利用傅立叶分析法衡量风险的新方法

Michael Grabinski, Galiya Klinkova
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引用次数: 0

摘要

我们利用傅立叶分析法来了解金融产品的风险。我们用它来分析股票等产品的价格变化。通过傅立叶分析法,我们可以定量分析价格变化的频率是否高于公司价值(保守)变化所允许的频率。如果是这样,这将是投机和风险的明确指标。整个方法或其更好的应用都是相当新的。然而,之前的尝试存在严重缺陷,导致结果(而非方法)存疑。我们通过使用傅里叶变换而不是离散傅里叶分析等方法纠正了所有这些错误。我们的分析在整个频段内都是可靠的,如果价格得到相应的记录,甚至 1/1d 或更高频率的分析也是可靠的。对于所研究的股票,我们发现股票价格在一周内的变化不成比例,这清楚地表明了投机行为。将该方法应用于加密货币将是一个有趣的扩展,因为这些货币没有保存价值,这使得对波动性的正常考虑变得困难。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new measure of risk using Fourier analysis
We use Fourier analysis to access risk in financial products. With it we analyze price changes of e.g. stocks. Via Fourier analysis we scrutinize quantitatively whether the frequency of change is higher than a change in (conserved) company value would allow. If it is the case, it would be a clear indicator of speculation and with it risk. The entire methods or better its application is fairly new. However, there were severe flaws in previous attempts; making the results (not the method) doubtful. We corrected all these mistakes by e.g. using Fourier transformation instead of discrete Fourier analysis. Our analysis is reliable in the entire frequency band, even for fre-quency of 1/1d or higher if the prices are noted accordingly. For the stocks scrutinized we found that the price of stocks changes disproportionally within one week which clearly indicates spec-ulation. It would be an interesting extension to apply the method to crypto currencies as these currencies have no conserved value which makes normal considerations of volatility difficult.
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