Revolutionizing the Way Financial Professionals Analyze ... · Innovative 2 Executive Summary Who is Prattle Analytics? • Prattle Analytics was founded by Evan A. Schnidman Ph.D

1www.prattle-analytics.com

Revolutionizing the Way Financial Professionals Analyze Market Chatter


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Executive Summary

Who is Prattle Analytics? • Prattle Analytics was founded by Evan A. Schnidman Ph.D. (Harvard University)• Along with co-founder, William D. MacMillan Ph.D. (University of Michigan), Dr. Schnidman developed the first

unbiased, comprehensive, quantitative data based on the sentiment of central bank communications.

Why Quantitative Central Bank Data?• “Fed watching” has become increasingly important in recent years.• Existing methods for examining central bank policies remain biased and qualitative.• These qualitative assessments are imprecise and hard to incorporate into investing models.

Data Product Summary• The Fed Playbook is unbiased, quantitative data based on central bank communications.• Central bank sentiment data is sold in both raw and time-series formats. • Data on the following central banks is currently available to all customers:

• U.S. Federal Reserve • Reserve Bank of India • Swedish Riksbank • European Central Bank • Reserve Bank of New Zealand • Banco de Mexico • Bank of England • Bank of Canada • Central Bank of Brazil • Bank of Japan • Bank of Korea • Central Bank of Russia • Reserve Bank of Australia • South African Reserve Bank • Bank of Israel

How to Use The Fed Playbook:• Quantitative data on the sentiment of central banks can be integrated directly into existing models.• Data indicates strong correlations to fixed income, equity and currency markets allowing for market forecasting. • Backtesting reveals this data to be a strong buy-signal, and a superb sell-signal across asset classes.

www.prattle-analytics.com 2


Anal

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alTable of Contents

www.prattle-analytics.com 3

Letter From CEO 4

Methodology 5-6

Fixed Income 7-8

Equity Markets 9-12

Predictive Analysis 13-15

Other Applications 16

Data Delivery 17

Leadership Team 18

Legal Disclaimer 19

We take the ambiguity out of investing by providing the only comprehensive, unbiased and quantitative central bank data that is directly tradable.


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Letter From the CEO

To Prospective Data Users: We sincerely appreciate your interest in Prattle Analytics’ Fed Playbook data. At Prattle Analytics we pride ourselves not just on our expertise at finding signals in noisy data, but on putting those signals in the most useful format for finance professionals. Our Fed Playbook data analyzes the most complex central bank communications and scores the sentiment of each communi-cation to produce concrete, quantitative data that portfolio managers can input as a signal in their investment models.

The Fed Playbook arose out of frustration with the current method of “Fed Watching.” While the current parsing of a few sen-tences or phrases in specific Fed communications presents a vast improvement over the “Briefcase Watch” of the early Green-span era, it remains an imprecise approach to analyzing central bank policy. By continuing to parse only a couple of sentences or phrases in a small subset of central bank communications, the financial media and most professional analysts essentially disregard vital central bank communications. The resulting analysis is inherently biased, incomplete and difficult to operation-alize in financial models. Moreover, this dated approach fails to recognize three key facts:

1. Central banks around the world have become more transparent over the last two decades.

2. Since the financial crisis, central bankers have made a point of telling us that communications matter, with Janet Yellen even going so far as to say that “communications are policy” in reference to forward guidance.

3. With advances in modern computing, we now have the ability to quantify qualitative central bank communications.

It is in this landscape that we developed The Fed Playbook. Our data examines every communication in a comprehensive and unbiased way. The result is the first ever quantitative data on the sentiment of central bank communications. This data provides dozens of macro market indicators wrapped into one signal that can be directly integrated into existing investment models or used to develop new trading models. Regardless of how our customers utilize this data, we are confident that you will find it useful in understanding global macroeconomic markets and shaping your models to better perform in an uncertain market.

As an independent data provider we are dedicated to innovation and service, so if you have any questions about our data or requests for future data development, please do not hesitate to contact us.

Sincerely,

Evan A. Schnidman


Methodology in

sigh

tful Fed Playbook Overview:

• Prattle Analytics’ Fed Playbook data utilizes proprietary, patent pending, textual analysis techniques to systematically ana-lyze the content of ALL central bank communications.

• The content of these communications are analyzed to determine the sentiment of each communication then scaled against all prior communications.

• The final product sorts through all the noise generated by central banks to provide a credible signal in the form of the first ever quantitative “Fed Watching” data.

• The sentiment indicator data specifically on the United States Federal Reserve is called:

• The Fed Playbook (FPSI).

• Prattle Analytics has also developed comparable Fed Playbook Sentiment Indicator data for central banks around the world, including:

• U.S. Federal Reserve • Reserve Bank of India • Swedish Riksbank • European Central Bank • Reserve Bank of New Zealand • Banco de Mexico • Bank of England • Bank of Canada • Central Bank of Brazil • Bank of Japan • Bank of Korea • Central Bank of Russia • Reserve Bank of Australia • South African Reserve Bank • Bank of Israel


Methodology In

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FPSI Details:

• In order to gather data on the U.S. Federal Reserve, Prattle Analytics examines all Fed communications, including:

4FOMC meeting minutes

4FOMC press releases

4Congressional testimony by members of the Federal Reserve Board

4Speeches by both members of the Federal Reserve Board and Presidents of regional Federal Reserve Banks

• These communications are measured by an algorithm that maps the words used in the communications to a value on a real number line for use in a statistical model.

• We then use a proprietary mix of statistical methods to scale the text of the documents to a latent dimension that we describe as the Fed’s “mood.”

• Utilizing interrupted time series statistical specifications we are able to continuously update this “mood” measure with each additional communication.

• The result is a measure that identifies the sentiment of each new communication weighted by the history of all previous communications, the FPSI.

• Comparable methods are used for each central bank we analyze.


Methodology Pr

agm

atic How to Use FPSI Data:

As quantitative data on the sentiment of central bank communications that correlates with fixed income, equities and currency markets, this U.S. data has a wide variety of applications.

1. Buy Signal: 4Based on established correlations to various asset classes, this data serves as a strong buy signal.

4Buy signs can be further refined by examining correlations between the FPSI and industry sectors or individual securities.

2. Sell Signal: 4While the FPSI serves as a strong buy signal, it is an even better sell signal across asset classes.

4�In particular, major drops in the FPSI have consistently been a leading indicator for equity market sell-offs over the last decade.

3. Forecasting Tool: 4�Using the established time-series pattern, the FPSI can be reliably forecast weeks or even months in advance; adding

key macroeconomic data inputs can further refine this forecast.

4�With a reliable FPSI forecast and established correlations between the FPSI and various assets, the FPSI can be used to forecast asset prices.

4�Breaking the FPSI into more refined data based on type of communication or speaker allows correlations to be identi-fied about which central bankers move specific segments of the market most. These correlations can be used to position investments ahead of a particular speaker’s scheduled media appearances.

NOTE: Each central bank for which we provide data has comparable applications and often greater arbitrage opportunities due to market uncertainty about less publicized central banks.


Fixed IncomeD

etai

led Sample Graph: The FPSI and Treasury Bonds

• The correlation between the FPSI and the benchmark 10-Year Treasury Bond is much tighter than the correlation between the 10-Year and the Fed Funds Rate


Fixed IncomePe

rcep

tive The FPSI and Treasury Bonds Explained:

• Although the Fed Funds Rate (FFR) is a demonstration of Fed action (as opposed to mere words) at Prattle Analytics we con-tend that in modern central banking words are action and the global move toward “forward guidance” not only proves this, but makes the FPSI that much more relevant.

• The preceding graph demonstrates that since 2011 the FPSI (blue) and FFR have decoupled, with the FPSI more accurately reflecting economic sentiment and financial markets in the U.S. than the FFR, which has been pinned to zero.

• The FPSI also correlates much more tightly with the benchmark 10-year Treasury Bond than the FFR does.

• This is noteworthy because the 10-year Treasury Bond correlation persists back to the 1990s and even highlights one of the key causes of the early/mid 2000s housing bubble; the FPSI did not drop as far as the FFR in the mid-2000s thus indicating Fed sentiment about the economy was higher than their own Fed Funds Rate reflected.

• This correlation between the FPSI and the 10-Year Treasury Bond proves noteworthy again in 2013 when the FFR remained pegged to zero, but both the FPSI and Bond rates began to rise.

• In nearly all of these instances, the rises and falls in the FPSI pre-date movements in the bond market, thereby serving as a leading indicator.

• The FPSI is a leading indicator because Fed policymakers are privy to a wide variety of macroeconomic information, there-fore this singular FPSI signal serves as an indicator for wide variety of macro-market drivers in addition to Fed policy itself.


Equity MarketsAn

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ical Sample Graph: The FPSI and Equities

• The correlation between the FPSI and the equity markets has been extremely tight since the onset of the financial crisis. Moreover large FPSI declines pre-date major market sell-offs, thus serving as a strong sell signal.


Equity MarketsD

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• Traditionally, equity analysts left Fed watching to the fixed income folks, but in the last couple years we have seen the Fed persistently impacting equity markets.

• With various rounds of asset purchases essentially injecting capital directly into the stock market, equity analysts must pay attention to the Fed more than ever.

• The preceding graph and the treemap to the right demonstrate extremely tight correlations (in excess of 0.7 on a -1 to +1 scale) between the FPSI and various equity market indexes.

• These correlations are useful for forecasting purposes AND the raw trend data demonstrates that the FPSI proved to be a leading indicator for stocks in the financial crisis.

Tree Map Generated by Mavenomics backtesting platform

The FPSI and Equity Indexes Explained:


Equity MarketsPr

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• Like the equity market index correlations, the FPSI can be correlated to equities broken down by industrial sector.

• The treemap on the right demonstrates the strong correlations between the FPSI and various industrial sectors.

• This treemap can also be broken down further to demonstrate the correlations between the FPSI and individual equities.

• These correlations can be used aid in buy/sell decisions in real time.

• Given the ability to forecast the FPSI, these correlations can also be used to predict future stock movements based on established FPSI correlations.

Tree Map Generated by Mavenomics backtesting platform

The FPSI and Individual Equities Explained:


Equity MarketsSc

ient

ific Sample Equity Portfolio

• Given the correlations on the preceding treemaps, Prattle Analytics ran simulations trading a 100% equity portfolio with standard sector weightings and no leverage using only the FPSI as a buy/sell signal from 2007 to 2014 (through the finan-cial crisis).

• This portfolio yielded 70% returns, beating major market indexes by over 30%.

• It is particularly noteworthy how this portfolio minimized downside risk in late 2008 and early 2009, at the height of the financial crisis. This highlights the value of the FPSI as a wealth preservation tool.


Predictive AnalyticsAc

cura

te Forecasting With FPSI Data:

• In addition to using the FPSI as a real time trading tool, FPSI trend forecasting can be conducted at time intervals ranging from minutes to months.

• Due to established correlations between the FPSI and various assets, these forecasts can be reliably used to aid in predict-ing the price of various securities.

• Prattle Analytics own forecasting based on the FPSI data has proven remarkably accurate with us being able to consistently predict the sentiment of upcoming FOMC meetings and thus identify likely market response.

• In December of 2013 we correctly predicted (blue trend line) the sentiment of the FOMC meeting that initiated Fed “taper-ing” of asset purchases.


Predictive AnalyticsD

etai

led Leading Indicator:

• Even without sophisticated forecasting based on correlations to particular assets, using the FPSI as a blanket 4-week lead-ing indicator can generate significant Alpha.

• In Prattle Analytics tests with a sample portfolio holding 80% equities, 20% fixed income, and standard sector weightings with no leverage and the FPSI as a 4-week leading indicator for the only buy/sell signal from 2007 to 2014 our sample portfolio yields a 50% return, beating major market indexes by almost 30%.

• Moreover, this portfolio demonstrates the value of the FPSI limiting downside risk because it only declined 12% during the throes of the financial crisis, while benchmarks went down by over 50%.


Predictive AnalyticsAn

alyt

ical Forecasting Example: The FPSI

and “Tapering”

FPSI 6-Month Moving Average (April-September 2013)

FPSI Data Helped Forecast

4Drop in interest rates

4Increase in equity markets

4�Drop in the value of the U.S. Dollar

• The sample portfolios provide an ideal platform to demonstrate long run returns based on the FPSI as a trading signal, but the FPSI also presents interesting tradable events on a regular basis.

• In September of 2013 one of these tradable events occurred when the market expected the Federal Reserve to begin “tapering” asset purchases.

• The FPSI indicated sentiment was rising at that time, but within the context of historical data it was obvious that the Fed would not begin tapering yet.

• Specifically, the six-month FPSI trend demonstrates that although sentiment was rising in September, it remained below highs from April and May when the tapering was still seen as unlikely. Tradable sentiment data like this is transmitted daily with our Fed Playbook central bank sentiment data.


Backtesting ResultsU

nbia

sed Independent Backtesting Results

The following results are from a fund that independently tested the Fed Playbook data in January of 2015. This fund primarily utilized a standard return to volatility futures trading strategy based on a common risk parity model to test the FPSI data from January 2000 to December 2014. All transactions costs are built into the testing. Their findings indicated the following:

• The FPSI is a superior trade signal to both of the most common trading strategies, “Trend Following” and “Buy and Hold.”

EQUITIES• Using a simple portfolio of the S&P 500, both Trend Following and Buy and Hold generate returns of roughly 27% over the

testing period. • The FPSI generates risk adjusted returns of 58%, more than double the most commonly used trading strategies. • FPSI returns were generated with almost perfect long/short balance.• The FPSI only has a 0.3 correlation to Trend Following and just a 0.1 correlation to Buy and Hold, so the FPSI can be used in

concert with these established strategies to generate even higher returns. • The FPSI also proved to be a superb indicator of downside risk, even beating Trend Following. • Optimal holding periods for an equity portfolio traded on FPSI data is 2-3 months.

FOREX• Examining only the U.S. Dollar and Euro based on just U.S. data indicates that the FPSI outperforms existing currency trad-

ing models. • Trend Following tends to dominate the currency trading space because over the sample period it generated a 55% return. • Over the same period the FPSI generates over 70% returns. • The FPSI only has a 0.17 correlation to Trend Following, so these two strategies could be used in concert to generate even

higher returns. • Optimal holding periods for a currency trade based on the FPSI data is 10-15 days.• These returns are only taking into account Prattle Analytics’ data on the U.S. Federal Reserve, since Prattle also has data on

the European Central Bank (along with more than a dozen other central banks), this information could be used to better understand the other side of the currency pair trade and generate even greater returns.


Other Applications Re

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cefu

l Other Uses of Fed Playbook Data:

• In addition to using the data as a leading indicator and/or forecasting tool, our central bank sentiment data can be used for a variety of other analytical purposes:

1. The data can be broken down by speaker to identify trends in market reaction when individual policymakers speak. Since the data relies on various types of Fed communications (minutes releases, press releases, speeches and testimony), speak-er identification is relatively simple. If a particular policymaker often elicits a specific market response, investments could be positioned ahead of scheduled speaking engagements by that policymaker.

2. The individual speaker (or type of communication) strategy can also be used to adjust a portfolio regarding particular industrial sectors, currencies or even individual securities.

3. Our international central bank data not only allows these strategies to be applied across international markets, but can also be used as a method for investors to identify greater arbitrage opportunities resulting from market confusion about less publicized central banks.

4. Although implicit in several of the graphs presented, it is worth specific note that this data serves as strong sell signal allowing investors to preserve wealth in down markets.


Data DeliveryIn

nova

tive Other Uses of Fed Playbook Data:

Purchase and Delivery Details:

• The Prattle Analytics database can transfer data to customers in the following ways:

1. Direct API to an individual license.

2. Direct API to an entire corporate entity.

3. Direct FTP to an individual license.

4. Direct FTP to an entire corporate entity

• All systems are setup so that data can be pushed to customers at a set time interval ranging from once per minute to once per week.

• If preferred, an automated email indicating data has been updated can be generated and the data can be pulled from our database on demand.

• All data transfer is secure and access to the Prattle Analytics database is highly restricted.

• Since we are an independent data provider, customers may also request specific, on-demand data development and analytics services.


Leadership Team

Evan A. Schnidman Ph.D. – Founder and Chief Executive OfficerEvan holds a Ph.D. from Harvard University as well as Bachelors and Masters Degrees from Washington University in St. Louis.

Evan has been featured in Bloomberg News and on The Deal. Evan’s financial research has been featured in The Wall Street Journal, Bloomberg View and Seeking Alpha while his academic research has been published in journals and edited volumes. Notably, Evan’s first article in Bloomberg, “Strong Dollar Advocates Make a Weak Case” (Jan. 25, 2012), show-cased a mathematical model he designed to successfully predict every intermediate S&P 500 market bottom and top since 2008. Evan’s financial research will be further showcased in his forthcoming book titled “How the Fed Moves Markets.”

In his consulting capacity, Evan has vetted the political, economic and financial risks of major infrastructure investments for large corporations. Evan has also vetted finances, man-agement structures and community engagement of small and midsize financial institutions to maximize relationships, tax status and grant opportunities from the government. From 2010-2014 Evan taught courses in economics, public policy and political science at Harvard University and Brown University.

William D. MacMillan Ph.D. – Co-Founder and Chief Technology OfficerWilliam holds a Ph.D. from the University of Michigan as well as a Masters from the Univer-sity of Iowa and Bachelors from University of Wisconsin-Eau Claire.

William has conducted extensive research on government finance that he has presented at Yale, Princeton, and the Stanford Graduate School of Business. His statistical and econo-metric work has been published in diverse disciplines including political economy, public health, and medicine. His work has also been featured in the Columbia Journalism Review.

As a researcher and programmer, William has authored original software to estimate spatio-temporal models of trade flows, dynamic discrete choice models of government policy, and hidden-state Markov switching models of exchange rates and policy regimes. He has taught computing, statistics, econometrics and political economy at the University of Michigan and Washington University. He has also worked as a professional data scientist and fraud analyst for several large corporations.


Legal Disclaimer

DISCLAIMER OF WARRANTIES AND LIABILITY:

THE MATERIALS IN THIS PRESENTATION ARE FOR INFORMATIONAL PURPOSES ONLY. THESE MATERIALS ARE PROVIDED “AS IS” WITH ALL FAULTS, WITHOUT ANY EXPRESS OR IMPLIED WARRANTY OF ANY KIND INCLUDING, WITHOUT LIMITATION, WARRANTIES OF MERCHANTABILITY, OWNERSHIP, NONINFRINGEMENT OF INTELLECTUAL PROPERTY, ABSENCE OF VIRUSES OR DAMAGING OR DISABLING CODE, OR OTHER HARMFUL COMPONENTS OR FITNESS FOR ANY PARTICULAR PURPOSE, IN-CLUDING ANY WARRANTY FOR THE USE OR THE RESULTS OF THE USE OF SERVICES OR PRODUCTS WITH RESPECT TO THEIR CORRECTNESS, QUALITY, ACCURACY, COMPLETENESS, RELIABILITY, PERFORMANCE, TIMELINESS OR CONTINUED AVAILABILITY.

NEITHER PRATTLE ANALYTICS LLC (PRATTLE) NOR ITS THIRD PARTY PROVIDERS SHALL BE RESPONSIBLE FOR INVESTMENT DECISIONS, DAMAGES, OR OTHER LOSSES RESULTING FROM USE OF THIS INFORMATION.

PAST PERFORMANCE OF A MUTUAL FUND, STOCK, OR OTHER INVESTMENT VEHICLE DOES NOT GUARANTEE FUTURE PER-FORMANCE. NEITHER PRATTLE NOR ITS THIRD PARTY PROVIDERS SHALL BE CONSIDERED AN “EXPERT” UNDER THE SECURI-TIES ACT OF 1933. NEITHER PRATTLE NOR ITS THIRD PARTY PROVIDERS WARRANT THAT THESE PRESENTATION MATERIALS COMPLY WITH THE REQUIREMENTS OF THE NATIONAL ASSOCIATION OF SECURITIES DEALERS (NASD), THE FINANCIAL IN-DUSTRY REGULATORY AUTHORITY (FINRA) OR ANY SIMILAR ORGANIZATION OR WITH THE SECURITIES LAWS OF ANY JURIS-DICTION.

LIMITATION OF LIABILITY: NEITHER PRATTLE NOR ITS THIRD PARTY PROVIDERS NOR ANY PERSON THROUGH WHOM PRAT-TLE MAKES THIS INFORMATION AVAILABLE SHALL BE LIABLE FOR ANY DAMAGES OF ANY KIND ARISING FROM OR RELATING TO THESE TERMS, THE INFORMATION PROVIDED, OR THE USE OF, OR RELIANCE ON, PRATTLE ANALYTICS DATA PRODUCTS, WHETHER IN CONTRACT OR TORT OR OTHERWISE.


Contact us for free data testing of our product:

Prattle Analytics

Evan A. Schnidman [email protected]

William D. MacMillan [email protected]

www.prattle-analytics.com

The Fed Playbook is the only commercially available—tradable source—for comprehensive, unbiased and quantitative data on central bank communications

Documents

Revolutionizing the Way Financial Professionals Analyze ... · Innovative 2 Executive Summary Who is Prattle Analytics? • Prattle Analytics was founded by Evan A. Schnidman Ph.D