IMPACT OF STOCK MARKET VOLATILITY(PART-I)

Impact of Stock Market Volatility (Part-I)

-----Dr.Debesh Bhowmik

The conventional finance theory suggests that the stock market (excess) return, being a forward-looking variable that incorporates expectation about future cash flows and discount factors, contains useful information about investment and future output growth. Empirical literature provides substantial evidence in favour of this proposition .It is also seen from a number of recent studies that increased stock market volatility depresses economic activity and output . Empirical results presented by Campbell et al. (2001), in particular, are very important in this regard. They show that each of stock market volatility and excess return, when considered singly (i.e. when only one of these variables - either return or volatility - is considered) after controlling the lag dependent variable, is significant in explaining future output growth. But, when both volatility and excess return are considered as regressors (in addition to lag dependent values), volatility drives out return in predicting future output growth. As per the existing literature, stock market volatility may affects output growth through several possible channels, such as, (i) its link with market uncertainty and hence economic activity, (ii) association between market volatility and structural change (which consumes resources) in the economy, (iii) link of volatility with cost-of-capital to corporate sector through expected return. It is, however, not clear to justify why volatility drives out return in predicting output growth as observed by Campbell et al.(2001). Guo (2002) has discussed major arguments put forward by the proponents of volatility effects on output and has reconciled the evidence provided by Campbell et al. (2001) with earlier empirical evidence on predictive power of the stock market returns and finance theory. Based on a small model he argues that volatility may influence output growth (or may drives out returns in predicting output) in some specifications possibly because of its influence on cost of capital through its link with expected return.

But if cost of capital is the main channel through which volatility affects output then returns should play more important role in forecasting output growth than volatility does. He also provides empirical results to support this hypothesis. He derives relevant results for three different time periods; one longer than (but covering), one identical with, and another adding more recent years but shorter in length than the Campbell et al. (2001) sample period. Interestingly, using Campbell et al. (2001) sample, he finds that

the volatility drives out returns in predicting output growth because of the positive relation between excess returns and past volatility; if this relation is controlled for, excess returns show up significantly in the forecasting equation. In the liberalisation era, volatility in Indian financial markets is believed to have

increased/changed and thus there is a need to assess the impact of financial market volatility on output growth. With this background, this article presents some preliminary observations regarding link between stock market volatility/excess return and future output growth.

Some recent studies have shown that elevated stock market volatility depresses output. As per the conventional finance theory, however, it is the stock market (excess) returns that should have impact on future output growth. Currently, the issue is important in India, as there has been a perception that the volatility in Indian financial markets has increased/changed during the liberalisation era. Empirical results show that stock market volatility is strongly influenced by its own past values – pointing to the presence of significant volatility-feedback effects in the stock market. The volatility is also quite strongly related (at least contemporaneously) to excess return in recent years. However, roles of stock market return and volatility in predicting future output growth are not clear. Because, coefficients of lags of both these variables in the equation for future output growth are generally insignificant and in some cases have wrong signs, though during April 1997 to December 2002 only the volatility shows quite strong influence on output growth. Thus, there is a need to undertake further in-depth research for understanding the relationship between stock market return/volatility and future output growth in the context of Indian economy.

Thus, stock market uncertainty can have large effects despite the fact that households’ direct stock market participation is rather limited. Similarly, if stock market volatility can be viewed as an indication of how uncertain firms regard future developments, it can have a large effect on investment even if only a small fraction of firms in an economy

are subject to financing conditions determined by stock price movements. We provide empirical evidence on the relationship between stock market volatility and the business cycle and review the existing literature.

The empirical observation that stock market volatility tends to be higher during recessions points toward a negative relationship between stock market volatility and output. Fig-1 shows a scatter plot of U.S. quarterly percentage growth of real GDP against implied U.S. stock market volatility together with a fitted regression line.

The negative relationship between volatility and output growth is clearly visible. Scatter plots using historical volatility or GJR-based volatility instead of implied volatility show a similar negative relationship.

Although the empirical evidence presentedin the previous section indicates a close relationship between stock market volatility and economic fluctuations, the evidence is only suggestive.However, several papers document similar linkages using more detailed empirical approaches. The empirical study of Romer (1990) deals primarily with the onset of the Great Depression. However, Romer also presents estimates of the relationship between stock market volatility and consumption in the U.S.A.

Table-1: U.S. Ouarterly Stock Market Volatility

in Periods of Expansion and Recession

Fig-1:U.S. Stock Market Volatility and GDP Growth

for the post-war period. Using annual U.S. data ranging from 1949 to 1986, she concludes that a doubling of stock market volatility reduces durable consumer

goods output by about 6%, whereas the effect on nondurables is essentially 0. This ordering of the magnitudes of the effects is consistent with the idea that stock market volatility is closely related to uncertainty about future real economic activity. This is

because non reversibility gives rise to a lock-in effect that is particularly pronounced

during periods of high uncertainty.

Consider for instance a consumer deciding to buy a durable consumption good. Given the durable nature of the good and the uncertainty about future income, it may turn out that the good is either too modest or too luxurious with respect to future income. However, if the consumer waits until uncertainty is resolved, it may be easier to choose an appropriate good.Thus, by postponing the purchase of the good, the lock-in effect can be avoided and the benefit of doing so increases with the level of uncertainty. It follows that decisions that are irreversible to a larger extent are postponed, resulting in particularly pronounced reactions of durable consumption expenditures and investment expenditures to increasing stock market volatility.

Since investment decisions are presumably the least reversible, one would expect that stock market volatility has the largest effect on investment spending, followed by durable consumption and nondurable consumption. Note that if households substitute away from durable consumption goods into nondurable consumption goods because of higher uncertainty, then nondurable consumption may even rise during periods of high stock market volatility. Raunig and Scharler (2010) evaluate the uncertainty hypothesis by estimating the influence of stock market volatility on durable consumption growth, nondurable consumption growth and investment growth. Their analysis is based on quarterly time series data for the U.S.A. Based on a number of different estimates of time-varying stock market volatility, Raunig and Scharler (2010) find that stock market volatility exerts an economically and statistically significant effect on aggregate demand.

Moreover, they find that the adverse effect of stock market volatility on aggregate

demand depends on the extent to which decisions are reversible. Based on their richest specification (Table 2), they find that an increase in volatility by one standard deviation reduces the quarterly growth of durable consumption by around –0.70 percentage points, whereas the effect on the growth of nondurable consumption is only –0.14 percentage points. Investment growth responds with a lag of one quarter and declines by 1.12 percentage points.

Table-2:Effect of an Increase in Stock MarketVolatility by one Standard Deviation

on U.S. Consumption and Investment Growth

Hence, the decline in the growth of durable consumption and investment is larger during periods of increased volatility than the decline in the growth of nondurable consumption, which is again fully consistent with the predictions of the uncertainty hypothesis. In addition to being statistically significant, the estimated effects are also substantial in an economic sense. Stock market returns, in contrast to volatility, have a quantitatively smaller and often statistically insignificant influence on consumption and investment.

This result is consistent with Lettau and Ludvigson (2004), who also find that returns exert only a limited influence on consumption. The reason is that although permanent shocks to stock prices have a strong effect on consumption, most fluctuations in prices are transitory and exert only small effects on consumption.

Alexopoulos and Cohen (2009) identify uncertainty shocks using vector autoregressive methods. To measure uncertainty, they use stock market volatility measures, as in Raunig and Scharler (2010) and Choudhry (2003), and also an index based on the number of New York Times’ articles on economic uncertainty. They find that uncertainty shocks play an important role for the business cycle. In particular, uncertainty measured by the New York Times’ index accounts for up to 25% of the short-run variation in employment

and output. Choudhry (2003) analyzes the influence of stock market volatility on GDP and the components of GDP using an error-correction framework. Under the assumption that volatility follows a non -stationary stochastic process, he estimates the short-run and long-run dynamics of GDP components using an error-correction framework. His results confirm that stock market volatility has adverse effects on consumption and investment.

A different, but closely related, issue is analyzed in Jansen and Nahius (2003) They analyze how stock market fluctuations influence consumer sentiment in a sample of eleven countries. They find that in the vast majority of countries under consideration, consumer sentiment and stock returns are positively related. They also find that causality runs from stock returns to consumer sentiment rather than vice versa. Moreover, they conclude that the correlation between stock returns and consumer sentiment mirrors expectations about future economic conditions. Therefore, the evidence presented in their paper also provides some backing for the uncertainty hypothesis, in the sense that stock market fluctuations give rise to uncertainty about future economic conditions.

Note that although the uncertainty hypothesis suggests that causality runs from stock market volatility to the business cycle, this need not necessarily be the case. Although the early literature on the determinants of stock market volatility finds only weak linkages between stock market volatility and macroeconomic variables, recent empirical research (e.g. Engle et al., 2008; Diebold and Yilmaz, 2010) establishes important linkages between macroeconomic fundamentals and stock market volatility. In particular, Arnold and Vrugt (2008) find a strong link between macroeconomic uncertainty and stock market volatility using survey data from the Survey of Professional Forecasters maintained by the Federal Reserve Bank of Philadelphia. The authors find that rising uncertainty about future macroeconomic developments increases stock market volatility. Thus, taken together with the evidence presented above, it appears that causality between macroeconomic outcomes and stock market volatility is bidirectional.

Financial Crisis and Global Imbalances:A Development Perspective- by Yilmaz Akyuz(Orient Black Swan,South centre,2012)pp xix+190,Rs625/-

An Analysis………..    

 By Dr.Debesh Bhowmik

It is argued that the global economy suffers from a demand gap in large part because of sustained declines in the share of labour income in most major economies, including the US,Europe,Japan and China. Until the outbreak of the subprime debacle , the deflationary threat posed by underconsumption was averted and the global economy enjoyed a rapid growth .This, however, resulted in growing global trade imbalances and financial fragility which eventually culminated in a global crisis.A return to the pre-crisis pattern of growth can prove to be more damaging.A global rebalancing between major surplus and deficit countries would be necessary .This can not be done through nominal currency adjustments.A nominal appreciation of the of the Chinese Yuan against the dollar will not solve Chinese underconsumption or US overspending. China should move to consumption led growth through faster growth of wages.This would appreciate the real exchange rate of the Yuan and reduce net exports,but it would at the same time provide a domestic offset by expanding domestic consumption, and hence allow it to maintain strong growth.The US should move to export led growth not through wage cuts but through increased productivity through investment in infrastructure and education.However, a US –China rebalancing would not be sufficient to restore an acceptable pace of growth in the world economy.The two major mature surplus economies,Japan and Germany, which have been siphoning global demand without adding to global growth ,would also need to reduce their reliance on exports and add to global demand.Until the outbreak of the subprime crisis, the resulting trade deficits in the periphery were financed  with large capital inflows from the core Eurozone countries,notably from  German and French banks, encouraged by the changed risk perceptions and convergence of interest rates after the move to the Economic and Monetary Union.These unsustainable intra-uerozone imbalances and debt accumulation were laid bare with the global crisis.The renewed surge in capital inflows has created different imbalances and fragilities in different developing countries accordint to their degree of openness to various forms of capital and policy response.Major economies such as Brazil,india, SouthAfrica and Turkey have been relying increasing on foreign capital to meet their growing external shortfalls and many of them  have been experiencing currency appreciations faster than surplus  developing economies in East Asia .By constrast, most East Asian countries have been successful in maintaining  strong payment positions, but they have also been facing credit and asset bubbles.in other words, all major recipients are now exposed to the risk of a sudden  stop and reversal, though in different ways, even to a greater extent than that experienced after the Lehman collapse.The countries which have been enjoying the twin benefits of global liquidity expansion-ie, the boom in commodity prices and capital flows-as well as those running growing deficits are particularly vulnerable.Asian economies with strong current account and reserves positions are unlikely to face serious payments and currency instability even in the event of sharp and sustained declines in  capital inflows.However, their financial markets are highly exposed to destabilizing impulses from abroad  because of increased foreign presence and their closer integration into the international financial system.The consequent damage could be more severe and longer lasting than that experienced during the Lehman collapse at both global and national level.

For most emerging economies in other regions,there is a need to reduce dependence on capital inflows.Collectively developing economies have been running a current account surplus and they do not need capital from advanced economies for external financing.in fact they have been recycling their twin surpluses to the  advanced economies in the form of investment in reserve currencies.However, a number of developing countries have been running structural deficits and are dependent on capital inflows to finance imports, investment and growth.There is thus a need to establish, at both the regional and global levels, reliable and stable mechanisms for South South recycling from surplus to deficit countries without going through Wall Street or the City.

The above book states more than that because it is collection of papers for the South Centre during 2009-2011 on the global crisis.

FACTORS AFFECTING STOCK MARKET VOLATILITY

The Factors affecting stock market volatility

----Dr. Debesh Bhowmik

We learnt from recent theoretical explanations that the countercyclical behavior of stock volatility can be understood as the result of a rational valuation process. However, how much of this countercyclical behavior is responsible for the sustained level aggregate volatility has experienced for centuries? Approximately one third of this level can be explained by macroeconomic factors, and that some unobserved component is needed indeed to make stock volatility consistent with rational asset valuation. Moreover, it is shown that a business cycle factor is needed to explain the inevitable fluctuations of stock volatility around its average.

The risk-premiums arising from fluctuations in this volatility are strongly countercyclical, certainly more so than stock volatility alone. In fact, the risk-compensation for the fluctuation in the macroeconomic factors is large and countercyclical, and explains the large swings in the VIX index during recessions. When the VIX reached a record high of more than 70%, which the model successfully reproduces, through a countercyclical variation in the volatility risk-premiums.  Finally, it is evident that the same volatility risk-premiums might help predict developments in the business cycle in bad times and the end of a recession.

Which macroeconomic factor matters? It was found that industrial production growth is largely

responsible for the random fluctuations of stock volatility around its level, and that inflation plays, instead, a quite limited role in this context. At the same time, inflation plays an important role as a determinant of the VIX index, through two channels: (i) one, direct, channel, related to the inflation risk-premium, and (ii) an indirect channel, arising from the business cycle propagation mechanism, through which inflation and industrial production growth are correlated. The second channel is subtle, as it gives rise to a correlation risk that it is significantly priced by the market.(Corradi,Distaso &Male,2010).

Fig-1,VIX index

The key aspect is that the relations among the market, stock volatility, volatility risk- premiums and the macroeconomic factors, are consistent with no-arbitrage. In particular, volatility is endogenous in our framework: the same variables driving the payoff process and the volatility of the pricing kernel, and hence, the asset price, are those that drive stock volatility and volatility-related risk-premiums. A question for future research is to explore whether the no-arbitrage framework in this paper can be used to improve forecasts of real economic activity.

In fact, stock volatility and volatility risk-premiums are driven by business cycle factors. An even more challenging and fundamental question is to explore the extent to which business cycle, stock volatility and volatility risk-premiums do endogenously develop.

The volatility in global equity markets since late summer 2011 continues to attract widespread media and investor attention. Much of the commentary has focused on perceived causes for the volatility—such as the growth of hedge funds, high-frequency trading, quantitative investment programs, and vehicles such as exchange-traded funds (ETFs), specifically, leveraged and inverse ETFs. Little focus, meanwhile, has been placed on the global macro environment, which faces the continuing Eurozone debt crisis; the prospect of a slowing global economy; political brinkmanship in Washington, D.C., including the failure of the super committee created by the U.S. Congress to help reduce the national debt; and the rating downgrade of U.S. Treasury bonds from their AAA status by Standard & Poor’s in early August 2011.

Fig-2: Daily percentage change in price of S &P 500 index

All investments are subject to risk. Foreign investing involves additional risks, including currency fluctuations and political uncertainty. Investments in bond funds are subject to interest rate, credit, and inflation risk. U.S. government backing of Treasury or agency securities applies only to the underlying securities and does not prevent share-price fluctuations. Unlike stocks and bonds, U.S. Treasury bills are guaranteed as to the timely payment of principal and interest. Diversification does not ensure a profit or protect against a loss in a declining market. There is no guarantee that any particular asset allocation will meet your investment objectives or provide you with a given level of income. Past performance is no guarantee of future returns. The performance of an index is not an exact representation of any particular investment, as you cannot invest directly in an index.

Fig-3: Relationship between equity market volatility and economic volatility 

“Volatility in economic conditions” is defined here as the annualized rolling standard deviation over 36 months through December 31, 2011, in the Federal Reserve Bank of Philadelphia’s Aruoba-Diebold-Scotti Business Conditions Index, which is designed to track real business conditions at high frequency. The index’s underlying (seasonally adjusted) economic indicators (weekly initial jobless claims, monthly payroll employment, industrial production, personal income less transfer payments, manufacturing and trade sales, and quarterly real gross domestic product) blend high- and low-frequency information and stock and flow data. Volatility in the S&P 500 Index is defined here as the annualized rolling standard deviation over the 36 months through December 31, 2011, in the price returns of the index.

Fig-4: Intraday volatility is calculated as daily range of trading prices (high–low/open) for the Dow Jones Industrial Average. 

To be sure, the 2000s have so far witnessed two severe bear markets and an extreme level of volatility and risk during the global financial crisis, yet it’s important to note that between 2003 and 2007, stock market volatility and risk aversion were at all-time lows historically. And when we compared the first decade of the 2000s and 2011 with long-term history, do not support the theory. In fact, Figure 3 shows that volatility since 2000 has been on a par with the long-term averages (i.e., 1929–1999).

Standard deviation of S&P Index returns for selected periods:

Lasly, We also know that realized volatility is a critical factor in the equity risk premium (ERP)—that is, the extra return demanded by investors for investing in stocks instead of less risky assets such as bonds or cash. Indeed, periods of heightened volatility or risk can actually increase the forward ERP. Fortunately, according to data from Morningstar, most investors are not solely invested in equities, but instead have a mixture of assets that prevents them from being fully exposed to sudden stock market volatility. So, although we understand that these can be unsettling times for investors, those who have determined an appropriate asset allocation, who employ broad diversification, and who rebalance as necessary are in a better position to weather this period of uncertainty, as well as the inevitable market dislocations to come.

The political history showed that during the Great Depression, aggregate stock market volatility in a large number of advanced economies reached levels not seen before or since. Schwert (1989b) estimates that in the US, there was a two- to threefold increase in variability. According to his measure, the monthly variation of stock returns peaked at over 20 percent in 1932. Other developed countries experienced similar increases in volatility. This is all the more puzzling since macroeconomic series such as money growth and interest rates showed markedly smaller increases in variability . As a general rule, neither wars nor periods of financial panic appear to lead to significantly higher variability of equity returns over an extended period — despite the highly unstable behavior of other macroeconomic series. Recessions, however, are clearly associated with higher volatility . The argument that political risk during the Great Depression is partly to blame is supported by the recent finding that unusually high levels of synchronicity of individual stock returns contributed substantially to aggregate volatility .

The data on civic unrest and political stability is from the cross-national data set compiled by Arthur Banks under the auspices of the Center for Comparative Political Research at the State University of New York. In addition to a set of demographic and economic variables, it also contains information on the nature of the political system and social instability for a set of 166 over the period 1815-1973. Overall, the interwar data set for a number of countries that are developed today shows a relatively high level of political instability and violence. For most indicators of political uncertainty, the levels are twice the average observed in the larger data set. This is true of the number of assassinations, of general strikes, government crises, riots, and anti-government demonstrations. In three categories, the subsample actually appears more stable - there were fewer revolutions, purges and acts of guerrilla warfare than in the 166 country sample. The variability of the measures of political instability is considerable, ranging from a coefficient of variation of 3.9 in the case of revolutions to 1.98 for government crises. While Germany scores very high on almost all measures of political fragility, recording a total of 188 events of unrest, Switzerland marks the opposite extreme. Only three acts indicating instability are recorded - two assassinations (in 1919 and 1923) and one riot (in 1932). There is also plenty of change over time. While 1919 saw, for example, four times the average number of assassinations in the subsample of 10 countries, there were none in 1936-38. The number of anti-government demonstrations reached more than twice is average level in 1932, and the number of riots peaked in 1934 at almost twice its normal frequency. Unsurprisingly, the tendency of governments to resort to violent acts of repression also peaked during the tumultuous years of the Great Depression, with the frequency of purges reaching a high of 2.6 times its average level in 1934. Europe and the US experienced two waves of turmoil and increasing uncertainty. In each case, the continued existence of the established political and economic order was in question. Following the end of World War I and the Russian Revolution in 1917, chaos and civic unrest broke out in numerous countries. After the end of the Habsburg dynasty and the disintegration of the Austro-Hungarian Empire, a large number of new nation states was formed. In Germany, the Emperor abdicated; revolution came when Navy sailors mutinied and widespread strikes broke out. Returning troops supporting the Social Democratic government were fighting former comrades who sought to establish a German equivalent to the Soviet Union, led by two leading communist intellectuals of the day, Rosa Luxembourg and Karl Liebknecht . Right-wing putsches such as the Kapp Putsch in 1920 and the Hitler Putsch in 1923 destabilized the new democratic order, already undermined by the harsh terms of the Versailles treaty. Leading political figures such as Matthias Erzberger and Walter Rathenau fell victim to political murder. A Belgian-French invasion of the industrial heartland, the Ruhr, as well as Communist uprisings in Saxony and Thuringia compounded problems . In the years 1919-23, there were 13 government crises, the same number of riots, and three general strikes. In France, there were waves of strikes in 1919 and 1920, considered by some observers as "a concerted attack upon the structure of bourgeois society". Nonetheless, these attacks ultimately failed -the trade union activist Merrheim said he "found in France a revolutionary situation without ... any revolutionary spirit in the working classes" .

In the US and Britain, demobilizations and the end of war did not lead to the same degree of extreme instability as in continental Europe. However, the very sharp contractions in output and employment in 1920/21, engineered in part as an attempt to reduce prices and return to the gold standard at prewar parities, led to a considerable rise in worker militancy. This occurred against the background of a considerable strengthening of organized labor. As in the other belligerent countries, the position of labor had strengthened as a result of the war effort - governments recognized unions and encouraged cooperation between them and employers. Trade union membership in the TUC (Trades Union Congress) soared from 2.2 million in 1913 to 6.5 million

in 1920. In the data set, Britain records 39 riots between 1919 and 1922, 12 assassinations, 6 general or politically motivated strikes, and 5 major government crises over the period. The average number of days lost in industrial disputes soared from 4.2 million in 1915-18 to 35.6 million in 1919- 23, the highest recorded value. Dissatisfaction with the established order could take a number of forms. In the US, there were 5 assassinations and four general or politically motivated strikes in 1919-23. Only one riot broke out, but 17 anti-government demonstrations were recorded. The total number of strikes increased sharply, to 3,630 in 1919, involving 4.2 million workers . Fear of a Communist takeover took the form of the so-called "Red Scare". Following the founding of the Third International in March, two Communist parties were formed in 1919, and quickly became active in propaganda . In response to bombs mailed to politicians by terrorists, a widespread crack-down, led by the Justice Department's Radical Division under J. Edgar Hoover, began. The second half of the 1920s saw a considerable decline in worker militancy and political violence. The 'roaring twenties' brought prosperity to many countries, with some exceptions. The US economy expanded rapidly, France reaped the benefits of currency stabilization under Poincare, and Germany, with the help of foreign loans, experienced an upsurge in activity after the end of the hyper inflation . At the same time, Britain's economy - tied to gold at an overvalued exchange rate - continued to languish . But even in those countries that didn't experience booms, labor militancy was on the wane. With the exception of the general strike in Britain in 1926, labor movements created few troubles. The democracies of central Europe appeared to be stabilizing . Riots declined to less than one-third their average frequency in the preceding half-decade; government crises, which had been running at an average of more than 10 per year in the early 1920s, fell to 3 in 1927, 2 in 1928, and 5 in 1929. The second wave of unrest and politically motivated violence began in 1930, with the start of the Great Depression. Over the course of the crisis, industrial output in the US and Germany fell by 40-50 percent from peak to trough, and between a quarter and a fifth of all industrial workers were unemployed over the period 1930-38. In the face of massive capital outflows and pressure on reserves as a result of banking panics in Germany, Austria and the US, central banks first tried to defend the gold standard by a policy of deflation . Eventually, more and more countries abandoned the peg, either by devaluing or via a system of capital controls. Countries that remained on gold for a long time experienced the most severe contractions. France, which had initially avoided problems, eventually experienced major difficulties. Faced with a slump that extended into the second half of the 1930s, it was eventually forced to devalue in June 1937. Britain, which was amongst the first to abandon the gold standard, escaped relatively lightly.'' Recovery came faster and in a more robust way to the countries that abandoned gold first .

Economic difficulties were quickly reflected in the politics of the street and the factory floor. The total number of anti-government demonstrations soared from 22 in 1925-29 to 72 in 1930-34; riots rose from 62 to 108. The number of politically motivated general strikes increased from 7 to 10. In Germany, there is clear evidence that high rates of unemployment did much to boost the fortunes of the Communist party, already one of the strongest in the world . Recent research also demonstrates that areas in which incomes contracted particularly sharply saw the largest increase in votes for the Nazis . In Britain, the Bank of England decided to leave the gold standard instead of raising the (relatively low) discount rate - a decision that can only be understood as an attempt to avoid any further rise in unemployment, and the threat of instability that would follow from it .  Apprehensiveness was accentuated by the mutiny of the Royal Navy in the port of Inverness in 1931.

In the US, the Communist party expanded rapidly during the Great Depression, and union membership soared. As "Hoovervilles" spread around American cities, bitterness against the rich and civic unrest became more widespread. Arthur Schlesinger noted about the year 1931 that "a malaise was seizing many Americans, a sense at once depressing and exhilarating, that capitalism itself was finished" . The Hoover administration - despite its general willingness to balance the budget by whatever means necessary - opposed a cut in Army infantry units in 1931 because it would "lessen our means of maintaining domestic peace and order."  In a secret message to Congress, the President urged that troops be exempted from a 10 percent pay cut so that the nation would not have to rely on disaffected troops in case of internal troubles. William Z. Foster, one of the most outspoken Communists in the US, published his book Toward Soviet America in 1932. The party found rich grounds for its agitation amongst the millions of unemployed and impoverished . In the same year, the so-called Bonus Army marched on Washington - veterans demanding that their bonuses be paid ahead of time. It took cavalry, infantry and tanks, commanded by General Douglas MacArthur, to regain control .

Perhaps even more importantly, the crisis rapidly increased the chances of Franklin D. Roosevelt gaining office. While even the most conservative businessmen did not equate this with a communist take-over, worries about the continued existence of "capitalism as we know it" were

rampant. As Schlesinger noted, the "New York governor was the only presidential candidate in either major party who consistently criticized business leadership, who demanded drastic (if unspecified) changes in the economic system, who called for bold experimentation and comprehensive planning."  Worries about future economic policy was compounded by the increasing realization that a return to the so-called "New Era" of prosperity and growth was impossible. Faced with growing labor militancy and an increasing willingness to contemplate central planning among the mainstream parties, right-wing radicalism also began to gain a following. Some observers and politicians, including prominent US senators, began to call for a Mussolini-style government, and magazines such as Vanity Fair and Liberty argued the case for a dictatorship .(Voth,2002)

This paper provides a systematic approach to evaluate the impact of political elections on currency values and market volatility across 22 countries. We have found that there is a significant relationship between political uncertainty and financial crises after controlling for market contagion and differences in economic conditions. We have also discovered increased market volatility during political election and transition periods. We further confirmed the result of Radelet and Sachs (1998) that the defining element of financial crises is the vulnerability to panic, as measured by high levels of short-term debt to reserves. Another important predictor of crisis is the rapid buildup of bank claims.

Our results about political risk have a few interesting practical applications: First, our analysis suggests that emerging market governments should increase their vigilance against financial crisis during political election and transition periods.23 Second, investors should note that the odds of financial crisis tend to be much larger during the political election periods. Thus, proper protection or risk adjustment needs to be taken when making emerging market investment during those time periods. It is worth noting, however, political election does not necessarily lead to financial crisis.24 Thus, we would like to caution against using the result as a simple “sure-win” investment strategy. Third, the pricing of emerging market derivatives should not be based on assumption of constant market volatility. As a matter of fact, market volatility tends to be much higher during political election and transition periods.(Mei and Guo,2002)

(Zahid and Rajaguru,2010) paper investigated the impact of internal and external shocks on financial market whichcan affect the macroeconomic performance. Pakistan experienced major international and domestic political shocks during the decade starting May 1998 and thus makes it an interesting choice for such an analysis. An autonomy of the historical events unfolded in

Pakistan from 1999-2008 suggests that even the external shocks were the results of certain

policies of the ruling regime. We term these shocks as events and use Markov switching

process to perform an event analysis. The paper first lists a number of events unfolded

during the period under analysis using a variety of internet and published sources and then

identifies the nature and expected impact of these shocks based on a survey results. Finally,

empirical estimation is performed to determine the number of regime changes and the impact

of shocks on the currency market. Later, Granger causality within Markov switching VAR

framework is used to find evidence of financial market interlinkages. The shocks can affect

the macroeconomic performance through spillover effects from one sector of financial market

to another.

The empirical evidence of this paper suggests 2 regime changes with low and high volatile

periods in Pakistan during the period under analysis. The results show that the financial

market is expected to move between two regimes where the mean and variances are different

in each state. The empirical results are, in general, consistent with the expectations obtained

through of the survey methods. The political events are expected to have positive or negative

impact on the financial market consistent with the nature of shocks.

Finally, the empirical evidence on the market interlinkages supports the view that all three

markets under the broad category of financial market in Pakistan are closely interlinked. As

such, any shock that disturbs the currency market will have spillover effects on the stock and

money markets thus leading to slow down of the economy. These are interesting results and

have important policy implications. The findings of this paper suggest that regimes should be

mindful of an extreme political decision. Measures such as a reduction in fiscal spending (or

cutting budget deficits) and less reliance on external borrowing will help reduce country’s

exposure to shocks and her capability to absorb them.

REFERENCES

Corredi,Valentina,Walter Distaso and Antonio Male,2010,Macroeconomic Determinants of stock market volatility and volatility risk premium-London School of Economics.

Khalid,A.M.,and Gulassekaran Rajaguru,2010,The impact of Political events on Financial Market volatility using a Markov switching process.Bond University,WP no-43.

Mei,Jianping and LiminGuo,2002,Political uncertainty Financial crisis and Market volatility, NewYork University.

Voth,Hans-Joachim,2002,Why was stock market volatility so high during the great depression? Evidence from 10 countries during the interwar period.MIT,WP-02/09