Application of machine learning to short-term equity return prediction

Cooper showed how a filter method could be used to predict equity returns for the next week by using information about returns and volume for the two previous weeks. Cooper's method may be regarded as a crude method of Machine Learning. Over the last 20 years Machine Learning has been successfully applied to the modeling of large data sets, often containing a lot of noise, in many different fields. When applying the technique it is important to fit it to the specific problem under consideration. We have designed and applied to Cooper's problem a practical new method of Machine Learning, appropriate to the problem, that is based on a modification of the well-known kernel regression method. We call it the Prototype Kernel Regression method (PKR). In both the period 1978-1993 studied by Cooper, and the period 1994-2004, the PKR method leads to a clear profit improvement compared to Cooper's approach. In all of 48 different cases studied, the period pre-cost average return is larger for the PKR method than Cooper's method, on average 37% higher, and that margin would increase as costs were taken into account. Our method aims to minimize the danger of data snooping, and it could plausibly have been applied in 1994 or earlier. There may be a lesson here for proponents of the Efficient Market Hypothesis in the form that states that profitable prediction of equity returns is impossible except by chance. It is not enough for them to show that the profits from an anomaly-based trading scheme disappear after costs. The proponents should also consider what would have been plausible applications of more sophisticated Machine Learning techniques before dismissing evidence against the EMH.

Advanced high frequency switched-mode power supply techniques and applications

This Thesis examines the operation and dynamic performance of a single-stage, single-switch power factor corrector, S4 PFC, with an integrated magnetic device, IM. Also detailed isthe development and analysis of a high power light emitting diode, HP LED, power factorcorrection converter and proposed voltage regulation band control approach.The S4 PFC consists of a cascaded discontinuous current mode, DCM, boost stage anda continuous current mode, CCM, forward converter. The S4 PFC achieves a high powerfactor, low input current harmonics and a regulated voltage output, utilising a singleMOSFET. A steady-state analysis of the S4 PFC with the IM is performed, identifying theoperating boundary conditions for the DCM power factor correction stage and the CCMoutput voltage regulation stage. Integrated magnetic analysis focuses on understanding theperformance, operation and generated flux paths within the IM core, ensuring the device doesnot affect the normal operation of the converter power stage. A design method for the S4 PFCwith IM component is developed along with a cost analysis of this approach. Analysis predictsthe performance of the S4 PFC and the IM, and the theoretical work is validated by MATLABand SABER simulations and measurements of a 180 W prototype converter.It is not only the development of new topological approaches that drives theadvancement of power electronic techniques. The recent emergence of HP LEDs has led to aflurry of new application areas for these devices. A DCM buck-boost converter performs thepower factor correction and energy storage, and a cascaded boundary conduction current modebuck converter regulates the current through the LED arrays. To match the useful operatinglifetime of the HP LEDs, electrolytic capacitors are not used in the PFC converter. Analysisexamines the operation and dynamic characteristics of a PFC converter with low capacitiveenergy storage capacity and its implications on the control method. A modified regulationband control approach is proposed to ensure a high power factor, low input current harmonicsand output voltage regulation of the PFC stage. Small signal analysis describes the dynamicperformance of the PFC converter, Circle Criterion is used to determine the loop stability.Theoretical work is validated by SABER and MATLAB simulations and measurements of a180 W prototype street luminaire.EThOS - Electronic Theses Online ServicePSU DesignsDialight LumidrivesGBUnited Kingdo

Blip glitches in Advanced LIGO data

Blip glitches are short noise transients present in data from ground-based gravitational-wave observatories. These glitches resemble the gravitational-wave signature of massive binary black hole mergers. Hence, the sensitivity of transient gravitational-wave searches to such high-mass systems and other potential short duration sources is degraded by the presence of blip glitches. The origin and rate of occurrence of this type of glitch have been largely unknown. In this paper we explore the population of blip glitches in Advanced LIGO during its first and second observing runs. On average, we find that Advanced LIGO data contains approximately two blip glitches per hour of data. We identify four subsets of blip glitches correlated with detector auxiliary or environmental sensor channels, however the physical causes of the majority of blips remain unclear

Application of machine learning to short-term equity return prediction

Cooper showed how a filter method could be used to predict equity returns for the next week by using information about returns and volume for the two previous weeks. Cooper's method may be regarded as a crude method of Machine Learning. Over the last 20 years Machine Learning has been successfully applied to the modeling of large data sets, often containing a lot of noise, in many different fields. When applying the technique it is important to fit it to the specific problem under consideration. We have designed and applied to Cooper's problem a practical new method of Machine Learning, appropriate to the problem, that is based on a modification of the well-known kernel regression method. We call it the Prototype Kernel Regression method (PKR). In both the period 1978-1993 studied by Cooper, and the period 1994-2004, the PKR method leads to a clear profit improvement compared to Cooper's approach. In all of 48 different cases studied, the period pre-cost average return is larger for the PKR method than Cooper's method, on average 37% higher, and that margin would increase as costs were taken into account. Our method aims to minimize the danger of data snooping, and it could plausibly have been applied in 1994 or earlier. There may be a lesson here for proponents of the Efficient Market Hypothesis in the form that states that profitable prediction of equity returns is impossible except by chance. It is not enough for them to show that the profits from an anomaly-based trading scheme disappear after costs. The proponents should also consider what would have been plausible applications of more sophisticated Machine Learning techniques before dismissing evidence against the EMH

Neuroprotection by minocycline in murine traumatic spinal cord injury: analyses of matrix metalloproteinases

Aim: Minocycline has neuroprotective activities in several models of neurological disorders including spinal cord injury (SCI) where it prevents axonal loss and improves functional recovery. There are still gaps of knowledge on minocycline in SCI including whether it ameliorates neuronal loss at the focal site of trauma, and whether minocycline reduces the activity of matrix metalloproteinases (MMPs), a family of enzymes implicated in the pathophysiology of SCI. This study addressed these gaps. Methods: Mice were treated with either minocycline or vehicle control after a spinal cord contusion. MMPs were compared between the two groups using real time polymerase chain reaction and zymography. Immunohistochemistry was used to examine microglial activation and neuronal cell death. Results: While several MMP members were elevated in the spinal cord following injury, treatment with minocycline did not affect their expression. Importantly, minocycline reduced the loss of neurons in the epicenter of damage to the spinal cord and in segments caudal and rostral to the injury. Conclusion: Despite the inability of minocycline to alter MMPs, the results of neuroprotection at the lesion site support the continued testing of minocycline as a neuroprotective medication in experimental and clinical SCI

Inner hair cell responses to the velocity of basilar membrane motion in the guinea pig

Triangular wave acoustic stimulation at 200 Hz produced the expected square wave cochlear microphonic at the round window membrane and within the scala media. Intracellular recordings from inner hair cells (IHC) of the first cochlear turn showed a combination waveform having both spike impulse and square wave features. The IHC response suggests a sensitivity of these cells to both the displacement and to the velocity of basilar membrane motion.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24391/1/0000661.pd

Synchrotron X-Ray Studies of Surface Disordering

Contains an introduction and reports on three research projects.Joint Services Electronics Program Contract DAAL03-92-C-000

The impact of age and psychosocial factors on cognitive and auditory outcomes during the COVID-19 pandemic

Purpose: In March 2020, the UK government announced that people should isolate to reduce the spread of the virus that causes COVID-19. Outside a pandemic, psychosocial factors, such as socialisation and mental health, may impact the relationship between hearing loss and increased dementia risk. We aim to report the impact of psychosocial factors, including social isolation, depression, and engagement in activities, on hearing and cognitive function in younger and older adults during the COVID-19 pandemic. Method: An online survey and experiment assessed self-reported psychosocial factors, self-reported hearing ability and speech-in-noise perception, and cognition. Data were collected between June 2020 and February 2021. Older (N = 112, MAGE = 70.08) and younger (N = 121, MAGE = 20.52) monolingual speakers of English, without any language or neurological disorders participated. Multiple linear regression models were employed to investigate hypothesised associations between psychosocial factors, and hearing and cognition, in older and younger adults. Results: Multiple regression analyses indicated that older adults displayed poorer speech-in-noise perception and poorer performance on one of four cognitive tasks, compared to younger adults; and increased depression was associated with poorer subjective hearing. Other psychosocial factors did not significantly predict hearing or cognitive function. Conclusions: Data suggest that self-reported hearing and depression are related. This conclusion is important for understanding the associations between hearing loss and cognitive decline in the long-term, as both hearing loss and depression are risk factors for dementia

The impact of age and psychosocial factors on cognitive and auditory outcomes during the COVID-19 pandemic

Purpose: In March 2020, the UK government announced that people should isolate to reduce the spread of the virus that causes COVID-19. Outside a pandemic, psychosocial factors, such as socialisation and mental health, may impact the relationship between hearing loss and increased dementia risk. We aim to report the impact of psychosocial factors, including social isolation, depression, and engagement in activities, on hearing and cognitive function in younger and older adults during the COVID-19 pandemic. Method: An online survey and experiment assessed self-reported psychosocial factors, self-reported hearing ability and speech-in-noise perception, and cognition. Data were collected between June 2020 and February 2021. Older (N = 112, MAGE = 70.08) and younger (N = 121, MAGE = 20.52) monolingual speakers of English, without any language or neurological disorders participated. Multiple linear regression models were employed to investigate hypothesised associations between psychosocial factors, and hearing and cognition, in older and younger adults. Results: Multiple regression analyses indicated that older adults displayed poorer speech-in-noise perception and poorer performance on one of four cognitive tasks, compared to younger adults; and increased depression was associated with poorer subjective hearing. Other psychosocial factors did not significantly predict hearing or cognitive function. Conclusions: Data suggest that self-reported hearing and depression are related. This conclusion is important for understanding the associations between hearing loss and cognitive decline in the long-term, as both hearing loss and depression are risk factors for dementia