"Rothschild coaches careered down highways;
Rothschild boats set sail across the Channel; Rothschild messengers were swift
shadows along the streets. They carried cash, securities, letters and news.
Above all, news---latest, exclusive news to be vigorously processed at stock
market and commodity bourse."
Morton (1962), "The Rothschilds: Portrait of a Dynasty"
many stories and legends surrounding the Rothschild family, and probably most
are untrue. It is widely acknowledged
that Nathan Rothschild was the first Londoner
to receive the news that Wellington had defeated Napoleon at the Battle of
Waterloo in 1815. Rothschild received
this information through his network of fast carrier pigeons, which one of his
agents released from Waterloo when the battle was likely to be won.
News of the
outcome of the Battle of Waterloo was breathlessly awaited in the British financial
markets. According to legend, when Nathan
Rothschild entered into the Exchange the day of the victory, he was already
known as a master of speedy information. As such he took up his usual trading
position and began quietly selling British Consols (bonds) into the
market. Traders quickly identified his
selling, spurring a panic. It was assumed by traders that Rothschild had
heard Wellington was defeated. Then,
legend has it, in the midst of the panic Rothschild began stealthily buying
Consols. He purchased a sizable position
before traders realized they had been fooled and drove prices higher. Rothschild increased his profit from the
victory dramatically by engineering a short-term panic and then buying into it.
serves to illustrate that there are two primary ways to profit as an investor: 1) Get
important information fastest, and 2) Know
how the herd will react. If you
know what the investing herd believes, fears, and expects, then you know how it
is likely to react to new information.
Back to point
1). Getting relevant information fastest
has always been the most straightforward key to successful investing. And the hunt for the fastest information has
spawned the term “Algo Wars” to
describe the arms race among HFTs
for faster servers, co-location, re-engineered routers, and other accoutrements
of light-speed trading. The time
advantage HFTs use is incredibly narrow.
For example, the May 1, 2013 WSJ profiles how HFTs use a 1-10 millisecond
advantage to rapidly detect order-flow and front-run larger orders.
MarketPsych Data our clients include the largest hedge funds in the world, and we
can’t say exactly how our clients are trading off our sentiment feed. The TRMI are published minutely as a 1440
minute (24-hour) rolling average. And
several of our indices do show evidence of the #HackCrash event as you can see
To be clear
about the title question, I doubt the
Reuters MarketPsych Indices
(TRMI) data feed contributed to Tuesday April 23rd’s HackCrash in
which the S&P 500 plunged 1% and then recovered all within the span of 4
minutes. But I can’t be sure. The TRMI both show fast evidence of the event
and also give an excellent read on the beliefs and expectations of the
looks at the role of information speed
and herd impact. We’ll first take a look at a famous failure
related to United Airlines, then we’ll visit how our systems dealt with the hacked
Associated Press tweet and its aftermath, and finally we review a few
investment ideas for the week.
For those who
criticize High Frequency Traders (HFTs) and their use of social and news media
feeds for risk management, I’m going to step up in their defense about this
the vast majority of market makers
are high frequency traders. As a market
maker, every day you are buying and selling in the market for clients. That’s your job. But your job is very risky. The single biggest risk to you as a market
maker is being caught flat-footed –
not being prepared for a dramatic event that your clients see before you and
trade against you. So you exercise risk
management. In this case, like
Rothschild, you need to see the defeat or victory first.
typically engineers and computer scientists, and many of them understand social
media and text analytics well enough to construct simple systems that detect catastrophes reported in the
news. When an Associated Press tweet
contains the words: “Obama, bomb, White
House, injured” – that’s an easy catch for a text analytics algorithm.
would a market maker do in such a case?
They withdraw their bids. They won’t go long if a potential catastrophe
is in play. Then as selling enters the
market, it causes a steep dive. When it
is clear the tweet is a “hoax” or a “false alarm” or no longer corroborated by
other sources, their algorithms begin to ignore the information – “all clear”
they signal. And bids re-enter,
This may not
be a pleasant reality of the market-making system, but it is necessary for
market-makers in the age of Twitter to be
as fast as Twitter. Otherwise they
would not survive.
Do some high
frequency traders also pursue Rothschild’s second key to profit, manipulating
the herd? Absolutely. Look at Business Insider’s indictment of HFT’s manipulating Natural Gas prices in the low-volume seconds
before inventory releases, called “Banging the Beehive.” Anxious traders are led to believe the news has
been released (or someone knows more than them), and panic ensues in one
direction. Limit orders and stops are
filled, then prices reverse dramatically in the opposite direction.
Our data satisfies
the need for both of Rothschild’s insights: 1) minutely access to low-latency
Thomson Reuters news and social media feeds and 2) a quantitative measure of
the fears, expectations, and consensus of the market herd. The following example illustrates how the
intersection of quick reactions to bad news (1) and herd fear (2) can drive
enormous price moves.
Reported United Airlines’ Bankruptcy 6 Years Late
September 8, 2008 a South Florida Sun-Sentinel United Airlines (UAUA)
bankruptcy article from 2002 was listed onto the live Google News website as if
it were current. From Google News a
hurried editor at Bloomberg republished the article onto the Bloomberg news
feed at 10:53 a.m. The below chart
depicts the price action in UAUA (United Airlines) stock at the news of its
frequency traders performing text analytics on the Bloomberg news wire
decimated the price of UAL in minutes.
According to MarketWatch:
“Trading in UAL (US:UAUA) stock was halted at about 11:06 a.m. Eastern
time after falling nearly 76% to $3 a share. Shares resumed trading at about
12:25 p.m. They closed with an 11.2% loss at $10.92.” A dramatic daily loss occurred for UAUA
despite the released information being 6
analytics has been a robust business since the mid-2000s. Firms including Thomson Reuters, Bloomberg,
and Dow Jones offer low-latency news feeds.
Thomson Reuters and Dow Jones (indirectly) offer pre-analyzed feeds with
low-latency sentiment tagging. In the
past two years social media has been added into the low-latency news mix, including our own product with Thomson
is remarkable because it occurred due to social
media. Despite the prevalence of
trading on social media (including our own fund, which was the first), social
media communications have never before impacted markets so significantly.
image from MarketWatch captures the drama of the tweet and the price impact on
the S&P 500:
can see, the fall was fast and the recovery even more dramatic.
if any, was our role in the event?
movement in several of our indices after the incriminating AP Tweet was
released. To be clear, we and most other
text analytics firms have screens to detect when information being conveyed is explicitly
false. For example, when information
about an event is qualified as a “hoax,” “fake,” or “false alarm” our systems
ignore the indicated content of the message (it is not scored). So when we looked at our minutely Thomson Reuters
MarketPsych Indices for the
S&P 500 and the United States using combined social and news media content,
we see interesting evidence of the event, but only a tiny – almost
imperceptible - blip indicating that there was an attack, as it was quickly
Below are visuals showing both the long-term and the short term impacts of
the event on our relevant sentiment feeds.
In these charts, keep in mind that you are seeing a 24-hour average
(1440 minute rolling average). On a
minutely level the action is much more dramatic. Nonetheless, it can be seen here as well.
In the big picture, we note that the Thomson Reuters
MarketPsych Optimism Index for the
S&P 500 fell steeply following the fake AP tweet and the market price tremor. The following chart depicts a 48-hour
period in GMT/UTC time from April 23rd through April 24th. (GMT time is currently 4 hours ahead of the
U.S. East Coast time zone). The
decreased Optimism was fairly short-lived, lasting for about 24-hours.
the course of minutes we saw rapid dissemination of the event reflected in
our S&P 500 PriceUp index
(PriceUp is a net of references to prices rising or falling). Conversations about the price first falling
and then rising were rapidly disseminated through social and news media.
a result of the language used to describe the event, we saw the Thomson
Reuters MarketPsych MarketRisk
index surge. The MarketRisk index
measures emotive and speculative conversations that tend to predict riskier
markets to come. Though it surged for
a few hours, it declined rapidly thereafter as concerns faded.
The above graphics display our findings around the S&P 500 and its
constituents. In our United States data
feed, we noticed a rise in Anger at the United States government. The report of Syrian hackers posting the
tweet due to anger at the U.S. Government’s support for the Free Syrian Army was
accurately scored. Because the news of
the alleged perpetrators and their motivation arrived late, it does not appear
as a dramatic jump but rather a slow rise in the index over 24 hours.
The event was
an odd event – it wasn’t an ACTUAL attack.
For example, it should not have appeared in our United States Violence
index. And it didn’t - it registered
only as a tiny blip due to it being quickly identified as a fake. That said, the price reaction did impact
investor perceptions, for example the event increased pessimism significantly
over 24 hours.
How was this
event trade-able? I’d say that in the
1440 minute average, it likely was not.
That said, on a raw minutely level the action was very interesting.
underlying sentiment feed is perfect for market-maker
risk management uses. If you’re a market
maker, let me know if you’d like more information about how to use our data to
quickly identify and avoid risks.
our ideas this week are related to the #HackCrash. We’re currently seeing a one-week sell on Trina Solar (TSL). We also see a one-week sell on Herbalife (HLF) – a surge of excitement
in that stock likely to peak this week.
SEE DISCLAIMER at end of email.
These ideas were developed using backtesting and a hedge against the
S&P500, but you invest at your own risk.
week’s Buys on GLD, GDX, SLW, and ABX
went well, with all being significantly positive on the week (I’ll quantify
these later). There were no shorts last
week. I’ll give exact stats on recommendations
in another newsletter.
We are adding a monthly individual U.S. stock sentiment-based investment model
and a Russell 1000 sentiment ranking system to www.marketpsychinvest.com.
Users will be able to follow Ben Graham’s advice to buy from pessimists
and sell to optimists (easier said than done, of course). Please respond to this email for a free trial.
Keep in mind
Rothschild’s stratagem as you go forward.
If you don’t have the fastest information in the market, then you’ve got
to know the herd. What are they thinking and feeling, and how
are they likely to react to the next news release or major event?
Please contact us if
you’d like to see into the mind of the market using our Thomson Reuters
MarketPsych Indices to monitor
market psychology for 30 currencies, 50 commodities, 120 countries, and 40
equity sectors and industries in social and news media. This data is used by top global hedge funds
to improve their investment returns.
Please let us know if you’d like to learn more.
We love to chat with our readers about their
experience with psychology in the markets and with behavioral economics! Please also send us feedback on what you’d
like to hear more about in this area.
We have upcoming 2013 speaking engagements in New York, Orlando,
London, Chicago, and San Francisco – we look forward to seeing our friends in
those cities! Please contact Derek
Sweeney at the Sweeney
Agency to book us: [email protected],
Richard L. Peterson, M.D. and The MarketPsych
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