Currency Investment Insights Alternative Risk Premia Benchmarks July 6 2020 Bloomberg Systematic Strategies a Bloomberg Professional Service Offering
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Bloomberg Systematic Strategies A Bloomberg Professional Service offering Currency investment insights Alternative risk premia benchmarks July 6 2020 Bloomberg Systematic Strategies A Bloomberg Professional Service offering Currency investment insights Alternative risk premia benchmarks For decades, the currency markets have been the first port of call for discretionary Kartik Ghia, PhD investors looking to express macroeconomic views. In more recent years, this has +1 212 617 5649 been accompanied by a plethora of quantitative investment strategies aimed at [email protected] providing access to alternative risk premia factors in the currency markets. Despite increasingly widespread use within systematic investment portfolios, the lack of Michael K. Donat, CFA established benchmarks even for the most popular investment styles—carry, value +1 212 617 5509 and trend—has made performance comparisons difficult. This has often led to a wide [email protected] range of conclusions about long run performance. Zarvan Khambatta, CFA, CAIA In this publication, we establish tradable benchmarks for three alternative factors— +1 212 617 5418 carry, value, and trend. We highlight the properties of the individual styles, the [email protected] implications for portfolio construction and propose rules-based, transparent implementations. The resulting benchmarks can either be used to replicate factor returns in the currency markets or as a tool to measure the performance of existing portfolios. The intention is to provide a common frame of reference around which asset owners and managers can base performance expectations. Our discussion includes: Examining the performance characteristics of the carry trade Investigating the value factor and propose a transparent, rules-based strategy using a measure of purchasing power parity (PPP) Assessing the role of signals and portfolio construction in developing a transparent trend following benchmark Performance attribution and case studies for three investment styles Proposing a multi-factor currency benchmark using a risk-based approach Figure 1: Diversified profiles: carry, value and trend Source: Bloomberg Bloomberg Systematic Strategies A Bloomberg Professional Service offering Introduction Systematic investment strategies have long been a staple of currency investors. Viewed as a relatively inexpensive way to express macroeconomic views, the most popular styles are carry, value, and trend following. Each provides exposure to an identifiable risk factor in exchange for a long-run positive expected return. Differences in the drivers of returns translate to distinct returns profiles—which can potentially be combined to develop robust return-seeking portfolios. Alternative beta strategies have four important elements: (1) universe selection and the choice of instrument, (2) signal and ranking methodology, (3) constituent weighting and (4) rebalancing frequency. As we see in later sections, currency strategies have one additional feature—exposure to the US dollar. Despite the existence of multiple parameters that promote a plethora of implementations, the relative similarity in signals across each implementation within a style, permits the identification of broad benchmarks for carry, value, and trend following in currencies. There is a significant amount of academic and practitioner literature discussing these styles—both the drivers of returns and the various considerations surrounding implementation. Our prior publications on the subject are listed in the bibliography. In later sections, we simply refer to these findings where appropriate. In the initial sections, we describe an example of a transparent, robust implementation for each investment style. The implementations discussed are intended to be accessible to a wide audience. To promote the flexible use of the benchmarks the construction process is modular and facilitates customization to specific requirements. The four main considerations are: 1. Transparency of methodology and data 2. Understanding whether a common consensus exists (using published literature and invested funds) 3. Implementation feasibility 4. Ability to isolate exposure to the style (‘purity’) After the individual index style construction and design has been laid out, the latter sections of this publication will discuss a multi-style benchmark. There are two main use cases for these style benchmarks; the first in a primary role as a return generator and the second in an ancillary capacity as a return enhancer/risk reducer. These can be summarized as (1) a source of investment return which is typically part of a macro portfolio and (2) an excess return overlay in conjunction with an international asset portfolio/cash flows. This is typically used by asset managers and/or the treasury department of a corporation to enhance risk-adjusted returns by systematically managing underlying currency exposures. The style benchmarks discussed here are intended to highlight longer term performance characteristics and illustrates portfolio use-cases. The aim is to construct an investible factor-based framework to provide investors with the ability to customize these benchmarks and address individual requirements. Data The currency universe for the style benchmarks is comprised of 24 indices within the Bloomberg FX Forward Index Family. The indices span developed and emerging markets Bloomberg Systematic Strategies A Bloomberg Professional Service offering and represent the excess return of holding and rolling a 1-month currency forward contract against the U.S. dollar. The pricing source for the spot and forward rates used to construct these indices is Bloomberg FX Fixing (BFIX). For liquidity purposes, trades are via the US dollar pairs—even for (non-US dollar) crosses. By region, the currency indices cover: Asia Pacific: AUD*, IDR, INR, JPY*, KRW, NZD*, PHP, SGD, and TWD EMEA: CHF*, CZK, EUR*, GBP*, HUF, ILS, NOK*, PLN, RUB, SEK*, TRY, and ZAR Americas: BRL, CAD*, and MXN The asterisk (*) denotes a currency classified as a developed market (or G10) currency. For more information about this family of indices please refer to the Bloomberg FX Forward Index Family, July 2019. The inception date is January 1999 with the exception of selected emerging market (EM) currencies which start at later dates depending on data availability. For the carry strategy, we need a measure for the US funding rate. In-line with general industry practice, we use the US 1-month LIBOR. OIS rates can be used instead of LIBOR with minimal change in stated results. Given the transparency in methodology and public availability, we use PPP data from the Organization for Economic Cooperation and Development (OECD) to calculate the signal for the value strategy. The data is published with periodic revisions. Due to circumstances, our data collected prior to 2018 includes revisions. The data following this date are point-in-time. We address the impact of this in the value investing section. The carry trade The currency carry trade is defined as investing in a high yielding currency and funding in a (relatively) lower yielding currency. The profile of the risk premium is steady, incremental gains during periods of low-to-medium market volatility interspersed with sudden, large drawdowns when investor sentiment turns bearish. The compensation for this ‘crash risk’—manifested by a strong negative skewness in returns—is a positive long run expected return. The returns profile can be compared to an insurance underwriter who earns a steady income through premium but must pay-out sporadically when specified events occur. For an extended discussion on the drivers of returns and the different variations in the strategy, refer to The G10 FX carry premium, November 2010, Bloomberg LP and Deconstructing currency carry, January 2019, Bloomberg LP. The G10-EM currency classification is both a manifestation of structural differences between economic regimes and an artifact of tradition. The broad economic classification is based on aspects such as whether the currency is actively managed, the existence of capital controls, the state of economic development, and the independence of fiscal and monetary institutions. (See The EM FX Carry Premium, September 2010, Bloomberg LP). At the same time, the steady institutional developments within emerging markets has muddied the traditional distinctions between the two groups—leaving some room for discretion. For the purposes of our carry benchmark, we maintain the distinction between the two groups since many institutions still segment portfolios by traditional definitions. The currency carry benchmark comprises of a weighted average of the G10 and EM carry benchmarks. The standalone G10 and EM-only carry portfolios are combined to create Bloomberg Systematic Strategies A Bloomberg Professional Service offering the final (composite) portfolio; which contains an equal number of offsetting G10 and EM currencies in the funding and investment legs. Over extended periods, relative to this carry portfolio (which enforces separation between G10 and EM currencies), a portfolio using a combined universe will tend to overweight the number of G10 and EM currencies in the funding and investment legs respectively.1 In turn, this translates into higher sensitivity (for the combined universe portfolio) to global ‘risk-on/off’ sentiment. Signal Currency carry strategies have signals with varying degrees of complexity. These range from the magnitude of pairwise interest rate differentials