Recursive estimation for continuous time stochastic volatility models

AbstractVolatility plays an important role in portfolio management and option pricing. Recently, there has been a growing interest in modeling volatility of the observed process by nonlinear stochastic process [S.J. Taylor, Asset Price Dynamics, Volatility, and Prediction, Princeton University Press, 2005; H. Kawakatsu, Specification and estimation of discrete time quadratic stochastic volatility models, Journal of Empirical Finance 14 (2007) 424–442]. In [H. Gong, A. Thavaneswaran, J. Singh, Filtering for some time series models by using transformation, Math Scientist 33 (2008) 141–147], we have studied the recursive estimates for discrete time stochastic volatility models driven by normal errors. In this paper, we study the recursive estimates for various classes of continuous time nonlinear non-Gaussian stochastic volatility models used for option pricing in finance

RCA models with correlated errors

AbstractFinancial time series data cannot be adequately modelled by a normal distribution and empirical evidence on the non-normality assumption is very well documented in the financial literature; see [R.F. Engle, Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation, Econometrica 50 (1982) 987–1008] and [T. Bollerslev, Generalized autoregressive conditional heteroscedasticity, J. Econometrics 31 (1986) 307–327] for details. The kurtosis of various classes of RCA models has been the subject of a study by Appadoo et al. [S.S. Appadoo, M. Gharahmani, A. Thavaneswaran, Moment properties of some volatility models, Math. Sci. 30 (2005) 50–63] and Thavaneswaran et al. [A. Thavaneswaran, S.S. Appadoo, M. Samanta, Random coefficient GARCH models, Math. Comput. Modelling 41 (2005) 723–733]. In this work we derive the kurtosis of the correlated RCA model as well as the normal GARCH model under the assumption that the errors are correlated

Generalized moving average models and applications in high frequency data

This paper considers a new class of first order moving average type time series model with index δ (\u3e 0) to describe some hidden features of a time series. It is shown that this class of models provides a valid, simple solution to a new direction of time series modelling. In particular, for suitably chosen parameters (coefficient β and index δ) this type of models could be used to describe data with low or high frequency components. Various new results associated with this class are given in a general form. A simulation study is carried out to justify the theory. We justify the importance of this class of models in practice using a set of real time series data

Applications of recursive estimation methods in statistical process control

In recent years there has been a growing interest in recursive estimation techniques as applied to statistical process control (SPC). In cases where prior information about the processes are available, it is shown that procedures based on the “optimal” smoothing can be superior to the classical procedures like Shewhart’s CUSUM control charts (see, for instance, Thavaneswaran, McPherson and Abraham (1998)). This paper reviews the recursive algorithms based on EWMA (exponentially weighted moving average), DLM (dynamic linear modeling), KF (Kalman filtering) and OS (optimal smoothing) in statistical process control with correlated data. We also discuss various relationships among the asymptotic mean square errors (MSE) of these procedures in SPC

Joint Estimation Using Quadratic Estimating Function

A class of martingale estimating functions is convenient and plays an important role for inference for nonlinear time series models. However, when the information about the first four conditional moments of the observed process becomes available, the quadratic estimating functions are more informative. In this paper, a general framework for joint estimation of conditional mean and variance parameters in time series models using quadratic estimating functions is developed. Superiority of the approach is demonstrated by comparing the information associated with the optimal quadratic estimating function with the information associated with other estimating functions. The method is used to study the optimal quadratic estimating functions of the parameters of autoregressive conditional duration (ACD) models, random coefficient autoregressive (RCA) models, doubly stochastic models and regression models with ARCH errors. Closed-form expressions for the information gain are also discussed in some detail

A signal-seeking Phase 2 study of olaparib and durvalumab in advanced solid cancers with homologous recombination repair gene alterations

Purpose: To determine the safety and efficacy of PARP plus PD-L1 inhibition (olaparib + durvalumab, O + D) in patients with advanced solid, predominantly rare cancers harbouring homologous recombination repair (HRR) defects. Patients and methods: In total, 48 patients were treated with O + D, 16 with BRCA1/2 alterations (group 1) and 32 with other select HRR alterations (group 2). Overall, 32 (66%) patients had rare or less common cancers. The primary objective of this single-arm Phase II trial was a progression-free survival rate at 6 months (PFS6). Post hoc exploratory analyses were conducted on archival tumour tissue and serial bloods. Results: The PFS6 rate was 35% and 38% with durable objective tumour responses (OTR) in 3(19%) and 3(9%) in groups 1 and 2, respectively. Rare cancers achieving an OTR included cholangiocarcinoma, perivascular epithelioid cell (PEComa), neuroendocrine, gallbladder and endometrial cancer. O + D was safe, with five serious adverse events related to the study drug(s) in 3 (6%) patients. A higher proportion of CD38 high B cells in the blood and higher CD40 expression in tumour was prognostic of survival. Conclusions: O + D demonstrated no new toxicity concerns and yielded a clinically meaningful PFS6 rate and durable OTRs across several cancers with HRR defects, including rare cancers

ElectrochemicalN-demethylation of tropane alkaloids

A practical, efficient, and selective electrochemicalN-demethylation method of tropane alkaloids to their nortropane derivatives is described. Nortropanes, such as noratropine and norscopolamine, are important intermediates for the semi-synthesis of the medicines ipratropium or oxitropium bromide, respectively. Synthesis was performed in a simple home-made electrochemical batch cell using a porous glassy carbon electrode. The reaction proceeds at room temperature in one step in a mixture of ethanol or methanol and water. The method avoids hazardous oxidizing agents such as H(2)O(2)orm-chloroperbenzoic acid (m-CPBA), toxic solvents such as chloroform, as well as metal-based catalysts. Various key parameters were investigated in electrochemical batch or flow cells, and the optimized conditions were used in batch and flow-cells at gram scale to synthesize noratropine in high yield and purity using a convenient liquid-liquid extraction method without any need for chromatographic purification. Mechanistic studies showed that the electrochemicalN-demethylation proceeds by the formation of an iminium intermediate which is converted by water as the nucleophile. The optimized method was further applied to scopolamine, cocaine, benzatropine, homatropine and tropacocaine, showing that this is a generic way ofN-demethylating tropane alkaloids to synthesize valuable precursors for pharmaceutical products

Bridging the gap between robotic technology and health care

Although technology and computation power have become more and more present in our daily lives, we have yet to see the same tendency in robotics applied to health care. In this work we focused on the study of four distinct applications of robotic technology to health care, named Robotic Assisted Surgery, Robotics in Rehabilitation, Prosthetics and Companion Robotic Systems. We identified the main roadblocks that are limiting the progress of such applications by an extensive examination of recent reports. Based on the limitations of the practical use of current robotic technology for health care we proposed a general modularization approach for the conception and implementation of specific robotic devices. The main conclusions of this review are: (i) there is a clear need of the adaptation of robotic technology (closed loop) to the user, so that robotics can be widely accepted and used in the context of heath care; (ii) for all studied robotic technologies cost is still prohibitive and limits their wide use. The reduction of costs influences technology acceptability; thus innovation by using cheaper computer systems and sensors is relevant and should be taken into account in the implementation of robotic systems

ICECREAM: randomised phase II study of cetuximab alone or in combination with irinotecan in patients with metastatic colorectal cancer with either KRAS, NRAS, BRAF and PI3KCA wild type, or G13D mutated tumours

BACKGROUND: Patients with metastatic colorectal cancer whose disease has progressed on oxaliplatin- and irinotecan-containing regimens may benefit from EGFR-inhibiting monoclonal antibodies if they do not contain mutations in the KRAS gene (are &quot;wild type&quot;). It is unknown whether these antibodies, such as cetuximab, are more efficacious in refractory metastatic colorectal cancer as monotherapy, or in combination with irinotecan. Lack of mutation&nbsp;in KRAS, BRAF and PIK3CA predicts response to EFGR-inhibitors. The ICECREAM trial examines the question of monotherapy versus combination with chemotherapy in two groups of patients: those with a &quot;quadruple wild type&quot; tumour genotype (no mutations in KRAS, NRAS, PI3KCA or BRAF genes) and those with the specific KRAS mutation in codon G13D, for whom possibly EGFR-inhibitor efficacy may be equivalent. METHODS AND DESIGN: ICECREAM is a randomised, phase II, open-label, controlled trial comparing the efficacy of cetuximab alone or with irinotecan in patients with &quot;quadruple wild type&quot; or G13D-mutated metastatic colorectal cancer, whose disease has progressed on, or who are intolerant of oxaliplatin- and fluoropyrimidine-based chemotherapy. The primary endpoint is the 6-month progression-free survival benefit of the treatment regimen. Secondary endpoints are response rate, overall survival, and quality of life. The tertiary endpoint is prediction of outcome with further biological markers. International collaboration has facilitated recruitment in this prospective trial of treatment in these infrequently found molecular subsets of colorectal cancer. DISCUSSION: This unique trial will yield prospective information on the efficacy of cetuximab and whether this is further enhanced with chemotherapy in two distinct populations of patients with metastatic colorectal cancer: the &quot;quadruple wild type&quot;, which may \u27superselect\u27 for tumours sensitive to EGFR-inhibition, and the rare KRAS G13D mutated tumours, which are also postulated to be sensitive to the drug. The focus on establishing both positive and negative predictive factors for the response to targeted therapy is an attempt to improve outcomes, reduce toxicity and contain treatment costs. Tissue and blood will yield a resource for molecular studies. Recruitment, particularly of patients with the rare G13D mutation, will demonstrate the ability for international collaboration to run prospective trials in small colorectal cancer molecular subgroups.<br /