Interactive Graphic for new Working Paper: 'Fake News'

My coauthor (William Pratt) and I will post our new working paper 'Fake News' here and to SSRN shortly.  It is an analysis of how false information of a takeover of Twitter on July 14 2015 was incorporated into market (stock and option) prices.

To accompany the paper, I created an interactive graphic to help understand the realtionship between Twitter's stock price and options implied volatility.  I am posting the graphic HERE, and linking to it in the journal article.  Take a look, and feedback is always welcome.

New Working Paper: Parameter Variation & the Components of Natural Gas Price Volatility

I have posted a new working paper of mine to the 'Working Paper' section.  The paper, Parameter Variation & the Components of Natural Gas Price Volatility, hypothesizes that parameters linking natural gas returns to fundamental variables will tend to change as market participants learn.  I therefore estimate the parameters using the Kalman filter.  I also decompose conditional natural gas volatility into portions attributable to each variable.  The abstract is below.


Estimating a static coefficient for a deseasoned gas storage or
weather variable implicitly assumes that market participants react
identically throughout the year (and over each year) to that variable.
In this analysis we model natural gas returns as a linear function of
gas storage and weather variables, and we allow the coefficients of this
function to vary continuously over time. This formulation takes into
account that market participants continuously try to improve their
forecasts of market prices, and this likely means they continuously
change the scale of their reaction to changes in underlying variables.
We use this model to also calculate conditional natural gas volatility
and the proportion of volatility attributable to each factor. We find
that return volatility is higher in the winter, and this increase is at-
tributable to increases in the proportion of volatility due to weather
and natural gas storage. We provide time series estimates of the chang-
ing proportion of volatility attributable to each factor, which is useful
for hedging and derivatives trading in natural gas markets.

State Dependence in the Natural Gas and Rig Count Relationship

I just posted a new working paper, 'State Dependence in the Natural Gas and Rig Count Relationship' to the USAEE working paper series on SSRN.  The paper is available for download here:

In a nutshell, the paper finds that changes in the north American natural gas rig count does affect future changes in natural gas prices (previous  research has not found this result).  The relationship is state dependent however.  When natural gas prices are above $6.74/MMBtu then increases in the rig count will drive down natural gas prices. Below this threshold the rig count does not affect gas prices (however gas prices affect the rig count). In sum, the evidence is consistent with gas producers, 'killing the rally' in gas prices by markedly increasing gas production.