Stock Returns

This paper investigates which events of World War II (WWII) the US investors (at that time) considered as turning points (structural breaks) of the war. The empirical study employs daily Dow Jones industrial average stock index and volatility from January 1939 to December 1945 and applies structural shift oriented test to determine endogenously the structural breaks during the WWII period. Results show that the majority of the wartime events (on and off the battlefield) labelled important by historians did result in structural breaks in both price movement and stock returns volatility (risk). These results have major implications for investors of the present and future. 1 Tsiakas is able to show that events during trading and non-trading hours both have substantial effect on both stock price and volatility. During wartime, events can take place during trading and non-trading hours. 2 According to Mazouz et al. (2009) investors under-react to both positive and negative shocks, irrespective of the magnitude of the shocks.

Event studies focus on the impact of particular types of firm-specific events on the prices of the affected firms' securities. In this paper, observed stock return data are employed to examine various methodologies which are used 111 event studies to measure security price performance. Abnormal performance is Introduced into this data. We find that a simple methodology based on the market model performs well under a wide variety of conditions.

This paper employs a components-jump volatility filter to investigate the possible market impact of political risk. The filter operates by identifying jump return dates, which are then associated with political events, allowing us to measure the market return and volatility effects of political announcements. Our empirical results show that political developments in Hong Kong have a significant impact on its market volatility and return. The results have some interesting implications for option pricing and political risk management.  2001 Published by Elsevier Science Ltd.

In spite of popularity and theoretical simplicity of the one-factor Capital Asset Pricing Model (CAPM) used in the valuation of financial assets, researchers are more concerned with the important extension proposed by , that is, the Three-Factor Pricing Model (TFPM). Alongside beta, average stock returns could be explained by some size and book-to-market supplementary effects. With these two complementary models, estimation of the cost of equity is carried out for the Tunisian banking sector. In order to account for inter-individual heterogeneity, estimation of parameters is conducted according to random coefficient specifications within the context of panel data analysis.

This study analyzes the effect of corporate bond rating changes by international agencies on stock prices. This topic has not yet been analyzed for the Spanish stock market, despite the growing importance of ratings in Spanish financial markets. On an efficient market, rating changes will only have an effect if they contain some new information. The results from an event study indicate that rating actions cause significant negative abnormal returns in issuing firms around the date of the announcement. This evidence indicates an informational effect related to downgrades, which supports the hypothesis that credit rating agencies provide information that may reduce the asymmetric information problem between firms and investors. In the case of upgrades, our results are compatible with a redistribution of wealth between bondholders and owners or with the reputation hypothesis.

This study contributes to the stock returns-inflation relation literature in developing countries by revisiting the issue with reference to the emerging economy, India. More specifically, it tests whether the Indian stock market provides an effective hedge against inflation using monthly data on real stock return, inflation and real activity from April 1980 to March 2004 and a two-step estimation procedure. Results of the study indicate that (i) the Indian stock market reflects future real activity; (ii) the negative stock returns-inflation relation emerges from the unexpected component of the inflation and (iii) this negative relation vanishes when we control for the inflation-real activity relation, thereby providing a strong support for Fama’s proxy effect hypothesis. The split sample analyses indicate that the Fama hypothesis is valid only in pre reform period. In the post reform period, real stock returns have been independent of inflation, i.e., the Fisher Hypothesis is valid.

Saunders (1993) and Hirshleifer and Shumway (2001) document the effect of weather on stock returns. The proposed explanation in both papers is that investor mood affects cognitive processes and trading decisions. In this paper, we use a database of individual investor accounts to examine the weather effects on traders. Our analysis of the trading activity in five major U.S. cities over a six-year period finds vistually no difference in individuals propensity to buy or sell equities on cloudy days as opposed to sunny days. If the association between cloud cover and stock returns documented for New York and other world cities is indeed caused by investor mood swings, our findings suggest that researchers should focus on the attitudes of market-makers, news providers or other agents physically located in the city hosting the exchange. NYSE spreads widen on cloudy days. When we control for this, the significance of the weather effect is dramatically reduced. We interpret this as evidence that the behavior of market-makers, rather than individual investors, may be responsible for the relation between returns and weather.

The foreign exchange rate fluctuations do create an
impact on stock returns, which has been
investigated for non-financial listed Pakistani firms. The real
effective exchange rate has been used as the true measure of foreign
exchange exposure. The modelled econometric equation includes;
firm size, firm liquidity, money supply and inflation as predictors
of stock returns. Twenty-five non-financial listed firms have been
evaluated for the study period 2004 to 2013, which signifies the
military regime era proceeded by peoples party rule in Pakistan.
Financial data analysis, including; ADF unit root and Johansen
Co-integration tests, have been applied to evaluate financial data,
which further led to correlation, descriptive stats and panel data
regression analysis. The results have suggested a very weak
relationship between stock returns and foreign exchange exposure.
Therefore, sample non-financial listed firms have not been foreign
exchange exposed; however, firm size, liquidity, money supply and
inflation rates have definitely created an impact on stock returns.

From the perspective of the agent-based model of stock markets, this paper examines the possible explanations for the presence of the causal relation between stock returns and trading volume. The implication of this result is that the presence of the stock price-volume causal relation does not require any explicit assumptions like information asymmetry, reaction asymmetry, noise traders, or tax motives. In fact, it suggests that the causal relation may be a generic property in a market modeled as evolving decentralized system of autonomous interacting agents.

We examine persistence in the conditional variance of U.S. stock returns indexes. Our results show evidence of long memory in high-frequency data, suggesting that models of conditional heteroskedasticity should be made flexible enough to accommodate these empirical findings. JEL classification : C22 * Corresponding author SSDI 0165-1765(94)00430-A 282 N. Crato, P.J.F. de Lima I Economics Letters 45 (1994) 281-285

E-commerce has changed the way of doing business in India. E-commerce provides various advantages to the consumers such as availability of goods and services at cheaper cost, wide options for shopping, saving time etc. in well-developed cities whereas people become more aware with e-commerce benefits. On the other hand, most of the people avoid the shopping through e-commerce portals due to some challenges like; Logistics and Supply chain, payment, Slow Internet, Return and cancellation, and poor customer services of the e-commerce. This study explores the various problems and challenges faced by the customers in the study area. The objective of the study is to analyse the various problems faced by the customers during the online transactions as well as the opinion of the customers about the problems and challenges of e-commerce in Varanasi and Prayagraj. The study was conducted through collection of primary data from 300 respondents in Varanasi and Prayagraj district. In this way, by analysing the data, it was identified that most people are agreed that they face problems during online shopping. The data analysis reveals the result of Percentage analysis test to find out the opinion of the respondents in the study area. Further, it is found that most of the people are agreed with the statement of the problems and challenges facing by them during online transactions so it is suggested that e-commerce portals need to decrease or overcome such problems.

Stock market returns are significantly correlated with inflation and money growth. The impact of real macroeconomic variables on aggregate equity returns has been difficult to establish, perhaps because their effects are neither linear nor time invariant. We estimate a GARCH model of daily equity returns, where realized returns and their conditional volatility depend on 17 macro series' announcements. We find six candidates for priced factors: three nominal (CPI, PPI, and a Monetary Aggregate) and three real (Balance of Trade, Employment Report, and Housing Starts). Popular measures of overall economic activity, such as Industrial Production or GNP are not represented.

This study examines the nature of the linkages between stock market prices and exchange rates in six advanced economies, namely the US, the UK, Canada, Japan, the euro area, and Switzerland, using data on the banking crisis between 2007 and 2010. Bivariate GARCH-BEKK models are estimated producing evidence of unidirectional spillovers from stock returns to exchange rate changes in the US and the UK, in the opposite direction in Canada, and of bidirectional spillovers in the euro area and Switzerland. Furthermore, causality-invariance from stock returns to exchange rates changes is found in Japan and in the opposite direction in the euro area and Switzerland, whilst there is evidence of bidirectional feedback in the US and Canada. These findings imply limited opportunities for investors to diversify their assets during this period.

Investors are forever in need of an asset that adds value to the portfolio. Therefore, along with fixed income investments, stocks, gold and other assets are inevitable parts of a balanced portfolio. For Indian investors, gold is not only an investment asset but a commodity with a major importance in the social customs that makes it all the more interesting to study. As an investment asset, it is considered a diversifier asset and a hedging asset. Not only that, it is called a ‘safe-haven’ asset for times of economic distress, meaning that it retains its value when the stock market is giving low or negative returns. In this paper, we analyze the risk-return parameters of both the gold and Sensex for a period from 1992 to 2017 and find out how they perform along with each other. We also do detailed subperiod analysis in terms of Pearson’s correlation coefficient and see how it changes in pre-recession and post-recession period. We analyze whether gold is a diversifier asset, a hedge,...

We examine the predictability of stock market returns by employing a new metric entropy measure of dependence with several desirable properties. We compare our results with a number of traditional measures. The metric entropy is capable of detecting nonlinear dependence within the returns series, and is also capable of detecting nonlin-ear\a±nity" between the returns and their predictions obtained from various models thereby serving as a measure of out-of-sample goodness-of-¯t or model adequacy. Several models are investigated, including the linear and neural-network models as well as nonparametric and recursive unconditional mean models. We¯nd signi¯cant evidence of small nonlinear unconditional serial dependence within the returns series, but fragile evidence of superior conditional predictability (pro¯t opportunity) when using market-switching versus buy-and-hold strategies.

Extreme returns in stock returns need to be captured for a successful risk management function to estimate unexpected loss in portfolio. Traditional value-at-risk models based on parametric models are not able to capture the extremes in emerging markets where high volatility and nonlinear behaviors in returns are observed. The Extreme Value Theory (EVT) with conditional quantile proposed by McNeil and Frey (2000) is based on the central limit theorem applied to the extremes rater than mean of the return distribution. It limits the distribution of extreme returns always has the same form without relying on the distribution of the parent variable. This paper uses 8 filtered EVT models created with conditional quantile to estimate value-at-risk for the Istanbul Stock Exchange (ISE). The performances of the filtered expected shortfall models are compared to those of GARCH, GARCH with student-t distribution, GARCH with skewed student-t distribution and FIGARCH by using alternative back-t...

In this study, we test whether the overconfidence bias explains several stylized market anomalous, including a short-term continuation (momentum), a long-term reversal in stock returns, high levels of trading volume and excessive volatility. Using data of French stocks market, we find empirical evidence in support of overconfidence hypothesis. First, based on a restricted VAR framework, we show that overconfident investors overreact to private information and underreact to public information. Second, by performing Granger-causality tests of stock returns and trading volume, we find that overconfident investors trade more aggressively in periods subsequent to market gains. Third, based on a two GARCH specifications, we show that self attribution bias, conditioned by right forecasts, increases investors overconfidence and trading volume. Fourth, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a contribution to the observed excessive volatility.

This paper investigates the role incremental information content of inflation-adjusted data plays in explaining the market value of equity and stock returns on the Istanbul Stock Exchange (ISE). We show the effect of inflation accounting application on basic financial ratios, and we test the value relevance of inflation-adjusted and historical cost-based book value and earnings. The findings show that inflation adjustment affects financial ratios significantly, which may create different risk assessments for the selected firms. Furthermore, the results indicate that both inflation-adjusted and historical cost-based earnings and book values are significantly value relevant. The two sets of data are not to be used as substitutes, but, rather, they are complementary. For this reason, inflationadjusted data should be required as supplementary data to the historical cost information rather than in place of historical cost data.

We demonstrate significant interdependencies in stock returns across different segments of the insurance industry. Return interdependency is strongest between property and casualty (P&C) and accident and health (A&H) insurers, and weakest between life (Life) insurers and insurers from the other segments. We do not find empirical support for the existence of significant volatility transmission across the three segments. In terms of market and interest rate betas, we find that market risk is greatest for A&H insurers, followed by Life insurers and P&C insurers, while interest rate sensitivity is greater for Life insurers than that for A&H and for P&C insurers. The findings on stock return interdependencies across insurance segments complement research on diversification and focus strategies, while the results on market and interest rate risk complement the literature on insurer financial strength.

Firm valuation has been an important domain of interest for finance. However, most financial models do not include customer-related metrics in this process. Studies in marketing have found that one particular customer metric, customer satisfaction, improves the ability to predict future cash flows, long-term financial measures, stock performance, and shareholder value. However, most of these studies predominantly employ models that are not directly used in finance practice. This article extends existing literature by examining the impact of customer satisfaction on firm valuation by employing multiples and risk-adjusted abnormal return models borrowed directly from the practice of finance. Data include 3600 firm-quarter observations from the American Customer Satisfaction Index, COMPUSTAT, and Center for Research in Securities Prices databases from 1996 to 2006. The results indicate that a portfolio of stocks consisting of firms with high levels and positive changes in customer satisfaction will outperform the other three possible portfolio combinations (low levels and negative changes, low levels and positive changes, and high levels and negative changes in customer satisfaction) along with Standard & Poor's 500. Initially, the stock market undervalues positive satisfaction information, but the market adjusts in the long run.

Over time, estimates of multivariate market model coefficients for commercial bank stock returns have shown varying sensitivity to changes in market price, interest rates, and foreign exchange rates. One component which has developed significant explanatory power in recent years is basis risk, defined as a change in spread between the prime rate and an average of the LIBOR and Fed funds rates. The basis risk component is inversely related to the (change in commercial and industrial loans less core deposits)/assets.

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [

In the field of optimisation models for passive investments, we propose a general portfolio construction model based on principal component analysis. The portfolio is designed to replicate the first principal component of a group of stocks, instead of a traditional benchmark, thus capturing only the common trend in the stock returns. The main advantage of this approach is that the reduction of the noise present in stock returns facilitates the replication task considerably and the optimal portfolio structure is very stable.

This work presents a new prediction-based portfolio optimization model that can capture short-term investment opportunities. We used neural network predictors to predict stocks' returns and derived a risk measure, based on the prediction errors, that have the same statistical foundation of the mean-variance model. The efficient diversification effects holds thanks to the selection of predictors with low and complementary pairwise error profiles.

Following the Brown-Warner simulation approach and using Chilean daily security return data we examine the specification and power of three parametric t-tests commonly employed in event studies: the standardized, the cross-sectional and the portfolio t-test. Our findings show that although individual security returns and security abnormal returns are evidently nonnormal, the cross-sectional mean abnormal returns converge to normality as the sample size increases. Thus, in event study setting involving event period of one day, methods based on the use of parametric t-tests seem to be well specified, at least at the 5% significance level. In terms of power, our simulation results show the standardized t-test always more likely to detect the presence of an abnormal return that its two parametric competitors: the cross-sectional and the portfolio t-test. We also find, however, that the power of the three t-tests is very sensitive to either the sample size or the length of the event period.

This article investigates the relationship between stock returns and inflation in four high inflation (Latin and Central American) countries: Argentina, Chile, Mexico and Venezuela. Compared to the bulk of the previous research (involving low inflation) this article provides evidence of a positive relationship between current stock market returns and current inflation. This result confirms that stock returns act as a hedge against inflation. Results also show that past rates of inflation also influence the current rate of stock returns. Similar tests are conducted using real rate of stock returns. Some evidence of an inverse relationship between current real returns and current and one-period lagged inflation is found.

A zero-cost portfolio that takes a long (short) position in stocks with the least (most) diversified individual investor clientele generates an annual, risk-adjusted return of 5-9%. This spread reflects the combined effects of sentiment-induced mispricing, narrow risk framing, and asymmetric information, where the sentiment effect is the strongest. Furthermore, the influence on returns is stronger among smaller, low institutionally owned, and hard-to-arbitrage stocks. These results are robust to concerns about relatively short sample size, improper factor model specification, slow information diffusion, and high transactions costs. r 2007 Elsevier B.V. All rights reserved. JEL classification: G11; G12

We examine the association between the provision of non-audit services and earnings quality. Because of concerns regarding the effect of non-audit services on financial reporting credibility, the Securities and Exchange Commission recently issued revised auditor independence rules requiring firms to disclose in their annual proxy statement the amount of fees paid to auditors for audit and non-audit services. Using data collected from proxy statements filed between February 5, 2001 and June 15, 2001, we present evidence that firms purchasing more non-audit services from their auditor are more likely to just meet or beat analysts' forecasts and to report larger absolute discretionary accruals. However, the purchase of non-audit services is not associated with meeting other earnings benchmarks. We also find that the unexpected component of the non-audit to total fee ratio is negatively associated with stock returns on the filing date. These results are consistent with arguments that the provision of non-audit services strengthens an auditor's economic bond with the client and that investors price this effect.

corporations do not issue and repurchase debt and equity to counteract the mechanistic effects of stock returns on their debt-equity ratios. Thus over one-to five-year horizons, stock returns can explain about 40 percent of debt ratio dynamics. Although corporate net issuing activity is lively and although it can explain 60 percent of debt ratio dynamics (long-term debt issuing activity being most capital structure-relevant), corporate issuing motives remain largely a mystery. When stock returns are accounted for, many other proxies used in the literature play a much lesser role in explaining capital structure.

Executives can only impact firm outcomes if they have influence over crucial decisions. On the basis of this idea, we develop and test the hypothesis that firms whose CEOs have more decision-making power should experience more variability in performance. Focusing ...

This paper investigates the relationship between stock returns and inflation
in India during 1991:4 to 2009:3. Weekly, monthly and quarterly indexes
of BSE Sensex and NSE Nifty are used. Weekly, monthly and quarterly
Wholesale Price Index (WPI) and monthly Consumer Price Index (CPI) are
used as measures of inflation. The analysis is also carried for the subperiod
2002:4-2009:3, and the pre-crisis and post-crisis analysis is conducted
through the analysis of the subperiod 2005:1-2009:4. Unit root tests,
Granger causality test and regressions are performed for examining the
nexus between the variables. Vector Autoregression (VAR) methodology
has been employed to investigate the causal link between stock returns and
inflation. Impulse Response Functions (IRF) check the response to
disturbance in the system. The results suggest that there is no significant
relation between stock returns and inflation in post-reform period in India.

Assessing the sensitivity of firm value to exchange rate changes has been one of the most challenging issues in international financial management over the last two decades. This paper reviews the rapidly growing exchange exposure literature, with particular reference to recent developments. The studies reviewed focus on two primary areas of inquiry: the theoretical foundations of exchange risk exposure and the empirical evidence on the link between stock returns and currency fluctuations. Although much has been learned in each field, this survey highlights the areas of research in which our understanding of the mechanism of exchange exposure is still incomplete.

In this study, we test whether the overconfidence bias explains several stylized market anomalous, including a short-term continuation (momentum), a long-term reversal in stock returns, high levels of trading volume and excessive volatility. Using data of French stocks market, we find empirical evidence in support of overconfidence hypothesis. First, based on a restricted VAR framework, we show that overconfident investors overreact to private information and underreact to public information. Second, by performing Granger-causality tests of stock returns and trading volume, we find that overconfident investors trade more aggressively in periods subsequent to market gains. Third, based on a two GARCH specifications, we show that self attribution bias, conditioned by right forecasts, increases investors overconfidence and trading volume. Fourth, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a...

In this paper we employ a Markov-Switching EGARCH model to investigate the dynamic linkage between stock price volatility and exchange rate changes for four emerging countries over the period 1994-2009. Results distinguish between two different regimes in both the conditional mean and the conditional variance of stock returns. The first corresponds to a high mean-low variance regime and the second regime is characterized by a low mean and a high variance. Moreover, we provide strong evidence that the relationship between stock and foreign exchange markets is regime dependent and stockprice volatility responds asymmetrically to events in the foreign exchange market. Our results demonstrate that foreign exchange rate changes have a significant impact on the probability of transition across regimes.