April 2013
1 post
2 tags
Piled Higher and Deeper
The business press is reporting on a recently published paper,
Quantifying Trading Behavior in Financial Markets using Google Trends, by Tobias Preis, Helen Susanannah Moat, and H. Eugene Stanley.
This paper has not had as much impact as that of Bollen et al., probably because it does not make
such outlandish claims, but likely also because Google Trends is not as sexy as Twitter.
The Preis et...
March 2013
1 post
3 tags
Did you ever think your tweets might predict the...
Not wanting to get be left behind on all this ‘social media’ stuff, Fox Business News
trotted out Johan Bollen
for an interview regarding his research. Bollen notes that his system is designed
for hedge funds looking for a little extra alpha, not retail clients. This displays
shrewd market positioning on his part, since Derwent’s experiment with bringing
social media trading to...
February 2013
1 post
3 tags
The Sentiment Trading Platform is for Sale
Derwent Capital, the former hedge fund turned retail broker
announced that they are auctioning themselves to the
highest bidder. At the moment, the highest bid id 100K GBP, far lower than the
350K over/under number for profitability,
according to Paul Hawtin,
Derwent’s CEO.
The ‘guidance figure’ (read: anchor) is 5M GBP, and as part of the deal you take ownership of
the...
July 2012
5 posts
1 tag
You had me at the third significant digit
I have, in the past,
been rather harsh
on Bollen, Mao and Zheng for their Twitter
paper, which boggles the imagination with its naïveté. However, to their credit,
theirs is not clearly the most ridiculous ‘quant’ paper I have ever seen.
A recent contender for that distinction is
Limited Attention, Salience, and Stock Returns, by A. Subrahmanyam, J. Wei, and H-Y. Yu,
dated March 25,...
2 tags
Converting Timing Edge to Sharpe
Let \(x_t\) be the time series of relative returns of some instrument. As a very
rudimentary market timing model, suppose you have a signal \(s_{t-1}\) which equals
\(\mbox{sign}\left(x_t\right)\) with probability \(p = \frac{1}{2} + g\), and otherwise
equals \(-\mbox{sign}\left(x_t\right)\). Here \(g \in \left[-0.5,0.5\right]\) is one’s
timing edge over a coin flip. Note that I find this...
nancefinance asked: Thanks for your response. Question: Why did you address your letter to Johan Bollen and not to Derwent?
nancefinance asked: do you have the screenshots for the 2012 managed account reports at derwent? thanks.
3 tags
An open letter to Johan Bollen
Johan,
You may be wondering why you are not living on your own Carribean island
by now. I had the same feeling once, a long time ago, after my first hedge fund
launch. You will get over it. I am guessing that Paul Hawtin
is no longer returning your calls, since Derwent
somehow fumbled
in implementing your ideas. Well, you do not need them: I am going to
offer you a chance to redeem your...
June 2012
1 post
4 tags
Derwent closes shop
In May the Financial Times reported
that Derwent Capital, the hedge fund
that partnered with Johan Bollen and Huina Mao to trade
the “Twitter Predictor” Strategy “shut down”.
The official story
is that Derwent’s Capital Markets’ Absolute Return fund opened
for investments in July 2011, and shuttered after a single month, with reported
returns of 1.86%.
...
May 2012
1 post
3 tags
The 'Twitter Hedge Fund' has an out-of-sample...
Derwent Capital, the Hedge fund which is
working with Johan Bollen and Huina Mao to implement
their ‘Twitter Predictor’ strategy, had, until recently, been
publishing their monthly returns on the web. This is fairly irregular: hedge funds typically do
not release this data due to regulatory concerns and performance anxiety. Even more irregular, as of
May 3rd, 2012, the monthly...
April 2012
1 post
3 tags
The junk science behind the 'Twitter Hedge Fund'
“Twitter Mood Predicts the Stock Market”
In a widely cited study, Johan Bollen, Huina Mao and Xiao-Jun Zeng claim
that
… collective mood states derived from large-scale Twitter feeds are correlated to the value of
the Dow Jones Industrial Average (DJIA) over time. … We find an accuracy of 87.6% in predicting
the daily up and down changes in the closing values...
