Financial marketsDiversification as a mechanism of Financial Panics in Africa

Kennnedy MuturiFebruary 1, 202348017 min

Part two of the series titled, “Mechanics of Financial Panics in Africa’s Financial markets

Normally a desirable force that reduces risk concentration, diversification plays an interesting role in panic mechanics, in that it can cause panics in one market to spread to other seemingly unrelated markets. For example, in March and April of 2020, large moves in macro assets such as equities, fixed income, and oil have been followed by large shocks to equity market neutral factors such as low risk, size, and short term reversal.  

What could link equity and oil prices with market neutral style factors? One linkage is that big, diversified players have exposures to many strategies in their books, across the entire smorgasbord of alpha- and beta-generating capabilities. If a big, diversified investor is weakened by performance in one of its books, that can spell trouble for other, unrelated books via two channels: one mechanical and one behavioral.

First, a diversified manager may mechanically unwind one part of their book in connection with funding losses or making “readjustments” in risk exposure across their broader portfolio. For example, a manager may suffer large losses on long oil positions, forcing it to unwind other positions to rebalance its portfolio risk or to strengthen its overall cash position: perhaps the manager unwinds other energy positions that had been expected to hedge the losing oil trade. These adjustments put pressure on other managers that might hold positions in these newly affected markets, even if they had none of the original oil exposure that sparked this sequence of events. Expand this to a larger number of highly diversified portfolios, each with some degree of direct and indirect overlap (and often each employing leverage), and the situation can get quite challenging indeed. 

Unwinds can spread even across asset classes. During the 2007 quant crisis, many speculate that long/short equity books were “raided” for cash in order to fund losses in macro-related books. Throughout March of 2020, we saw losses incurred by managers with exposure to risk assets like equities and energy potentially lead to dramatic moves in fixed income markets. These moves were not simply parallel shifts in the yield curve, but rather consisted of changes in the steepness of the curve, differences in yield changes across typically correlated markets, and even breakdowns of usually stable relationships among Treasuries, bond futures, and interest rate swaps (all theoretically anchored to the same fundamental rates).

An example: in normal times a fixed income future and the cash bond that underlies it are linked very tightly. This is intuitive since one instrument is more or less a derivative placed on the other. However, in stressed times, liquidity becomes paramount, and the cash bond is suddenly an illiquid cash hog relative to the liquid future, and the two instruments are no longer similar along the relevant dimension (liquidity), and thus are effectively not similar at all. The relationship is shattered, and the basis blows out, causing pain that is almost untraceable to its original source (the coronavirus pandemic). 

Performance of style factors** during Financial crisis- March 2020 (MSCI* )

Source: Morgan Stanley Capital Index (MSCI)
*MSCI Africa Frontier Market index

**Cumulative returns of MSCI’s Africa Frontier Market Index Style factors in August 2007 and cumulative returns of Select MSCI’s Africa Frontier Market Index Style factors in March 2020. For a given factor, for each day T of the month we compute the arithmetic sum of its daily returns since the start of the month. We then divide this sum by the expected standard deviation of this sum which we approximate by root(T) x stdev where stdev is the daily standard deviation of the factor as reported by MSCI at the beginning of the month.

Why did these typically tight relationships break down? The cash/futures Treasury basis, for example, does not seem at first glance to be fundamentally connected to the coronavirus pandemic. These relationships break down because they are economic relationships tied to fundamentals that hold over the medium to long term, when all players are strong. When weakness emerges in other parts of a diversified book (again due to direct exposure to the pandemic), leverage reduction and liquidity creation are at a premium, and relative differences in those newly relevant attributes (liquidity and leverage as opposed to fundamentals) become pivotal. 

In another recent example, long/short equity portfolios appear to have gone through a significant amount of deleveraging in March of 2020, akin to the “Quant Quake” of August 2007. As mentioned above, one theory underpinning the August 2007 incident was that multi-strategy funds suffering losses in their macro books raised cash by unwinding their equity market neutral books.

Back then, slow-moving, crowded factors, such as value and growth, suffered large drawdowns. This time, faster, traditionally High-Sharpe factors, such as short-term reversal, were hit hardest, with magnitudes equal to or even greater than the worst seen for the slower factors in 2007. Higher-Sharpe factors are typically traded with more leverage, since players are more confident in their performance, and this may have exacerbated the unwind. 

In both 2007 and 2020, performance had mostly recovered by the end of the month in which the drawdowns occurred, but of course this was little consolation for those that unwound and weren’t able to participate in the recovery. Pundits will surely debate the catalyst for liquidations in March 2020, but it would not be surprising to see, once again, how diversification may have contributed to cascading unwinds.  

Preparing to panic

The second channel through which diversification transmits panic is more behavioral than mechanical. If a diversified manager suffers large losses in one part of their book, they know they would be too weak to survive an unwind spiral in another, unrelated, part of their book. Knowing this, they may think they need to unwind their unrelated book now, even though nothing is wrong with it, rather than wait until it’s too late.

What’s more, other, stronger players may be able to predict this reasoning from the weakened players, and they can “guess” that mechanical unwinds like those detailed above will occur. If you hold a cash/futures bond basis position and see equity markets crash, you may intuit that that will cascade to your basis position via diversified players, even if you were not directly impacted by the equity crash at all. The mutual circle of mistrust of a bank run or food panic develops, and even strong players may try to get ahead of such unwinds by unwinding themselves first, from a position of strength. They “prepare to panic” (see cartoon below), but preparation itself is unwinding some of their book, which itself can start the cascade.

Like leverage and liquidity, diversification is a useful financial tool in normal times that cruelly morphs into an exacerbating force during market panics. Two markets can never really be unrelated as long as there are players that hold exposure in both markets. Losses in one market generate mechanical rebalancing, grabs for cash, and overall weakness, which cause pressure to unwind in other markets, which causes losses there as well. Notably, similar to a bank run, none of this needs to actually be true, the run will happen so long as others fear it might be. 

To sum up, diversification means that problems in one area of the market can lead to unwinds both mechanical and behavioral in other areas of the market. Throw in some game theory, and we can see that unwinds can occur at the mere speculation of vulnerability from others in the market, much like a bank run. Within short order, formerly staid and unrelated markets can turn into connected panic-zones.

It is important for asset owners and asset managers to build an understanding of these mechanics. To start, knowledge of how decisions in a panic may be forced by one’s own constraints, the constraints of the managers they hire, and others around them, is critical. Also critical is a grasp of how diversification can link different, and seemingly unrelated, sleeves of a portfolio. These concepts can serve as a framework for investors to assess why performance can be outside typical expectations during panic episodes. This context should be weighed alongside longer-term expectations in thinking about how best to allocate capital.

Kennnedy Muturi

Ken is a Quantitative Trader with experience in investments, quantitative finance, financial modelling and algorithmic trading in Global Investable Markets (GIM). He enjoys using Bayesian Statistics, Time Series and Machine Learning in developing Robust consistent Alphas in Equities Market, FX, ETPs and Derivatives instruments. He enjoys deep dives in understanding High Frequency Trading infrastructures and improving how the African financial markets work. He holds a Bachelor's in Actuarial Science from Strathmore Institute of Mathematical Sciences : An Executive Program in Algorithmic Trading (EPAT) certificate in Algo Trading from QuantInsti : A current MSc student in Financial Engineering at World Quant University.

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