Capital by Thomas Piketty – A Critical Review

Thomas Piketty’s Capital in the Twenty First Century is a translation of the original French work, Le Capital au XXIe siècle published in 2013. Capital, a 577 page text, complemented by another 110 pages of supplementary notes and indices is the author’s attempt to illustrate the history of wealth and income inequality. While Piketty’s research provides some insight into emerging markets (China, India, Latin America), most of the research is centered on France, Germany, Britain and the US. Given the difficulty in obtaining reliable data, the research is further restricted to the time period from the 1800s to present…

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2016 – A Change in Investment Paradigm

 

SUMMARY:

  • A confluence of three global macroeconomic changes will result in the investment paradigm of the past few years
  • First – Tighter monetary policy and its repercussions on the U.S. equity market
  • Second – Overestimation of tighter monetary policy and its effect on the US Dollar and commodities
  • Third – Presidential elections in 2016 and their global ramifications
  • Strategies like managed futures should perform the best in 2016

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What You Can Expect After the Next Correction

Summary

  • Instead of speculating on the timing of the next correction, we would like to paint a picture of a possible scenario that is likely to unfold after the correction.
  • The 3 main weapons of choice have been to lower the price of money, increase the supply of money and generate wealth effect. But these are not likely to work.
  • With the current Fed Funds rates at 0 and the Fed in no hurry to hike, this policy gun is empty.
  • As the Japanese case study shows despite aggressive quantitative easing and government deficit spending, the Nikkei 225 has not budged.
  • Once the investor confidence is dented, policy measures lose their sting.

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Alternatives for Retail, It’s All About the Vehicle

In a recent Bloomberg article, the author lambasted the managed futures industry for non-performance, high fees and being confusing.  In our opinion, the research done by the author and the facts presented were not representative of the industry as a whole.  The article’s research analyzed the commonly available managed futures investments to the retail investor in the form of mutual funds and summarized their shortcomings.

The problem is not with the managed futures asset class or its place in the investor’s portfolio, but with the vehicle through which they are available to the general public.

In our article, Managed Futures Mutual Funds Don’t Work.  Here is Why published in December 2012, we pointed out these mutual fund shortcomings for investing in alternatives and why they could not deliver what they promised or aspire to do.

According to Opalesque, assets in US alternative mutual funds “have ballooned to $550 billion” with an equally impressive growth in the asset class in Europe.  It is therefore imperative that financial advisors understand the shortcomings of mutual funds in delivering what they promise and seek out alternative vehicles that are available to the retail investors.

Lack of Exposure and Costs

Mutual funds, which are registered under the 1940 Act, limit the non-security exposure of a mutual fund to no more than 25%.  This creates two problems for mutual fund when investing in futures contracts or CTAs.  The first is obviously not enough exposure to the asset class as they are limited to investing only 25% of capital directly into managed futures.

The second problem comes when mutual funds try to circumvent the 25% limitation.  A mutual fund will set up an offshore vehicle in the Caymans or British Virgin Islands and invest 25% of the mutual fund’s capital in this offshore vehicle.  Then the mutual fund will engage in a total return swap between the offshore vehicle and a prime broker to leverage their exposure to managed futures.  This practice is not illegal, but the conduit involving a foreign corporation and swaps adds another 0.50% to 2% in costs annually to the mutual fund investor and an added layer of counterparty risk where the mutual fund investor is now exposed to the credit risk of the prime broker.

A hedge fund registered under the 1933 Act is not limited by how much it can invest in managed futures and therefore does not have to set up offshore vehicles and incur additional costs.  Contrary to popular belief that hedge fund structures are only available to accredited investors with high minimums, usually $1 million, and lock up an investor’s money for a long time, there are managed futures offerings listed with the SEC as hedge funds that are available to non-accredited investors with minimums as low as $5,000 and no lock-ups.

Increased Performance Dispersion Requires Skill in Picking the Right Strategy

A look at the Barclay CTA Index shows not just a drop in performance but also increased dispersion of returns.  The CTA index has performed poorly since 2008 both on an absolute basis as well as on a relative basis when compared to the S&P 500 Index.

Estimated YTD performance for 2013 calculated with reported data as of November-6-2013 14:29 US CST

This poses a challenge for the portfolio manager who is trying to create a fund of managed futures strategies.  Given the poor overall performance and the large dispersion between the successful and the average strategies, the portfolio manager needs to possess an investment edge.

The dispersion of 449 CTA one-year returns shows an extremely wide distribution.

The highest one-year return is                                     56%.

The lowest one-year return is                                     -87%.

The percentage of CTAs with positive returns is           35%.

The percentage of CTAs with negative returns is          65%.

And worse still, 13% of these CTAs are so deeply negative that most likely they will go out of business.

Source: BarclayHedge, MA Capital Management.  Data is a compilation of one year returns of 449 CTAs from 7/2012-7/2013.

The above dispersion chart of 449 CTAs shows that 33% of CTAs have positive returns for 2013, even though the index is negative and 24% have performed very well in 2013 with returns greater than 10%.

This clearly shows that the managed futures as an asset class is a viable performer even in a low volatility year like 2013, but it also shows the need for expertise on part of the portfolio manager in identifying the right strategy to put in their portfolio.

Unfortunately, most managed futures mutual fund portfolio managers do not have this required expertise, as few have ever traded futures or managed other futures traders in their careers, which means that they provide little to no edge when picking strategies for their mutual funds.

In the book, The Future of Hedge Fund Investing (Wiley,09) our Chief Investment Officer, Monty Agarwal, states that portfolio managers who invest in alternative strategies need to understand how these strategies work and how to pick the right traders to trade them.  The only way to acquire these skills is through experience in trading and managing traders.  Just as you would not go to a heart surgeon who does not possess the right education and experience, similarly, an investor should not invest with a managed futures mutual fund portfolio manager who has not traded these strategies himself.

Alpha is Not a Constant but Depends on Market Volatility Cycle

In one of our papers, Constructing a Robust Absolute Return Portfolio, we showed that there are three types of markets, trending, shock and noise with different volatility profiles.  But more importantly, a managed futures strategy exhibits different risk/return profile under different market cycles.  It is the job of the portfolio manager to understand these cycles and how different strategies behave under these cycles and allocate capital accordingly.

A systematic allocation of capital that changes with the market volatility cycles can ensure that the managed futures portfolio performs well in not just a 2008 type market cycle, but also in a 2013 market cycle.

If you would like to learn more about an alternative vehicle other than a mutual fund or are interested in distributing it to your clients, please email us at info@macmllc.com.

Constructing a Robust Absolute Return Portfolio

Summary

Most investors are familiar with the concept of an absolute return portfolio.  As the name suggests, “an absolute return portfolio” strives to provide positive returns over any distinct time period, regardless of the performance of the relevant index, such as the S&P 500 Index.

Clearly, constructing such a portfolio requires asset classes that exhibit return and volatility characteristics that are not correlated to other assets in the portfolio.  The earliest attempts were made to construct such portfolios with a mix of long-only assets such as domestic stocks and bonds.  Then global securities were added to the mix as well, including developed markets, such as in Europe, emerging markets, and even frontier markets of Africa or South East Asia.  Later, alternative strategies were also added to the mix using hedge funds, managed futures, real estate and other esoteric classes such as art and wine.

But most such absolute return portfolios suffered from an over reliance on historical performance parameters.  Market history has shown time and time again that correlations are not stable and market returns are not normally distributed.  In fact, in a recent research piece[i], we showed that the number of months that the S&P 500 Index is down greater than 3σ has been occurring with a higher frequency since 2000 than at any time since 1950.

Research has also shown repeatedly, that a portfolio of only hedge funds or only managed futures does not produce alpha on a consistent basis.  Later in this paper we will show how the hedge fund index beta to the S&P 500 Index is quite high and higher still during large volatility periods.

In our quest to create a robust absolute return portfolio that can adapt with changing market conditions we started with a mix of stocks, bonds, managed futures and hedge funds.  We further assigned the following constraints to the portfolio:

-       High liquidity

-       Low bid-offer spreads

-       Complete transparency at the position level, including pricing

-       Low counterparty credit risk

The philosophy behind our portfolio construction was:

-       Returns, alpha, volatility and correlations are not a constant but change with market conditions

-       100% systematic approach to portfolio construction, allocation and risk management

-       Dynamic allocation across strategies

-       Active risk management

Conclusions:

  1. A portfolio of only alternatives, like hedge funds or managed futures, does not create a robust absolute return portfolio.
  2. The most robust absolute return portfolio we found had systematic beta, in the form of actively managed S&P 500 sub-index ETFs and a portfolio of multi-manager managed futures strategies.
For the full research paper, please click the link below:

Constructing a Robust Absolute Return Portfolio

 


[i] Monty Agarwal, A Statistical Analysis Of S&P 500 Index, MA Capital Management, Palm Beach Gardens, FL, Feb 11, 2013, http://seekingalpha.com/article/1172871-a-statistical-analysis-of-s-p-500

The Next Credit Driven Crisis

Since 1998, markets have been stuck in a vicious boom and bust cycle which is a direct result of the Fed’s over tampering with monetary policy.  The last three major global financial crises have all been caused by prolonged periods of easy credit which were then followed by rapid tightening phases.  There are quite a few parallels that can be drawn between the previous three situations and the current market environment.

The three past crises we are referring to are:

  1. The 1998 Asian financial crisis
  2. The Internet bust from 2000-2002
  3. The housing crisis of 2008

Asian Financial Crisis of 1998.  1998 is remembered most commonly in the financial markets as the year of Asian crisis.  In reality it was far more widespread than just Asia.  The crisis spread to other emerging markets including Russia and Latin America and was averted in the US by some deft maneuvering by the Federal Reserve who intervened to shore up market confidence by bailing out Long Term Capital Management.

The Asian bubble of 1998 was fueled by a massive inflow of global capital into the Asian markets that resulted in the funding of poor projects that eventually went bankrupt.  Recession and low interest rates in the developed capitalist world generated substantial interest on the part of investment houses and international banks in the “emerging” markets of Southeast Asia.  The trigger for the crisis was the eventual realization by foreign investors that their investments were not performing, which led to concerted selling, loss of confidence and a massive outflow of capital.

Fast forward to the present and once again it is quite clear that a rush of capital into certain asset classes over the past four years has been engineered by cheap credit and a lack of global investment opportunities.

Case study 2; the internet bust of 2000.  If you remember, the Fed had cut rates aggressively in the US as a result of the 1998 Asian crisis and had also flooded the market with liquidity in anticipation of disruption from the Y2K computer bug.  This had led to aggressive buying of internet stocks, a lot of which was done on margin, leading the NASDAQ to record heights of 4,572 and the Fed Chairman, Alan Greenspan to remark about the “irrational exuberance” of the markets.  To curb the market exuberance, the Fed had started hiking interest rates, as it took them from 5% to 6% all through 2000.  The result was the bursting of the internet bubble and a subsequent drop of 74% in the NASDAQ.

Case study 3; the more recent housing bubble burst of 2008.  Once again a lot of fingers have been pointed at the Fed for keeping monetary policy too easy for too long after the internet crisis of 2000.  The Fed Fund rates had dropped to a low of 1% in 2003 and it took the Fed three years to normalize them.  This prolonged period of cheap credit fueled the housing market bubble which eventually burst in 2008 as once again investors realized that they were invested en-masse in non-performing assets.

In all the three cases, asset bubbles were inflated by cheap credit and a lack of investment opportunities, which caused capital to rush into a few select asset classes and markets.  And then the bubbles burst, when investors realized that they were invested in non-performing assets and the Fed realized that credit needed to be tightened.

Once again when we see the market dynamics of the past four years, we are seeing history repeat itself.  The housing crisis of 2008 caused the Fed to lower rates to effectively zero and embark on quantitative easing to promote US equity markets.  The three asset classes that have been the best beneficiaries of the current Fed policy have been Gold, Bonds and the US equity markets both on an absolute basis as well as a relative basis.

1/2008 – 3/2012:

Gold + 100%

30 year US Treasury Bond Price: +50%

S&P 500: +21%

Over the same period, the European equity markets returned -38% (SPDR EURO STOXX 50) and the emerging markets indices have returned anywhere from -1% for MSCI ASIA APEX 50 to -9% for the BRIC Index.

I think it is quite easy to see which market has been the beneficiary of easy credit policy and where the largest bubble potential lies.  In the past two months, gold has fallen from a high of $1,900 to $1,250, a drop of 34%.  The market is calling for a fair value bottom around $1,100, but rarely does the market stop at its fair value.  It always overshoots, so if is not unrealistic to conclude that gold might fall to below $1,000.

US 30 year bonds yields hit a low of 2.47% and have since risen to 3.60% a drop in price of nearly 15%.  Yields could easily rise to 5% as the Fed normalizes the yield curve and stops buying bonds.

The S&P 500 has been resilient thus far, with a drop of only 6% from its high of 1,660.  But if history is a guide, the US equity markets have a lot further to correct if the Fed’s credit spigot is turned off.

The chart below is a comparison of the expansion of the Fed’s balance sheet and the performance of the S&P 500 as money has been driven from bonds into stocks.  The data from 2008 shows an 86% positive correlation between the S&P 500 performance and the size of the Fed’s balance sheet.  So, it is logical to assume that as the Fed’s balance sheet stops expanding, we can see the S&P 500 lose steam.   Also, if the Fed’s balance sheet starts contracting, the S&P 500 could go in reverse quite sharply.

Therefore, it is no surprise that the smart money is listening very closely to what the Fed governors are saying and selling the S&P in anticipation of such an announcement.

The problem with credit driven crises is that the unwind is never orderly.  This is mostly because in times of cheap and plentiful credit, leverage is abused heavily and during an exodus the selling gets magnified by the leverage in the system.  We see no reason why the past four years of asset binging period be any different as investor behavior rarely changes.  The best course of action is to be smart and recognize that the party is over and head for the exits before the masses do.

Portfolio Risk Management – Position Sizing

The next article in our series on strategic risk management talks about position sizing, why it’s useful and how to determine it.

Position sizing and stop-losses [link to blog post] go hand in hand.  Having the proper position size will limit loss in any one holding.  The best way to illustrate this is through an example.  Take a $40,000 account, we decide to limit our loss per trade to no more than $1,200.

But this $1,200 depends on two things: the position size and the size of the market move.

For example:

Position Size                        Market Move                        Loss

100 shares                           $12                             $1,200

200 shares                           $6                               $1,200

300 shares                           $4                               $1,200

The above example makes it clear that to limit your loss to $1,200 per trade you have to look at both the position size and the price move.

So which combination to choose?  Do you trade 100 shares and wait for a $12 adverse price move, or trade 300 shares and wait for a $4 adverse price move.

The answer to that question lies in the volatility of the stock.

Measuring the volatility of the underlying stock

If the underlying stock moves $2 in a day then clearly picking your price stop of $4 is way too tight, because if the stock moves two days in a row against you, you will be stopped out.  But, if your underlying stock moves $1 on average in a day, then you can probably pick a price stop of $4 and trade 300 shares.  The stock price would have to move against you for four days in this case.

This is a very simple example.  Professional money managers typically employ very intricate mathematical models to constantly measure the volatility of the underlying stock, currencies or commodities and constantly keep changing the position sizes and adjusting the stop-losses.  That discussion is out of the scope of this discussion, but we want to pass on the essence of the methodology.

Here are three simple steps to use when determining the stop-loss as a function of the underlying stock’s volatility.  Remember these are guidelines, and how an investor ultimately uses them depends on their portfolio’s particular circumstances.

Step 1:

Look at the daily move in the stock price as a percentage of the stock price over the last year.  There are many publicly available sources for price data such as Yahoo! Finance or CNBC.com.

Example:

Stock Price              Daily Move                Move – % of stock price

$25                      $0.50                          2.00%

$28                      $0.65                          2.32%

$22                      $0.40                          1.81%

Step 2:

Take the average of these percentage moves over the last year.  So you will have about 252 numbers to average (as there are roughly 252 trading days in a year). In our example above, the average of the three numbers is 2.04%.

Step 3:

Now that we know how much this stock can move in a day, give yourself a margin of three straight days of a move against your position.  This means that if the stock moves three days against your position, the position is liquidated. To calculate that stop-loss percentage, we multiply this daily average move by three.

In our example we get 6.12% (=2.04% x 3).

So on the day you put on the trade, if the stock is trading at $30, my stop loss on that stock would be $1.84 (=6.12% x $30).

And from this you can calculate how many shares to buy.  If you were going to set your total loss on this trade at $1,200, you would buy no more than 652 shares (=$1,200 / $1.84).

As always, never implement any trading or investing rules without thoroughly testing and refining them on a “paper portfolio”.

 

 

 

 

 

Portfolio Risk Management – Stop-Losses

Professional traders and investors have been using risk management techniques for decades to help safeguard their portfolios from catastrophic losses.

In our blog series, Portfolio Risk Management, you can begin to learn some of those same techniques and how to implement them in your portfolio. Some of the topics we will be covering will be:

Stop losses

Position sizing

Measuring stock volatility

Risk vs Reward ratio

Hit ratio

Let’s start with stop losses. Stop losses are designed to remove positions that are declining in value.

Ever wonder why some traders survive, or even thrive during times of high market volatility? Many who do exercise good risk management and cut their positions in time and lock in their gains. Those who waited for positions to “come back” may not do as well.

As any investor knows, the Internet crisis of the late 1990s was not an isolated event. Financial crises with massive drops in the market have become quite commonplace. Five years later, many are still recovering from the 2008 financial crisis, which saw many portfolios lose value.

Implementing proper stop losses is critical and at the core of proper risk management.

Let’s assume we have a $40,000 account; 3% of $40,000 is $1,200, which is where we set our stop. So, if our stop is hit, our position size needs to be such that our cash loss is no greater than $1,200.

A 3% maximum loss on a position will ensure that you will have a losing streak of 33 trades before you are taken out of the markets. This is arrived at by simply risking 3% of the original capital on every trade. So if there are 33 trades in a row wrong, the total loss of capital is (3% x 33trades = 99% of capital).

As always, we caution that prior to implementing a systematic rule to your investing, investors should test and perfect their techniques on paper portfolios. Stay tuned. In the following weeks we will delve deeper into more sophisticated risk management techniques.

Portfolio Management Rules – Balancing Risk and Reward

These days, we get a lot of questions of whether it is too late to start investing given the recent run up in the US market. For the long-term investor, disciplined portfolio management and risk management can mean the difference between generating and destroying wealth, regardless of when investing begins.

But many individual investors allow emotions to enter into it, often times buying too high or selling to low. While others try their hand at “market timing” based on what they are hearing the “experts” say on popular financial channels.

Last week, we wrote about security selection rules, and basically argued that broadly-diversified, low-cost portfolios in different asset classes make more sense to gain exposure than single-stock positions for most investors. This is especially true if, like most average investors, you don’t have the time, resources, or information to thoroughly analyze and track individual companies in a highly competitive world.

This week’s article addresses portfolio management and how to balance risk and maximize opportunities in your portfolio among different asset classes. Portfolio management is all about balancing risk and reward by allocating capital across different asset classes. Risk management is an integral part.

Different asset classes such as real estate, commodities or European equities will respond to different economic factors. For example, one economic environment may be more beneficial for certain commodities than it would be for real estate. It’s the old argument of not putting all your eggs in one basket. When one drops, another rises. This happens when assets have low correlations to each other – their price doesn’t move or correlate well together.

But correlations can and do change during financial crises. Risk management is especially important in these highly volatile markets or in any market where the correlations amongst disparate asset classes increases (like in 2008, when we saw broad drops in a variety of sectors.)

The mix of assets depends on an investors personal risk tolerances and investment goals. Eighty percent in stocks or risk assets may be just fine for an aggressive investor, but not for one who is prone to panic and sell during market drops. Generally portfolios lie on a range of equity/fixed income mixes and can include a broad variety of assets including emerging markets, commodities and real estate.

But what should not vary between investors is having robust risk management processes. There are a variety of forms of systematic risk management, but the premise is the same: a set of rules that reduces a portfolio’s volatility and tries to protect the downside. These can be as simple as having a sell rule of cutting losses at 5% (when an asset drops more than 5%) or a more technical one as faltering relative strength (price movement relative to other assets). These sell rules are based on price action. But they can also be based on fundamentals such as changes in earnings per share or profitability.

At MA Capital Management, we approach risk management from a systematic perspective, so our sell rules are generally based on price movements and asset strength in a particular market environment. An example of this occurred in March, when our models indicated a weakness in gold. We were able to get clients out of commodities several weeks before the sell off in April.

Tell us what you think.