Researchers develop method to compare pricing models

May 14, 2018, University of Erlangen-Nuremberg

A team of biophysicists from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) presents a mathematically concise method for comparing different pricing models in their latest publication in Nature Communications. This enables researchers to predict more accurately how parameters such as the volatility of stock prices change over time.

The ups and downs of are the result of a complex interplay between traditional investors, day-traders and high-frequency hedge funds. The seemingly erratic short-term price fluctuations can be characterized by a diffusion constant—called . However, volatility itself changes significantly over longer time scales. For example, unexpected Twitter announcements may trigger abrupt volatility spikes, while economic policy changes may induce gradual variations of volatility. Financial analysts notoriously struggle to estimate how volatility changes over time and often base their predictions on unsubstantiated assumptions.

Instead of evaluating the uncertainty of different predictions analytically, Christoph Mark and colleagues from the Biophysics group at FAU developed a numerical implementation of the principle of 'Occam's razor', which favors those models that describe the data with the least number of assumptions.

The researchers use this method to show that the so-called fat-tailed distribution of stock market returns (including rare but dramatic events such as Black Fridays and market bubbles) emerges naturally from sudden volatility fluctuations. Moreover, with their method they can pinpoint the triggering events (such as news announcements) in real-time.

Volatility fluctuations or, more generally speaking, heterogeneous random walks are not exclusive to finance, however, and also describe the movements of invasive cancer cells, the timing of accidents and disasters, and climate change. Here, their can be used to identify particularly invasive cells, to determine political measures that may reduce accidents, or to compare different climate models to forecast global warming.

Explore further: Stock market forces can be modeled with a quantum harmonic oscillator

More information: Christoph Mark et al, Bayesian model selection for complex dynamic systems, Nature Communications (2018). DOI: 10.1038/s41467-018-04241-5

Related Stories

Heterogeneous news flow on volatility

December 13, 2016

According to a new study from the University of Vaasa, it is possible to apply different statistical methods and information content of time series observations to estimate volatility. The results have importance, for example, ...

Using fear to guide smart investments

June 30, 2011

Playing the stock market can be a risky game. And when the market behaves unpredictably, public fear can lead to erratic investment responses and market chaos.

Ordered fear plays a strong role in market chaos

June 8, 2011

When the current financial crisis hit, the failure of traditional economic doctrines to provide any sort of early warning shocked not only financial experts worldwide, but also governments and the general public, and we all ...

Recommended for you

Permanent, wireless self-charging system using NIR band

October 8, 2018

As wearable devices are emerging, there are numerous studies on wireless charging systems. Here, a KAIST research team has developed a permanent, wireless self-charging platform for low-power wearable electronics by converting ...

Facebook launches AI video-calling device 'Portal'

October 8, 2018

Facebook on Monday launched a range of AI-powered video-calling devices, a strategic revolution for the social network giant which is aiming for a slice of the smart speaker market that is currently dominated by Amazon and ...

Artificial enzymes convert solar energy into hydrogen gas

October 4, 2018

In a new scientific article, researchers at Uppsala University describe how, using a completely new method, they have synthesised an artificial enzyme that functions in the metabolism of living cells. These enzymes can utilize ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.