Self excitation in equity indices

A "self-exciting" market is one in which the probability of observing a crash increases in response to the occurrence of a crash. It essentially describes cases where the initial crash serves to weaken the system to some extent, making subsequent crashes more likely. This thesis investigates if equity markets possess this property. A self-exciting extension of the well-known jump-based Bates (1996) model is used as the workhorse model for this thesis, and a particle-filtering algorithm is used to facilitate estimation by means of maximum likelihood. The estimation method is developed so that option prices are easily included in the dataset, leading to higher quality estimates. Equilibrium arguments are used to price the risks associated with the time-varying crash probability, and in turn to motivate a risk-neutral system for use in option pricing. The option pricing function for the model is obtained via the application of widely-used Fourier techniques. An application to S&P500 index returns and a panel of S&P500 index option prices reveals evidence of self excitation.

Bayesian indirect inference using a parametric auxiliary model

Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and computationally easier to deal with. Such an approach has been well explored in the classical literature but has received substantially less attention in the Bayesian paradigm. The purpose of this paper is to compare and contrast a collection of what we call parametric Bayesian indirect inference (pBII) methods. One class of pBII methods uses approximate Bayesian computation (referred to here as ABC II) where the summary statistic is formed on the basis of the auxiliary model, using ideas from II. Another approach proposed in the literature, referred to here as parametric Bayesian indirect likelihood (pBIL), we show to be a fundamentally different approach to ABC II. We devise new theoretical results for pBIL to give extra insights into its behaviour and also its differences with ABC II. Furthermore, we examine in more detail the assumptions required to use each pBII method. The results, insights and comparisons developed in this paper are illustrated on simple examples and two other substantive applications. The first of the substantive examples involves performing inference for complex quantile distributions based on simulated data while the second is for estimating the parameters of a trivariate stochastic process describing the evolution of macroparasites within a host based on real data. We create a novel framework called Bayesian indirect likelihood (BIL) which encompasses pBII as well as general ABC methods so that the connections between the methods can be established.

An examination of learning design in elite springboard diving

The overarching aim of this programme of work was to evaluate the effectiveness of the existing learning environment within the Australian Institute of Sport (AIS) elite springboard diving programme. Unique to the current research programme, is the application of ideas from an established theory of motor learning, specifically ecological dynamics, to an applied high performance training environment. In this research programme springboard diving is examined as a complex system, where individual, task, and environmental constraints are continually interacting to shape performance. As a consequence, this thesis presents some necessary and unique insights into representative learning design and movement adaptations in a sample of elite athletes. The questions examined in this programme of work relate to how best to structure practice, which is central to developing an effective learning environment in a high performance setting. Specifically, the series of studies reported in the chapters of this doctoral thesis: (i) provide evidence for the importance of designing representative practice tasks in training; (ii) establish that completed and baulked (prematurely terminated) take-offs are not different enough to justify the abortion of a planned dive; and (iii), confirm that elite athletes performing complex skills are able to adapt their movement patterns to achieve consistent performance outcomes from variable dive take-off conditions. Chapters One and Two of the thesis provide an overview of the theoretical ideas framing the programme of work, and include a review of literature pertinent to the research aims and subsequent empirical chapters. Chapter Three examined the representativeness of take-off tasks completed in the two AIS diving training facilities routinely used in springboard diving. Results highlighted differences in the preparatory phase of reverse dive take-offs completed by elite divers during normal training tasks in the dry-land and aquatic training environments. The most noticeable differences in dive take-off between environments began during the hurdle (step, jump, height and flight) where the diver generates the necessary momentum to complete the dive. Consequently, greater step lengths, jump heights and flight times, resulted in greater board depression prior to take-off in the aquatic environment where the dives required greater amounts of rotation. The differences observed between the preparatory phases of reverse dive take-offs completed in the dry-land and aquatic training environments are arguably a consequence of the constraints of the training environment. Specifically, differences in the environmental information available to the athletes, and the need to alter the landing (feet first vs. wrist first landing) from the take-off, resulted in a decoupling of important perception and action information and a decomposition of the dive take-off task. In attempting to only practise high quality dives, many athletes have followed a traditional motor learning approach (Schmidt, 1975) and tried to eliminate take-off variations during training. Chapter Four examined whether observable differences existed between the movement kinematics of elite divers in the preparation phases of baulked (prematurely terminated) and completed take-offs that might justify this approach to training. Qualitative and quantitative analyses of variability within conditions revealed greater consistency and less variability when dives were completed, and greater variability amongst baulked take-offs for all participants. Based on these findings, it is probable that athletes choose to abort a planned take-off when they detect small variations from the movement patterns (e.g., step lengths, jump height, springboard depression) of highly practiced comfortable dives. However, with no major differences in coordination patterns (topology of the angle-angle plots), and the potential for negative performance outcomes in competition, there appears to be no training advantage in baulking on unsatisfactory take-offs during training, except when a threat of injury is perceived by the athlete. Instead, it was considered that enhancing the athletes' movement adaptability would be a more functional motor learning strategy. In Chapter Five, a twelve-week training programme was conducted to determine whether a sample of elite divers were able to adapt their movement patterns and complete dives successfully, regardless of the perceived quality of their preparatory movements on the springboard. The data indeed suggested that elite divers were able to adapt their movements during the preparatory phase of the take-off and complete good quality dives under more varied take-off conditions; displaying greater consistency and stability in the key performance outcome (dive entry). These findings are in line with previous research findings from other sports (e.g., shooting, triple jump and basketball) and demonstrate how functional or compensatory movement variability can afford greater flexibility in task execution. By previously only practising dives with good quality take-offs, it can be argued that divers only developed strong couplings between information and movement under very specific performance circumstances. As a result, this sample was sometimes characterised by poor performance in competition when the athletes experienced a suboptimal take-off. Throughout this training programme, where divers were encouraged to minimise baulking and attempt to complete every dive, they demonstrated that it was possible to strengthen the information and movement coupling in a variety of performance circumstances, widening of the basin of performance solutions and providing alternative couplings to solve a performance problem even when the take-off was not ideal. The results of this programme of research provide theoretical and experimental implications for understanding representative learning design and movement pattern variability in applied sports science research. Theoretically, this PhD programme contributes empirical evidence to demonstrate the importance of representative design in the training environments of high performance sports programmes. Specifically, this thesis advocates for the design of learning environments that effectively capture and enhance functional and flexible movement responses representative of performance contexts. Further, data from this thesis showed that elite athletes performing complex tasks were able to adapt their movements in the preparatory phase and complete good quality dives under more varied take-off conditions. This finding signals some significant practical implications for athletes, coaches and sports scientists. As such, it is recommended that care should be taken by coaches when designing practice tasks since the clear implication is that athletes need to practice adapting movement patterns during ongoing regulation of multi-articular coordination tasks. For example, volleyball servers can adapt to small variations in the ball toss phase, long jumpers can visually regulate gait as they prepare for the take-off, and springboard divers need to continue to practice adapting their take-off from the hurdle step. In summary, the studies of this programme of work have confirmed that the task constraints of training environments in elite sport performance programmes need to provide a faithful simulation of a competitive performance environment in order that performance outcomes may be stabilised with practice. Further, it is apparent that training environments can be enhanced by ensuring the representative design of task constraints, which have high action fidelity with the performance context. Ultimately, this study recommends that the traditional coaching adage 'perfect practice makes perfect", be reconsidered; instead advocating that practice should be, as Bernstein (1967) suggested, "repetition without repetition".

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Software watermarking resilient to debugging attacks

In 2006, Gaurav Gupta and Josef Pieprzyk presented an attack on the branch-based software watermarking scheme proposed by Ginger Myles and Hongxia Jin in 2005. The software watermarking model is based on replacing jump instructions or unconditional branch statements (UBS) by calls to a fingerprint branch function (FBF) that computes the correct target address of the UBS as a function of the generated fingerprint and integrity check. If the program is tampered with, the fingerprint and/or integrity checks change and the target address is not computed correctly. Gupta and Pieprzyk's attack uses debugger capabilities such as register and address lookup and breakpoints to minimize the requirement to manually inspect the software. Using these resources, the FBF and calls to the same is identified, correct displacement values are generated and calls to FBF are replaced by the original UBS transferring control of the attack to the correct target instruction. In this paper, we propose a watermarking model that provides security against such debugging attacks. Two primary measures taken are shifting the stack pointer modification operation from the FBF to the individual UBSs, and coding the stack pointer modification in the same language as that of the rest of the code rather than assembly language to avoid conspicuous contents. The manual component complexity increases from O(1) in the previous scheme to O(n) in our proposed scheme.

Structure-mediated thermal transport of monolayer graphene allotropes nanoribbons

We report the study of the thermal transport management of monolayer graphene allotrope nanoribbons (size ∼20 × 4 nm2) by the modulation of their structures via molecular dynamics simulations. The thermal conductivity of graphyne (GY)-like geometries is observed to decrease monotonously with increasing number of acetylenic linkages between adjacent hexagons. Strikingly, by incorporating those GY or GY-like structures, the thermal performance of graphene can be effectively engineered. The resulting hetero-junctions possess a sharp local temperature jump at the interface, and show a much lower effective thermal conductivity due to the enhanced phonon–phonon scattering. More importantly, by controlling the percentage, type and distribution pattern of the GY or GY-like structures, the hetero-junctions are found to exhibit tunable thermal transport properties (including the effective thermal conductivity, interfacial thermal resistance and rectification). This study provides a heuristic guideline to manipulate the thermal properties of 2D carbon networks, ideal for application in thermoelectric devices with strongly suppressed thermal conductivity.

Conspiracy for good

"Tim Kring, Creator of the hit television show 'Heroes' tells how the big idea began, and where you can jump in. "A few years ago, I started thinking about an entirely new way to tell a story, far different from traditional TV. I didn't just want to talk about 'saving the world' in fiction, I wanted to create a narrative that spilled out into the streets. One that you could live inside of for a while. How cool would it be, I thought, to create a story that exists all around you all of the time? On your laptop, your mobile phone, on your sidewalks, as a secret message hidden in your favorite song or while standing at the bus stop on your way to work. And, taking it further, what if your participation over a few weeks or months actually impacts the story's development and creates positive change in the real world because a philanthropic mission is integrated into the narrative itself? The Conspiracy For Good is the culmination of this dream. This is the pilot project for a first-of-itskind interactive story that empowers its audience to take real-life action and create positive change in the world. Call it Social Benefit Storytelling. To achieve this, I need you to participate. Reality and fiction have to blur. Every story needs a villain and you will meet the villain in the STORY SO FAR section on this site. And every story needs a hero. That's where YOU come in. As part of The Conspiracy For Good you will join a collective of thinkers, artists, musicians, and causes, creating a unified voice to fight the forces of social and environmental injustice. This is our site, where together we can follow the story and build a community that focuses on changing the world for the better, one person and one action at a time. Welcome to the Conspiracy." Tim Kring"

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

Thought balloon : Dr Christy Dena

In this interview, we discuss the basics of transmedia storytelling and lessons for creatives considering making the jump to a transmedia project.

Cold water immersion enhances recovery of submaximal muscle function after resistance exercise

We investigated the effect of cold water immersion (CWI) on the recovery of muscle function and physiological responses following high-intensity resistance exercise. Using a randomized, cross-over design, 10 physically active men performed high-intensity resistance exercise, followed by one of two recovery interventions: 10 min of cold water immersion at 10°C, or 10 min active recovery (low-intensity cycling). After the recovery interventions, maximal muscle function was assessed after 2 h and 4 h by measuring jump height and isometric squat strength. Submaximal muscle function was assessed after 6 h by measuring the average load lifted during six sets of 10 squats at 80% 1RM. Intramuscular temperature (1 cm) was also recorded, and venous blood samples were analyzed for markers of metabolism, vasoconstriction and muscle damage. CWI did not enhance recovery of maximal muscle function. However, during the final three sets of the submaximal muscle function test, the participants lifted a greater load (p<0.05; 38%; Cohen’s d 1.3) following CWI compared with active recovery. During CWI, muscle temperature decreased 6°C below post-exercise values, and remained below pre-exercise values for another 35 min. Venous blood O2 saturation decreased below pre-exercise values for 1.5 h after CWI. Serum endothelin-1 concentration did not change after CWI, whereas it decreased after active recovery. Plasma myoglobin concentration was lower, whereas plasma interleukin-6 concentration was higher after CWI compared with active recovery. These results suggest that cold water immersion after resistance exercise allow athletes to complete more work during subsequent training sessions, which could enhance long-term training adaptations.

Statistical methods for electromyography data and associated problems

This thesis proposes three novel models which extend the statistical methodology for motor unit number estimation, a clinical neurology technique. Motor unit number estimation is important in the treatment of degenerative muscular diseases and, potentially, spinal injury. Additionally, a recent and untested statistic to enable statistical model choice is found to be a practical alternative for larger datasets. The existing methods for dose finding in dual-agent clinical trials are found to be suitable only for designs of modest dimensions. The model choice case-study is the first of its kind containing interesting results using so-called unit information prior distributions.

Is there a potential relationship between prior h amstring strain injury and increased risk for future a nterior cruciate ligament injury?

Hamstring strain injuries (HSIs) are the most prevalent injury in a number of sports, and while anterior cruciate ligament (ACL) injuries are less common, they are far more severe and have long-term implications, such as an increased risk of developing osteoarthritis later in life. Given the high incidence and severity of these injuries, they are key targets of injury preventive programs in elite sport. Evidence has shown that a previous severe knee injury (including ACL injury) increases the risk of HSI; however, whether the functional deficits that occur after HSI result in an increased risk of ACL injury has yet to be considered. In this clinical commentary, we present evidence that suggests that the link between previous HSI and increased risk of ACL injury requires further investigation by drawing parallels between deficits in hamstring function after HSI and in women athletes, who are more prone to ACL injury than men athletes. Comparisons between the neuromuscular function of the male and female hamstring has shown that women display lower hamstring-to-quadriceps strength ratios during isokinetic knee flexion and extension, increased activation of the quadriceps compared with the hamstrings during a stop-jump landing task, a greater time required to reach maximal isokinetic hamstring torque, and lower integrated myoelectrical hamstring activity during a sidestep cutting maneuver. Somewhat similarly, in athletes with a history of HSI, the previously injured limb, compared with the uninjured limb, displays lower eccentric knee flexor strength, a lower hamstrings-to-quadriceps strength ratio, lower voluntary myoelectrical activity during maximal knee flexor eccentric contraction, a lower knee flexor eccentric rate of torque development, and lower voluntary myoelectrical activity during the initial portion of eccentric contraction. Given that the medial and lateral hamstrings have different actions at the knee joint in the coronal plane, which hamstring head is previously injured might also be expected to influence the likelihood of future ACL. Whether the deficits in function after HSI, as seen in laboratory-based studies, translate to deficits in hamstring function during typical injurious tasks for ACL injury has yet to be determined but should be a consideration for future work.

Multi-modal deformable medical image registration

Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between images acquired from different individuals or atlases. Furthermore, certain applications require this type of registration to operate across images acquired from different imaging modalities. One popular local approach for estimating this registration is a block matching procedure utilising the mutual information criterion. However, previous block matching procedures generate a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. This paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo statistical procedure to optimally select grid points of interest. Three different methods are then compared to propagate the estimated sparse deformation field to the entire image including a thin-plate spline warp, Gaussian convolution, and a hybrid fluid technique. Results show that non-rigid registration can be improved by using the proposed algorithm to optimally select grid points of interest.

Hydrotherapy as a recovery strategy after exercise: A pragmatic controlled trial

Background Our aim was to evaluate the recovery effects of hydrotherapy after aerobic exercise in cardiovascular, performance and perceived fatigue. Methods A pragmatic controlled repeated measures; single-blind trial was conducted. Thirty-four recreational sportspeople visited a Sport-Centre and were assigned to a Hydrotherapy group (experimental) or rest in a bed (control) after completing a spinning session. Main outcomes measures including blood pressure, heart rate, handgrip strength, vertical jump, self-perceived fatigue, and body temperature were assessed at baseline, immediately post-exercise and post-recovery. The hypothesis of interest was the session*time interaction. Results The analysis revealed significant session*time interactions for diastolic blood pressure (P=0.031), heart rate (P=0.041), self perceived fatigue (P=0.046), and body temperature (P=0.001); but not for vertical jump (P=0.437), handgrip (P=0.845) or systolic blood pressure (P=0.266). Post-hoc analysis revealed that hydrotherapy resulted in recovered heart rate and diastolic blood pressure similar to baseline values after the spinning session. Further, hydrotherapy resulted in decreased self-perceived fatigue after the spinning session. Conclusions Our results support that hydrotherapy is an adequate strategy to facilitate cardiovascular recovers and perceived fatigue, but not strength, after spinning exercise. Trial registration ClinicalTrials.gov Identifier: NCT01765387 Keywords: Hydrotherapy; Heart rate; Fatigue; Strength; Blood pressure; Body temperature

Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods

In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.