An Empirical Study of Value at Risk in the Chinese Stock Market

Nowadays, value at risk (VaR) has developed into a standard indicator in the financial risk measuring field. The aim of this study is not only to measure the risk of the Chinese stock market using VaR methods, but also to value whether the downside risk is priced in the expected return in the market. This study estimates VaR of six indices using four approaches at both 95% and 99% confidence levels. Then by conducting the Kupiec backtest, we find the best fitted method for each sample. We conclude that the approach of historical simulation with volatility is the best one for most of the samples, and the non-parametric methods fit much better than the parametric ones in the Chinese stock market. Furthermore, this study uses these best VaR estimates to test the intertemporal risk-return trade-off between the downside risk and the expected return. The positive risk-return relation is proved when we consider control variables, which are the one-month-lag return and a dummy variable for financial crisis

Analyzing big time series data in solar engineering using features and PCA

In solar engineering, we encounter big time series data such as the satellite-derived irradiance data and string-level measurements from a utility-scale photovoltaic (PV) system. While storing and hosting big data are certainly possible using today’s data storage technology, it is challenging to effectively and efficiently visualize and analyze the data. We consider a data analytics algorithm to mitigate some of these challenges in this work. The algorithm computes a set of generic and/or application-specific features to characterize the time series, and subsequently uses principal component analysis to project these features onto a two-dimensional space. As each time series can be represented by features, it can be treated as a single data point in the feature space, allowing many operations to become more amenable. Three applications are discussed within the overall framework, namely (1) the PV system type identification, (2) monitoring network design, and (3) anomalous string detection. The proposed framework can be easily translated to many other solar engineer applications

Very short term irradiance forecasting using the lasso

We find an application of the lasso (least absolute shrinkage and selection operator) in sub-5-min solar irradiance forecasting using a monitoring network. Lasso is a variable shrinkage and selection method for linear regression. In addition to the sum of squares error minimization, it considers the sum of ℓ1-norms of the regression coefficients as penalty. This bias–variance trade-off very often leads to better predictions.<p></p> One second irradiance time series data are collected using a dense monitoring network in Oahu, Hawaii. As clouds propagate over the network, highly correlated lagged time series can be observed among station pairs. Lasso is used to automatically shrink and select the most appropriate lagged time series for regression. Since only lagged time series are used as predictors, the regression provides true out-of-sample forecasts. It is found that the proposed model outperforms univariate time series models and ordinary least squares regression significantly, especially when training data are few and predictors are many. Very short-term irradiance forecasting is useful in managing the variability within a central PV power plant.<p></p&gt

SOLAR IRRADIANCE FORECASTING FOR TROPICAL REGIONS USING NOVEL STATISTICAL ANALYSIS AND MACHINE LEARNING

Ph.DDOCTOR OF PHILOSOPH

Construction applicability of mechanical methods for connecting aisle in the bohai mudstone stratum with high water pressure

China’s traditional connecting aisle construction technology is mainly to combine soil reinforcement with mining excavation. The technology is relatively mature, but it has shortcomings such as long construction period and long-term construction settlement. In order to overcome the above shortcomings, mechanical methods for connecting aisle technology has become increasingly mature after years of research and development, and has been successfully applied in many areas. For the cross-sea tunnel project, this technology was first tried and applied in the interval tunnel of Qingdao Metro Line 8. It is challenging to construct the connecting aisle by mechanical method in Bohai mudstone stratum with high water pressure, which has the construction difficulties such as high excavation requirements, high requirements for post-support function and limited space of main tunnel. In this study, a cutter, propulsion system, and back supporting system were designed to handle the key and difficult points and risks of the aforementioned construction. Furthermore, targeted construction schemes were adopted for sleeve sealing, sleeve removal, and improvement of sleeve sealing. The applicability of the improved mechanical construction method to the geological conditions of the Qingdao area was verified through a numerical simulation. The research results can provide a reference for the mechanical construction of connecting aisle under similar formation conditions

Proof-Carrying Data from Multi-folding Schemes

Proof-carrying data (PCD) is a powerful cryptographic primitive that allows mutually distrustful parties to perform distributed computation defined on directed acyclic graphs in an efficiently verifiable manner. Important efficiency parameters include prover\u27s cost at each step and the recursion overhead that measures the additional cost apart from proving the computation. In this paper, we construct a PCD scheme having the smallest prover\u27s cost and recursion overhead in the literature. Specifically, the prover\u27s cost at each step is dominated by only one $O(|C|)$-sized multi-scalar multiplication (MSM), and the recursion overhead is dominated by only one $2r$-sized MSM, where $|C|$ is the computation size and $r$ is the number of incoming edges at certain step. In contrast, the state-of-the-art PCD scheme requires $4r+12$ $O(|C|)$-sized MSMs w.r.t. the prover\u27s cost and six $2r$-sized MSMs, one $6r$-sized MSM w.r.t. the recursion overhead. In addition, our PCD scheme supports more expressive constraint system for computations—customizable constraint system (CCS) that supports high-degree constraints efficiently, in contrast with rank-1 constraint system (R1CS) that supports only quadratic constraints used in existing PCD schemes. Underlying our PCD scheme is a multi-folding scheme that reduces the task of checking multiple instances into the task of checking one. We generalize existing construction to support arbitrary number of instances

Spatial Disassociation of Disrupted Functional Connectivity for the Default Mode Network in Patients with End-Stage Renal Disease

To investigate the aberrant functional connectivity of the default mode network (DMN) in patients with end-stage renal disease (ESRD) and their clinical relevance

CT-guided microcoil localization for scapula-blocked pulmonary nodules using penetrating lung puncture before video-assisted thoracic surgery

PURPOSETo retrospectively analyze the effectiveness and safety of computed tomography (CT)-guided microcoil localization for scapula-blocked pulmonary nodules using penetrating lung puncture prior to video-assisted thoracic surgery (VATS).METHODSOne hundred thirty-eight patients with 138 pulmonary nodules were included in this single-center retrospective study. Among them, 110 patients who underwent CT-guided microcoil localization using the routine puncture technique formed the routine group; the other 28 patients who underwent the CT-guided microcoil localization using the penetrating lung puncture technique formed the penetrating lung group. The main outcomes were the success rate and complication rate of the two groups.RESULTSThe localization success rate was 95.5% (105/110) in the routine group and 89.3% (25/28) in the penetrating lung group (P = 0.205). There was no statistical difference in any of the complications (pneumothorax, intrapulmonary hemorrhage, or moderate and severe chest pain) in both groups (P = 0.178, P = 0.204, P = 0.709, respectively). Localization procedure time was significantly increased in the penetrating lung group compared with the routine group (31.0 ± 3.0 min vs. 21.2 ± 2.8 min, P < 0.001).CONCLUSIONCT-guided microcoil localization for scapula-blocked pulmonary nodules using penetrating lung puncture prior to VATS resection is effective and safe. However, the deployment of the microcoil using penetrating lung puncture required more time than the routine puncture method