Stock Price Variations Research Articles

Do Monetary and Technology Shocks Move Euro Area Stock Prices?

I use a Bayesian vector autoregressive (VAR) model to investigate the impact of monetary and technology shocks on the euro area stock market in 1987-2005. I find an important role for technology shocks, but not monetary shocks, in explaining variations in real stock prices. The identification method is flexible enough to study the effects of technology news shocks. The responses are consistent with the idea that news on technology improvements have an immediate impact on stock prices. These findings are robust to several modeling choices, including the productivity measure, omitted variables, and the identifying restrictions.

A network perspective of the stock market

Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded over two periods of time (from July 2005 to August 2007; and from June 2007 to May 2009). The nodes are the stocks, and the connections are determined by cross correlations of the variations of the stock prices, price returns and trading volumes within a chosen period of time. Specifically, a winner-take-all approach is used to determine if two nodes are connected by an edge. So far, no previous work has attempted to construct a full network of US stock prices that gives full information about their interdependence. We report that all networks based on connecting stocks of highly correlated stock prices, price returns and trading volumes, display a scalefree degree distribution. The results from this work clearly suggest that the variation of stock prices are strongly influenced by a relatively small number of stocks. We propose a new approach for selecting stocks for inclusion in a stock index and compare it with existing indexes. From the composition of the highly connected stocks, it can be concluded that the market is heavily dominated by stocks in the financial sector.

Accounting Fundamentals and the Variation of Stock Price: Factoring in the Investment Scalability

This study develops a new return model with respect to accounting fundamentals. The new return model is based on Chen and Zhang (2007). This study takes into account theinvestment scalability information. Specifically, this study splitsthe scale of firm’s operations into short-run and long-runinvestment scalabilities. We document that five accounting fun-damentals explain the variation of annual stock return. Thefactors, comprised book value, earnings yield, short-run andlong-run investment scalabilities, and growth opportunities, co associate positively with stock price. The remaining factor,which is the pure interest rate, is negatively related to annualstock return. This study finds that inducing short-run and long-run investment scalabilities into the model could improve the degree of association. In other words, they have value rel-evance. Finally, this study suggests that basic trading strategieswill improve if investors revert to the accounting fundamentals.Keywords: accounting fundamentals; book value; earnings yield; growth opportuni­ties; short­run and long­run investment scalabilities; trading strategy;value relevance

Dividend Smoothing and Predictability

The relative predictability of returns and dividends is a central issue since it forms the paradigm to interpret asset price variation. A little studied question is how dividend smoothing, as a choice of corporate policy, affects predictability. We show that, even if dividends are supposed to be predictable without smoothing, dividend smoothing can bury this predictability in a finite sample. We further show that aggregate dividends are dramatically more smoothed in the postwar period than before. Therefore, the lack of dividend growth predictability in the postwar period, as widely documented in the literature, does not necessarily mean that there is no cash flow news in stock price variations; rather, a more plausible interpretation is that dividends are smoothed. Using two alternative measures that are less subject to dividend smoothing -- net payout and earnings -- we reach the consistent conclusion that cash flow news plays a more important role than discount rate news in price variations in the postwar period. Our take-away messages are that (i) dividend smoothing can severely affect dividend predictability in a finite sample, (ii) there is significant cash flow news in stock price variations, and (iii) when smoothed, dividends do not represent well the outlook of future cash flows.

Asymmetric Volatility and Cross Correlations in Stock Returns under Risk and Uncertainty

Capital market efficiency is a matter of great interest for policy makers and investors in designing investment strategy. If efficient market hypothesis (EMH) holds true, it will prevent the investors to realize extra return by utilizing the inherent information of stocks. They will realize extra returns only by incorporating the extra risky stocks in their portfolios. While empirical tests of EMH and risk-return relationship are plentiful for developed stock markets, the focus on emerging stock markets like India, Pakistan, Sri Lanka, etc., began with the liberalization of financial systems in these markets. With globalization and deregulation, the enormous opportunities of investment in South Asian stock markets have attracted the domestic and foreign institutional investors in general, and to reduce their portfolio risk by diversifying their funds across the markets in particular. The efforts are made in this study to examine the cross-correlation in stock returns of South Asian stock markets, their regional integration, and interdependence on global stock market. The study also examines the important aspects of investment strategy when investment decisions are made under risk and uncertainty. The study uses Bombay stock exchange listed index BSE 100 for India, Colombo stock exchange listed Milanka Price Index for Sri Lanka, Karachi stock exchange listed KSE 100 for Pakistan, Dhaka stock exchange listed DSE-General Index for Bangladesh, and S & P Global 1200 to represent the global market. It carries out a comprehensive analysis, tracing the autocorrelation in stock returns, cross correlations in stock returns under risk and uncertainty, interdependency among the South Asian stock markets, and that with the global stock market. The research methodology applied in the study includes application of Ljung-Box to examine the cross-correlation in stock returns, ARCH and its generalized models for the estimation of conditional and asymmetric volatilities, and Ljung-Box as a diagnostic testing of fitted models, and finally correlation to examine the interdependency of these markets in terms of stock returns and expected volatility. The results bring out the following: L-B statistics suggests the presence of autocorrelation in stock returns in all Asian stock markets; however, for the global market, autocorrelations are significant at 15 lags, and thereafter they are insignificant. The significant autocorrelations in stock returns report volatility clustering in stock returns, reject the EMH, and hold that current stock returns are significantly affected by returns being offered in the past. ARCH and its generalized models significantly explain the conditional volatility in all stock markets in question. The study rejects the relationship between stock returns and expected volatility; however, the relationship is significant with unexpected volatility. It brings out that investors adjust their risk premium for expected variations in stock prices, but they expect extra risk premium for unexpected variations. With their entry into the liberalization phase, South Asian stock markets have reported regional interdependence, and also interdependence with the global stock market.

OIL PRICE SHOCKS AND STOCK MARKET BOOMS IN AN OIL EXPORTING COUNTRY

ABSTRACTThis paper analyses the effects of oil price shocks on stock returns in Norway, an oil‐exporting country, highlighting the transmission channels of oil prices for macroeconomic behaviour. To capture the interaction between the different variables, stock returns are incorporated into a structural VAR model. I find that following a 10% increase in oil prices, stock returns increase by 2.5%, after which the effect gradually dies out. The results are robust to different (linear and non‐linear) transformations of oil prices. The effects on the other variables are more modest. However, all variables indicate that the Norwegian economy responds to higher oil prices by increasing aggregate wealth and demand. The results also emphasize the role of other shocks; monetary policy shocks in particular, as important driving forces behind stock price variability in the short term.

Do size and unobservable company factors explain stock price reversals?

We use daily price data from the Egyptian stock market and a Loser portfolio of 20 IPOs from the late 1990s that experienced dramatic 1-day price falls in the period 2004 to 2007 to estimate a 2-way fixed effects model of CARs. Observable covariates are company size and turnover growth and unobservables company and period fixed effects. Our results provide evidence of significant price reversal over the first 40 post-event days. Firm size is negatively correlated with post-event CARs, consistently with the argument that small firms have a stronger tendency to price-reverse due to greater informational opacity. But permanent, unobservable company-specific factors, account for a much larger percentage of post-event variation in stock prices and indicate an underlying heterogeneity in investor responses to initial price falls not uncovered before in the literature. Strong negative company effects following a price fall are found to presage reinforcing ‘long term’ price falls and strong positive company effects to presage countervailing ‘long term’ price reversals. At the extremes these company effects are sufficiently large to suggest that a trading strategy based on them would be profitable.

Fiscal Policy, Housing and Stock Prices

This paper investigates the link between fiscal policy shocks and movements in asset markets using a Fully Simultaneous System approach in a Bayesian framework. Building on the works of Blanchard and Perotti (2002), Leeper and Zha (2003), and Sims and Zha (1999, 2006), the empirical evidence for the U.S., the U.K., Germany, and Italy shows that it is important to explicitly consider the government debt dynamics when assessing the macroeconomic effects of fiscal policy and its impact on asset markets. In addition, the results from a VAR counter-factual exercise suggest that: (i) fiscal policy shocks play a minor role in the asset markets of the U.S. and Germany; (ii) they substantially increase the variability of housing and stock prices in the U.K..; and (iii) government revenue shocks have apparently contributed to an increase of volatility in Italy.

Fiscal Policy, Housing and Stock Prices

This paper investigates the link between fiscal policy shocks and movements in asset markets using a Fully Simultaneous System approach in a Bayesian framework. Building on the works of Blanchard and Perotti (2002), Leeper and Zha (2003), and Sims and Zha (1999, 2006), the empirical evidence for the U.S., the U.K., Germany, and Italy shows that it is important to explicitly consider the government debt dynamics when assessing the macroeconomic effects of fiscal policy and its impact on asset markets. In addition, the results from a VAR counter-factual exercise suggest that: (i) fiscal policy shocks play a minor role in the asset markets of the U.S. and Germany; (ii) they substantially increase the variability of housing and stock prices in the U.K.; and (iii) government revenue shocks have apparently contributed to an increase of volatility in Italy. JEL Classification: C32, E62, G10, H62 (This abstract was borrowed from another version of this item.)

Optimal trading range and firm value around the Asian financial crisis

The cross-sectional share price variation in eight East Asian markets before, during and after the 1997 Asian financial crisis is examined. The paper also studies whether firms in these markets correct their share prices to the optimal trading range using stock splits. The results vary across countries, across firms and across periods. Although some anomalies in some markets are found, most results are consistent with Merton's (1987) investor recognition hypothesis in an incomplete information market. Small firms as less-recognised firms choose low prices to attract small shareholders, thus increasing their shareholder base and the firm's value. Ownership concentration and corporate governance are found to be very important in explaining cross-sectional stock price variation. Specifically, small firms in Hong Kong, Malaysia and Thailand made stock splits to maintain their preferred share prices.

Dividend Smoothing and Predictability

The relative predictability of returns and dividends is a central issue because it forms the paradigm to interpret asset price variation. A little studied question is how dividend smoothing, as a choice of corporate policy, affects predictability. We show that even if dividends are supposed to be predictable without smoothing, dividend smoothing can bury this predictability. Because aggregate dividends are dramatically more smoothed in the postwar period than before, the lack of dividend growth predictability in the postwar period does not necessarily mean that there is no cash flow news in stock price variations; rather, a more plausible interpretation is that dividends are smoothed. Using two alternative measures that are less subject to dividend smoothing—net payout and earnings—we reach the consistent conclusion that cash flow news plays a more important role than discount rate news in price variations in the postwar period. This paper was accepted by Wei Xiong, finance.

Inflation, Monetary Policy and Stock Market Conditions: Quantitative Evidence from a Hybrid Latent-Variable VAR

This paper examines the association between inflation, monetary policy and U.S. stock market conditions during the second half of the 20th century. We use a latent-variable VAR to estimate the impact of inflation and other macroeconomic shocks on a latent index of stock market conditions. Our objective is to investigate the extent to which various shocks contribute to changes in market conditions, above and beyond their direct effects on real stock prices. We find that disinflation shocks promote market booms and inflation shocks contribute to busts. Further, we find that inflation shocks can explain more of the variation in real stock prices when stock market conditions are taken into account.

High Dividend Yield Does Predict Lower Dividend Growth: A Natural Experiment

Today, many financial economists believe that the time variability in expected returns is the dominant component of stock price variability. This modern-day view of stock prices is, nevertheless, dissatisfactory. According to Cochrane (2001, p. 398), is nonetheless an uncomfortable fact that almost all variation in price/dividend ratios is due to variation in expected excess returns. How nice it would be if high prices reflected expectations of higher future Very recently, dividend predictability has been critically re-examined by Ang and Bekaert (2007), Ang and Liu (2007), Bansal and Yaron (2004), Lettau and Ludvigson (2005), and Menzly, Santos, and Veronesi (2004). These efforts have so far shown that dividend growth is predictable, but have stopped short of presenting evidence of a desirably negative relation between dividend yields and expected dividend growth. In fact, Ang and Bekaert (2007) found the dividend yield coefficient in dividend growth predictive regression over the 1952-2001 period to be surprisingly positive. Why is it that the apparently intuitive relation between high prices relative to dividends today and high dividend growth in the future cannot be successfully uncovered in stock market data? This study argues that a potential reason for this is that dividends are usually poor measures of true value-relevant cashflows. It is well known that dividends are often smoothed, manipulated, censored at zero, related to perceived mispricing, and subject to structural shifts in corporate financial policy. Based on this observation, this study contributes to the current surge of interest in re-examining the predictability of dividend growth from dividend yields via a different empirical strategy. Specifically, we focus our study on a unique subset of U.S. stocks-equity real estate investment trust (REIT) stocks, whose dividends are arguably good measures of true value-relevant cashflows. REITs typically adopt a stable dividend policy and pay out almost all of their cashflows from operations as dividends. During the 1980-2000 period, REITs paid out an average 110% of taxable income. The study finds that, when dividends reasonably capture true value-relevant cashflows, expected dividend growth is forecastable from dividend yields. Furthermore, the empirical relation between dividend yields and expected dividend growth is desirably negative, which is consistent with the usual prediction of the present value model. At the three-year predictive horizon, the bootstrapped adjusted dividend yield coefficient is -1.09 with a bootstrapped t-statistic of -14.14. The OLS R2 value is 35.48%.

A model for stock market returns: non-Gaussian fluctuations and financial factors

While there are various theories to account for the large variations in stock prices, some observed statistical aspects require further analysis. A model is proposed for aggregate stock prices, based on observed data, rather than any efficient market hypothesis, and considering jumps in statistical parameters between phases of generally increasing, or generally decreasing, aggregate stock prices. The model relates a critical parameter for short-term behaviour directly to financial factors, especially interest rates, to explain large short-term variations which follow a non-Gaussian distribution. Economic fundamentals may affect changes over longer periods.

Behavior of Stock Price Variability over Trading and Nontrading Periods, and Daily Return Volatility

This study examined the behavior of stock price variability over trading and nontrading periods, and daily return volatility. This study used intraday data in Indonesia Stock Exchange. Sample was taken from the firms listed in LQ 45 indexes for the year of 1999-2006. The behavior of stock price variability and daily return volatility, according to previous theories, is influenced by the array of public and private information.This study concludes that return variance over trading and nontrading periods, along with overnight and lunch break nontrading session, and the first and second trading session, has differed significantly. In addition, daily return volatility is also not identical significantly. Subsequently, this study used size, trading volume, bid-ask spreads and up-down market as control variables. This study contradicts to all prior studies. This study especially suggests contra evidence in comparisons with previous concepts and theories in regards to size, trading volume, bid-ask spreads, and up-down market as control variables.

Volatility of stock price as predicted by patent data: An MGARCH perspective

Abstract This paper proposes to model stock price volatility and variations in innovation effort using a Multivariate GARCH structure designed to extract information for risk prediction. The salient feature is that the model order, alongside other parameters, is endogenously determined by the estimation procedures. Using stock prices of U.S. computer firms, it is found that the model can pick up the correlation between the two variables and aid in producing accurate Value-at-Risk estimates.

KEINFORMATIFAN HARGA SAHAM DALAM KAITANNYA DENGAN EFISIENSI INVESTASI

According to the Efficient Market Hypothesis, greater firm specific stock price variation reflects higher intensity firm specific information capitalization in stock price. In this study we propose that higher firm specific price variation maybe an indicator of greater functional-form market efficiency. We regress PER (Price to Earning Ratio) as a proxy of efficiency of investment as a function of Y (Firm Specific Stock Price Variation) as a proxy of firm specific information capitalization in stock price. We provide new evidence that Indonesian Capital Market does not efficient yet because the result at 2003 and 2004 does not consistent. With coefficient determination (IV) only 25.27% show that we should include another explanatory variable to explain about investment efficiencyKeywords: Firm-Specific Stock Price Variation, Investment Efficiency, Efficient Market Hypothesis

“What if the Fed increased the weight of the stock price gap in its reaction function?”

The Fed has never admitted targeting stock prices. Yet, our empirical analysis, based on a small macroeconometric model of the U.S. economy in the period 1981–2002, shows that the Fed explicitly takes into account stock price variations in its reaction function. Furthermore, our simulation results suggest that increasing the weight attributed to stock price changes could prove advisable, as the stock market wealth effect increases. This measure would help to contain the additional instability brought about by this economic evolution, and confirm the current political trend towards protecting stock owners.

Was There a “Vernacular Science of Financial Markets” in France during the Nineteenth Century? A Comment on Preda's “Informative Prices, Rational Investors”

This article deals with the emergence of the random walk hypothesis and the nineteenth-century “Science of Financial Investments”. It examines the relevance to explain this emergence thanks to an international “vernacular science of financial markets”, as Alex Preda (2004) suggested. The article shows that 1) there is no existence of such an international “vernacular science of financial markets”; 2) the relevance of the distinction between vernacular economics and academic economics for economic or financial theoretical work in nineteenth-century France remains unclear. Finally, this distinction is not enough for explaining the introduction of the random walk hypothesis by Regnault (1863). Although Regnault’s book felt within a global movement, it took place in academic debates and had no similitude with other financial publications of that time: indeed, before Bachelier (1900), the use of the probability calculus to analyze and to give a theoretical explanation to stock price variations was not common.

An extension of price improvement debate: The case of American Depository Receipts (ADRs)

We empirically test whether the change in minimum stock price variation (shifting from the eighth to sixteenth) in the late 90s in NYSE, followed by a system of full decimalization had any significant price improvement on the American Depository Receipts (ADRs). The trade data for August 1996 and August 1997 were included in the sample. Twenty-one trading days were selected in each year. Trades for each day in 1996 were matched with trades for each day in 1997. Price improvements were calculated before the change in minimum variation and after. The data was processed through a multi-stage filtering process: retrieve and filter raw data, match trades with quotes, calculate price improvements, perform paired t-tests, analyze the data and distribution graphs. The results did not reveal any consistent pattern of price improvement in the case of ADRs. Changing the minimum variation of stock pricing from 1/8 to 1/16 of a US dollar appears to have affected price improvement in almost 50% of the ADRs under analysis. No statistically significant connection is determined between the minimum price variation of ADRs and price improvement.