Constructing Equity Investment Strategies Using Analyst Reports and Regime Switching Models.

This study demonstrates whether analysts' sentiments toward individual stocks are useful for stock investment strategies. This is achieved by using natural language processing to create a polarity index from textual information in analyst reports. In this study, we performed time series forecasting for the created polarity index using deep learning, and clustered the forecasted values by volatility using a regime switching model. In addition, we constructed a portfolio from stock data and rebalanced it at each change point of the regime. Consequently, the investment strategy proposed in this study outperforms the benchmark portfolio in terms of returns. This suggests that the polarity index is useful for constructing stock investment strategies.

Surface-assisted unidirectional orientation of ZnO nanorods hybridized with nematic liquid crystals.

Inorganic semiconductor nanorods are regarded as the primary components of optical and electrical nanoscale devices. In this paper, we demonstrate the unidirectional alignment of monolayered and dispersed ZnO nanorods on a rubbed polyimide alignment layer, which was achieved by a conventional liquid crystal alignment technique. The outermost surfaces of the ZnO nanorods (average diameter 7 nm; length 50 nm) were modified by polymerization initiator moieties, and nematic liquid crystalline (LC) methacrylate polymers were grown by atom transfer radical polymerization. By regulating the densities of the polymerization initiator moieties, we successfully hybridized LC-polymer-grafted ZnO nanorods and small nematic LC molecules. The LC-polymer-modified ZnO nanorods were hierarchically aligned on the substrate via cooperative molecular interactions among the liquid crystal mesogens, which induced molecular orientation on the rubbed polyimide alignment layer.