Fear indices and policy-making

M. V. S. Santosh Kumar | Updated on March 07, 2011

Fear indices tend to ‘lead’ macro economic variables by up to eight quarters.

The fear gauge may help the investor to discount stock prices ahead of the event; it can also be a signal to policymakers for course correction.

Derivatives, famously dubbed as weapons of mass-destruction by Warren Buffett, normally come under spotlight only during scams and frauds.

Yet, one cannot deny that derivatives do provide useful price intelligence to capital markets, by capturing how market players perceive the future.

Among the indicators commonly used to measure the degree of complacency or otherwise among investors is the implied volatility index (VIX), more popularly known as the fear gauge.

The fear gauge may tell you whether it is the right time to invest, but can it be a signal to policymakers?

In a paper titled “Investor and central bank uncertainty and fear measures embedded in index options” (http://www.nber.org/papers/w16764.pdf), authors Mr Alexander David and Mr Pietro Veronesi prove that the VIX and put-call implied volatility ratio are actually good leading indicators to key macro economic variables such as capacity utilisation of industry and short-term interest rates.

The authors have used advanced statistical models to show that the fear indices tend to ‘lead' (or signal in advance) macro economic variables by up to eight quarters.

After modelling data for over 23 years, the paper concludes that “uncertainty in the options market has real economic consequences that are tempered by the efforts of the central bank”. The other takeaway from the paper is that, while the model offers evidence that the fear gauge may affect the central bank's policy-making but the central banks' actions often do not impact investor sentiment.

What volatility means

Before we get at the conclusion, what is implied volatility and put-call implied volatility used in this paper?

Volatility in statistical terms is the tendency of the asset's price to swing; it measured as the standard deviation of the asset's returns. Implied volatility of at-the-money options (ATMIV) captures the market's best guess on what future volatility will be; it is calculated using option pricing models. AMTIV goes up with higher uncertainty.

This paper uses these concepts to find that uncertainty (read: a high fear factor) may prompt companies to operate at sub-optimal capacity utilisation and put off their expansion plans.

When this happens, the central bank reacts by lowering the cost of funds to stimulate investment. Therefore, shifts in the economy (from boom to bust or back) are usually triggered by policy intervention.

Another finding is that the ATMIV and money growth are negatively correlated, particularly during periods of high policy stimulation.

Put-call implied volatility ratio, a modification on the IV, is arrived at by dividing the implied put volatility by implied call volatility.

This index measures the extent to which investors expecting a fall outnumber those expecting a rise in volatility. If the ratio is high, it implies that the downside risk is higher than the upside risk.

This ratio surprisingly is negatively correlated to the ATMIV. Simply put, this ratio is high during the good times and low during the bad times. Explaining this contradiction, the paper says “investors downwardly revise their beliefs in response to bad news by a larger amount in good times than in bad times. Therefore, investors' perceive greater downside risk in stocks in good times.”

However, both gauges demonstrate a V-shaped relationship with economic variables (put-call IV ratio demonstrating an inverse relationship).

That is, the volatility indicators spike when data points are at an extreme. The central bank reacts to extremes too, given that its preference is likely to be for stability.

Policy interventions

Most monetary policy intervention happens in order to establish ‘stability' in the economic regime.

The authors have also used four economic variables (consumer price index, earnings growth, capacity utilisation and money growth) to arrive at the probability of shifting from one regime to the other over a quarter.

The movement between these regimes is what is reflected in the option prices. A non-recessionary period, for instance, may feature low inflation, high earnings growth, optimal capacity utilisation and moderate money growth. Recession will be marked by high inflation, low earnings growth and high money growth (thanks to stimulus efforts by the central bank).

“The interest rate rule is then directly built into investors' pricing kernel to provide joint pricing implications for the stock index, treasury bonds, and stock index options as functions of investors' beliefs.”

The research points out “the model is also quite successful in explaining the spike in implied volatility in the current recession, which started with the fear of an increase in inflation to a medium level and an increase in investors' probability of the economy overheating and deep recession, followed by the collapse of inflation and increase in the fear of deflation in the second half of 2008.”


The authors give important caveat that the fear indices as a lead indicator aren't effective when markets are influenced by microstructure issues, such as the crash of 1987 (trading issues) or the collapse of LTCM (liquidity issues) in 1998.Overall, the paper confirms the theoretical premise that stock prices discount publicly available information ahead of the event i.e. the efficient market hypothesis.

Just that option prices and volatility are measured vis-a-vis monetary expectations, instead of spot prices.

The findings of this paper, however, may not be as applicable in Indian markets as in the US, given the far more mature state of markets there.

Additionally, the model assumes that the central bank and investors observe the same data and have the same access to information, which may be a theoretical premise.

The central bank, especially in developing markets such as India certainly has vast access to information, much more than investors.

The expectation that markets can fully discount monetary policy, eight quarters ahead, therefore appears optimistic.

Case in point, the Reserve Bank of India surprising the market time and again during Dr.Y.V Reddy's tenure.

Published on February 28, 2011

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