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CTA Confidential: Wellfleet Asset Management, LLC

Originally published by Managed Account Research, Inc. on October 2, 2007.

CTA ConfidentialSM
"An ongoing series of qualitative investigations
into managed futures trading programs"

CASE NO. 0369603
Wellfleet Asset Management, LLC
Daniel A. Seitz, Principal
Global Macro Program


Wellfleet Asset Management LLC, founded in May 2006 by Daniel A. Seitz, is a commodity trading advisor (CTA) specializing in the financial futures markets. Mr. Seitz, who has a BSBA from Boston University and a MBA from New York University's Stern School of Business, began his career in 1992 with Discount Corporation of New York Advisers. In 1995, Mr. Seitz became the youngest employee in the division's thirty year history to be promoted to the firm's Investment Policy Committee. The Committee managed global fixed income portfolios totaling more than $2 billion for institutional clients such as the John Paul Getty Trust. Mr. Seitz's contributions resulted in his assuming responsibility for the firm's proprietary trading accounts in 1996, and his analysis of the credit markets anticipated 1998's Pacific Rim currency crisis.

In 1999, Mr. Seitz joined Instinet Corporation which led to his becoming Sr. Quantitative Analyst for their Equity Research Group. In this capacity he researched stock index trading strategies and constructed sector rotation models using a method called logistics regression. Mr. Seitz was subsequently hired by State Street Global Markets as their Senior North American Equity Strategist. In this role, he authored tactical and strategic research on the U.S. and Canadian equity markets, making industry and sector recommendations based on quantitative and qualitative frameworks. Given this impressive background, Managed Account Research was keen to speak with Mr. Seitz about his institutionally-informed approach to trading, especially in light of current volatility that has led many market participants to make comparisons with 1998.

At Opal Financial Group's 2007 Family Office/Private Wealth Management Conference in Rhode Island, a question was posed to the assembled panel of specialists about what type of characteristics they looked for when they hired emerging managers. What these representatives of funds-of-hedge funds and billion dollar family offices said, without exception, was that they preferred to invest with experienced traders who had institutional "prop desk" backgrounds.

Daniel A. Seitz, who has expertise in equities, fixed income and currencies, hails from exactly the kind of environment which these sophisticated investors seek talent. Our conversation with Seitz did not disappoint, revealing a trader with vast knowledge about the markets, and someone who has given considerable thought as to the nature of trends, and to developing a philosophy why trends are both explainable and exploitable.

Wellfleet's Global Macro Program seeks to exploit price movements in financial futures, specifically stock indices, currency pairs and interest rates, through short- and intermediate-term directional trades. Trading decisions are based on a three-pillar approach involving the analysis of asset price, fundamentals, and some-thing Seitz calls the "market paradigm," a market belief system that reflects "virtuous" and "vicious" cycles.1

What fuses his analytical process, and what is truly a unique aspect of the trading program, is Seitz's incorporation of the Theory of Reflexivity, a profound and powerful sociological model first popularly advocated by the hedge fund legend George Soros, but with theoretical roots in academic research by Merton (1948, 1949), Popper (1957), Nagel (1961), Grunberg and Modigliani (1954) and Simon (1954).2

"Reflexivity basically states that investing is more like alchemy than science. In science those running the experiment should not influence its outcome, whereas in markets they do," explains Seitz. "It is extremely important to my investment process and it is one of the reasons why I had to go on my own," adding that, "not a lot of people really subscribe to it as much, and I wanted to stay true to the philosophy."

The problem is that reflexivity complicates the general notion of how objective analysis works in classical science: the collection of data through observation and experimentation, and the formulation and testing of hypotheses. As the scientific method relates to the study of the economy and the markets, Nobel Laureate Herbert Simon (1987) portrayed it as follows: "the rational person of neoclassical economics always reaches the decision that is objectively, or substantively, the best [choice] in terms of the given utility function."

Said another way, the conventional view of asset valuation, as typically professed by the run-of-the-mill market analysts regularly interviewed on CNBC, is that fundamentals alone determine pricing, and that the process of price discovery goes only one way, meaning that prices do not influence fundamentals. In this model, the market participants' biases are omitted from the equation. An enhanced view incorporates market perception by adding to the model a 'market paradigm,' which is a set of assumptions that constitutes a way of viewing reality, thereby providing market participants' rationale for their investment decisions. Yet, in this enhanced model too, prices still remain the dependent variable.

Both of the above asset pricing models are based on equilibrium theory, which stipulates that markets move towards equilibrium and that non-equilibrium fluctuations are merely random noise that will soon be corrected. In equilibrium theory, which is the theory that underlies classical economics, the long-term mean expected return of an asset reflects the underlying fundamentals, which are unaffected by prices.

Reflexivity, however, is discordant with equilibrium theory, and asserts that prices actually do influence fundamentals. Hence, the resulting new fundamental circumstances based on prior changes in price evolve market return expectations, re-influencing asset prices again. The process is, in essence, a self-reinforcing pattern, and as a result, the underlying assumption is that markets actually tend towards disequilibrium.

Disequilibrium is a key concept because it provides a logical impetus and behavioral explanation for trends. In Seitz's model, price movements reflect a feedback loop between asset prices, macro fundamentals, and the predominant market paradigm -- prices are both independent and dependent variables. Further, in this model it makes sense that prices are in constant motion, and that the important information to be gleamed from the market is not based on average returns, but in the 'tails'3 of the distribution curve.

"I think most people are operating under a framework that fundamentals are the independent variable, and prices are the dependent variable," explains Seitz. "What Soros basically said was, 'that is not really true, things operate on a feedback loop: fundamentals influence perception, perception influences prices, and vice versa.' Investing is a dirty process,4 and the market is, in fact, operating on various hypotheses; it is a breeding-ground for testing hypotheses which will either be proven correct or incorrect."

For example, in early 2003 there was scant fundamental evidence to suggest that the U.S. equity market would turn around after the bear market of 2001-2002. Yet, a major bottom was struck with buyers at that point anticipating the economy would turn around -- it turned out that these buyers were right and they were rewarded. In effect, the buyers tested a hypothesis which proved correct. However, investors not only tested the hypothesis of economic recovery but also played a role in the outcome of the experiment itself. Rising equity prices generated a wealth effect, contributing to the economic recovery that, in turn, validated the bull move in prices. Thus, markets can cause their own predictions to come true.

According to Seitz, what matters most is the market paradigm that market participants acknowledge and predominantly embrace; less important is the current snapshot of fundamentals, which can be influenced by perception and changed due to reflexivity. Therefore, "fundamentals are not a one-way method for determining asset prices -- prices reflect fundamentals, but they also reflect predictions," says Seitz.

So how does this translate into Wellfleet's trading? Signals are generated from a combination of market paradigm research which can be expressed either qualitatively or quantitatively, fundamental research using logistics regression to provide a framework for assessing the macro economy, and price research utilizing statistical tests to differentiate between trending and random price behavior.

An example of a qualitative paradigm is the "reflation5 trade" that kicked off in 2003. At the time, the Federal Open Market Committee (FOMC) made an unprecedented statement articulating the risk of "an unwelcome drop in inflation." Along with easy money and rising commodity prices, a weak dollar became the foundation for a market construct in which investors believed that the central banks, while promoting growth, were willing to stoke inflation. There are, however, a number of relationships that Seitz considers to be paradigms that are expressed quantitatively, such as with foreign currencies.

In the foreign exchange market Seitz runs a model ranking carry-trades in a schematic that indicates if carry is a driver of performance, and whether currencies are within the boom-bust cycle of performance. For instance, the Japanese Yen, which is currently the lowest yielding of six pairs that Wellfleet trades, ranks sixth where the Australian Dollar ranks first and is the highest yielding. From there, a cross-sectional correlation over time is compared to the other pairs. If correlation is high it suggests "the trade is about to go bust," while if very low, that indicates the "possibility of a re-emergence in a carry trade."

The concept of market paradigm, as described above, is easily confused with macro fundamentals. Seitz is, in fact, splitting these concepts into separate components. This hybrid model allows him to separately analyze how fundamentals, such as supply-demand, government reports, event risk, etc., influence market behavior, and whether the fundamentals either supports or detracts from the market paradigm. In other words, the trends Wellfleet actually trades are the market paradigm trends, not the fundamental trends.

That said, the analysis of macro fundamentals has a "quant" underpinning using a statistical method called "logistics regression,"6 which is used extensively in the medical and social sciences. Technically, it is a model for binomially distributed response/dependent variables, which Wellfleet populates using actual economic data or "macro variables which show a stable and long term relationship with that given asset."

The key with the logistics regression approach is that it is non-linear and assumes that relevant information is in the tails of a bell curve distribution. For example, when one analyzes two economic data sets or variables, results may show a low correlation. However, if the data sets or variables are organized within a standard normal distribution, and the first and fifth quintiles are analyzed only, one may find that correlation is very strong. Accordingly, the relevant information is in the tails of that relationship.

The method is also different in that logistics regression is a maximum-likelihood algorithm that yields a probability output between 0% and 100% that something will occur. So if the model is between 40% and 60%, that is neutral and Seitz doesn't pay attention to it; but if output is above 60%, it tells him that there is a high likelihood of occurrence, which is an actionable development. That is where logistics regression is different from other types of analysis, it allows for times when there is not a lot of information in the variables, and the middle portion, which is considered to be a neutral band for the variables, is ignored.

"Logistics regression analysis is something that appealed to me, and it is very consistent with my approach to the markets," says Seitz. "The way most people measure correlation that I've seen, is a pretty narrow definition; and if you were to instead look at something not in a simple linear correlation, but within a dichotomous or trichotomous framework, you would find that there is a lot more information."

For price research, Wellfleet employs price screen algorithms based on proprietary technical analysis similar to off-the-shelf indicators, but where "the idea of randomness versus non-randomness is introduced into the extremes." These price screens, which Seitz also describes as a rules-based pattern recognition method, dynamically classifies trending and non-trending markets in real time, and also produces a map of how a trend is likely to develop. According to Seitz, trending markets show different structure and momentum signatures compared to markets that are in corrective phases.

Positions are initiated when trends are identified and confirmed. In response to new price or fundamental information, the stop level is tightened to lock in gains or limit losses. When prices deviate from the expected trend map, positions are closed regardless of whether they are profitable or not. Additionally, Seitz employs a stop-loss limit, which manages individual position risk to a maximum of 1.5% of the portfolio when he first initiates a position. This "initial" stop-loss adheres to a minimum reward-to-risk ratio of 2:1, that is, the expected gain is twice as large as the potential loss.

Because of his belief that prices influence both perceptions and price fundamentals, Seitz states that he "elevate[s] price activity to a very important place in my investment process; positions are held as long as prices conform to the trend map," adding that, "when prices deviate from that rigid framework, a position is brought back to neutral, regardless of whether it is profitable or not." Thus, the price screening process contains embedded risk controls, and stop-losses need not be triggered for risk levels to be reduced.

Risk is also "budgeted" in accordance with a matrix that reflects twenty-seven possible combinations of asset classes that Wellfleet trades: currencies, fixed income and equities. Next, a size limit per asset class exposure is imposed in order to control redundant risks that may arise from volatility. Seitz recognizes that the financial markets he trades tend to exhibit high correlations. Therefore, the focus is to constrain volatility by limiting net asset exposures or risk factors, rather than by increasing portfolio diversification.

As Seitz explains, "I want to avoid redundant risk. If I am long the dollar and short the equity market, and I am also looking at trading the Euro, then there is an element to those risks that are redundant."

Wellfleet has also incorporated a variation of the Value-at-Risk (VaR) model, developed by Kritzman and Rich (2002), in order to constrain position sizes. VaR is a measure of how the market value of an asset or a portfolio of assets is likely to decrease over a certain time period (usually over one day or ten days) under typical conditions. It is used by many investment banks as a standardized way to measure market risk.

However, few participants in the managed futures industry reference the model. The reason why is due to a subtle but significant difference in perspective between traditional investing and futures trading, with respect to return/risk performance measurement. How this relates to Wellfleet is explained below.

For traditional investments, VaR is a relatively straightforward concept as securities are not leveraged and "market value at risk" is based on the market value of an investment (e.g., the number of shares times price).

However, crossing VaR into futures market dialect implies that "market value at risk" refers to the nominal contract size of a futures contract (e.g., the nominal contract size of the S&P 500 futures contract is $250 times the S&P 500 stock index; this is multiplied times number of open contracts to arrive at market value).

The reason this simple concept gets confused in the managed futures industry is because futures contracts are leveraged instruments. Instead, industry convention references account size as the "at-risk" capital. This usage is related to "margin-to-equity," in which initial margin (e.g., approximately $20,000 per S&P 500 futures contract) is divided into the capital size of the trading account including notional funds.

Knowing this helps one understand what Seitz means when he says that Wellfleet "constrains position sizes so that returns can be generated with the lowest possible odds of breaching our specified loss threshold." Position sizing is calculated using VaR,7 which is based on the nominal contract size of futures contract not the capital size of the trading account. Therefore, consistent with a loss parameter of 5% in any given month, Wellfleet's maximum allowable net exposure is "never more than 6 times" the nominal contract size of the total portfolio. This is very important to know because it elucidates Wellfleet's returns!

Performance in managed futures performance is based on how much a CTA gears leverage. Understanding how leverage is used in a trading program, including margin-to-equity, is important for helping an investor standardize risk exposure relative to expected returns from a program. In other words, context is key.

Wellfleet's composite return for the seven months ending 2006 is 8.74%, and YTD through September 2007 is 3.08%. However, Wellfleet's average margin-to-equity is mostly under 10% because the Global Macro Program is modeled from an institutional perspective, and therefore it is a 'de-leveraged program,' as opposed to many managed futures programs levered for the purposed of attracting naïve clients.

In other words, the 10% margin-to-equity Wellfleet uses to generate its returns should be compared apples to apples with the amount of leverage other CTAs use to generate their returns. For example, in comparison to a CTA utilizing 30% margin-to-equity, Wellfleet's 13.87% performance for the twelve months ending August 2007 converts into a 41.61% return, with the largest peak-to-trough drawdown translated into 16.11%. This comparison can be made by referencing the notional funds matrix in Wellfleet's disclosure document.

Furthermore, in light of this year's market volatility during February-March and July-August, Wellfleet's trading should be viewed within the context of a "vicious" cycle, not a "virtuous" trending cycle. The financial market turbulence of 2007 has led to losses across many alternative investment products and even closures in various hedge funds. The key consideration in these periods is risk management.

Seitz believes that the recent market turmoil reflects a tug of war between two paradigms. On the one hand, there is the "relative growth trade" whose key components feature rising stock and commodity prices, a controlled devaluation of the U.S. dollar, and a general expansion in risk appetite. On the other hand, there is the "debt/deflation panic," wrought by weakness in the housing market, and whose key components are widening credit spreads, falling stock markets, declining inflation expectations, and a general contraction in risk appetite. The battle of the two paradigms, which Seitz believes has been in effect since late 2006, has translated to a below-average environment for risk taking.

That said, Seitz believes that a victor will soon emerge. In light of the recent Federal Reserve Board action to cut the Federal Funds Rate and the Discount by 50 basis points, his prognosis seems to be coming true, although some would argue that the risk for a "stagflation cycle" has now increased. Putting aside market opinions, it is likely a new market paradigm will soon evolve and develop into trending market conditions. As a result, Seitz is prepared to elevate portfolio risk levels in anticipation of significant price moves.

The underlying complexity and institutionally oriented approached developed by Seitz, stresses the point that Managed Account Research repeatedly makes -- quantitative analysis of performance doesn't suffice as a sole basis for making managed futures investment decisions, qualitative analysis is essential. Even watching Wellfleet's day-to-day trading, which is deceptively simple in that it is either outright long or short financial futures contracts, belies the intellectual thought process behind the risk management constraints that impose a disciplined methodology, much less Seitz's discretionary trade decision process.

Sophisticated investors understand that the main responsibility with investing lies with managing risk, not performance. Given the overall methodology in which the Global Macro Program operates, Managed Account Research anticipates that Wellfleet is likely to attract the attention of institutional investors.

Likewise, individual investors, who understand that there is substantial risk of loss in futures trading and are interested in diversifying their traditional portfolio into alternative investment strategies, should take time to seriously investigate how Wellfleet's Global Macro Program may help diversify their portfolio.


[1] An example of a present-day market paradigm, which is currently entering into a "vicious cycle," is the credit crunch that resulted from the sub-prime housing market "bubble" (i.e., mortgage origination, asset securitization and derivative extrapolation process) that until early 2007 was operating in a "virtuous cycle."

[2] The philosophical basis for the Theory of Reflexivity dates back to Emanuel Kant's "The Critique of Pure Reason" (1781), which states that in the pursuit of knowledge "man is both knowing subject and the object of his own study."

[3] The distribution curve is a statistical tool, applicable in many fields, that is used for analyzing probabilities. The term "tails" is often used to describe the extreme end of standard deviations from the average of the distribution.

[4] When running experiments in a scientific laboratory, great effort is placed on ensuring that both the control and the experiment is sterile and "clean" so as to not reflect any contamination or bias of the person running the experiment.

[5] Reflation refers to an economic policy whereby a government uses fiscal or monetary stimulus in order to stimulate the economy through various actions such as reducing taxes or increasing the money supply by adjusting the fed funds rate.

[6] Logistics regression is sometimes referred to as a logistic model, logit model, or maximum-entropy classifier.

[7] For Wellfleet's Global Macro Program, the VaR for currencies is 2.5x of the aggregate nominal contract size of total currency exposure at any given time; VaR for fixed income is 4x of the aggregate nominal contract size of total fixed income exposure at any given time; and for equities VaR is 1.5x of the aggregate nominal contract size of total equity exposure at any given time.


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