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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How market liquidity causes price distortions

December 28, 2019

Liquidity is a critical force behind market price distortions (and related trading opportunities). First, the cost of trading in and out of a contract gives rise to a liquidity premium. Second, the risk that transaction costs will rise when market conditions necessitate trading commands a separate liquidity risk premium. Third, actual changes in liquidity can precipitate large price changes without any fundamental value consideration. Finally, low liquidity is conducive to ‘run equilibria`, where bids or offers of some institutional investors turn into pricing signals for others, giving rise to self-reinforcing dynamics with feedback loops and margin calls. Examples for liquidity-driven price distortions in the past include breakdowns of covered interest parity across currencies, bond market ‘tantrums’, and ‘fire sales’ in emerging local-currency 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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Rebalancing and market price distortions

December 14, 2019

Price distortions are an important source of short-term trading profits, particularly in turbulent markets. Here price distortions mean apparent price-value gaps that arise from large inefficient flows. An inefficient flow is a transaction that is not motivated by rational risk-return optimization. One source of such inefficient flows is ‘rebalancing’, large-scale institutional transactions that align allocation with fixed targets. Rebalancing flows are detectable or even predictable if one understands their rules. Their motives include benchmarking of portfolios, benchmark changes, regulatory changes, ETF designs, equity parity, capital protection, and – to some extent – high-frequency trading algorithms.

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Equity return anomalies and their causes

December 7, 2019

The vast range of academically researched equity return anomalies can be condensed into five categories: [1] return momentum, [2] outperformance of high valuation, [3] underperformance of high investment growth, [4] outperformance of high profitability, and [5] outperformance of stocks subject to trading frictions. A new empirical analysis suggests that these return anomalies are related to market inefficiencies, such as investor protection, limits-to-arbitrage, and investor irrationality. In particular, the analysis provides evidence that the valuation return anomaly is largely driven by mispricing.

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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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Bad and good beta in FX strategies

June 29, 2019

Bad beta means market exposure that is expensive to hedge. Good beta is market exposure that is cheap to hedge. Distinguishing between these is crucial for FX trading strategies. The market sensitivity of FX positions can be decomposed into a risk premium beta (‘bad beta’) and a real rate beta (‘good beta’). FX positions with risk premium betas are associated with a positive price of risk that increases in crisis periods. FX positions with real rate beta are hedges, whose value increases in crisis times. Many conventional currency trading strategies carry either excessive ‘bad beta’ or too little ‘good beta’ and, thus, fail to produce true investor value.

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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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Beta herding

September 1, 2018

Beta herding means convergence of market betas of individual stocks that arises from investors’ biased perceptions. Adverse beta herding denotes the dispersion of such betas that arises from a reversal of the bias. A new paper suggests that overconfidence in predictions of overall market direction and positive sentiment are key drivers of beta convergence, while uncertainty and negative sentiment are conducive to beta dispersion. Knowing which trends prevail helps macro trading. First, beta herding implies that directional market moves create price distortions (as the bad rise and fall with the good). Second, adverse beta herding causes low-beta stock returns to outperform high-beta stock returns on a risk-adjusted basis. This reinforces and qualifies what is commonly known as the “low beta bias” of equity returns. (more…)

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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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