Managed Futures–Chapter 22

The term managed futures refers to the active trading of futures and forward contacts on physical commodities., financial assets and currencies. The goal is not necessary diversification but instead added value. There are three ways to access the skill-based investing of the managed futures industry: public commodity pools, private commodity pools and and individual managed accounts. Public commodity pools are open to the public and requires registration with the SEC. Private commodity pools are open for high-net worth individuals and requires no SEC registration.

Even though managed futures trading has been around for decades, industry benchmarks to track the industry are relatively new; approximately one half have been developed since 2000. Those with longest historical track records are the Barclay CTA index, Center for International Securities and Derivatives Markets (CISDM) and Mount Lucas Management Index (MLMI). Similar to hedge fund indices, some of these benchmarks are equally weighted while others are asset weighted. Through observation all of these indices have a negative correlation with inflation and are therefore not an effective hedge against inflation.

Most CTAs are considered to be trend followers, while there are also discretionary CTAs. Discretionary CTAs tend not be as diversified as trend-following CTAs and are therefore perceived to be more risky.

Return distributions of Managed Futures

The book mentions these indices and individually presents a return distribution for each.

• Barclay Trader CTA Index
• CFSB/Tremont Managed Futures Index
• CFSB/Tremont Investable Managed Futures Index
• Barclay Newedge CTA Index
• FTSE Hedge CTA Index
• CISDM CTA Asset Weighted Index
• CISDM CTA Equal Weighted Index
• EDHEC-Risk CTA Global Hedge Index

Core, Value-Added and Opportunistic Real Estate

While Style Boxes have been used for many years in equity and fixed-income investing, real estate investment styles are relatively new. There are three main reasons for introducing styles into real estate portfolio analysis:

1. Performance measurement.

2. Monitoring style drift. Portfolio managers occasionally drift from their stated risk, return or other objectives. Classifying different styles of real estate investments allow an investor to measure the overlap among investment products.

3. Style diversification. The ability to determine the risk and return profile of a manager relative to its style will allow for a better diversification of the portfolio.

NCREIF has identified three styles that apply at the underlying asset level for direct real estate investing: core, value-added and opportunistic. NCREIF also classified eight attributes to distinguish the three types of real estate asset styles:

1. Property type

2. Life cycle

3. Occupancy

4. Rollover concentration

5. Near-term rollover

6. Leverage

7. Market recognition

8. Investment structure/control

 

Core

Core properties are the most liquid, most developed, least leveraged, and most recognizable properties in real estate portfolios.The properties have the greatest amount of liquidity but still are not sold quickly relative to traditional investments. Core properties tend to be held for a long period of time.The majority of their income come from the cash flows instead of value appreciation.

Value-added

Relative to core properties, these properties tend to produce less income and rely more on property appreciation to generate their total return. These properties can include new properties that might otherwise be core properties except that they are not yet fully leased, such as a new apartment complex or shopping center.

Opportunistic

Opportunistic real estate moves away from core/income approach to a capital appreciation approach. Often opportunistic real estate is accessed through real estate opportunity funds, sometimes called private real estate equity (PERE). The majority of the return from these properties comes from value appreciation. Opportunistic real estate tend to pursue some event that will result in the real estate being quickly and dramatically revalued, typically from development of raw property, redevelopment of property, or purchase in an area of renewal. Leverage is typically included to further enhance total returns.

A rule of thumb is to use 5th, 25th 75th and 95th percentiles ranges around the median as natural breakpoints for determining core, value-added and opportunistic return expectations. A core portfolio could have a range of returns between 8.3% and 19.1%, the 25th to 75th percentile. Value-added fits in the 5th to 25th percentile and 75th to 95th percentile. Initially, its expected to fall in the lower range as the new leasing strategy begins or repositioning of the property starts. Later, its expected to fall in the higher range, 75th to 95th percentile. Opportunistic fall between zero and 5th percentile and 95th to 100th percentile. Opportunistic real estate will often have negative reported returns early on as capital is deployed for the development, ground-up building of the property. It would then, hopefully, jump in to the highest percentile range.

Gearing: ratio of long term debt compared to equity capital.

Real Estate as an Investment–CAIA Chapter 8

There are five goals for adding real estate to an investment portfolio:

1. To achieve returns above the risk-free rate.

2. To provide a hedge against inflation

3. As a portfolio diversification tool that provides exposure to a different type of systematic risk and return than stocks and bonds.

4. To constitute an investment portfolio that resembles the global investment opportunity set.

5. To deliver strong cash flows to the portfolio through lease and rental payments.

Absolute returns above the risk-free rate

Examining this goal it was found both direct real estate investing and investing through REITs provide a very favourable risk-return trade-off compared to stocks and bonds. The Sharpe Ratios for the the NPI and its four sectors as well as its NAREIT index where significantly greater than those for large- or small-cap stocks, investment grade bonds. U.S Treasury Bonds had the second highest Sharpe ratio after the NAREIT apartment index. It was also noted that investing in REITs provide a significant return premium above the inflation rate.

A hedge against inflation

Direct real estate investing was found to be a hedge against inflation with moderately positive correlation coefficient. REITs did not show the same hedging ability, which was found to be adversely affected by inflation. NCREIF Retail index provided the best hedge against inflation. This is because current inflation increases the net operating income of retail properties much faster than the expenses associated with retail properties. The reasons are that retail real estate properties charge percentage rents based on revenues. (which adjust quickly to inflation).

NCREIF and the NCREIF Indexes–CAIA Chapter 7

One of the key benefits of NCREIF is the publication of NCREIF Property Index (NPI) and a set of sub indexes for direct real estate investing. Direct real estate equity investing involves direct property ownership as opposed to ownership of publicly traded claims to real estate. Every quarter, members of NCREIF submit data about the properties that they own to support computation of the NPI. The NPI is a proxy for the performance of direct investments in real property. The types of properties underlying the NPI are: Offices, Apartments, Retail, Industrial, Hotels. Conceptually, these property types form the core of a real estate portfolio. The NPI is calculated quarterly, which is a relatively infrequent interval compared to the daily calculations of most stock, bond or commodity indexes. The reason is the illiquid nature of real estate; properties simply do not turn over frequently enough to compute short-term returns. The NPI is calculated on “as if” basis; if the property was purchased at the beginning of the quarter at its appraised value and sold at the end of the quarter at its end-of-quarter appraised value. The return of the index is then as the change of appraised value plus any cash flow received for the quarter. Appraisals are generally based on two different methods. The first is the comparable sales method, the real estate appraiser looks at sales of similar sales of similar properties in the region. The second method is discounted cash flow analysis, the appraiser estimates the cash flows from a property and discounts them to form a a present value to the property. NPI is a smoothed; with a tendency to exhibit lower volatility than exists in the true property market. Although NPI is calculated quarterly, NPI properties are not appraised every quarter. Most properties are valued once a year, or even every two-three years. The property values are then adjust based on capital expenditures each quarter. Another reason for the smoothing is that the comparable sales method is based on previous sales. The effects of smoothing are; the volatility is dampened, slowness to react as changes in market values reacts slower then changes in macroeconomic event as quickly as stocks and bonds.

Real Estate Investment Trusts–CAIA Chapter 6

Real estate is included as an alternative asset class for the following reasons:

• Real estate is an overlooked asset class. Many investors have only a small or no allocation to real estate.
• Real estate provides a different systematic risk premium exposure from stock and bonds.
• Real estate is a tangible asset class, it drives a return stream that is different from the cash flows generated by a corporation.

Real Estate Investment Trusts (REITs) are stocks listed on major stock exchanges that represent an interest in an underlying pool of real estate properties. The key advantage of a REIT is that it provides a broad exposure to real estate properties that the investor would not otherwise be able to obtain.n One of the advantages of a REIT is the pass-through tax, a REIT avoids taxation at the corporate and individual level and instead pass all its income/gains to its shareholders. Another benefit is that REIT is the management of the REIT executives. These are often real estate professionals who know how to  acquire, finance, develop, renovate and negotiate agreements to get the most return. A disadvantage of REITs is that they are listed on stock exchanges. With being listed comes along a systematic risk associated with a broader market along with REITs, which reduces their diversification benefits. Most REITs fall into the capitalization range of $500 million – $5 billion, same range as small cap stock and lower end of mid-cap stocks. Therefore they are more highly correlated with small-cap stocks. There are three basic types of REITs: equity REITs, mortgage REITs and hybrid REITs.

An equity REIT uses the pooled capital from investors to purchase property directly.

An mortgage REIT derives it value from financing the purchase of real estate properties. Mortgage REITs are invest in loans to real estate, they are lenders to owners, developers, and purchasers of real estate. They generate return from interest on loans.

Hybrid REITs invest in both the equity and mortgages of real estate properties. Some hybrids are explicit as to the amount of equity ownership and mortgage financing, such as 50-50 split.

A single-property REIT accumulates capital to purchase a single large property. A finite life REIT establishes a termination date by which the REIT will sell its underlying properties and unwind its affairs. A dedicated REIT is typically established to invest in: one type of property only, a single development, a geographic region. An umbrella partnership REIT (an UPREIT) is a REIT where the REIT itself does not own any real estate properties directly but rather holds the properties in an opening partnership. A Down-REIT is a way for property owners to contribute property to a REIT in exchange for stocks in the Down-REIT.

REITs are in general considered to be a good hedge against inflation. The reason is that typically rental/lease payments are adjusted upwards during times of inflation.

The Calculus of Active Management–CAIA Chapter 5

Alternative assets focus on adding value to the portfolio through the use of active bets, both long and short, with and without concentrated portfolios. A portfolio manager is judged on how effectively he/she is in his/her designated portfolio specialty. The answer lies with the Fundamental law of active management.

The information ratio (IR) is measured as the active return (alpha) produced by the manager divided by the tracking error (TE), or standard deviation of the alpha. The information ratio is a measure of risk-adjusted return much like the Sharpe ratio. The Sharpe ratio is a risk-adjusted return based on the total deviation of the active manger’s return because the benchmarked that is used has no volatility. The Sharpe ratio assumes. It’s not appropriate to apply the Sharpe ratio to individual securities or managers, because it ignores the fact that the manager’s correlation with the rest of the portfolio is a major determinant of its risk-return profile. The Sharpe ratio is appropriate only to compare standalone investments. IR is a special form of risk-adjusted rate of return where the performance is measured relative to a risky benchmark. The IR measure the volatility of the active manager compared to its volatile benchmark, the excess return is measured relative to a risky benchmark.

The Fundamental law of Active Management is based on two key components of every actively managed investment strategy: breath and skill. The breath of a strategy is the number of independent active bets placed into and active portfolio. The skill is measured by the information coefficient. The information ratio is the information coefficient multiplied by the square root of the breadth. There is a trade off between breadth and information coefficient, its not generally possible for an active manager to breadth and the IC at the same time.

Alternative investment managers typically do not have a mandate to follow a benchmark. Therefore investors have created custom benchmarks, the simplest being a Sharpe style analysis approach with the goal to create a portfolio of readily investable assets that best replicates the return on the active manager.

The long only constraint, recognized as the most restrictive portfolio requirement, has led to an expanded form of the Fundamental law of Active Management. The Transfer Coefficient, the cross sectional-sectional correlation between risk-adjusted active weights and and risk-adjusted forecasted residual returns, is the multiplication of the transfer coefficient, information coefficient and the square root of the breadth.

Alpha versus Beta–CAIA Chapter 4

 

Beta drivers are low cost investment products designed to efficiently capture the risk premium associated with an asset class such as equity, fixed income, commodities or real estate. Beta drivers do not attempt to outperform well-defined benchmarks. Their purpose is not to generate excess return but to provide a rate of return consistent with a fundamental risk premium. Conversely, alpha drivers exploit informational advantage in the financial markets. Their purpose is to generate excess returns. Since they tend not to be highly correlated with traditional asset classes, they provide diversification benefits as well. In between pure beta drivers and pure alpha drivers are a wide range of products. At one end of the scale are the 130/30 funds, hedge funds, tactical asset allocations, these are product innovators. At the other end asset gatherers are striving to deliver beta as cheap as possible. These are process drivers. These process drivers efficiently carve up financial assets into as many systematic risk factors as they can find.

Alpha is typically identified through the use of factor models, such as the capital asset pricing model (CAPM). It was the first model that identified a systematic risk factor, the beta, associated with an asset class. Alpha is determined ex-post (after the fact) (opposite to ex-ante, before the event). The problem with determining alpha is that it depends on the systematic risk factors of the beta component. If the beta factor is not included the alpha can be artificially high. This leads to two implications:

1. Asset managers must be rigorous and intellectually honest about what is beta and what is alpha.

2. An information asymmetry exists between asset managers and asset owners. Since alpha is not directly observable, asset managers have more information about their true alpha-producing ability than the asset owners who hire them.

Alpha is a zero-sum game only IF:

1. Investors have the same time horizon

2. Investors have the same level of risk tolerance

3. Investors are allowed the same access to all asset classes.

4. Investors have the same expectations about return and asset class risk premiums.

5. Investors pay the same tax rate, or equivalently, there is not tax.

 

Governance in the asset management industry must address these asymmetries of information:

• Beta is a commodity and should be priced cheaply.
• Unbundling drives price transparency. The unbundling of alpha from beta allows asset managers to price their products more accurately and with greater transparency.
• Asset managers must demonstrate a clear and transparent investment process.
• Investors must accept a balance between transparency and alpha generation. The ability to generate alpha will decline if information about the asset manager’s competitive advantage is made public.
• Asset managers must be transparent in their risk taking.

 

ERP (Equity risk premium): ERP is the return premium that investors must earn in order to entice them to hold stocks over bonds. Over the last ~30 years the ERP in US have been 3.9%, that is stocks have yielded 3.9% more then Treasury bonds.

Sharpe Ratio & Information Ratio

Sharpe Ratio

Sharpe Ratio/Sharpe Index/Sharpe measure or reward-to-variability ratio is a measure of the excess return per unit of risk in an investment asset or trading strategy. The Sharpe ratio is used to characterize how well the return of an asset compensates the investor for the risk taken, the higher the ratio the better. The Sharpe ratio is directly computable from any observed series of return as long as the measured returns are normally distributed, as the returns can always be annualized. As not all asset returns are normally distributed therein lies a weakness in the Sharpe ratio.

 

R: asset return

R_f: return on the benchmark asset, such as the risk free rate of return

E[R − R_f]: expected value of the asset excess return over the benchmark return

σ: standard deviation of the asset excess return. This is often confused with the excess return over the benchmark return (i.e the tracking error) which is used in calculating the Information Ratio.

Note: With positive Sharpe ratios, a portfolio’s Sharpe ratio decreases if the risk increases, all else equal. With negative ratios, however, increasing risk results in a numerically larger Sharpe ratio. Therefore, in comparison of negative Sharpe ratios, the larger Sharpe ratio cannot generally be interpreted as better risk-adjusted performance. However, if the standard deviations are equal the portfolio with the ratio closer to zero are superior.

Information Ratio

Information ratio/appraisal ratio is a measure of the risk-adjusted return of a financial security, asset or portfolio. It is defined as expected active return divided by tracking error, where active return is the difference between the return of the security and the return of a benchmark index and the tracking error is the standard deviation of the active return. The information ratio is used to gauge the skill of managers of hedge funds, mutual funds etc. In this case it measures the expected active return of the manager’s portfolio divided by the amount of risk the manager takes relative to the benchmark. The higher the information ratio, the higher the active return of the portfolio given the amount of risk taken, and the better the manager.

 

,

R: portfolio return

R_b: benchmark return

α = E[R − R_b]: expected value of the active return

ω = σ: standard deviation of the active return (tracking error)

 

Examples

1.

Fund	Mean return	Standard deviation of return
SLASX	12.58%	19.44%
PRFDX	11.64%	13.65%

Suppose Tbills is used for the risk-free rate of return with a mean annual return of 4.38%.

Sharpe_SLASX = 0.42 and Sharpe_PRFDX= 0.53

2.

Suppose a portfolio that achieved a mean return of 9% during the same period that its benchmark earned a mean return of 7.5%, and the portfolio’s tracking risk during that time frame was 6%. This will evaluate to an IR of (9% – 7.5%)/6% = 0.25

 

 

http://en.wikipedia.org/wiki/Sharpe_ratio

http://en.wikipedia.org/wiki/Information_ratio

Defusco, McLeavey, Pinto, Runkle Quantitative Investment Analysis 2nd edition: Wiley

The Beta Continuum–CAIA Chapter 3

Beta is defined as the efficient capture of risk exposures tied to broad asset classes. It represent systematic risk exposure associated with equity markets, bonds, commodities and so forth. Beta is generally speaking the art of passive portfolio management and alpha is the active part. Beta and alpha can be considered as opposites at their highest level. However, both of them exist on a continuum, a linear line where beta is at one end and alpha is at the other end with no clear point where beta turns to alpha or alpha turns to beta. Along the line of beta, the beta continuum the following beta classes are described in the CAIA Level I book:

• Classic Beta
• Bespoke Beta
• Alternative Beta
• Fundamental Beta
• Cheap Beta
• Active Beta
• Bulk Beta

Classic Beta

Classic beta is typically defined with reference to a broad stock market index such as the S&P 500, Russell 1000, FTSE 100 or Nikkei 225. All these indexes are designed to passively track the systematic risk associated with investing in the equity markets. Classic beta, and other types of beta, are linear in their performance compared to a benchmark such as the indexed mentioned. In classic beta this linear performance is a function or perfect correlation between the investment product and the index it tracks.

Bespoke Beta

Bespoke beta describes the method in which asset managers capture local risk premiums. Exchange trades funds are the best example of bespoke beta. ETFs divide up the broad markets into submarkets, sectors, industries and other localized risk exposures. ETF (and Bespoke) is “a local beta” the local systematic risk associated with a smaller, local part of the market. Investors may seek bespoke beta for several reasons, as a cheap and efficient way to make sector, style, size, country and other bets. Investors without knowledge in individual securities may have some knowledge in fundamentals that may impact certain sectors. ETFs which are passive products can be used in an active fashion due to that they trade on an exchange, can be traded throughout the day and can be sold short.

Alternative Beta

Currency exposure has generally been considered a by-product of international economic exposure. Currency risk is often hedged out of institutional portfolios to provide a return which is consistent with the returns earned from assets in the investor’s home currency. Alternative Beta can be accessed through ETFs. Take for example a Euro-Dollar ETF. This ETF captures captures, in a targeted manner, the systematic risk exposure associated with the variation of the U.S. dollar vis-a-vis other currencies.

Fundamental Beta

Fundamental Beta is connected to fundamental indexation. The thesis of fundamental indexation is that capitalization-weighted stock indexes have an inherent inefficiency because they force index providers to purchase more stocks that have higher weighting in the index and to buy less of stocks that have a lower weighting in the index. This can produce a systematic bias of “buying high and selling low” in the returns associated with the cap-weighted index. Cap-weighted indexes also produce a large-cap bias by the very nature of the index construction. Research of Arnott, Hsu, and Moore spurred the classification of Fundamental Beta. They devised a stock index based on the fundamental factors: book value, dividend pay-out, sales revenue, operating income and employees. Fundamental beta comes from the design of an index itself, while active beta is a way to outperform and existing index.

Cheap Beta

Beta can be embedded as a complex basket of or risk premium capture such as index funds or ETFs. Convertible bonds, a mix of debt and equity, is a hybrid mix that makes their intrinsic risk exposure less transparent. A convertible bond has five systematic risk factors that can influence its value: interest rate risk, stock market risk, credit risk, volatility risk, autocorrelation risk. Convertible arbitrage traders carve up a convertible bond into its systematic risk components; they keep those beta pieces that are priced cheaply and hedge out (sell) those beta components that are overpriced.

Active Beta

Active Beta constitutes the world of products that use quantitative tools and models to capture so-called systematic irregularities. in the equity markets. The most popular of these products are are known as 130/30 funds. These are equity based products that can short up to 30% of net assets of the fund while simultaneously leveraging the long portion up to 130% of the net asset value. These 130/30 funds can increase the active risk versus active return trade-off along two dimensions. The number of active bets can be increased and relaxing the long only constraint allows greater opportunity to act on larger overweight’s and under underweights. 120/20, 150/50 etc funds also exist. A more appropriate name for products of this type is beta one products. The term beta one as the systematic risk of a portfolio can be tuned to equal the systematic risk of a benchmark but with greater active active security selection compared to the benchmark. Active beta and beta one products can also be called enhanced index funds. Another form of active beta is tactical asset allocation (TAA). TAA is the process by which systematic risk premiums are overweighed or underweighted depending on macroeconomic conditions.

Bulk Beta

Traditional active products are judged relative to a benchmark. This means that these products combine a blend of beta (systematic market risk) with alpha (excess return). Bulk beta products contain a considerable amount of systematic risk in their returns, but with the trade-off is that there is a large capacity for assets under management. Bulk beta products produce a linear relationship with their benchmark. However, the linearity has a lower correlation to the benchmark compared to other types of beta such as classic, bespoke and alternative beta.

Studying for the CAIA Level I Exam

I’ve started my studies for the Level I CAIA Exam (Chartered Alternative Investment Analyst) which I hope to take in September 20111 and will post a series of blog post from my readings in the study material and elsewhere on the topic.