner | 3 | 461 | 103.97 |