An adaptive modeling and asset allocation approach to financial markets based on discrete microstructure model
An adaptive modeling and asset allocation approach to financial markets based on discrete microstructure model
复制标题
基于离散微观结构模型的金融市场自适应建模和资产配置方法
DOI：
10.1016/j.asoc.2016.02.034
复制
发表时间：
2016-06
影响因子：
8.7
通讯作者：
Chen, Xiaohong
中科院分区：
文献类型：
--
作者：
Xi, Yanhui;Xie, Wenbiao;Sun, Yapeng;Chen, Xiaohong
In previous works, it was verified that the discrete-time microstructure (DTMS) model, which is estimated by training dataset of a financial time series, may be effectively applied to asset allocation control on the following test data. However, if the length of test dataset is too long, prediction capability of the estimated DTMS model may gradually decline due to behavior change of financial market, so that the asset allocation result may become worse on the latter part of test data. To overcome the drawback, this paper presents a semi-on-line adaptive modeling and trading approach to financial time series based on the DTMS model and using a receding horizon optimization procedure. First, a long-interval identification window is selected, and the dataset on the identification window is used to estimate a DTMS model, which will be used to do asset allocation on the following short-term trading interval that is referred to as the trading window. After asset allocation is over on the trading window, the length-fixed identification window is then moved to a new window that includes the previous trading window, and a new DTMS model is estimated by using the dataset on the new identification window. Next, asset allocation continues on the next trading window that follows the previous trading window, and then the modeling and asset allocation process will go on according to the above steps. In order to enhance the flexibility and adaptability of the DTMS model, a comprehensive parameter optimization method is proposed, which incorporates particle swarm optimization (PSO) with Kalman filter and maximum likelihood method for estimating the states and parameters of DTMS model. Based on the adaptive DTMS model estimated on each identification window, an adaptive asset allocation control strategy is designed to achieve optimal control of financial assets. The parameters of the asset allocation controller are optimized by the PSO algorithm on each identification window. Case studies on Hang Seng Index (HSI) of Hong Kong stock exchange and S&P 500 index show that the proposed adaptive modeling and trading strategy can obtain much better asset allocation control performance compared with the parameters-fixed DTMS model.
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影响因子：
1.8
作者：
Hui Peng;G. Kitagawa;Min Gan;Xiao-hong Chen
通讯作者：
Hui Peng;G. Kitagawa;Min Gan;Xiao-hong Chen
影响因子：
1
作者：
Xanthi Pedeli;K. Fokianos;M. Pourahmadi
通讯作者：
Xanthi Pedeli;K. Fokianos;M. Pourahmadi
DOI：
10.2139/ssrn.1968889
发表时间：
2012-10
期刊：
Econometrics: Applied Econometric Modeling in Financial Economics eJournal
影响因子：
--
作者：
P. Leung;Hon-Yip Ng;W. Wong
通讯作者：
P. Leung;Hon-Yip Ng;W. Wong
影响因子：
6.1
作者：
ENGLE, RF
通讯作者：
ENGLE, RF
影响因子：
1.4
作者：
Na Song;T. Siu;W. Ching;H. Tong;Hailiang Yang
通讯作者：
Na Song;T. Siu;W. Ching;H. Tong;Hailiang Yang