Comparison of Statistical Underlying Systematic Risk Factors and Betas Driving Returns on Equities

The objective of this paper is to compare four dimension reduction techniques used for extracting the underlying systematic risk factors driving returns on equities of the Mexican Market. The methodology used compares the results of estimation produced by Principal Component Analysis (PCA), Factor Analysis (FA), Independent Component Analysis (ICA), and Neural Networks Principal Component Analysis (NNPCA) under three different perspectives. The results showed that in general: PCA, FA, and ICA produced similar systematic risk factors and betas; NNPCA and ICA produced the greatest number of fully accepted models in the econometric contrast; and, the interpretation of systematic risk factors across the four techniques was not constant. Additional research testing alternative extraction techniques, econometric contrast, and interpretation methodologies are recommended, considering the limitations derived from the scope of this work. The originality and main contribution of this paper lie in the comparison of these four techniques in both the financial and Mexican contexts. The main conclusion is that depending on the purpose of the analysis, one technique will be more suitable than another.

Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative in the Mexican stock exchange

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns

To capture the dynamics of idiosyncratic volatility of stock returns over different horizons and investigate the relationship between idiosyncratic volatility and expected stock returns, this paper develops and estimates a parsimonious model of idiosyncratic volatility consisting of a short-run and a long-run component. The conditional short-run and long-run components are found to be positively and negatively related to expected stock returns, respectively. The positive relation between the short-run component and stock returns may be caused by investors requiring compensation for bearing idiosyncratic volatility risk when facing trading frictions and hold underdiversified portfolios. The negative relationship between the long-run component and stock returns may reflect the fact that stocks with high long-run idiosyncratic volatility are less exposed to systematic risk factors and, hence, earn lower returns. Moreover, the low-risk exposure of stocks characterized by high idiosyncratic volatility lends support to real-option-based mechanisms to explain this negative relation. In particular, the systematic risk of a firm with abundant growth options crucially depends upon the risk exposure of these options. The value of growth options could rise significantly because of convexity when the increase in idiosyncratic volatility occurs over long horizons. And growth options’ systematic risk could fall because the relative magnitude of their value in relation to systematic risk factors decreases. This paper was accepted by David Simchi-Levi, finance.

A retrospective analysis of risk factors associated with catheter-related thrombosis: a single-center study

Background: Catheter-related thrombosis may lead to catheter infections and failure, further deep venous thrombosis, and pulmonary embolism. Recognizing the risk factors for catheter-related thrombosis is extremely important to inform the development of catheter care guidelines. Methods: Data were collected from a total of 1,532 patients who had undergone venous catheterization, including indwelling catheterization from 19 March 2019 to 30 March 2019 in the Sun Yat-sen Memorial Hospital. The factors for which data were to be collected included the patients’ physical characteristics, catheter-related factors, and catheter care-related factors. Logistic regression analysis, the chi-squared test, Fisher’s exact test, and the t-test were used to analyze the data. Results: Of the 1,532 patients studied, 28 developed intraductal thrombi, and of the factors analyzed, malignancy, a catheterization history, a history of thrombophilia, surgery during the week before catheterization, the catheterization duration, and anticoagulant therapy were significant risk factors associated with catheter-related thrombosis (all p < 0.05). There were no significant associations between the catheter brand, the number of lumens, the insertion direction, or the factors associated with catheter care and catheter-related thrombosis (all p > 0.05). Conclusion: Our study incorporated clear and systematic risk factors associated with catheter-related thrombosis. Malignancy, history of thrombophilia, history of catheterization, surgery during the week before catheterization, and catheterization duration were associated with increased risks of catheter-related thrombosis. Prophylactic anticoagulation was effective for preventing and treating catheter-related thrombosis.

Do Oil and Gas Risk Factors Matter in the Malaysian Oil and Gas Industry? A Fama-MacBeth Two Stage Panel Regression Approach

This study examines whether oil and gas risk factors are priced in the returns of Malaysian oil and gas stocks employing asset pricing model with improved version of Fama-MacBeth two-stage panel regression. The findings reveal that oil price risk, gas price risk, and exchange rate risk are priced factors in the returns of oil and gas stocks, alongside market-based risk factors. Oil price, gas price and exchange rate factors are found to be associated with positive risk premium implying that they are systematic risk factors in the Malaysian oil and gas industry. Investors demand compensation for exposure to changes in oil price, gas price and exchange rate, implying that the risk cannot be eliminated through diversification. The risk premium for common systematic risk factors such as market, book-to-market, and momentum factors are found to be negative. The results suggest that in the Malaysian oil and gas industry, momentum driven strategy produces negative returns and investors receive higher returns from investing in growth oriented oil and gas stocks. Our results offer implications for asset pricing and portfolio management.

A retrospective analysis of risk factors associated with catheter-related thrombosis: a single-center study

Background: Catheter-related thrombosis (CRT) may lead to catheter infections and failure, further deep venous thrombosis (DVT), and pulmonary embolism (PE). Recognizing the risk factors for CRT is extremely important to inform the development of catheter-nursing guidelines.Methods: Data were collected from a total of 1532 patients who had undergone venous catheterization, including indwelling catheterization from March 19 to March 30, 2019 in Sun Yat-sen Memorial Hospital. The factors for which data were to be collected included the patients’ physical characteristics, catheter-associated factors, and factors associated with catheter nursing. Logistic regression analysis, the chi-square test, Fisher’s exact test, and the t-test were used to analyze the data. Results: Of the 1532 patients studied, 28 developed intraductal thrombi, and of the factors analyzed, tumor, a catheterization history, a history of thrombophilia, surgery during the week before catheterization, the catheterization duration were significant risk factors associated with CRT (all P < 0.05). There were no significant associations between the catheter brand, the number of lumens, the insertion direction, or the factors associated with catheter nursing and CRT (all P > 0.05). Anticoagulation therapy significantly decreases the risk of CRT ( P < 0.05 ). Conclusion: Tumor, a history of thrombophilia, a history of catheterization, surgery during the week before catheterization, and catheterization duration were associated with increased risks of CRT. Prophylactic anticoagulation is effective for preventing and treating CRT. Our study incorporates clear and systematic risk factors associated with CRT. The results are different from those of previous studies.