Nonlinear predictability of stock market returns: evidence from nonparametric and threshold models

Recent empirical evidence suggests that stock market returns are predictable from a variety of financial and macroeconomic variables. However, with two exceptions this predictability is based upon a linear functional form. This paper extends this research by considering whether a nonlinear relationship exists between stock market returns and these conditioning variables, and whether this nonlinearity can be exploited for forecast improvements. General nonlinearities are examined using a nonparametric regression technique, which suggest possible threshold behaviour. This leads to estimation of a smooth-transition threshold type model, with the results indicating an improved insample performance and marginally superior out-of-sample forecast results. D 2001 Elsevier Scienc

The information content of the stock and bond return correlation

We believe that the correlation between stock and bond returns carries information for the future values of these return series and economic conditions more widely. The correlation reflects investor perceptions regarding future economic performance, with a declining and negative correlation indicating heightened economic and market risk. Using US data from 1900, we show that the correlation has predictive power for subsequent stock and bond returns and can be used in a market timing strategy to improve portfolio performance. Moreover, the correlation also predicts bear market periods. Further, the correlation contains predictive power for a set of key macroeconomic variables, and has predictive content for contractionary periods. We believe the results in the paper are of interest and relevance to academics, practitioners and policy-makers

Enhanced recovery after surgery

Enhanced Recovery or Fast Track Recovery after Surgery protocols (ERAS) have significantly changed perioperative care following colorectal surgery and are promoted as reducing the stress response to surgery. The present systematic review aimed to examine the impact on the magnitude of the systemic inflammatory response (SIR) for each ERAS component following colorectal surgery using objective markers such as C-reactive protein (CRP) and interleukin-6 (IL-6). A literature search was performed of the US National Library of Medicine (MEDLINE), EMBASE, PubMed, and the Cochrane Database of Systematic Reviews using appropriate keywords and subject headings to February 2015. Included studies had to assess the impact of the selected ERAS component on the SIR using either CRP or IL-6. Nineteen studies, including 1898 patients, were included. Fourteen studies (1246 patients) examined the impact of laparoscopic surgery on the postoperative markers of SIR. Ten of these studies (1040 patients) reported that laparoscopic surgery reduced postoperative CRP. One study (53 patients) reported reduced postoperative CRP using opioid-minimising analgesia. One study (142 patients) reported no change in postoperative CRP following preoperative carbohydrate loading. Two studies (108 patients) reported conflicting results with respect to the impact of goal-directed fluid therapy on postoperative IL-6. No studies examined the effect of other ERAS components, including mechanical bowel preparation, antibiotic prophylaxis, thromboprophylaxis, and avoidance of nasogastric tubes and peritoneal drains on markers of the postoperative SIR following colorectal surgery. The present systematic review shows that, with the exception of laparoscopic surgery, objective evidence of the effect of individual components of ERAS protocols in reducing the stress response following colorectal surgery is limited

Equity/bond yield correlation and the FED model: evidence of switching behaviour from the G7 markets

This paper considers how the strength and nature of the relation between the equity and bond yield varies with the level of the real bond yield. We demonstrate that at low levels of the real bond yield, the correlation between the equity and bond yields turns negative. This arises as the lower bond yield implies heightened macroeconomic risk (e.g. deflation and economic stagnation) and causes equity and bond prices to move in opposite directions. The FED model relies on a positive relation for its success in predicting future returns. Thus, we argue that the mixed empirical evidence regarding the FED model arises due to this switch in correlation behaviour. We present supportive evidence for the switching relation and its link to the level of the bond yield using linear and nonlinear smooth transition panel regression techniques for the G7 markets. The results presented here should be of interest to market practitioners who may wish to use the FED model to aid market timing decisions and for academics interested in understanding the interrelations between markets

Long-term follow-up of patients undergoing resection of tnm stage i colorectal cancer: an analysis of tumour and host determinants of outcome

Background Screening for colorectal cancer improves cancer-specific survival (CSS) through the detection of early-stage disease; however, its impact on overall survival (OS) is unclear. The present study examined tumour and host determinants of outcome in TNM Stage I disease. Methods All patients with pathologically confirmed TNM Stage I disease across 4 hospitals in the North of Glasgow between 2000 and 2008 were included. The preoperative modified Glasgow Prognostic Score (mGPS) was used as a marker of the host systemic inflammatory response (SIR). Results There were 191 patients identified, 105 (55 %) were males, 91 (48 %) were over the age of 75 years and 7 (4 %) patients underwent an emergency operation. In those with a preoperative CRP result (n = 150), 35 (24 %) patients had evidence of an elevated mGPS. Median follow-up of survivors was 116 months (minimum 72 months) during which 88 (46 %) patients died; 7 (8 %) had postoperative deaths, 15 (17 %) had cancer-related deaths and 66 (75 %) had non-cancer-related deaths. 5-year CSS was 95 % and OS was 76 %. On univariate analysis, advancing age (p < 0.001), emergency presentation (p = 0.008), and an elevated mGPS (p = 0.012) were associated with reduced OS. On multivariate analysis, only age (HR = 3.611, 95 % CI 2.049–6.365, p < 0.001) and the presence of an elevated mGPS (HR = 2.173, 95 % CI 1.204–3.921, p = 0.010) retained significance. Conclusions In patients undergoing resection for TNM Stage I colorectal cancer, an elevated mGPS was an objective independent marker of poorer OS. These patients may benefit from a targeted intervention

Validation of a modified clinical risk score to predict cancer-specific survival for stage II colon cancer

Many patients with stage II colon cancer will die of their disease despite curative surgery. Therefore, identification of patients at high risk of poor outcome after surgery for stage II colon cancer is desirable. This study aims to validate a clinical risk score to predict cancer-specific survival in patients undergoing surgery for stage II colon cancer. Patients undergoing surgery for stage II colon cancer in 16 hospitals in the West of Scotland between 2001 and 2004 were identified from a prospectively maintained regional clinical audit database. Overall and cancer-specific survival rates up to 5 years were calculated. A total of 871 patients were included. At 5 years, cancer-specific survival was 81.9% and overall survival was 65.6%. On multivariate analysis, age ≥75 years (hazard ratio (HR) 2.11, 95% confidence intervals (CI) 1.57–2.85; P<0.001) and emergency presentation (HR 1.97, 95% CI 1.43–2.70; P<0.001) were independently associated with cancer-specific survival. Age and mode of presentation HRs were added to form a clinical risk score of 0–2. The cancer-specific survival at 5 years for patients with a cumulative score 0 was 88.7%, 1 was 78.2% and 2 was 65.9%. These results validate a modified simple clinical risk score for patients undergoing surgery for stage II colon cancer. The combination of these two universally documented clinical factors provides a solid foundation for the examination of the impact of additional clinicopathological and treatment factors on overall and cancer-specific survival

Factors associated with the efficacy of polyp detection during routine flexible sigmoidoscopy

Objective: Flexible sigmoidoscopy reduces the incidence of colonic cancer through the detection and removal of premalignant adenomas. However, the efficacy of the procedure is variable. The aim of the present study was to examine factors associated with the efficacy of detecting polyps during flexible sigmoidoscopy. Design and patients: Retrospective observational cohort study of all individuals undergoing routine flexible sigmoidoscopy in NHS Greater Glasgow and Clyde from January 2013 to January 2016. Results: A total of 7713 patients were included. Median age was 52 years and 50% were male. Polyps were detected in 1172 (13%) patients. On multivariate analysis, increasing age (OR 1.020 (1.016–1.023) p<0.001), male sex (OR 1.23 (1.10–1.38) p<0.001) and the use of any bowel preparation (OR 3.55 (1.47–8.57) p<0.001) were associated with increasing numbers of polyps being detected. There was no significant difference in the number of polyps found in patients who had received an oral laxative preparation compared with an enema (OR 3.81 (1.57–9.22) vs 3.45 (1.43–8.34)), or in those who received sedation versus those who had not (OR 1.00 vs 1.04 (0.91–1.17) p=0.591). Furthermore, the highest number of polyps was found when the sigmoidoscope was inserted to the descending colon (OR 1.30 (1.04–1.63)). Conclusions: Increasing age, male sex and the utilisation of any bowel preparation were associated with an increased polyp detection rate. However, the use of sedation or oral laxative preparation appears to confer no additional benefit. In addition, the results indicate that insertion to the descending colon optimises the efficacy of flexible sigmoidoscopy polyp detection

Do artificial neural networks provide improved volatility forecasts:Evidence from Asian markets

This paper enters the ongoing volatility forecasting debate by examining the ability of a wide range of Machine Learning methods (ML), and specifically Artificial Neural Network (ANN) models. The ANN models are compared against traditional econometric models for ten Asian markets using daily data for the time period from 12 September 1994 to 05 March 2018. The empirical results indicate that ML algorithms, across the range of countries, can better approximate dependencies compared to traditional benchmark models. Notably, the predictive performance of such deep learning models is superior perhaps due to its ability in capturing long-range dependencies. For example, the Neuro Fuzzy models of ANFIS and CANFIS, which outperform the EGARCH model, are more flexible in modelling both asymmetry and long memory properties. This offers new insights for Asian markets. In addition to standard statistics forecast metrics, we also consider risk management measures including the value-at-risk (VaR) average failure rate, the Kupiec LR test, the Christoffersen independence test, the expected shortfall (ES) and the dynamic quantile test. The study concludes that ML algorithms provide improving volatility forecasts in the stock markets of Asia and suggest that this may be a fruitful approach for risk management.</p

Do artificial neural networks provide improved volatility forecasts:Evidence from Asian markets

This paper enters the ongoing volatility forecasting debate by examining the ability of a wide range of Machine Learning methods (ML), and specifically Artificial Neural Network (ANN) models. The ANN models are compared against traditional econometric models for ten Asian markets using daily data for the time period from 12 September 1994 to 05 March 2018. The empirical results indicate that ML algorithms, across the range of countries, can better approximate dependencies compared to traditional benchmark models. Notably, the predictive performance of such deep learning models is superior perhaps due to its ability in capturing long-range dependencies. For example, the Neuro Fuzzy models of ANFIS and CANFIS, which outperform the EGARCH model, are more flexible in modelling both asymmetry and long memory properties. This offers new insights for Asian markets. In addition to standard statistics forecast metrics, we also consider risk management measures including the value-at-risk (VaR) average failure rate, the Kupiec LR test, the Christoffersen independence test, the expected shortfall (ES) and the dynamic quantile test. The study concludes that ML algorithms provide improving volatility forecasts in the stock markets of Asia and suggest that this may be a fruitful approach for risk management.</p

Systemic inflammation predicts all-cause mortality: a Glasgow Inflammation Outcome Study

Introduction: Markers of the systemic inflammatory response, including C-reactive protein and albumin (combined to form the modified Glasgow Prognostic Score), as well as neutrophil, lymphocyte and platelet counts have been shown to be prognostic of survival in patients with cancer. The aim of the present study was to examine the prognostic relationship between these markers of the systemic inflammatory response and all-cause, cancer, cardiovascular and cerebrovascular mortality in a large incidentally sampled cohort.&lt;p&gt;&lt;/p&gt; Methods: Patients (n = 160 481) who had an incidental blood sample taken between 2000 and 2008 were studied for the prognostic value of C-reactive protein (&gt;10mg/l, albumin (&#62;35mg/l), neutrophil (&#62;7.5×109/l) lymphocyte and platelet counts. Also, patients (n = 52 091) sampled following the introduction of high sensitivity C-reactive protein (&#62;3mg/l) measurements were studied. A combination of these markers, to make cumulative inflammation-based scores, were investigated.&lt;p&gt;&lt;/p&gt; Results: In all patients (n = 160 481) C-reactive protein (&#62;10mg/l) (HR 2.71, p&#60;0.001), albumin (&#62;35mg/l) (HR 3.68, p&#60;0.001) and neutrophil counts (HR 2.18, p&#60;0.001) were independently predictive of all-cause mortality. These associations were also observed in cancer, cardiovascular and cerebrovascular mortality before and after the introduction of high sensitivity C-reactive protein measurements (&#62;3mg/l) (n = 52 091). A combination of high sensitivity C-reactive protein (&#62;3mg/l), albumin and neutrophil count predicted all-cause (HR 7.37, p&#60;0.001, AUC 0.723), cancer (HR 9.32, p&#60;0.001, AUC 0.731), cardiovascular (HR 4.03, p&#60;0.001, AUC 0.650) and cerebrovascular (HR 3.10, p&#60;0.001, AUC 0.623) mortality. Conclusion The results of the present study showed that an inflammation-based prognostic score, combining high sensitivity C-reactive protein, albumin and neutrophil count is prognostic of all-cause mortality