Retail investor beliefs

August 3, 2019

Survey evidence suggests that retail investors adjust positions rather sluggishly to changing beliefs and the beliefs themselves contradict classic rationality. Sluggishness arises from two features. First, the sensitivity of portfolio choices to beliefs is small. Second, the timing of trades does not depend much on belief changes. Contradictions to classic rationality arise because different investors cling stubbornly to different beliefs with little convergence. Also, retail investors associate higher returns with higher economic growth expectations and lower returns with fears of large drawdowns (contradicting the notion of tail risk premia). Overall this suggests that retail investors feel better informed than the market, with no need for updating their beliefs quickly and thoroughly. Opportunities for professional macro trading may arise through front running retail flows and applying more consistent rationality.

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Why herding is the death of momentum

February 2, 2019

Momentum trading, buying winning assets and selling losing assets, is a most popular trading strategy. It relies on sluggish market adjustment, allowing the trader to follow best-informed investors before the more inert part of the market does. Herding simply means that market participants imitate each others’ actions. Herding accelerates and potentially exaggerates market adjustments. The more quickly the herd moves, the harder it becomes to follow informed leaders profitably. In a large agile herd, sluggish adjustment gives way to frequent overreaction. Momentum strategies fail. This suggests that popularity and commoditization of momentum strategies (and trend-following) are ultimately self-defying. Conditioning momentum strategies on the estimated degree of herding should produce superior investment returns.

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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…)

Basic theory of momentum strategies

January 27, 2018

Systematic momentum trading is a major alternative risk premium strategy across asset classes. Time series momentum motivates trend following; cross section momentum gives rise to ‘winners-minus-losers strategies’. Trend following is a market directional strategy that promises ‘convex beta’ and ‘good diversification’ for outright long and carry portfolios as it normally performs well in protracted good and bad times alike. It works best if the underlying assets earn high absolute (positive or negative) Sharpe ratios and display low correlation. By contrast, cross section momentum strategies benefit from high absolute correlation of underlying contracts and are more suitable for trading assets of a homogeneous class. The main pitfalls of both momentum strategies are jump events and high costs of ‘gamma trading’ conjoined with high leverage.

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Credit market herding and price distortions

December 10, 2016

Corporate credit markets have historically been especially prone to herding. The main drivers of herding have been past returns, rating changes and liquidity. Sell herding has been particularly strong and flows have been disproportionate after very large price moves. Herding can be persistent and lead to significant price distortions. Non-fundamental price overshooting is a valid basis for profitable contrarian trading strategies.

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Mutual fund flows and fire sale risk

September 10, 2016

A new empirical paper looks at the drivers of U.S. mutual funds flows across asset classes. An important finding is that changes of monetary policy expectations towards tightening trigger net outflows from bond funds and net inflows into equity funds. Typically, the costs of redemptions are borne by investors that do not redeem or redeem late. This creates incentives for fire sales and causes of price distortions, particularly if the outlook for monetary policy is revised significantly.

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The 1×1 of trend-following

July 2, 2016

Trend-following is the dominant alternative investment strategy. Its historical return profile has been attractive on its own and for diversification purposes. It is suitable for rising and falling prices, albeit not for range-bound and “gapping” markets. A basic trend-following algorithm is easy to build. Trend-following commands over USD300 billion in dedicated assets and a lot more are managed by informal trend-followers. The style is itself a major force of price trends, with no direct ties to fundamental asset value.

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How poor liquidity creates rational price distortions

June 4, 2016

When OTC markets become illiquid and dealers fail to buffer flows, institutional investors effectively face each other directly in the market. They can observe each other’s actions and position changes. For example, if large investors make offers to sell under illiquidity, the market expects to become “over-positioned” and will avoid bids at a fair price or even put in offers. In equilibrium investors transact at prices below true value and exacerbate initial negative shocks.

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Pension funds and herding

April 2, 2016

Pension funds have three types of motivations for herding: rebalancing rules, the effects of regulatory changes and peer pressure of senior executives. A new empirical study detects all of these in the trading flows of the large Dutch pension funds. These flows offer opportunities for contrarian traders that provide liquidity to the “herd”.

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Rational informational herding

February 27, 2016

It can be rational for traders to buy with rising prices and sell with falling prices. In particular, this should be the case if traders possess private information suggesting that “something big” is coming and that prices may move significantly, even if direction is not certain (e.g. “make-or-break” situations). Experiments confirm such rational informational herding.

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asset management Asset Purchase Program banks bond returns bond yields bubbles capital regulation central counterparty clearing China collateral commodities credit returns default ECB economic data EM equity returns euro area crisis Fed financial crisis FX FX interventions FX returns government debt government deficits herding inflation information insurances Japan leverage liquidity machine learning market turmoil price factors regulation risk management shadow banking statistical methods term structure trend following variance risk premium VIX volatility ZLB
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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 over eighteen years. 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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