RisKl.io

Smart stock chart annotations to understand jump risk

Explaining jumps in stock prices by using annotations. Annotations establish context between data and the underlying narrative.

What

Making sense of price movements is a hard thing to do. Looking at quantitative data only gives us an understanding of how prices jumped. It does not tell us why they jumped. Combining price jumps with reasons for why people bought / sold assets provides relevant context.

Identify

Jumps in financial price time series are identified using statistical methodology.

Classify

Machine-readable news headlines provide context to identified jumps. Using machine learning methods allows to match cause (news) and effect (price movement).

Analyse

Using tags allows to group together similar causes to identify the frequency and severity of reasons for different event categories.

How

Proof of conceptShare price of Deutsche Bank (DBK) by Google Finance, 01/06/2015 to 08/07/2016. Hyperlinks to articles in the description.
In case the chart is not loading please see this screenshot of the proof of concept.

Tag #the number of associated jumps within the time period 1-day changethe on-day price impact of the new information 5-day changethe price development following the next five days Description
Conduct 3 1.86% -7.69% News about fraud or any other wrongdoing
Operations 3 0.15% 1.32% News related to actions taken
Strategy 2 -6.23% -8.94% Strategy-related news about the business directon
Outlook 3 -1.78% -5.90% News related to overall market expectations

Why

The basis of RisKl.io is deeply rooted within financial modelling due to Robert Merton. In one of his seminal papers, he added to "normal" (the omni-present geometric Brownian motion) price movements a new component, representing "abnormal" movements or jumps (modelled by a compound Poisson jump process). He understood such jumps as
"the arrival of important new information about that stock that has more than a marginal effect on price." - Merton (1975, p.4)
Since then the how generated ample interest in the field whilst the why got sidelined. So let's pick up where Robert Merton left things more than 40 years ago.