A framework for HF operational due diligence

Here is another in a series by guest blogger Cox Owen on hedge fund operational due diligence (see part 1 and part 2 here). Please direct any comments to him directly at coxowen1 at yahoo.com.

A framework for OPDD
We have been jumping around a bit to try to show a broad picture of OPDD. I will try to use this post as a framework for start-up funds so that these first- timers will get a glimpse at the hoops the institutional investors will expect them to jump through from an OPDD perspective. Also, please understand that this is only a small portion of what institutional investors are looking for. As a start up you should be prepared to provide biographies of key staff, references, a list or service providers, a list a fund expenses and much more. Remember you are asking these institutions to trust you with their money. (not all start-ups are first-timers)

We must first discuss the hedge fund landscape. 10 years ago you could launch a single strategy fund (for the sake of this conversation we will assume that the strategy will be successful ) without having to jump through all of the hoops that HF’s must jump through today. This occurrence can be attributed to two primary factors. 1st – because OPDD has evolved tremendously since 1999. Every time there is a financial catastrophe, scandal, scheme, implosion, etc., our natural response is to say “How do we make sure that this does not happen to us again?”, and then we reactively add this new mechanism to our OPDD format. Second, because there were far fewer funds in 1999 than in 2009, the institutional investors did not have the luxury of saying. “Why should we put money with you when we can put our money with manager ABC who has a similar strategy and an enormous operational infrastructure.” Let me see if I can be a little more clear, in 1999 it was not an industry standard to have a robust operational infrastructure, in 2009 it is a standard ( a very expensive one). This does not mean the institutional investors will not invest in start-ups if the fund does not have all of the OPDD infrastructure listed below. Once again, this is only a small portion of OPDD that a fund should expect from an institutional investor.

Frameworks

1. Valuation
2. Trading
3. Operations and Accounting
4. Ethics
5. Compliance
6. Disclosure
7. The risk profile
8. Disaster Recovery & Business Continuity

I could write over 100 pages discussing the frameworks for these sections. Rather than bore you, I will try to condense a few topics that can be applied to each. Much of what I discuss can be found in the report Best Practices for the Hedge Fund Industry by the asset managers’ committee to the President’s Working Group on Financial Markets.

A) Is there a person or committee responsible for oversight of the framework? (In some instances a person would be better than a committee and vice versa . A good example of this would be to compare risk to valuation. Generally speaking, you would definitely want a valuation committee because valuation decisions are not difficult and it is easy to build consensus. Whereas in a risk profile you would much rather have a single person because the decisions are more complex , risk methodologies can be argued from many different perspectives, it would most likely be difficult to build consensus, and it would also be very expensive to have a team risk professionals debating methodologies for the profile. However this is not always the case.

B) Is there a documented procedure that describes how the framework is applied to the fund? (A good example of the would-be ethics. How does the firm ensure that all of its employees are following a code of ethics)

C) Who is responsible for monitoring the framework? (The best example here is probably compliance or DR/BC. Who is monitoring all of the evolving compliance matters are being met by the fund? Business interruptions from black-outs, terrorist attacks, hurricanes, floods, snow storms, earthquakes and many other reasons do occur. Who is monitoring and all of the operational and investment enhancements for DR/BC?)

D) Who is responsible for executing the framework? (Now I know this sounds a lot like monitoring but there is a big difference. Let’s use risk as an example. You can certainly have a lower level employee monitoring, let’s say position limits, and he notices that 8 separate traders each decided to take a long position in crude. Each decides to put on 1500 contracts in the front month, a total of 12000. Two big problems have occurred here. First, the position limits for exchange (NYMEX) is 10000 contracts in any one month. So this would certainly lead to some type of warning and possibly a fine by the exchange. Second is that the internal position limits of the fund have more than likely been breached (assuming the fund has internal position limits). Funds with sound risk profiles don’t want to find that they are holding 25% of the open interest in a commodity, so they instill an internal position limit. If a fund does hold such a large percentage of the open interest and the trade begins to move against them they will more than likely find themselves moving the market into limit up or limit down scenarios. So a senior officer of the fund should be responsible for executing (telling traders they have limits) the framework.

Where does the buck stop?
We could certainly dive further into OPDD framework, however let’s migrate a little bit and discuss accountability. As investors, we are always trying to protect our investments as best we can. We conduct thorough due diligence, we develop relationships with managers, we make every effort to ensure our investments. All of this, to find out that a rogue trader circumvented the risk teams at SocGen, or Amaranth or whereever. Let’s says for a minute that I actually believe the manager's story, if that’s the case, the manager seems to be negligent. After all, they verified in our DDQs that they have preventative measures in place to prevent these types of situation. The point here is that we need claw back provisions that allow investors to recover losses from poorly managed funds. Just my $.02 .

I certainly appreciate all of your e-mails and posts. I apologize if I have not been able to reply to all of you as the response has been much greater than I have expected. However, please continue to send e-mails and posts and I will do my best to reply.

I hope the read was beneficial. Thanks again for all of your kind e-mails and posts.

Feedback on a book project

I would like to ask for your help in giving me some feedback.

Over the years, I have watched as a number of experienced friends and colleagues move from the sell side to the buy side and struggle with the business realities of the money management business. Their problems were mainly attributable to the fact that there is a lot more to investment management than knowing what to buy and sell.

I have posted on this topic (see part 1, part 2 and part 3). I decided to work on a book outlining some of the issues surrounding the business of investment management, as training in this topic seems to be severely deficient. Just as dentists come out of dental school knowing all about dentistry, but most don’t know anything about running a dental practice, analysts come out of business school knowing little about investment management.

I have outlined a table of contents for the proposed book. I would welcome any comments from investment professionals or MBA students in business programs.

How do you feel about this topic?

Is there anything else that I should address?

Please leave your feedback in the comment section or email me at cam at hbhinvestments.com.


-------------------------------

Table of Contents

Introduction: Just because you can cook doesn’t mean you can run a restaurant
Investment management is a business, treat it that way.


Part I: The Investment Process
Chapter 1: The investment process is the production line of your business
Selection: Deciding on what to buy and sell
Portfolio construction: How much do you buy and sell?
Portfolio Implementation: Trading is a game of inches
Review and Control: Putting it all together

Chapter 2: Product Engineering and the Client Relationship Benchmark
Learning to actively listen
Building a client relationship benchmark is the key to business risk management
The defined benefit pension plan client
The individual client
The Family Office client
The hedge fund trader
Introducing the Factor Analyzer

Chapter 3: Portfolio construction and optimization
The fundamental law of active management
Why use a portfolio optimizer
Portfolio construction the fundamental way
Quantitative risk models have many flavors
Stupid quant tricks, or how to use risk models
Sizing your stock bets
The cautionary tale of manager A: When to use optimization

Chapter 4: Trading is a game of inches
The best execution standard
Legal, regulatory and ethical considerations
Measuring execution costs
Trading intelligently: No one-size-fits-all solution

Chapter 5: Troubleshooting your portfolio
The Deming system
Measure, measure, measure!
Is selection positive? But portfolio performance negative?
Dealing with difficult or unexpected macro environments
Learning from failure
Investment philosophy, business model and business risk


Part II: Marketing and Client Relationship Management
Chapter 6: Marketing to gatekeepers
The due diligence process: The 5Ps
Maintaining discipline to stay on message
The mutual fund gatekeeper
The consultant gatekeeper

Chapter 7: Managing client relationships
Business risk management
Client reporting and communication: telling your story
Being proactive to build relationships
Using clients for product development
The portfolio dispersion conundrum
The investment process change conundrum


Part III: Hedge Fund Operations
Chapter 8: So you want to start a hedge fund?
The hedge fund business model
The business plan
The hedge fund startup organization: personnel functions and requirements
Legal structure and financial structure
Operational issues
The hedge fund due diligence process
Risk control
Managing the process well enough to grow and survive

The curious case of the stubborn leaders

In this bear market it is difficult to find chart patterns that look attractive. For more details on this mystery chart, read on…

Leadership changes during bear markets
Bear markets are periods of catharsis. They serve to cleanse away the excesses of the previous market cycle. That’s why, as a general rule, technicians look for a change in leadership to mark the beginning of a new cycle.

During the early 70s, the Nifty Fifty was the dominant leadership. The late 70s saw inflation hedge vehicles such as the oils and golds lead the market. The 80s was the era of Japan and consumer oriented stocks (remember the LBO boom, which was focused on many of the consumer names?) The bull of the 90s was fueled by Technology, led by Internet stocks. The latest bull was led by the emerging markets and commodity producers, which were views as levered plays on the growth in China and other emerging market economies.


Watching for the leadership change
To watch for changes in leadership, technicians often use relative price charts. As an example, the chart below shows the NASDAQ 100 relative to the S&P 500 during the Tech Bubble and its aftermath. The NASDAQ peaked in March 2000 and fell, on an absolute basis and relative to the S&P 500. On a technical basis, the NASDAQ 100 tested the relative uptrend line in January 2001 and broke below it decisively a month later.

Comparing the above chart to today’s market, the S&P 500 peaked on October 9, 2007 at 1565.15. Over a year later after the market peak, the chart below shows the relative charts of the Energy Select Sector SPDR (XLE), which is a proxy for the commodity stocks, and the iShare MSCI Emerging Market Index to the S&P 500.


Surprise! Surprise! The leadership is still intact. While it is true that the EEM/SPX line is now testing an uptrend line, these charts look very healthy by comparison.

What about the leaders within the leadership? The chart below shows the Internet HOLDRs (HHH) relative to the NASDAQ 100 at the peak and after the peak of the Tech Bubble. Internet stocks, as represented by HHH, peaked in December 1999, a few months before the NASDAQ actual peak, and were in substantial decline afterwards.


Stubborn leadership
By contrast, we come to the mystery chart at the beginning of this post, which represents the chart of XLE relative to EEM. Energy stocks had been in a basing pattern compared to emerging markets for several years. They began an relative uptrend in October 2007 and staged an upside breakout in October 2008.


What about the economy?
Right now, the world is swamped by deflation. China recently reported very disappointing 4Q economic growth.

However, I continue to believe that we should still give inflation a chance given the enormous policy consensus to reflate the banking system and the US consumer. As a result, the USD is at risk of a substantial decline, with the GBP as the canary in the mine. Well, with Pound Sterling is falling that canary is now falling over.


Listen to the tape
Despite the sense of panic out there, the market tape is telling us that the situation is starting to stabilize. Housing stocks have stopped falling and they are now forming a base. The Baltic Dry Index, which had been in freefall, is showing some minor signs of recovery.

If we listen to the tale of the tape, we have the unusual situation where the previous leadership of commodity producers remaining intact. With that in mind, I am still inclined to give the inflation trade the benefit of the doubt for now.


What to do?
My inner investor tells me to nibble away at energy and commodity positions, as this kind of analysis has a tendency to be early by as much as a year or two. My inner trader, on the other hand, tells me to put on the long XLE/short EEM trade on any kind of decent pullback.

Some signs of spring for the homebuilders

Remember housing? That’s where this crisis started. I have been waiting for stabilization from the Homebuilders for some time as a sign that this bear market may be at an end.

Now comes an article by Irwin Kellner that housing valuations are becoming more reasonable. Scott Grannis at Calafia Beach Pundit largely agrees and is cautiously optimistic about the housing sector as well. Though these signs do not mean that housing prices don’t overshoot on the downside, it does portend some hope for the Homebuilders.


Listen to the market
Kellner's views are confirmed by the market action of the homebuilders. The chart below shows the relative returns of the Homebuilder SPDRs compared to the S&P 500. The Homebuilders have broken out of a relative downtrend relative to the market and they are now in a basing period. I would expect the group to stay in this trading range some time before breaking out on the upside.




Watch this space for the upside breakout in the next 6-18 months as that could be another indicator the bull is ready for a sustainable run to the upside.

For everything there is a season

I have always been a proponent of the intelligent use of quantitative models. Examine your assumptions and make sure they hold, I said. Quant models work 99% of the time, but that 1% tail has really nasty consequences. The 1% can blow up your firm. Not only that, it can blow up the country and possibly the global economy.

There are no models for all seasons (assumptions), but there are seasons (assumptions) for models. Broadly speaking, there are three classes of quantitative models in use. I would like to examine each of those and their assumptions, or seasons.


Equilibrium models
The equilibrium model represents the orthodoxy of economics and financial modeling. Virtually all the works of mainstream economists are based on equilibrium models. In finance, the discounted cash flow model (DCF) is a good example of an equilibrium model.

The DCF model has spawned a variety of value-based models. The dividend discount model is one variation. The PB-ROE model is another.

Investors use elements of the DCF model to approximate value. The P/E ratio, or E/P ratio, is really nothing more than shorthand for a single term of the DCF model. Other variations, based on going up the income statement, use EBITDA to EV, Sales to Price or Sales to EV. Value investors have used these measures for years.


Behavioral models
Equilibrium models don’t explain everything that the market does. A case in point is the curiosity of the relationship between U.S. stock and long bond yields. U.S. stock dividend yields traded above long bond yields until the 1950s, when the relationship inverted. Recently, they inverted again, when dividend yields rose above those of the long bond. Mark Hulbert reported a possible explanation for this phenomena [emphasis mine]:

Cliff Asness, however, thinks he has come up with some clear answers. He is managing and founding principal at AQR Capital Management, a Greenwich, CT-based quantitative research firm. In the March/April 2000 issue of Financial Analysts Journal, Asness argued that neither the pre-1958 period nor the decades since are anomalous. On the contrary, he found that -- below the surface -- stock and bond yields have always been strongly positively correlated.

The reason that this strong correlation was hidden, according to Asness, is that investors' expectations have changed of the relative volatility of stocks and bonds. Prior to the last 50 years, investors expected the stock market's volatility to be much greater than bond market volatility. To entice investors to incur that greater volatility, the stock market had to provide a higher yield than bonds.

This is an example of where equilibrium models break down. Equilibrium models assume that we are all rational human beings who make rational decisions based on expected returns and, even if every person isn’t the same, risk aversion functions are relatively well-behaved.

This example of the stock and bond yield question demonstrates that risk preferences can shift in very a dramatic fashion. Quantitative models that depend on the past are only looking at a single snapshot of history and not all the possible variations.

Recently, the field of behavioral finance has received greater attention. The likes of Andy Lo have done work in the field of neuroscience of how the brain reacts to positive and negative stimuli (see example here).

Technicians have been using behavioral finance principles to explain market behavior for years. Technical analysts use trend following techniques to jump on the investor bandwagon and a variety of overbought/oversold models to try to jump off the bandwagon. They use techniques such as advance-decline lines to better measure the underlying trend. Divergences are thought of as significant, as the indicator, such as the A-D line, is a better model of the “true” trend.

Growth investing have a behavioral basis in its own way. Numerous studies show that growth stocks, as defined by high P/E or high P/B, lag the market over the long term. Growth investors use momentum techniques to chase the next Xerox, the next Microsoft, the next Google, etc., based on the high psychological payoff of finding the big ten or twenty-bagger.


Non-linear models and chaos theory
Benoit Mandelbrot was an early advocate of the Big Idea that the universe operates in a non-linear fashion. This was known as Chaos Theory. Nassim Taleb later popularized the same idea with the Black Swan. The blog Crossing Wall Street skeptically comments that:

If you’re not familiar with Taleb, he has one idea and one idea alone. Actually, it’s not even his idea. The man who really impresses me Benoit Mandelbrot. Anyway, the idea is that stock returns don’t follow the normal distribution (the bell curve). That’s it—that’s the Big Think idea.

Here’s the deal: If stocks don’t follow a bell curve, then a lot of the ways we measure risk are flawed. For Taleb, of course, it’s much more than that. His idea (meaning Mandelbrot’s) is really an impossible to comprehend discourse on the human soul.

My own experience with non-linear models is that it is difficult to get them to work, owing to their extreme sensitivity to initial conditions. Some researchers have successfully measured the degree of non-linearity in the market and thus been able to better forecast risk. My own limited observation of non-linear models is that if they do work, their forecasts aren’t all that better than linear models.

Your own mileage will vary.


The Financial Modelers’ Manifesto
Over at Paul Willmott’s blog, he published a Financial Modeler’s Manifesto, which starts with an echo of the Communist Manifesto with:

A spectre is haunting Markets – the spectre of illiquidity, frozen credit, and the failure of financial models.

It concludes with “Modelers' Hippocratic Oath”:

~ I will remember that I didn't make the world, and it doesn't satisfy my equations.
~ Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.
~ I will never sacrifice reality for elegance without explaining why I have done so.
~ Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.
~ I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.

I wholeheartedly agree. Read the whole thing. Examine the assumptions in your models and apply them intelligently.

Where are we on the roadmap?

Recently, there have been increasing calls from economic forecasters for a prolonged recession, or an L-shaped recovery (see here, here and here).


A roadmap to the future?
The latest study from Reinhart & Rogoff, whose paper was presented at the recently concluded American Economic Association shindig in San Francisco, sheds some light on the future based on past events. They studied banking related downturns in the pre-World War II era, as well as a couple of pre-war episodes for which they had data. Their main conclusions are:

First, asset market collapses are deep and prolonged. Real housing price declines average 35 percent stretched out over six years, while equity price collapses average 55 percent over a downturn of about three and a half years.

Second, the aftermath of banking crises is associated with profound declines in output and employment. The unemployment rate rises an average of 7 percentage points over the down phase of the cycle, which lasts on average over four years. Output falls (from peak to trough) an average of over 9 percent, although the duration of the downturn, averaging roughly two years, is considerably shorter than for unemployment.

Third, the real value of government debt tends to explode, rising an average of 86 percent in the major post–World War II episodes. Interestingly, the main cause of debt explosions is not the widely cited costs of bailing out and recapitalizing the banking system. Admittedly, bailout costs are difficult to measure, and there is considerable divergence among estimates from competing studies. But even upper-bound estimates pale next to actual measured rises in public debt. In fact, the big drivers of debt increases are the inevitable collapse in tax revenues that governments suffer in the wake of deep and prolonged output contractions, as well as often ambitious countercyclical fiscal policies aimed at mitigating the downturn.

These conclusions aren’t all that different from the IMF study published earlier. Both agreed that financial related economic downturns tend to be deeper and more severe. The IMF study indicated that average recession length of 8.4 quarters (see Table 4.2 on page 9), whereas the Reinhart & Rogoff study showed an average of 1.9 years.


Where are we now?
If history is any guide, given that the U.S. recession began in early 2008, then on average the recession will end in late 2009/early 2010. Reinhart & Rogoff showed that equity prices had an average decline of 55% and the S&P 500 has neared that mark on a peak to trough basis.

This environment suggests that equity markets are in a bottoming, base-building process. We should be prepared for a test or even small breakdown from the lows seen late last year, but the downside is limited. If the average recession ends in late 2009/early 2010, then the timing of the final bottom should occur sometime in 2Q or 3Q 2009.

This analysis seems right to me at a gut level. Equity valuations are relatively attractive. Long term sentiment is washed out. The sentiment level is similar to the first half of 1982, when every day the market saw another piece of bad economic news and the market seemed to suffer the Chinese water torture treatment of declining daily, until no one wanted to hear about the stock market.

Under these circumstances, investors with long-term horizons could start raising their equity allocations now, on a dollar-average basis. Traders have to be mentally prepared for the grind ahead and the opportunities that come with the final bottom this year.

A sentimental warning for gold

With gold having shown a nice bounce in the last couple of months from about 700 and now moving in the mid-800s, sentiment models now show that the advance may be overdone in the short run.

First, via Barrons, Mark Hulbert’s reading of gold timers are show excessive bullishness, which is contrarian bearish

The Commitment of Traders data from the CFTC confirms the high level of risk for gold bulls. The chart below shows the net positions as a percentage of open interest of commercials, or hedgers, in gold. While readings are technically in the neutral zone, they are very near levels where a signal to go short is generated.
The chart of the net positions of large speculators, or hedge funds, is mostly a mirror image of the chart of the hedgers’ positions and tells the same story of excessively bullishness, which is contrarian bearish for bullion:

The blogger COTs Timer is also cautious:

My trading setup for gold is in cash for the third week in a row. Large speculator net positioning has climbed gradually since it collapsed in August, when a bullish signal was triggered. It hasn't yet climbed to what my setup considers any kind of bullish extreme. But the other signal I use for this setup - based on the large speculator total open interest - has been on a bearish signal for the past four weeks. This is owing to a 31-percent increase in the large spec total open interest in the past month - typically a sign of downward pressure on the price of gold. So since the two signals don't agree, the overall setup is in cash.

In my past post Giving inflation a chance, I remain of the belief that inflation is destined to rear its head, which will be commodity bullish, but commodity prices are probably in a trading range for the next year or so and need to base before making a sustained advance.

In the short term, it looks like gold prices are facing stiff headwinds.

Addendum: Mebane Faber at World Beta has a blog entry about the XAU/Gold ratio being at a historic low. I refer readers to my previous post on the analysis of gold stock vs. gold ratio and why it might be out of whack, i.e. are production costs at gold companies rising?

A proposal for reforming Wall Street

The fact that there is a culture of greed and excess on Wall Street is no secret. The blogger Cunning Realist wrote that in his experience, Wall Streeters are not exactly rocket scientists (and being a rocket scientist has its own problems) but focuses on how to be a BSD:

The culture rewards speed, opportunism, and quite often recklessness. It does not reward what most people consider "intelligence" -- advanced mathematics ability, or knowing or caring about the difference between Shia and Sunni.

Efforts to rein in risk are not working because of the culture of revenue generation. A recent survey shows that risk managers are still second-class citizens at banks despite the onset of the financial crisis.


A case of misaligned incentives
The downfall of WaMu, Bear Stearns, Lehman and so on can be laid at the feet of the agency problem. If you work at a bank or broker, your compensation is tied to revenue generation and not risk control. It’s not your money!

Compensation payoffs on Wall Street, whether it’s at an investment bank or hedge fund, are asymmetric. If things go right, the investment banker, broker or hedge fund manager gets a disproportionate part of the upside and the investor gets a limited part. If things go wrong, the investor bears virtually all of the downside.

There is a really simple answer to all this. Bring back the partnership investment bank. Let Goldman Sachs and all the i-banks be partnerships again. That way, it’s the partners’ money again. If the partners want to lever the balance sheet up to 30-1 or 40-1, let them. If it doesn’t work, the partners get personally wiped out and some may have to declare personal bankruptcy. In the end, the return function becomes symmetric and the net aggregate effects will be positive. I don’t believe that partners of i-banks would collectively be willing to take those kinds of risks again, nor would they be willing to sacrifice long-term liability for short-term profits.

I would like to say that Rubin's departure from Citigroup marks the end of this era of greed, but until until the incentives are made symmetric and a large portion of future Bob Rubins' personal wealth are tied up in the investment bank, nothing will change.

Smart funds surprisingly defensive

The "Idiot’s Market Neutral Fund" 2008 report card
I first wrote about construction of an idiot’s market neutral fund about a year ago here and I further addressed the controversy of why the technique may work here. For the year 2008, this hypothetical strategy was down -0.7%. These returns are roughly in line with the HFRX Equity Market Neutral Index return of -1.2%. (Recall that this strategy goes long 5 Morningstar top rated, low cost and no-load large cap growth funds and 5 top rated value funds, called the smart fund sample, while shorting the S&P 500 Spyder (SPY) against the long positions.)

2008 was a tumultuous year and these returns are not bad considering the market environment the strategy had to contend with. The strategy had a good first half as the mid-year update showed that returns to June 30 was 3.5%. Given that the average annual turnover of the long portfolio was about 50% per annum, it was virtually impossible for any manager, even with good foresight, to outperform the market both in the first half and the second half of 2008. He would have had to be long the inflation bet in the first half and then switch to a low-beta bet in the second half. Indeed, the consensus sample of 20 large cap blend funds from the top mutual fund complexes, which usually perform in line with the market, underperformed by about 5% in 2008.

This strategy has also shown remarkably low turnover. Of the 10 funds in the portfolio, the strategy kept all of the growth funds and turned over only 3 of the value funds. Two value funds were taken out for style drift and only one was taken out for performance reasons.


What are smart funds doing now?
I reverse engineered the macro exposures of the smart fund sample, as well as the exposures of the consensus funds, and looked for significant differences. Smart funds show a surprising level of defensiveness considering the number of well-known investors who have turned bullish in the last few months.

As the chart below shows, the estimate beta of the smart fund investors is significantly lower than the consensus:

Analyzing the exposure by sector, smart funds are underweight Financials:

...and Energy:

While smart funds are overweight traditionally defensive sectors such as Consumer Staples:



…and Health Care:

Surprising defensive readings
I find these readings surprising given the bullishness shown by investors like Ken Heebner (see his record here), John Neff, Warren Buffett, the ValueLine Survey, and many others too numerous to name. After all, the annual turnover of the smart fund sample is about 50% (as is the consensus fund sample) and these funds really don’t turn their portfolios around on a dime. So if these managers see value in the market, I would expect that they would start to be raising their beta exposures now.

Hedge fund due diligence: the visit

Further to the last post on Hedge fund operational due diligence, here is another by Cox Owen on the site visit.

I just have one addition to his comments. If I were to do a site visit of an investment manager, hedge fund or otherwise, I would ask the portfolio managers, traders and other staff questions about the investment and operating philosophy of the firm to see if there are any significant differences between the operational view and the marketing spin. In times of market stress, these differences in philosophy and approach can make the difference between successful control and catastrophic failure.

You can respond to him directly at coxowen1 at yahoo.com

On-site visit
We are going to fast forward quite a bit so we can jump into the “On-Site Visit”. In proper OPDD we would have discussed numerous other items prior to the on-site visit such as extensive phone conversations, verifications, background checks, reviewing the DDQ and much more. The on-site visit is not an overwhelming task if it is done correctly. Depending on the depth of your experience and the complexity of the fund, the visit should take a minimal amount of time. (usually only a day of two but can take up to a week if necessary). I will try to keep this very high level and extremely general in discussion, there is certainly more to the “On-Site Visit” than what is listed below.

A checklist for the visit
The on-site visit is a critical component of the due diligence process. Make sure the manager is aware that you are coming for a scheduled visit. You want to make sure that all key personnel are informed of your visit and are there to answer any questions you might have.

This is where the rubber meets the road. You have had the opportunity to review the offering documents, understand the managers fund structure and investment philosophy as well as answer almost any question you have about the manager via prior phone conversations. Now you starting the on site visit. This is how you will verify that the manager is operating according to what the offering documentation and DDQ have revealed.

a) Verify the business location is as stated in the legal documents.
b) Meet all of the principals, PMs, analyst, operational staff, etc.
c) Verify all internal groups operate accordingly. (technology, accounting, operations, trading, risk, research etc.). Walk through the entire trade process: Trade generation, execution and processing, reconciliation, accounting, database and systems administration etc.
d) Verify the Disaster Recovery site is operational and working. (When was it last tested? How often does the manager use it? Does the manager have a DR plan? If so get a copy of it, how was the manager affected by key events, such as 9/11 and the 8/14/2003 blackout, other business continuity planning, etc.)
f) Does the manager have a non-investment group that provides control oversight in an open and transparent manner?
g) Verify that the working relationships with service providers are fluid and work under stress.
h) Verify that other investors are also sophisticated investors. (you will certainly feel more comfortable if other investors have preformed their OPDD)
i) Develop an overall assessment of the team and infrastructure
j) Does the compliance environment include documented policies and procedures for all relevant areas (soft dollar, personal trading, trade allocations, etc)? (Ask for a copy of the compliance manual.)
k) Verify cash controls and movements.
l) Develop a list of likes and dislikes.
m) Portfolio administration: Does the manager use Advent, Advisorware or some other recognized software application, or are they using Excel? The software used is critical because robust software can reduce fail points and errors.
n) Does the manager rely on service providers for NAV accounting?
o) Does the manager have an independent set of books and records reconciled to the prime broker?
You should ask to see redacted key trades – let’s say the fund discusses a drawdown of 7% in February and a 21% peak in March you want to verify those trades actually occurred internally and with the Prime broker and the fund administrator.
p) Does the manager plan on trading new instruments?
q) Is the manager experiencing employee turnover?
r) Is the manager planning on making any material changes to management, administration, the strategy or key personnel?
s) Is the manager or any key personnel the subject of any governmental or regulatory investigation?
t) Does the manager have an experienced non-investment leadership providing oversight of internal processes and service providers?
u) Does the manager have a consistent and well – documented valuation and pricing process, if so ask for a copy.
v) Does the manager have an external administrator providing full service support including daily trade capture and reconciliation to prime broker?
w) Does the manager have a dedicated operational team with well defined procedures and processes?
x) Are cash movements and account openings authorized by a single signature?
y) Is the back office subject to key man risk due to being understaffed?
z) Verify the accuracy of the historical data (compare it to cleansed data – I’ve seen a PM show a profitable trade but when I took a closer look at the data it was not remotely close to what the market actually traded on the date in question.)
aa) Verify that the firm has followed its Business Plan.
bb) Does the manager provide annually audited finical statements for the considered funds?

The on-site visit is much broader than the few areas mentioned above. Obviously the operational due diligence criteria will differ from manager to manager and is quite extensive. After all relevant information is collected it should be turned over to the investment committee for review. OPDD does have a black and white science behind it. But there is also the art of connecting all of the procedures and practices that lead to understanding the workflows that actually occur. Anyone new grad student can go down a check list, but to truly understand all of the operational fund complexities can only be done through experience.

“Double Dip” call sets up market bottom

Further to my recent post 10 contrarian reasons for a bottom the long-term investor psychology continues to deteriorate, which is contrarian bullish. First, there is widespread acceptance that the U.S. is in recession. Moreover, fears of a repeat of the Great Depression seem to have peaked and are subsiding. As the chart below shows, a Google Trend analysis shows that searches of the term “Great Depression” reached its zenith at the start of 4Q.

Google Trend Search: Great Depression

I have said before that the stock market will not put in a convincing bottom until there are widespread calls for a double-dip recession. Well, we are now seeing the first call from Niall Ferguson in a FT article entitled An imaginary retrospective of 2009:

2009 proved to be an annus horribilis. Japan was plunged back into the deflationary nightmare of the 1990s by yen appreciation and a collapse of consumer confidence. Things were little better in Europe. There had been much anti-American finger-pointing by European leaders in 2008. The French president Nicolas Sarkozy had talked at the G-20 summit in Washington as if he alone could save the world economy. The British prime minister Gordon Brown had sought to give a similar impression, claiming authorship of the policy of bank recapitalisation. The German chancellor Angela Merkel, meanwhile, voiced stern disapproval of the excessively large American deficit.

While Ferguson doesn’t actually come out and use the “double-dip” term in the article, a rose by any other name smells just as desperate and despondent.


Still a little too soon to buy
While this is the first call of a double-dip recession from a leading bear, I would like to see the double-dip term creep more into the consensus. A Google search of “double-dip” recession still shows entries dating from 2002 and 2003 on the first page.

I would like to see other doomsters and leading bears like David Rosenberg, Nouriel Roubini and Stephen Roach call for a double-dip before I can believe that a bottom is in convincingly for equities.

Could the GBP be the canary in the mine?

Further to my last post about the inevitability of inflation in the U.S. because of the massive fiscal and monetary stimulus, CynicusEconomicus points out that the UK suffers from a similar problem:

[I]n the UK (and the same could be said of the US), there had been no real growth in what I considered to be wealth creating assets over the last ten years which could explain GDP growth; manufacturing, commodity extraction, export of services, and tourism (no net growth).

Instead I pointed to the growth in debt, and asset inflation (real estate) as the source of all of the GDP growth of the last ten years. This debt, in conjunction with the multiplier effect, along with upwards levers such as immigration, created an illusion of growth in wealth. It led to the 'post industrial', 'service economy'. My argument was that this was completely unsustainable, and that a collapse in asset prices would signal a self-reinforcing downward spiral in the economy, driven by a collapse in consumer sentiment (a massive belt tightening) leading to the collapse of the service economy, higher unemployment, more belt tightening and so forth into a downward spiral.

Because virtually all governments around the world are pursuing similar fiscal and monetary policies, it is possible that the USD does not fall against other currencies. Instead, inflationary expectations show up in commodity prices, inflation-indexed bonds and the long end of the yield curve.

When does Mr. Market realize that inflation becomes a problem?

I have no idea. One way would be to watch Pound Sterling. If the UK suffers from the same problems, then one way that these pressures manifest themselves would be a fall in the GBP, which is not a significant reserve currency the same way the USD is.