A thread on an interesting report by Goldman Sachs' Peter Oppenheimer, the bank's chief global equity strategist. He points out that Goldman's "Bear Market Risk Indicator" is looking ominous.

There are three factors that suggest that the recent stability could evaporate and that equities are "about to enter a sustained bear market", Oppenheimer says.
First is the fact that growth, inflation and interest rate outlook is unfriendly for equities.
Second is that greater volatility, such as multiple corrections and new peaks (which we've seen in 2018) tend to presage a full bear market.
Here is Goldman's data showing how falls and bounces tend to come ahead of "the dramatic final fall".
Oppenheimer: "The risk, therefore, is that from these levels the market enjoys a short-term rally but this becomes a signal to sell rather than buy the market."
Oppenheimer's third reason to worry is Goldman's own bear market risk indicator (made from a mix of jobs data, inflation, yield curve and valuations). When it rises above 60% it has historically been a good time to turn cautious, and its currently at 73%.
However, on balance Goldman's Oppenheimer says a prolonged period of more subdued returns is more likely than an outright crash, mostly because valuations are now actually pretty modest after October's slump.
Goldman also reckons growth will slow but stay positive, points out the multi-decade trend towards less economic volatility. and doesn't see any major financial imbalances.
Against that, Goldman can see three causes for concern. 1. A lack of fiscal and monetary policy flexibility in the US, with budget deficit ballooning and interest rates still low compared to history.
Secondly, (and a subject dear to my heart), the seismic shift towards more machine-driven markets, which seems to have lifted the volatility of market volatility, even as economic volatility has drooped lower.
Thirdly, Oppenheimer highlights concentrated flows, ETF explosion, positioning and crowding, which could lead to more exaggerated market moves in a downturn.
The report ends by examining the anatomy of different types of bear markets, categorizing them into the classic cyclical downturn, event-driven ones triggered by an external shock, and structural ones, driven by financial bubbles and imbalances.
Here is a list of every US bear market since the 1800s, categorised according to type, and with how long they lasted and how long the recovery took.
FIN.

More from Economy

One of the hardest problems post-pandemic will be how to revive so-called "left behind" places.

Post-industrial towns, run-down suburbs, coastal communities - these places were already struggling before the crisis and have fared worst in the last year.

What should we do?

Today, @ukonward sets out the beginning of a plan to repair our social fabric. It follows our extensive research over the last year, expertly chaired by @jamesosh, and funded by @jrf_uk, @Shelter and @peoplesbiz.

https://t.co/d3T5uPwG9N


Before I get into recommendations, some findings from previous Onward research.

In 2018, we found 71% of people believe "community has declined in my lifetime"

In 2019, we found 65% would rather live in “a society that focuses on giving people more security” vs 35% for freedom


This was the basis for our identification of 'Workington Man' as the archetypal swing voter in 2019, and led us to predict (correctly) that large numbers of Red Wall seats could fall. A key driver was a desire for security, belonging and pride in place.


There is also a key regional dimension to this. We also tested people's affinity with the UK's direction of travel, across both cultural and economic dimensions - revealing the extraordinary spread below: London vs. the Rest.
https://t.co/HrorW4xaLp
1/ Trend Factor: Any Economic Gains from Using Information over Investment Horizons? (Han, Zhou, Zhu)

"A trend factor using multiple time lengths outperforms ST reversal, momentum, and LT reversal, which are based on the three price trends separately."

https://t.co/udkvsdw2Lz


2/ This resembles combining multiple measures of ST reversal, momentum, and LT reversal (forecasts determined by walking forward rather than using signs from the full sample).

Unlike normal moving average signals, these are *cross-sectional.* More below:
https://t.co/wkIFLg9jtK


3/ Unsurprisingly, the Trend factor formed by this approach outperforms benchmarks in terms of both Sharpe ratio and tail metrics. It's combining momentum with two factors that are negatively correlated to it AND using multiple specifications.

More here:
https://t.co/x8Tloz3iyL


4/ "Average return and volatility of the trend factor are both higher in recession periods. However, the Sharpe ratio is virtually the same.

"Interestingly, all of the factors still have positive average returns.

"Momentum experiences the greatest increase in volatility."


5/ "In terms of maximum drawdown and the Calmar ratio, the trend factor performs the best.

"The trend factor is correlated with the short-term reversal factor (35%), long-term reversal factor (14%), and the market (20%) but is virtually uncorrelated with the momentum factor."

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