Alternative Beta Replication

The new investment paradigm


Net returns to investors can be improved by separating market-driven beta returns and skill-based alpha returns, and providing them individually, at competitive fees. The alternative beta replication strategy takes beta exposures directly through exchange-traded instruments, thereby offering weekly unrestricted liquidity and full transparency, and avoiding hedge fund specific and operational risks (of the LTCM and Amaranth type).

Quest for beta replication

Academic research has shown that only a small and diminishing portion of hedge fund returns is derived from alpha return sources, and that the majority (over 80%) is attributed to market-driven beta returns. Both diminishing alpha and high ‘one size fits all’ hedge fund fee structure-5% to 7% per annum-results in low net returns to investors.

In addition, hedge fund investors are restricted by lock-ups, gates and poor transparency, and carry hedge fund specific risks. Beta replication gives a new opportunity to reduce risks, restrictions, and fees, and thus improves net returns, liquidity and transparency. At the same time it provides an economically meaningful way to define and measure beta and alpha returns.

Components of hedge fund returns

Beta replication is based on the idea that hedge fund returns can be broken down into different return components: alpha returns, linear and non-linear beta returns, and fund-specific returns.

Beta returns arise from factors driven by systematic market risks, and they are deemed to be ‘good risks’ as they carry a premium. Beta measures the sensitivity of hedge fund return with respect to a given risk factor and indicates how much factor risk the portfolio is exposed. Beyond traditional factors like the stock or bond market there are many other factors, commonly referred to as ‘alternative’ or ‘exotic’ factors.

The most common alternative beta factors are credit spreads, yield curve slope and shape, interest rate differentials, emerging markets, volatility, and volatility of volatility, exposure to small versus large capitalisation equities, and the more exotic beta factors include complexity, hedging and liquidity risks, and related premia. In general systematic risk factors can be passive like a broad stock market index or evolving over time as is the case with the shape of the yield curve.

Many alternative beta factor returns are non-linear because hedge fund managers pursue dynamic trading strategies and hold positions that have option-like payoffs. For example, return to merger arbitrage strategy behaves in a different way in up and down markets. To some extent it can be characterised as a financing position and short put position in the stock market. Thus the return to merger arbitrage strategy not only depends on the overall stock market performance but also on the markets direction and volatility conditions in a non-linear way.

Alpha returns are uncorrelated with beta returns and they are based on managers’ special skills and expertise to benefit from non-systematic opportunities in the market. The fact that these returns cannot be modelled and captured by market-driven beta returns make them also very valuable and sought-after as they are complementary to the systematic returns. Alpha returns are well suited as return enhancers and diversifiers in an investment portfolio.

Implementation of alternative beta replication strategy

Beta replication models are based on academic studies, notably those by professors Bill Fung, David Hsieh and Narayan Naik, who have written seminal research in this field. The studies were not written with beta replication in mind, but to better understand where the hedge fund returns come from. Their ‘factor-based approach’ forms the foundation for beta replication applications. Blue White Alternative Investments has developed its alternative beta strategy jointly with Fung, Hsieh and Naik. The strategy is built on their ‘factor-based approach’ and it includes the latest research and knowledge, some of it yet unpublished. The state-of-the-art beta replication model incorporates linear and non-linear return components.

It is stressed that the identification of the factors was conducted ex-ante and without data mining, and all performance tests have been computed out-of-sample. The approach is transparent and based on financial economic modelling published in numerous academic articles.

Last spring, Blue White Alternative Investments launched an EC on-shore fund that follows the strategy. At the same time, a number of investment banks launched their versions of beta-tracking funds and indices, all of them based on different and somewhat opaque and ‘proprietary’ methods.

The Blue White Alternative Beta strategy combines a wide range of trading strategies and systematic beta exposures to global equities, small versus large capitalisation equities, yield curve, credit, emerging markets, currency and commodity markets into one single fund.

The positions are complemented by a series of lookback straddles that pick up non-linear returns and momentum, and provide mitigation of possible drawdowns in adverse market conditions. All investments are made in liquid exchange-traded instruments only and, therefore, the strategy is very liquid and scaleable, and avoids hedge fund specific (Amaranth and LTCM type) and most of the operational risks.

Target and performance of Blue White Alternative Beta strategy

The objective of the Blue White Alternative Beta strategy is to track the systematic factor exposures of ‘smart money’ managers and aggregate them into a single liquid and transparent portfolio. ‘Smart money’ managers are carefully screened from the set of several thousand funds, monitored on a regular basis, and reviewed periodically. The choice of the target funds critically influences the quality and characteristics of the fund returns.

In our opinion, tracking an investable index does not serve the purpose because investors can directly invest in an investable index, and we do not see a reason in tracking ‘average’ funds or non-investable funds either because they include all ‘good, bad and ugly’ and dead funds.

Blue White Alternative Beta strategy is ‘absolute return seeking’ wherethe return target is 9% to 11% per annum net-of-fees with a monthly return volatility of 6% (annualised). Alternatively, it can be viewed as a ‘LIBOR-product’, with a return target of LIBOR (or EURIBOR) plus 4% to 6% per annum.

The strategy has no other benchmark. Although the recently published JPMorgan Alternative Beta Research index is based on comparable modelling, it is not investable and is based on a different implementation tracking a different target.

Since the objective of the Blue White Alternative Beta strategy is to track a carefully chosen target portfolio reflecting the systematic exposures of the smart money managers, the strategy does not take directional views or make discretionary positioning decisions other than those dictated by the volatility constraints and some risk management considerations in extreme stress scenarios. To manage the tail risk, the strategy employs a number of positively convex lookback straddles. It is stressed that the strategy does not (i) take short straddle positions, (ii) write options, or (iii) try to capture, bear and sell tail risk and then show the resulting premium as returns to the investors .

Figure 1 shows the performance of the actual Blue White Alternative Beta strategy and its target against indices constructed by Hedge Fund Research. The tracking performance of Blue White Alternative Beta strategy is based on an out-of-sample simulation conducted by our academic advisers.

The Blue White Alternative Investments started trading the strategy on 7 May 2007, and within two months, the strategy went through the most severe stress test when the global markets were hit by a major turbulence created by the spill-over from the sub-prime credit markets, followed by a severe liquidity and confidence crisis, and flight to quality. During the market turbulence the Blue White Alternative Beta strategy kept its posture and fared very well against investable hedge fund indices (HFRX Global Hedge and Equally-Weighted), as well as the JPMorgan Alternative Beta Research index.

As it can be seen in Figure 2, when compared with other alternative beta strategies provided by Goldman Sachs, Deutsche Bank, and Merrill Lynch, and investable HFRX indices the Blue White Alternative Beta strategy performed much better during the market turbulence.

The main reasons behind the Blue White Alternative Beta strategy’s good performance during the market turbulence are that (i) the lookback straddles that cover many markets mitigated the tail risk during the turbulent times, and (ii) the strategy’s return volatility was managed and kept below 6%.

Table 1 shows annualised volatilities of alternative beta strategies and hedge fund indices. It is interesting to note that both the DB Absolute Return Beta Index and the Goldman Sachs Absolute Return Tracker have very high, almost equity-like volatilities, 12.67% and 10.65%, respectively, whereas the Blue White Alternative Beta strategy and Merrill Lynch Factor Index both have a low bond-like volatility, 5.57% and 5.49%, respectively.

We would like to stress the point that the level of volatility is linked to the downside risk in the strategy. Figure 3 shows the actual drawdowns during turbulent periods in the summer of 2007. The performance of alternative beta trackers and hedge funds share similar features, however, there are some notable differences. For example, the downside risk of the Blue White Alternative Beta strategy has been close to zero, whereas others share more similar downside risk, but at different magnitudes. Figure 3 implies that perhaps the alternative beta trackers are exposed to a different amount of risk.

Many players – the secret is in the mix

To gauge differences in the factor exposures of alternative beta funds and hedge fund indices during the turbulent period in July and August 2007, we estimated a multivariate regression with tracker strategy returns as the dependent variable and common risk factors as the independent variables. The results of the following regression equation are given in Table 2.

Table 2 indicates that during the turbulent period, alternative beta trackers shared many similar features but, at the same time, they were also very different. Interestingly, alternative beta trackers as well as the HFRX Global Hedge index, all had a positive beta on emerging markets, but exhibited differences in other aspects. Furthermore, all trackers except Blue White Alternative Beta strategy had a positive credit beta and this long credit position resulted in losses for the others when the credit spreads exploded due to the sub-prime contagion and resulting credit tightening.

With respect to equity, credit, currency and emerging market factors, Merrill Lynch Factor Index and Deutsche Bank Absolute Return Beta Index had similar and significant beta sensitivities to HFRX Global Hedge index. This raises the possibility that these two indices, and possibly Goldman Sachs Absolute Return Tracker, could be statistically tracking the HFRX Global Hedge index, both Deutsche Bank Absolute Return Beta index and Goldman Sachs Absolute Return Tracker in a leveraged form.

With respect to the non-linear return factors, the Blue White Alternative Beta strategy differs even more strikingly from other alternative beta strategies. Among the current investable beta trackers and indices, as far as the authors know, only Blue White Alternative Beta strategy employs positively convex lookback straddles as non-linear factors and tail risk mitigation vehicles. As the lookback straddles are a key component in explaining the major differences in the recent performances and risk, the next section explains how they work in mitigating downside risks.

Lookback straddles mitigate downside risk

One main reason behind the superior performance of the Blue White Alternative Beta strategy during the market turbulence in July and August 2007 is the fact that the Blue White Alternative Beta strategy included a number of lookback straddle positions. These straddles changed the characteristics of the Blue White Alternative Beta strategy return distribution in following ways: (i) long straddle positions introduced long volatility sensitivity (positive convexity) to the portfolio, (ii) the lookback feature ensured that if there was a momentum in the underlying security valuation, it was picked up, and (iii) they captured non-linear beta returns.

There are two distinct features in the lookback straddle: the long volatility option position and the path dependent lookback feature. Long positions in straddles are constructed from long positions exchange-traded put and call options. Long ordinary straddle position benefits from increases in volatility. As the implied volatility increases during financial crisis the value of the straddle increases and it thus provides a partial hedge against bad news.

A lookback straddle is constructed from ordinary straddles by dynamically managing and resetting the long call and put option positions. Periodically we roll over the lookback straddle position and at the rollover the payoff of the position is approximately the maximum underlying range over the bespoke period. It follows from this that during very turbulent market conditions, like in July – August 2007 (see Figure 3), a lookback straddle provides a payoff which is larger thanthe payoff from an ordinary straddle. Lookback straddle benefits more from market volatility than plain vanilla straddle. For example, during the Russia crisis and LTCM liquidity squeeze period of May to October 1998, the lookback straddles contributed 3.1% to the strategy return, resulting in a positive performance of 2.7% for the said period.

Copernican crossroad

The new investment paradigm is about separation of alpha and beta returns, fees and liquidity. A Copernican Crossroad of investing has been passed and informed investors have moved on from the old ways of bundled returns with low liquidity, long redemption notices, gates and lock-ups, and sky high alpha-type fee structures for all types of returns, including the majority returns – the systematic beta returns.

By paying higher alpha level fees for alpha returns only, and much lower fees for all beta returns, investors can significantly improve their net returns.

Jaakko P. Karki, PhD, CAIA is CEO and Founding Partner and Tapio Pekkala, PhD, MBA is Investment Manager of Blue White Alternative Investments Ltd.