Cointegration and Asset Allocation: A New Fund Strategy

Many recent papers have documented the existence of periodicities in returns, return volatility, bid-ask spreads and trading volume, in both equity and foreign exchange markets. In this paper, we propose and employ a new test for detecting subtle periodicities in financial markets based on a signal coherence function. The technique is applied to a set of seven half-hourly exchange rate series. Overall, we find the signal coherence to be maximal at the 8 hour and 12 hour frequencies. Retaining only the most coherent frequencies for each series, we implement a trading rule based on these observed periodicities. Our results demonstrate in all cases except one that, in gross terms, the rules are able to generate returns considerably greater than those of a buy-and-hold strategy. We conjecture that this methodology could constitute an important tool for market microstructure researchers, which will enable them to better detect, quantify and rank the various periodic components in financial data.Hedge Fund, Cointegration, Equity, Market Neutral

New Associations between Drug-Induced Adverse Events in Animal Models and Humans Reveal Novel Candidate Safety Targets.

To improve our ability to extrapolate preclinical toxicity to humans, there is a need to understand and quantify the concordance of adverse events (AEs) between animal models and clinical studies. In the present work, we discovered 3011 statistically significant associations between preclinical and clinical AEs caused by drugs reported in the PharmaPendium database of which 2952 were new associations between toxicities encoded by different Medical Dictionary for Regulatory Activities terms across species. To find plausible and testable candidate off-target drug activities for the derived associations, we investigated the genetic overlap between the genes linked to both a preclinical and a clinical AE and the protein targets found to interact with one or more drugs causing both AEs. We discuss three associations from the analysis in more detail for which novel candidate off-target drug activities could be identified, namely, the association of preclinical mutagenicity readouts with clinical teratospermia and ovarian failure, the association of preclinical reflexes abnormal with clinical poor-quality sleep, and the association of preclinical psychomotor hyperactivity with clinical drug withdrawal syndrome. Our analysis successfully identified a total of 77% of known safety targets currently tested in in vitro screening panels plus an additional 431 genes which were proposed for investigation as future safety targets for different clinical toxicities. This work provides new translational toxicity relationships beyond AE term-matching, the results of which can be used for risk profiling of future new chemical entities for clinical studies and for the development of future in vitro safety panels.This work was supported as part of the PhD project of K.A.G funded by the European Research Council and AstraZeneca Early Oncology TD

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Multivariate embedding methods: forecasting high-frequency financial data in the first INFFC

Forecasting software is described, where each point to be forecast is embedded in an mdimensional library made from historic data. The approach is based on the well-known 'nearest neighbour' algorithm of Casdagli (1989) but there are important differences, including the facility for multivariate embedding, the use of predictor variables which may be different from the embedding variables, and the 'rolling library' which is of a constant size but is continuously updated as each successive point is forecast. In this way the univariate Casdagli algorithm has been developed into a more sophisticated 'pattern recognition' technique for short-term forecasting, whilst augmenting its original purpose of searching for evidence of chaos in time series. Because each point to be forecast has its own parameter estimates a certain amount of variability between successive forecasts is to be expected. However it was interesting to find that forecasts made on the training data were in fact exceptionally smooth over certain periods so that for some time (not usually longer than a few days) all points fell within similar close point groups. On the other hand there were other, shorter periods (typically a few hours long) where forecasts became 'chaotic', because adjacent points fell into totally different areas of the library. Hence a by-product of our work for the INFFC has been to provide empirical evidence of the local stability results of Yao and Tong (1994)

Cointegration and asset allocation: a new active hedge fund strategy

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