转向市场时机:二项近似

Benjamin L. Cotton
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引用次数: 0

摘要

利用简单的二项式建模技术,我考虑了技术分析对预期收益、预期波动率和更高时刻风险的潜在影响。虽然作为一种实用的评估工具有限,但这种方法允许相对直观的观察与正在进行的关于市场时机有效性的论述相关。我展示了时间框架参考对风险感知的影响,表明市场时机在短期内类似于期权策略,而更准确地描述为从风险资产转移的配置。在没有序列自相关的情况下,在任何时间范围内,这种配置转移都是非常低效的,因为它会放大相对于回报相等的买入并持有风险资产配置的波动性(以方差或标准差衡量),并提供较差的下行保护。然而,市场择时作为一种下行保护策略的缺点可能会在较短的观察期内被掩盖,特别是如果分析忽略了与回报相当的买入并持有策略的苹果与苹果之间的比较。序列自相关改善了市场时机在回报、波动性和下行风险方面的前景,但达到风险调整盈亏平衡所需的水平可能高于经验记录中存在的水平。我使用了公认的基本技术,以开发和记录关键观察结果的方式,希望更容易被特定的目标受众——对继续学习金融和投资感兴趣的早期统计学/微积分预科课程的学生,以及较少接触更正式的符号惯例的投资者——所接受。高级学生/从业者会发现这种治疗有点不正统,但希望还是有趣的。
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On Turning to Market Timing: A Binomial Approximation
Utilizing simple binomial modeling techniques, I consider the potential impact of technical analysis on expected returns, expected volatility, and higher moment risk. While limited as a practical evaluation tool, this approach allows for relatively intuitive observations relevant to the ongoing discourse regarding the efficacy of market timing. I demonstrate the impact that timeframe reference can have on the perception of risk, showing that market timing can resemble an option strategy in the short-run while it is more accurately described as an allocation shift away from the risky asset. Absent the presence of serial autocorrelation and over any time horizon, this allocation shift is highly inefficient as it can magnify volatility (measured as variance or standard deviation) relative to a return equivalent buy-and-hold allocation to the risky asset and provides inferior downside protection as well. However, market-timing's shortcomings as a down-side-protection strategy are likely to be masked over shorter observations periods, particularly if the analysis omits an apples-to-apple comparison to a return equivalent buy-and-hold strategy. Serial autocorrelation improves the outlook for market timing in terms of return, volatility and down-side risk, but the level required to reach a risk-adjusted break-even is likely to be higher than has been present in the empirical record. I utilize techniques which are admittedly elementary in order to develop and document the key observations in way that is hopefully more accessible to a specific target audience - students in early statistics / pre-calculus courses with an interest in continued studies in finance and investing and investors with less exposure to more formal conventions of notation. Advanced students/practitioners will find this treatment a bit unorthodox, but hopefully interesting nonetheless.
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