After reaching elevated levels during the financial crisis, volatility across major fixed income rates markets has been in decline and is now at multi year lows. A similar dynamic can also be seen in other sectors such as credit and equities (Fig.1). Notwithstanding an uptick in Q4 2015 and Q1 2016, volatility remains below its long term averages in US, UK, German and Japan bond markets.
The drivers for this reduction have been well discussed but most agree that central bank policy including QE has played a major role (Fig.2). With the US in the process of (gradual) normalisation, should we be expecting rate market volatility to increase?
Perhaps counter-intuitively, in the past, rate hiking cycles have typically been associated with a reduction in volatility (Fig.3). Some grounds for this are as follows:
In contrast to a rates cutting cycle when a Central Bank may be forced to act swiftly in the face of deteriorating conditions, in a typical hiking cycle the Bank can be more firmly in control. The timing of hikes can be more carefully managed and by telegraphing upcoming action and by providing soothing rhetoric, they can manage the volatility around the process.
Viewed another way, a benign volatility environment could be seen as a precondition for hiking. Evidence for this can be found in recent communications from the Fed which have been explicit in acknowledging macro volatility as a consideration in it interest rate policy decisions.
While there are some key differences between previous hiking cycles and the current one (rates are starting from a lower base; markets are less liquid; policy divergence between CBs to name a few), there are good reasons to believe that rate hikes may not be a catalyst for increased volatility.
But there is a reason to expect volatility to increase at some stage:
Empirically, asset volatility reverts to a long-run mean, and the longer it remains below this level the more likely it is to increase. An explanation for this is that as volatility declines, any new arrival of information becomes relatively more important to market participants (the hurdle prompting the incremental buyer to buy or seller to sell is reduced; this buying and selling then increases the variability of the price .
Supporting the mean reversion concept is a recent discussion paper  from the Systemic Risk Centre at London School of Economics which demonstrates that prolonged periods of low volatility are statistically significant predictors of financial and banking crises. The paper posits that this is due to some variant of Minsky’s financial instability hypothesis whereby low volatility acts as an incentive to increase risk taking which in turn increases the probability of a crisis. Or more succinctly: stability is inherently destabilising.
This is a concern which has been voiced by a number of market participants including Yellen herself as well as the Treasury Borrowing Advisory Committee which warned the US Treasury in 2014 that “against an environment of low volatility and low returns, the only way to achieve the same return targets is to take on more risk” .
These structural forces mean that while bond market volatility may decrease further in the short term, it will increase eventually. With this in mind there are some points to consider.
Firstly, while volatility is a key factor in understanding an investment’s risk, and it can be indicative of risk, it is not risk per-se. An increase in volatility does not necessarily equate to any permanent loss of capital, and in fact higher volatility often provides the best opportunities for longer term investors. It is also important to acknowledge the benefits of diversification. Broadening the range of investments even within a narrow asset class can reduce overall volatility and can immunize against sharp increases in its level.
By its nature volatility is not something that can be easily predicted but understanding the above issues and the implications of changing volatility is a key part of the investment process.
 For a more elegant explanation and proof see: “Volatility clustering in Financial Markets: Empirical Facts and Agent-Based Models”, Cont. R
 “Learning from History: Volatility and Financial Crises” Danielsson J, Valenzuela M, and I Zer.