Impact of stock market volatility (Part-II)
…………Dr.Debesh Bhowmik
It is certain that monetary policy can exert a direct influence on risk premiums and volatility. In fact, an alternative view of the asymmetric return-volatility relationship proposed by Campbell and Hentschel (1992) and subsequently referred to as the volatility feedback hypothesis, postulates that negative news spur an increase in future volatility. According to the volatility feedback hypothesis, time-varying risk premiums relate the increase in future volatility to a decrease in contemporaneous returns. More specifically, the negative news leads to an increase in the expected stock returns (i.e. risk premiums) as investors require additional compensation to account for the increased riskiness of holding stocks. If volatility is a priced risk factor, and given a positive correlation between future volatility and expected returns, the increase in future volatility feeds back into and lowers contemporaneous returns. In sum, negative news decreases returns contemporaneously and increases both future volatility and expected stock returns. An unexpected monetary policy tightening constitutes negative news to stocks whose future cash flows (dividends) are valued at a higher than expected discount rate. This implies that a monetary policy shock is expected to decrease returns contemporaneously and to increase future stock market volatility. Evidently, both the leverage and volatility feedback channels can operate simultaneously as argued in Wu (2001). While previous research (Lobo, 2000; Bomfim, 2003; Flannery and Protopapadakis, 2002) uses Generalized Autoregressive Conditional Heteroskdasticity (GARCH) models to investigate the link between monetary policy and the volatility of some assets. Schwert (1989) studies the relationship between macroeconomic and stock market volatility but does not explicitly tackle the effect of monetary policy on stock market volatility. In this paper, we undertake an in-depth analysis, at the monthly level, of the effect of futures-based monetary policy shocks on stock market volatility and the variance risk premium.
It was examined that the dynamic effects of monetary policy shocks, identified from Federal funds futures data, by employing a vector autoregressive (VAR) model. The use of market-based measures of monetary policy shocks allows us to avoid the need to resort to identifying assumptions and circumvents dimensionality (degrees of freedom) problems in the estimated
VAR. Our goal from this analysis is threefold. First, they assess the dynamic response of stock market volatility and the variance risk premium to monetary policy shocks. Second, their analysis allows us to characterize asymmetries in the return-volatility relationship. Third, they study the channels through which monetary policy shocks affect stock market volatility by analyzing the joint response of several financial variables to market-based measures of monetary policy shocks. By inspecting the channels of monetary policy transmission to volatility, we also identify the importance of changes in the risk premium or leverage on stock market volatility and therefore investigate in further detail the importance of the volatility feedback and leverage effect hypotheses.
Their results show a contemporaneous decrease in excess returns of 1% and an increase in stock market volatility which peaks one month following the shock at 0.8%. The results illustrate an asymmetric return-volatility relationship and demonstrate that monetary policy exerts an effect on the variance risk premium. They further explore the effect of monetary policy by estimating a bivariate GARCH model relating federal funds futures to stock market volatility.
The bivariate GARCH model uncovers a novel and significant bidirectional volatility effect. Theoretically, volatility is a key component of many derivative pricing models and an understanding of the dynamic response of volatility to monetary policy shocks would allow for better derivative pricing.
Using a VAR model that incorporates a futures-based measure of monetary policy shocks, their findings uncover a significant response of stock market volatility to monetary policy shocks. Our results show an asymmetric return-volatility response to a monetary policy shock and reveal an important response of the variance risk premium, and by extension, of risk aversion, to monetary policy. They also study the channels through which monetary policy affects stock market volatility. Their findings suggest that while leverage and futures-trading volume display an increase following a monetary policy shock, the importance of these channels in affecting shortterm changes in volatility is limited. The longer-term dynamic response of volatility appears to be dominated by the persistent effect of monetary policy on stock market fundamentals (dividends). In light of the important dynamic response of stock market volatility to monetary Policy, they investigate the volatility interaction among a futures contract written on the monetary policy rate set by the Fed, namely federal funds futures, and the stock market using a bivariate GARCH model. Their analysis points to a bidirectional volatility relationship between the federal funds futures and stock markets. This, in turn, suggests an important role for market participants’ uncertainty about the future course of monetary policy in determining stock market volatility.Their results entail important practical and policy making implications. From a policy perspective, our results demonstrate that Fed actions have a significant effect on stock market
volatility and the variance risk premium. This, in turn, implies that the Fed might be able to influence market volatility and market-wide risk aversion through better communication or
increased transparency. From a trading perspective, the results show that investors might be able to trade profitably, by entering into suitable derivatives positions, due to the persistent increase in volatility that follows a monetary policy shock. It would be interesting to explore whether investors can realize a profit, once trading costs are accounted for, using swap contracts.
An attempt is made to examine price and volatility spillover effects across international stock markets, based on the wavelet methodology in decomposing time series data. In particular, we investigate the relationships between the matured stock markets in the U.S., Japan and Germany and the emerging markets in the MENA region. Using the composite stock indices such as ISE-100 of Turkey and CMS of Egypt together with those for Dow Jones Industrial Average of the U.S., Nikkei 225 of Japan, and DAX of Germany, new evidence is found for price as well as volatility spillover effects from the developed stock markets to the MENA counterparts, but not vice versa. The results confirm the importance of news from developed international stock markets in the determination of stock returns and volatility in emerging markets.
A few interesting observations can be pointed out from the empirical analysis. First, the Turkish stock market seems quite well integrated globally with the major developed markets in the world. Such an observation is in agreement with an earlier result in Benkato and Darrat (2000). On the other hand, the linkage between the Egyptian market and the global market appears to be rather weak, although evidence can be found for spillover effects from the developed stock markets to the Egyptian market. The difference in the degree of spillover effects between the two MENA countries lies in the difference in the degree of capital market liberalization between them.
Although interesting results are presented in this paper via wavelet analysis, much work remains to be done. First of all, our methodology can naturally be applied to any sets of international stock market returns to provide new evidence on spillover effects. Hence the next item on the research agenda should include an empirical investigation into international spillovers from the developed markets such as the U.S. to other emerging markets around the globe including other stock markets in the MENA region. The current approach can also be extended to multivariate framework. Such multivariate analysis would be useful in providing new evidence on spillover effects in the context of uncertainty associated with the potential interaction among any set of stock market return series.
While the wavelet methodology is used here to just decompose time series data, the wavelet analysis is much more powerful in signal processing than what is discussed here. For instance, the wavelet approach can be used to investigate whether innovations in one market may lead to asymmetric impact on other markets depending on the sign as well as the size of such shocks, as discussed in, e.g., Cheung and Ng (1992) and Koutmos and Booth(1995).
The other objective is to determine if volatility surprises in one market influence the volatility of returns in the other market. It was used ARCH school of models such as GARCH (1, 1) and EGARCH (1, 1) for modeling of spillovers between stock returns and exchange rate returns. It is found that the volatility in both the markets is highly persistent and predictable on the basis of past innovations. The impact of these innovations is asymmetric. It was found that there is evidence of bidirectional volatility spillover between the stock market and foreign exchange market except the stock indices such as S&P CNX NIFTY and S&P CNX 500. The findings of the study also suggest that both the markets move in tandem with each other and there is a long run relationship between these two markets.
In general, the results of significant bidirectional volatility spillover suggest that there is an information flow (transmission) between these two markets and both these markets are integrated with each other. These results suggest that investors can predict the behavior of one market by using the information of the other. The long run relationship between these markets also suggests that at least there is a unidirectional causality between two variables in either way. Accordingly, financial managers can obtain more insights in the management of their portfolio affected by these two variables (stock price and exchange rate). This should be particularly important to domestic as well as international investors for hedging and diversifying their portfolio.
The studies of the transmission of shocks in financial markets across economies have become an important issue in the international financial literature. Eun and Shim (1989) and Becker et al. (1990) investigate such spillover effects for instance. Thereby, their models involve Vector Autoregressive (VAR) models or a set of single linear equations attempting to capture the dependencies between international equity returns. These contributions though are focused on the asset return series and on the question how returns are correlated across different economies. They find evidence of significant price-volatility spillover effects arising from the US-stock market passing over the British and Japanese markets and from the British market merging to the Japanese market with respect to the post-crash period. The model being based on VAR and a refinement of multivariate GARCH models shows that volatility spillover impacts from the German to the Swedish and British stock markets increased by 73.87%, respectively, 15.52% when comparing the last two decades.
We find that the volatility of the stocks affected by the reform declines after the implementation of the reform, relative to other stocks, which means that the effect of retail trading on volatility is positive. We argue that this positive effect is consistent with the view that some retail investors behave as noise traders. In support of this claim, we show that the reform also triggers a drop in the size of price reversals and the price impact of trades for the stocks affected by the reform. All these observations are predicted by models of noise trading. One must be careful in interpreting these findings: they are consistent with the view that some retail investors play the role of noise traders but they do not imply that all retail investors are noise traders or that only retail investors are noise traders. Moreover, we do not identify the drivers of retail trades (misperception of future payoffs, risk aversion, or hedging needs). Thus, our findings should not be construed as evidence that retail investors are irrational traders.
Our findings also raise new questions. The literature on retail investors predominantly finds that these investors follow contrarian strategies, on average. We use our data on retail investors to measure the contribution of contrarian and momentum trades to retail trading activity. The reform has a more negative impact on contrarian trades. This observation can be reconciled with our finding regarding volatility in one of two ways: either retail contrarian trades dampen volatility but their stabilizing effect is smaller than the destabilizing effect of retail momentum trades, or retail contrarian trades also have a positive effect on volatility. Both stories are plausible. The first story is consistent with Kaniel, Saar, and Titman (2008), who argue that retail investors act as liquidity providers. The second story is consistent with Bloomfield, O’Hara, and Saar (2009). They consider an experiment in which some participants have no specific reason to trade and have no information. Instead of staying put, these agents trade and realize losses. Interestingly, they use contrarian trading strategies and contribute to mispricing by slowing down price adjustments to true values. There might be several reasons why noise traders may appear to act as contrarian investors.
For instance, they may be prone to behavioral biases such as the disposition effect or they may not realize that their limit orders are more likely to execute in the case of adverse price movements.Therefore amplify volatility. Our quasi-experiment cannot tell which story is correct. To do so, in keeping with the spirit of our study, one would need to find a separate instrument for contrarian retail trades and momentum retail trades. We leave this question to future research.
The findings in the other paper highlight the importance of information regarding stock market volatility in the monetary policy-making process,and also warn that the stock market boom stimulated by an accommodative monetary policy may easily turn into a financial bubble. If the bubble bursts, both the financial system and the real economy will be devastated. Therefore, the side effect of an accommodative monetary policy on the stock market should draw more attention from monetary authorities. From this perspective, the conclusion of the present paper may be generalized to take into account more nations across the world.
In particular, a recent study by Chris- tiano et al. (2008) calls for further investigation of the relation between monetary policy and stock market volatility. Christiano et al. (2008) find that the implementation of accommodative monetary policy can signal that a rebound of the stock market is just around the corner, and the imperfect rationality of investors can make the stock market uctuate more frequently than is usual. To date, the literature has come to a general consensus that stock market volatility has a negative e_ect on the recovery of the real economy. What remains controversial is whether monetary policy may increase stock market volatility, and therefore central banks should take this possibility into account when setting monetary policies. For example, Bernanke andGertler (1999) and Cecchetti et al. (2000) provide distinct conclusions. Bernanke and Gertler (1999) explore how the macro economy is affected by alternative monetary policy rules either with or without the stock market volatility being taken into account. Their results suggest that it is desirable for central banks to focus on inflationary pressures while stock market volatility becomes relevant only if it signals potential inflationary or deflationary forces. Therefore, monetary policy with additional focus on stock market volatility does not benefit the economy in any significant manner.
However, Cecchetti et al. (2000) raise several objections to Bernanke and Gertler's (1999) conclusion. Cecchetti et al. (2000) believe that one of the final goals of monetary policy is to maintain a stable financial system.Large fluctuations in the stock market can cause adverse shock to the real economy. Therefore, central banks should not only concentrate on inflation and real economic growth, but also set a goal to react to the stock market volatility. Filardo (2004) is sympathetic to this argument and proposes that central banks should focus solely on stock market volatility in calibrating monetary policy trade-offs. In addition, Gilchrist and Saito (2006) employs a general equilibrium model on the basis of the Real Business Cycle theory and shows that it is necessary for monetary policy to consider stock market volatility.
However, leverage has no impact on asymmetric volatility at the daily frequency and, moreover, we observe asymmetric volatility for stocks with no leverage. Also, expected returns may vary with the business cycle, that is, at a lower than daily frequency. Trading activity of contrarian and herding investors has a robust effect on the relationship between daily volatility and lagged return. Consistent with the predictions of the rational expectation models, the non-informational liquidity-driven (herding) trades increase volatility following stock price declines, and the informed (contrarian) trades reduce volatility following stock price increases. The results are robust to different measures of volatility and trading activity.
Other research investigates the issue of temporal ordering of the range-based volatility and volume in the Indian stock market for the period 1995-2007. Here it was examined the dynamics of the two variables and their respective uncertainties using a bivariate dual long-memory model. They distinguish between volume traded before and after the introduction of futures and options trading. They find that in all three periods the impact of both the number of trades and the value of shares traded on volatility is negative. This result is in line with the theoretical argument that a marketplace with a larger population of liquidity providers will be less volatile than one with a smaller population. It was found that (i) the introduction of futures trading leads to a decrease in spot volatility, (ii) volume decreases after the introduction of option contracts and, (iii) there are significant expiration day effects on both the value of shares traded and volatility series.
The decline in volatility in the early, pre-World War I period reflects ongoing improvements in the information and contracting environment, which find reflection in the improved operation of financial markets. Indeed, there is a considerable literature on the growth and development of financial markets in this period, although it has paid relatively little attention to stock markets, given their still limited role in resource allocation. Following the Great Depression of the 1930s, there was then a period of tight regulation of financial markets and institutions, one consequence of which was limited volatility (with some sharp exceptions, such as during World War II). The subsequent rise in volatility reflects financial liberalization inadequately supported by prudential control; an increase in the instability of macroeconomic policies, especially following the breakdown of the Bretton Woods System; and financial globalization, which may have been a factor in rising volatility in some countries. Although he found that both stock returns and output are more volatile in recessions, which can explain why volatility is higher in some periods than others, the additional volatility of activity such periods appears to be insufficient to explain the additional volatility in asset markets. The point is most obvious for episodes like the Great Depression of the 1930s, but it is more general. In terms of this paper’s finding, the point can be put as follows. Most investigators agree that there has been a secular decline in macroeconomic volatility in the now advanced economies. But while this decline in output volatility has been broadly linear, the same has not been true of stock market volatility. Thus, it is hard to see how the former can explain the latter. At a minimum, other factors must also be at work. Schwert.s conclusion that changes in stock market volatility cannot be adequately explained by observed changes in macroeconomic policies and conditions. In effect, they responded by introducing additional macroeconomic variables. Kose, Prasad and Terrones (2003) suggest that financial integration (due mainly to the removal of capital controls) is responsible for an increase in the relative volatility of consumption and asset returns, especially in countries that have liberalized their capital accounts only relatively recently and partially. When negative shocks hit these countries, these authors observe, they tend to lose access to international capital markets. The rapid reversal of capital flows in response to these events amplifies the volatility of their consumption and asset market outcomes. Dellas and Hess, on the other hand, find that the removal of capital controls is associated with less output and stock market volatility. This runs counter to the thesis that financial integration increases stock market volatility.
Kose, Prasad and Terrones find that consumption and financial market volatility rise with financial liberalization mainly in countries that have liberalized only partially and relatively recently that is, in low and middle income countries. This suggests that the dominant effect of the removal of capital controls in high income countries is to enhance the liquidity, depth and efficiency of financial markets.In low income countries, in contrast, the main effect of the removal of capital controls is to expose the economy to sudden stops, exacerbating consumption and financial volatility.
We found a positive association of monetary volatility with stock market volatility; an interpretation is that the conduct of monetary policy and the nature of the monetary regime are important for stock market volatility. That monetary policy became increasingly volatile in a number of countries in the 1970s and 1980s thus may be part of the explanation for why stock markets have been more volatile in recent decades.
Probing deeper, we found that fixed exchange rate regimes are associated with relatively low levels of stock market volatility, flexible exchange rate regimes with relatively high ones. This makes it tempting to conclude that the collapse of currency pegs and the transition to floating explain the recent rise in stock market volatility. But not only the official exchange rate regime but also the conduct of monetary policy under that regime appear to matter, in that we find a positive effect of monetary volatility on stock market volatility even after controlling for the exchange rate regime. Not just the putative exchange rate regime matters for the volatility of financial market outcomes, in other words; also important is the credibility and conduct of monetary policy under that regime. We further find, for the majority of countries considered, that financial internationalization is positively associated with stock market volatility. That international financial markets were open both in the late 19th century and in recent decades may thus be another part of the explanation for why we observe a u-shaped pattern in stock market volatility. This interpretation is consistent with Calvo and Mendoza.s conjecture that the globalization of financial markets has reduced the incentive for investors to assemble and process information about individual market conditions, resulting in greater financial volatility. Specifically, if the exchange rate anchor for monetary policy is cut adrift, it is important to put another anchor such as inflation targeting in its place. And, if the capital account is opened, it is important to put in place the institutional supports needed to ensure that capital account transactions are a stabilizing force. For the emerging markets that are following in the footsteps of the now advanced economies, the implications are mixed. On the one hand, the historical decline in stock market volatility enjoyed by the advanced economies as their financial markets developed and matured suggests that emerging markets may similarly experience a decline in volatility as they graduate from the early stages of financial development.