Severe financial market events, like the “Brexit” vote in which Britons opted to leave the 28-member European Union (EU), stoke up uncertainty and make appropriate strategy selections all the more important. These events can also make stock pricing a difficult task (especially under the theory-driven capital asset pricing model),
Global stock markets – London’s in particular – were plunged into uncertainty and extreme volatility in the wake of the dramatic June 2016 vote, with stock markets seesawing from hefty losses to gradual recoveries partly thanks to hopes for central bank stimulus packages.
For investors, particularly those heavily invested in the London exchange, the numerous uncertainties about the Brexit process and what this will mean for the UK business environment makes strategy selection and stock picking that much tougher.
The British pound fell as much as 11.5% to reach a 31-year low against the dollar in the days after the vote, before recovering somewhat in the following few days. The FTSE 250 index plunged 7% and 6.96% respectively in the two trading days following the vote results, wiping enormous value off benchmark index funds and leading to widespread capital losses across markets. Further, the financial market risk pushed ratings agencies to downgrade UK credit. Meanwhile, contagion meant global markets shed $2 trillion in value in the hours after the referendum.
But some quantitative strategies, which rely on rules-based methodologies and which scour markets for abnormalities which might help boost returns and control risks, bucked the trend and delivered strong gains.
Quantitative- or factor-based strategies can be tailored to take advantage of, or defend against, periods of market risk – including the risks brought about by the Brexit vote.
One quantitative approach which took advantage of the pound’s dive was going long foreign exchange (FX) volatility funds. This approach uses factor analysis in currency trading.
Based on quantitative analyses of currency fundamentals, which indicate gaps between market prices and long term value, FX volatility funds which were short the pound made strong gains on the back of the sterling’s woes. Long term currency values can be measured by analysing a currency’s corresponding current account alongside other economic or financial data. Trends away from fair value, as shown by these data analyses, present opportunities for savvy investors.
On the other side of the coin, correctly-positioned long-only FX volatility strategies also performed well in the wake of the Brexit turmoil.
Selecting appropriate factor strategies
The vote also raised fears that the gradual but shaky global economic recovery might stumble, adding another layer of information uncertainty and market risk to the investment climate. The drawn-out negotiation process between London and the European Union will likely mean prolonged periods of uncertainty and trading volatility.
Fund managers and analysts, therefore, will have a difficult job making discretionary stock selections. Sound risk management, as well as data and information analysis, will be essential going forward.
Factor strategies fitting for prevailing market conditions
Negative sentiment may pull financial markets into a downward trend; though at the same time, the underlying fundamentals of many stocks and their business models will remain intact.
For this reason, value investment strategies will be attractive to investors looking to buy stocks which are undervalued by the market relative to their intrinsic value.
Amid high levels of market risk, value strategies can perform well on a risk-adjusted basis given the flight to quality – essentially aiding in risk management. For example, a well-constructed value smart beta index which favours undervalued stocks will likely outperform the benchmark against which it is measured.
A corresponding risk premia approach to the above smart beta strategy might go long the value smart beta index while short-selling the market-related benchmark index, with the goal of generating absolute returns irrespective of broad financial market risk and performance.
Momentum strategies, meanwhile would likely be more at risk since a change in market trends can result in losses. However, changing market conditions could make way for new trends to be exploited.
Some investors favour combined momentum-value funds, which tend to outperform on a risk-adjusted basis over the long term.
In particular, long-short momentum and value strategies are often pooled together since they tend to perform at different phases of the market cycle. This helps to smooth long-term performance and manage volatility and market risk.
In addition to equities, smart beta funds can also target other asset classes, including the less volatile credit market. But partly because fixed income products like credit are more difficult to include in a rules-based strategy, they feature less prominently in smart beta funds than equities and commodities.
Managing risks will be a key focus for fund managers in the face of unpredictable global markets, as will capital allocation decisions. Allocating capital across different factors, rather than across asset classes, appears more attractive than ever before. This is largely because different asset classes tend to re-correlate in times of severe market weakness.
The implications of Brexit on UK constituents in Euro indices
Index providers MSCI and Stoxx told the market in the days after the Brexit vote that London-based shares featuring in their benchmark European indices would not be removed despite Britain’s exit from the European Union.
The removal of companies listed on the London Stock Exchange would effectively shift the goalposts for many smart beta indices, whose returns are compared against major benchmarks. Benchmarks like the S&P 500 Index and FTSE 100 Index act as barometers for broader financial markets.
The S&P 500 tracks major US companies, while the FTSE 100 tracks the performance of 100 companies listed in London, the capital of the UK.
Among other return measures, funds can be rated by the excess returns they yield, a model which indicates their under- or out-performance against the benchmark index. By using excess return (alpha) and volatility risk (as described by beta), investors can evaluate a fund’s total performance on a risk-adjusted basis.