Lack of proprioceptive feedback is one cause for the high upper-limb prosthesis abandonment rate. The lack of environmental interaction normalcy from unreliable proprioception creates dissatisfaction among prosthesis users. The purpose of this experiment is to investigate the effects of square breathing on learning to navigate without reliable proprioception. Square breathing is thought to influence the vagus nerve which is linked to increased learning rates. In this experiment, participants were instructed to reach toward targets in a semi-immersive virtual reality environment. Directional error, peak velocity, and peak acceleration of the reaching hand were investigated before and after participants underwent square breathing training. As the results of<br/>this experiment are inconclusive, further investigation needs to be done with larger sample sizes and examining unperturbed data to fully understand the effects of square breathing on learning new motor strategies in unreliable proprioceptive conditions.
Following a study conducted in 1991 supporting that kinesthetic information affects visual processing information when moving an arm in extrapersonal space, this research aims to suggest utilizing virtual-reality (VR) technology will lead to more accurate and faster data acquisition (Helms Tillery, et al.) [1]. The previous methods for conducting such research used ultrasonic systems of ultrasound emitters and microphones to track distance from the speed of sound. This method made the experimentation process long and spatial data difficult to synthesize. The purpose of this paper is to show the progress I have made in the efforts to capture spatial data using VR technology to enhance the previous research that has been done in the field of neuroscience. The experimental setup was completed using the Oculus Quest 2 VR headset and included hand controllers. The experiment simulation was created using Unity game engine to build a 3D VR world which can be used interactively with the Oculus. The result of this simulation allows the user to interact with a ball in the VR environment without seeing the body of the user. The VR simulation is able to be used in combination with real-time motion capture cameras to capture live spatial data of the user during trials, though spatial data from the VR environment has not been able to be collected.
本文根据市场有效性理论与行为金融学、交易反馈策略等理论,结合某大型基金公司过去16年累积的权益类基金投资者的日度交易数据,对投资者投资基金的交易行为特别是持有时间与投资回报的相关关系进行统计分析,验证投资期限与投资回报之间的相关关系。同时,研究投资者在不同交易结构下的申赎行为对投资回报的影响;以及投资者选择不同特征的基金产品对投资回报的影响和投资者持有基金期间的市场波动率对于投资回报的影响。
本文在实证研究的部分将通过数据分析验证理论模型,具体揭示不同因素(持有基金产品时间、申购赎回周期、基金经理换手率、大盘波动率、Jensen指数、基金资产规模、基金经理管理经验、基金经理更换频率等)与投资回报的相关关系。在此基础上,结合相关理论和实践背景,分析在不同情形下,基金投资者可以采取什么样的交易策略、应该重点关注基金产品的哪些指标,来调整自身的投资行为,提升投资回报;或者基金管理人可以通过哪些方式来帮助投资者采取正确的投资行为。
本文研究的意义在于利用大量个人投资者的日度交易数据,去探讨其交易行为与策略对投资回报的影响,剖析基金投资者难以赚钱的实际原因,从不同维度分析出现这种状况的多方面影响因素,从微观层面实现对基金投资者交易行为与基金投资回报研究这一课题在学术研究层次上的有效补充。并以此为依据,对基金管理公司、个人投资者、基金销售机构和监管层提出具有实践意义的建议,期望通过这些建议或措施逐渐改善基金投资者的投资回报。