4 research outputs found
Two Essays in Asset Pricing and FinTech: Out-of-Sample Equity Premium Predictability and Stock Co-jump Networks with Mixed Membership
No full textIn Chapter 1, we introduce a new method for forecasting stock returns. Despite exhibiting strong in-sample predictive power, a wide range of predictors proposed in the literature are shown by Goyal and Welch [2008] to underperform the historical average in out-of-sample forecasts of the equity premium. We propose an unconventional approach for out-of-sample equity premium prediction that avoids parameter estimation, adopting a conservative constant as the predictive coefficient. Our methodology retains the same zero-variance advantage as the historical average, while achieving lower bias, thereby outperforming the benchmark. We show that our forecast first-order stochastically dominates the historical average. Using our methodology, we reveal that many predictors exhibit statistically and economically significant out-of-sample gains for the market return. We also compare our method with machine learning models and apply our framework to out-of-sample bond return predictability. In Chapter 2, we study stock dependence across many firms using pairwise co-jump networks with high-frequency data. Stock cojumps contain important information about the risk linkage among stocks. Ding et al. [2024] discovered a block structure among stocks based on their co-jumps and proposed a model DCBM-DMP. In this paper, we exhibit that this structure can greatly benefit from an essentially additional component: mixed membership. Specifically, we propose a Degree Corrected Mixed Membership network model with Dependent Multivariate Poisson edges (DCMM-DMP) and develop a Mixed Spectral Clustering On Ratios-of-Eigenvectors for networks with Dependent Multivariate Poisson edges (Mixed-SCORE-DMP) algorithm. We show that Mixed-SCORE-DMP is asymptotically consistent in estimating the mixed membership structures. Empirically, we show that (1) the mixed membership network DCMM-DMP enhances DCBM-DMP by providing a more precise risk structure; (2) “peers” defined by our mixed membership model offer significant advantages in return prediction over benchmarks, such as GICS, self-grouping, or counting analyst coverage linkage; (3) a “purity” measure based on our model provides insightful perspectives about stocks’ risk profile and investment opportunities. We also construct a lead-lag jump network to study the leading and lagging group effect.</p
How to Dominate the Historical Average
No full textWe present a novel methodology for the out-of-sample forecast of the equity premium. Our predictive slope coefficient is a conservative constant that has a lower bias than the zero slope employed by the historical average, but has the same variance. We demonstrate that, theoretically and empirically, our method dominates the historical average in forecast performance. Our methodology establishes a simple yet powerful paradigm for exploiting the real-time equity premium predictability derived from a predictor. Applications of our method reveal that many predictors can forecast the equity premium, and that parameter estimates in previous studies add value to out-of-sample forecasts
MALDI-TOF Mass Array Analysis of Nell-1 Promoter Methylation Patterns in Human Gastric Cancer
No full textMass spectrometry (MS) enables rapid and sensitive qualitative and quantitative analyses of biomolecules (proteins, peptides, oligosaccharides, lipids, DNA, and RNA), drugs, and metabolites. MS has become an essential tool in modern biomedical research, including the analysis of DNA methylation. DNA methylation has been reported in many cancers, suggesting that it can be utilized as an early biomarker to improve the early diagnosis rate. Using matrix-assisted laser desorption/ionization time-of-flight MS and MassCLEAVE reagent, we compared Nell-1 hypermethylation levels among tumor tissues, paracarcinoma tissues, and normal tissues from gastric cancer patients. Almost 80% of the CpG sites in the amplicons produced were covered by the analysis. Our results indicate a significant difference in methylation status between gastric cancer tissue (a higher level) and normal tissue. The real-time PCR. Furthermore, immunohistochemical analyses revealed that Nell-1 staining was less intense in cancer tissue relative to normal tissue and that the tumor cells had spread to the muscle layer. These findings may serve as a guide for the early diagnosis of gastric cancer.National Natural Science Foundation of China [81200762]; Heilongjiang Province Natural Science Foundation [ZD200920]SCI(E)[email protected]
Active vitamin D activates chondrocyte autophagy to reduce osteoarthritis via mediating the AMPK–mTOR signaling pathway
No full textOsteoarthritis (OA) is a common joint degenerative disease. Vitamin D (VD) is essential for bone health. We hypothesized that active VD could be used as a therapeutic treatment for OA. Low serum levels of 25-hydroxyvitamin D [25(OH)D] have been found in patients with OA, and thus the serum level of VD could be diagnostic of OA. To test this, we established a mouse model of OA. The results from staining with hematoxylin–eosin and Safranin O – Fast Green indicated that active VD reduced the symptoms of OA in mice. The results from Western blotting indicated that treatment with VD increased the activity of the p-AMPK–AMPK signaling pathway and decreased the p-mTOR–mTOR pathway; it also increased the ratio of LC3II:LC3I antibodies and the protein expression levels of Beclin-1, but decreased the level of p62. Further, treatment with VD reduced the levels of tumor necrosis factor-α and interleukin-6 both in cartilage tissues and in chondrocytes. Administration of the AMPK inhibitor compound C and autophagy inhibitor 3-methyladenine (3-MA) reversed these changes following VD treatment. In addition, the results from transfection with mRFP-GFP-LC3 indicated that active VD led to autophagosome aggregation in OA chondrocytes. 3-MA inhibited cell autophagy and promoted inflammation in OA. This study provides evidence that active VD activate chondrocyte autophagy to reduce OA inflammation via activating the AMPK–mTOR signaling pathway. Treatment with active VD could be a novel therapeutic option for OA.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
