TY - GEN
T1 - Extracting GARCH effects from ASSET returns using Robust NMF
AU - De Fréin, Ruairí
AU - Rickard, Scott
AU - Drakakis, Konstantinos
PY - 2009
Y1 - 2009
N2 - Identification of assets on the stock market that exhibit co-movement is a critical task for generating an efficiently diversified portfolio. We present a new application of non-negative matrix factorization to factor analysis of financial time series. We consider a conditionally heteroscedastic latent factor model, where each series is parameterized by a univariate ARCH model. Volatility clustering characteristics, e.g. GARCH effects, of the constituent assets of the Dow Jones Industrial Average are leveraged to cluster assets based on the commonality of their volatility clusters. We present a new non-negative matrix factorization algorithm which is robust in the presence of noise, Robust NMF. We use a mixed low-rank over-complete dictionary learning approach to separate out the background Gaussian noise, emphasize the GARCH effects and achieve clearer asset groupings.
AB - Identification of assets on the stock market that exhibit co-movement is a critical task for generating an efficiently diversified portfolio. We present a new application of non-negative matrix factorization to factor analysis of financial time series. We consider a conditionally heteroscedastic latent factor model, where each series is parameterized by a univariate ARCH model. Volatility clustering characteristics, e.g. GARCH effects, of the constituent assets of the Dow Jones Industrial Average are leveraged to cluster assets based on the commonality of their volatility clusters. We present a new non-negative matrix factorization algorithm which is robust in the presence of noise, Robust NMF. We use a mixed low-rank over-complete dictionary learning approach to separate out the background Gaussian noise, emphasize the GARCH effects and achieve clearer asset groupings.
KW - Autoregressive conditional heteroscedasticity
KW - Clustering
KW - Low rank decomposition
KW - Non-negative matrix factorization
KW - Sparseness
UR - http://www.scopus.com/inward/record.url?scp=63649088746&partnerID=8YFLogxK
U2 - 10.1109/DSP.2009.4785921
DO - 10.1109/DSP.2009.4785921
M3 - Conference contribution
AN - SCOPUS:63649088746
SN - 9781424436774
T3 - 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings
SP - 200
EP - 205
BT - 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings
T2 - 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009
Y2 - 4 January 2009 through 7 January 2009
ER -