The basics of low-risk strategies

March 28, 2020

Low-risk investment strategies prefer leveraged low-risk assets over high-risk assets. The measure of risk can be based on price statistics, such as volatility and market correlation, or fundamental features. The rationale for low-risk strategies is that leverage is not available for all investors (but required to increase the weight of low-risk longs) and that many investors pay over the odds for assets with lottery-like upwardly skewed return expectations. Popular versions of this strategy principle include “betting against beta”, “betting against correlation”, “stable minus risky” or “quality minus junk”. Empirical research suggests that low-risk strategies have delivered significant risk-adjusted returns for nearly a century and that this performance has not deteriorated over time.

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The q-factor model for equity returns

January 25, 2020

Investment-based capital asset pricing looks at equity returns from the angle of issuers, rather than investors. It is based on the cost of capital and the net present value rule of corporate finance. The q-factor model is an implementation of investment capital asset pricing that explains many empirical features of relative equity returns. In particular, the model proposes that the following factors support outperformance of stocks: low investment, high profitability, high expected growth, low valuation ratios, low long-term prior returns, and positive momentum. According to its proponents, the investment CAPM and q-factor model complement the classical consumption-based CAPM and explain why many so-called ‘anomalies’ are actually consistent with efficient markets.

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The price effects of order flow

December 20, 2019

Order flow means buyer- or seller-initiated transactions at electronic exchanges. Order flow consumes liquidity provided by market makers and drives a wedge between transacted market price and equilibrium price, even if the flow is based on information advantage. Flow distorts market prices for two reasons. First, the need for imminent transaction carries a convenience charge. Second, the prevalence of informed flow justifies a charge for market risk on the part of the market maker. Standard models suggest that the price impact is increasing in the square root of the order flow, i.e. increases with the order size, but not linearly so. New theoretical work suggests that the price impact function may be “S-shaped”, i.e. increases more than proportionately in the smaller size range and less than proportionately for large sizes. The price effects of order flow are relevant for the design of algorithmic trading strategies, both as signal and execution parameter.

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Dealer capital ratios and FX carry returns

November 9, 2019

When financial market intermediaries warehouse net risk positions of other market participants the marginal value of their capital should affect the expected and actual returns of such positions. This is of particular importance in the FX market, where excess positions typically end up on the balance sheets of a small group of international banks. Empirical evidence confirms that currency returns have been related to the dynamics of capital ratios of the largest dealers. Excess returns on FX carry trades can, to some extent, be interpreted as compensation for the balance sheet risk. Currencies that trade at a high forward discount have paid off poorly when intermediary capital ratios decreased.

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The low-risk effect: evidence and reason

September 7, 2019

The low-risk effect refers to the empirical finding that within an asset classes higher-beta securities fail to outperform lower-beta securities. As a result, “betting against beta”, i.e. leveraged portfolios of longs in low-risk securities versus shorts in high-risk securities, have been profitable in the past. The empirical evidence for the low-risk effect indeed is reported as strong and consistent across asset classes and time. The effect is explained by structural inefficiencies in financial markets, such as leverage constraints for many investors, focus on the performance of portfolios against benchmarks, institutional incentives to enhance beta and – for some investors – a preference for lottery-like securities with high upside risks.

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The mighty “long-long” trade

July 13, 2019

One of the most successful investment strategies since the turn of the century has been the risk-parity “long-long” of combined equity, credit and duration derivatives. In a simple form this trade takes continuous joint equal mark-to-market exposure in equity or credit and duration risk. A simple passive portfolio in the G3 would have outmatched most macro hedge funds since 2000, with a Sharpe ratio well above one and not a single annual drawdown. There have been three apparent contributors to this success: undiversifiable risk premia, implicit subsidies paid by central banks, and great diversification benefits from negative return correlations. These forces remain largely in place, but setback risks bear careful watching: excessive leverage in duration exposure, exhaustion of downside scope for yields, attempts of monetary policy normalization, and the possibility of a fundamental shift in macroeconomic policy regimes.

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Active fund risk premia in emerging markets

June 22, 2019

Security returns, adjusted for market risk, contain risk premia that compensate for the exposure to active fund risk. The active fund risk premium of a security can be modeled as the product of its beta premium sensitivity and price for exposure to active fund risk. Both components change overtime and mutually reinforce each other in episodes of negative fund returns and asset outflows. This explains why securities with high exposure to active fund risk command high expected returns. Active fund risk premia are particularly prevalent in local EM bond markets, where on average 20% of securities are held by foreign institutional investors, many of which are sensitive to drawdowns. Empirical evidence confirms that bonds whose returns positively correlate with active fund returns command substantial premia. The highest premia and expected returns would be offered at times of large capital outflows.

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The implicit subsidies behind simple trading rules

April 27, 2019

Implicit subsidies are premia paid by large financial markets participants for reasons other than risk-return optimization (view post here). Their estimation requires skill and a strong “quantamental system”. However, implicit subsidies are behind the popularity and temporary success of many simple trading rules, including those based on variance risk premia, contract hedge value, short volatility bias, and “low-risk effects”. The closest link is between implicit subsidies and cross-asset carry. However, carry is not itself a reliable measure of a subsidy but just correlated with it and – at best – a starting point for estimation The distinction between subsidy and conventional carry is essential for actual long-term value generation of related trading strategies.

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Implicit subsidies paid in financial markets: updated primer

April 20, 2019

Implicit subsidies in financial markets are premia paid through transactions that have motives other than conventional risk-return optimization. They manifest as expected returns over and above the risk-free rate and conventional risk premia. Implicit subsidies are a bit like fees for the service of compliant positioning. They are opaque rather than openly declared, typically for political reasons. Implicit subsidies have valid motives, such as financial stabilization objectives of governments, profit hedging of commodity producers, or downside protection of institutional portfolios. Detecting and receiving implicit subsidies is challenging and information-intensive but creates stable risk-adjusted value. Implicit subsidies are receivable in all major markets, albeit often at the peril of crowded positioning and recurrent setbacks. It is critical to distinguish strategies based on implicit subsidies, which actually create investor value through information efficiency and those that simply receive non-directional risk premia, which are based on rough proxies and do not create risk-adjusted value.

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How salience theory explains the mispricing of risk

March 2, 2019

Salience theory suggests that decision makers exaggerate the probability of extreme events if they are aware of their possibility. This gives rise to subjective probability distributions and undermines conventional rationality. In particular, salience theory explains skewness preference, i.e. the overpricing of assets with a positive skew and the under-pricing of contracts with a negative skew. There is ample evidence of skewness preference, most obviously the overpayment for insurance contracts and lottery tickets. In financial markets, growth stocks with positively-skewed expected returns have historically been overpriced relative to value stocks. This is important for macro trading. For example, a specific publicly discussed disaster risk should pay an excessive premium, and short-volatility strategies in times of fear of large drawdowns for the underlying should have positive expected value.

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Macrosynergy is a London based macroeconomic research and technology company whose founders have developed and employed macro quantamental investment strategies in liquid, tradable asset classes, across many markets and for a variety of different factors to generate competitive, uncorrelated investment returns for institutional investors for two decades. Our quantitative-fundamental (quantamental) computing system tracks a broad range of real-time macroeconomic trends in developed and emerging countries, transforming them into macro systematic quantamental investment strategies. In June 2020 Macrosynergy and J.P. Morgan started a collaboration to scale the quantamental system and to popularize tradable economics across financial markets.

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