Predictability of China’s Stock Market Returns Based on Combination of Distribution Forecasting Models

No consensus exists in the literature on whether stock prices can be predicted, with most existing studies employing point forecasting to predict returns. By contrast, this study adopts the new perspective of distribution forecasting to investigate the predictability of the stock market using the model combination strategy. Specifically, the Shanghai Composite Index and the Shenzhen Component Index are selected as research objects. Seven models – GARCH-norm, GARCH-sstd, EGARCH-sstd, EGARCH-sstd-M, one-component Beta-t-EGARCH, two-component Beta-t-EGARCH, and the EWMA-based nonparametric model – are employed to perform distribution forecasting of the returns. The results of out-of-sample forecasting evaluation show that none of the individual models is “qualified” in terms of predictive power. Therefore, three combinations of individual models were constructed: equal weight combination, log-likelihood score combination, and continuous ranked probability score combination. The latter two combinations were found to always have significant directional predictability and excess profitability, which indicates that the two combined models may be closer to the real data generation process; from the perspective of economic evaluation, they may have a predictive effect on the conditional return distribution in China’s stock market.

Exploiting Sparse Statistics for a Sequence-Based Prediction of the Effect of Mutations

Recent work showed that there is a significant difference between the statistics of amino acid triplets and quadruplets in sequences of folded proteins and randomly generated sequences. These statistics were used to assign a score to each sequence and make a prediction whether a sequence is likely to fold. The present paper extends the statistics to higher multiplets and suggests a way to handle the treatment of multiplets that were not found in the set of folded proteins. In particular, foldability predictions were done along the line of the previous work using pentuplet statistics and a way was found to combine the quadruplet and pentuplets statistics to improve the foldability predictions. A different, simpler, score was defined for hextuplets and heptuplets and were used to predict the direction of stability change of a protein upon mutation. With the best score combination the accuracy of the prediction was 73.4%.

BIOMETRIC SCORE FUSION

Multimodal biometric innovation in light of unique mark and finger knuckle has pulled in footing among scientists as of late. Despite the fact that Uni-modular framework offers many focal points, it has certain intrinsic shortcomings which deny it of the appeal. Uni-modular unique finger impression biometric frameworks performed singular acknowledgment in light of a particular wellspring of biometric data. However the match score esteem must be enhanced by working with low quality little closer view zone biometric pictures. In fact, the confirmation forms delivered by Finger Knuckle Print (FKP) brings about higher relative changes. The distortions between FKP pictures of same finger are of higher extent. The unimodal biometric check framework frequently gets influenced after accomplishing higher match score esteem. Besides, bimodal check framework does not accomplish higher security level which prompts to lesser combination score esteem. To diminish relative change on multimodal biometric framework, NonFracture based Fingerprint and Finger-Knuckle print Biometric Score Fusion (NFF-BSF) component is proposed in this paper. At first, particular estimation of match score is measured utilizing multimodal fitting coarse grained dissemination work. Multimodal fitting coarse grained dissemination capacity is utilized to work with low quality petite frontal area biometric pictures that accomplish high fitting score on the test and preparing biometric pictures. Also, Non-Fracture misshapening handling is completed in NFF-BSF instrument to diminish the adjustment fit as a fiddle of protest by utilizing bend length on biometric picture surfaces. At last, a coordinating technique in NFF-BSF instrument is utilized to decrease the relative changes. Thus, the relative changes on multimodal biometric framework expands the match score combination esteem. Investigation is directed on variables, for example, certifiable acknowledgment rate, coordinating score combination level and blunder rate on multimodal coordinating