WHAT DRIVES THE TIME‐SERIES AND CROSS‐SECTIONAL VARIATIONS IN BANK CAPITAL RATIOS? EVIDENCE FROM JAPAN

This paper documents the time‐series and cross‐sectional variations in bank capital ratios and investigates their underlying driving forces using listed Japanese bank data from 1977 to 2009. We derive an overall framework in the form of a present‐value model to decompose the variation in bank capital ratios into changes in expected future stock returns, profitability and leverage ratios. Moreover, we use the variance decomposition approach to examine the relative importance of these factors. We find that the expected future stock returns dominate the time‐series variation in bank capital ratios, and that the expected future profitability also plays an important role as the expected stock returns in the cross‐sectional variation.     

Oil Price Shocks and Volatility in Australian Stock Returns

This paper examines the effect of oil shocks on return and volatility in the sectors of Australian stock market and finds significant effects for most sectors. For the overall market index, an increase in oil price return significantly reduces return, and an increase in oil price return volatility significantly reduces volatility. An advantage of looking at sector returns rather than a general index of stock returns is that sectors may well differ markedly in how they respond to oil price shocks. The energy and material sectors (as expected) and the financial sector (surprisingly) are out of step (in different ways) with results for the other sectors and for the overall index. A rise in oil price increases returns in the energy and material sectors and an increase in oil price return volatility increases stock return volatility in the financial sector. Explanation for the negative (positive) association between oil return (oil return volatility) and returns (volatility of returns) in the financial sector must be based on the association via lending to and/or holdings of corporate bonds issued by firms with significant exposure to oil price fluctuations and their speculative positions in oil‐related instruments.     

A FURTHER EXAMINATION OF THE PRICE AND VOLATILITY IMPACT OF STOCK DIVIDENDS AT EX‐DATES*

We examine the price and volatility reaction around stock dividend ex‐dates for an Australian sample, over the period January 1992 to December 2000. We find that price reaction around stock dividend ex‐dates provides positive abnormal returns both prior, and subsequent, to the abolishment of par value of shares in July 1998. When we partitioned the sample into financial, industrial non‐financial and mining firms, the price reaction is found to be positive and significant only for industrial non‐financial companies. Volatility of daily returns for periods subsequent to ex‐dates is significantly greater than corresponding periods prior to announcement dates, while cumulative raw returns subsequent to ex‐dates are significantly lower than periods prior to announcement dates for industrial non‐financial companies. The magnitude of the price reaction is statistically significantly related to an increase in the volatility of daily returns and to a reduction in cumulative raw returns subsequent to the ex‐dates, for industrial non‐financial companies. These findings support buying pressure hypothesis suggested by Dhatt et al. (1994, 1996 ).     

PREDICTING STOCK RETURNS AND VOLATILITY WITH INVESTOR SENTIMENT INDICES: A RECONSIDERATION USING A NONPARAMETRIC CAUSALITY‐IN‐QUANTILES TEST

Evidence of monthly stock returns predictability based on popular investor sentiment indices, namely S^BW and S^PLS as introduced by Baker and Wurgler (2006, 2007) and Huang et al. (2015) respectively are mixed. While, linear predictive models show that only S^PLS can predict excess stock returns, nonparametric models (which accounts for misspecification of the linear frameworks due to nonlinearity and regime changes) finds no evidence of predictability based on either of these two indices for not only stock returns, but also its volatility. However, in this paper, we show that when we use a more general nonparametric causality‐in‐quantiles model of Balcilar et al., (forthcoming), in fact, both S^BW and S^PLS can predict stock returns and its volatility, with S^PLS being a relatively stronger predictor of excess returns during bear and bull regimes, and S^BW being a relatively powerful predictor of volatility of excess stock returns, barring the median of the conditional distribution.     

The Availability Heuristic and Reversals Following Large Stock Price Changes

The author explores the effect of the availability heuristic on large daily stock price changes and on subsequent stock returns. He hypothesizes that if a major positive (negative) stock price move takes place on a day when the stock market index rises (falls), then its magnitude may be amplified by the availability of positive (negative) investment outcomes. In both cases, the availability heuristic may cause price overreaction to the initial company-specific shock, resulting in subsequent price reversal. In line with the hypothesis, the author documents that both positive and negative large price moves accompanied by the same-sign contemporaneous daily market returns are followed by significant reversals on the next 2 trading days and over 5- and 20-day intervals following the event, the magnitude of the reversals increasing over longer postevent windows, while large stock price changes taking place on the days when the market index moves in the opposite direction are followed by nonsignificant price drifts. The results remain robust after accounting for additional company (size, beta, historical volatility) and event-specific (stock's return and trading volume on the event day) factors, and are stronger for small and volatile stocks.     

DUALITY WITH SECTOR‐SPECIFIC EXTERNALITIES UNDER SOCIAL CONSTANT RETURNS*

We develop dual approaches to quantity and price relationships of production in a general multisectoral model with sector‐specific externalities. The production of each good exhibits socially constant returns to scale but privately decreasing returns. We find that the Stolper‐Samuelson theorem holds for factor intensity ranking from the social perspective and that the Rybczynski theorem holds for factor intensity ranking from the private perspective. The price‐output dual fails to hold in general. Moreover, we re‐establish the Heckscher‐Ohlin theorem in the two‐sector case, as well as the factor endowment–factor price and price‐output comparative statics in the high‐dimension case under proper conditions.     

Impact of oil prices on firm stock return: industry-wise analysis

The study investigates the impact of oil prices on firm-level stock returns in case of Pakistan over the period 1998–2014, as this relationship is neglected by the previous literature. By using the panel data estimation, the results of full sample indicate significant positive effect of oil price changes on firm stock returns in the same period, whereas the lagged oil price changes have significant negative effect on firms’ stock return. Moreover, the industry-level analysis also confirms the similar findings; results indicate significant positive impact of oil price on firms’ stock return in full sample, textile, chemical and miscellaneous industry, while the lagged oil price changes negatively affect the stock returns of full sample and all the industries except tobacco, jute and vanaspati industries. The study confirms that rise in oil price transfers a positive signal in the stock market that boosts the firm-level stock returns in Pakistan. In contrast to the negative shocks, the stock returns are significantly affected by the positive oil price shocks.     

Economic policy uncertainty,financial markets and probability of US recessions

We use probit recession forecasting models to assess the ability of economic policy uncertainty indexes developed by Baker et al. (2013) to predict future US recessions. The model specifications include policy indexes on their own, and in combination with financial variables, such as interest rate spreads, stock returns and stock market volatility. Both in-sample and out-of-sample analysis suggests that the policy uncertainty indexes are statistically and economically significant in forecasting recessions at the horizons beyond five quarters. The index based on newspaper reports emerges as the best predictor, outperforming the term spread at the longer forecast horizons.     

STOCK‐BOND CO‐MOVEMENTS AND FLIGHT‐TO‐QUALITY IN G7 COUNTRIES: A TIME‐FREQUENCY ANALYSIS

This paper examines co‐movement between stock returns and changes in 10‐year government bond yields as well as flight‐to‐quality behaviour in G7 countries. We conduct the wavelet squared coherence analysis to explore the dynamics in both time and frequency domain. Our results provide evidence of positive co‐movements, which vary over time and across investment horizon. The higher co‐movement is found to be more concentrated in the lower frequency bands. We further analyse the dynamic nature of the scale‐dependent wavelet correlations and find that the correlations are highly volatile and significantly increase across different time scales during the episodes of equity market turbulence. The increase in correlations reflects flights from stocks to safer bond investments as a result of dramatic changes in investor sentiment and risk aversion at times of market stress.     

The Pricing of Italian Equity Returns

In this paper, we investigate the relationship between common risk factors and average returns for Italian stocks. Our research has identified the Italian stock market's economic variables by using the results from factor analyses and time series regressions. We study several multi‐factor models combining the relevant macroeconomic variables with the mimicking equity portfolios SMB (small minus big) and HML (high minus low) proposed by Fama and French (1993). The key question we want to ask ourselves, is whether the influential role of the size and book‐to‐market equity factors in explaining average stock returns can stand up well when competing with some macroeconomic factors. In other words, do stock returns carry some risk premium that is independent of either the market return or the economic forces that underlie the common variation in returns? Our empirical work estimates risk premiums using both traditional two‐pass procedures and one‐pass (full information) methodologies. We show that only the market index and variables linked to interest rate shifts are consistently priced in the Italian stock returns. The role of other factors, and in particular both the size and the price‐to book ratio, are crucially dependent on the estimation procedure. (J.E.L.: G11, G12).     

Stock Market‐Induced Currency Crises—A New Type of Twins

This paper explores the link between currency crises and the stock market in emerging economies. By integrating foreign stock market investors in a currency crisis model, we reveal a new fundamental inconsistency as a potential crisis trigger: since emerging economies' stock markets often have high returns, whereas central bank reserves grow slowly or decline, the amount of reserves foreign investors can deplete when selling their stocks and repatriating the proceeds grows over time and is considerably higher than funds that have been invested in the stock market. Capital withdrawals of foreign stock market investors can trigger currency crises by depleting central bank reserves, particularly in successful countries with booming stock markets and large foreign investment.     

The Time Varying Relation Between Consumer Confidence and Equities

We examine the impact of changes in consumer confidence measures on future stock index returns. Our analysis is built on the growing understanding that investor sentiment is an important factor in the stock market. By using frequency dependent regression methods, we show that there is a time-varying relation between consumer confidence and stock returns. Higher levels of consumer confidence imply greater returns in the short term but negative returns in the medium term. However, this effect is only observed for the small firm index. Moreover, there is evidence to suggest that consumer confidence is significantly affected by stock returns in reverse causality.     

THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET*

It is shown that the reaction of U.S. real stock returns to an oil price shock differs greatly depending on whether the change in the price of oil is driven by demand or supply shocks in the oil market. The demand and supply shocks driving the global crude oil market jointly account for 22% of the long‐run variation in U.S. real stock returns. The responses of industry‐specific U.S. stock returns to demand and supply shocks in the crude oil market are consistent with accounts of the transmission of oil price shocks that emphasize the reduction in domestic final demand.     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

Inflation and Stock Market Returns:Some Australian Evidence*

This paper analyzes the relationship between Australian stock returns and inflation over the period 1965-79. The effects of inflation in a ‘rational investor’ valuation framework are discussed. Empirical tests suggest that nominal stock returns and inflation are related in a significantly negative fashion, implying that stocks have been extremely poor inflationary hedges for the investor over the period. In addition, Granger-Sims tests of causality indicate a mainly unidirectional relationship between inflation and stock returns, with price level charges leading the equity index in time.     

Nonlinear effects of oil shocks on stock returns: a Markov-switching approach

Using Markov-switching models, we investigate whether oil price shocks have nonlinear effects on stock returns. Empirical evidence from a set of international stock indexes suggests that an increase in oil prices has a negative and significant impact on stock prices in one state of the economy, whereas this effect is significantly dampened in another state of the economy. Furthermore, it is shown that changes in oil prices or in oil price volatility do not lead to a higher probability of switching between regimes.     

Asymmetric effects of oil price shocks on stock returns: evidence from a two-stage Markov regime-switching approach

The asymmetric effects of oil price shocks on stock returns have attracted the attention of many researchers in the past several decades. Most of these researchers’ studies, however, do not separate out the sources of oil price shocks when examining the asymmetric effects. In this article, we address this limitation using a two-stage Markov regime-switching approach. Our results indicate that oil supply and demand shocks have a null or minimal impact on stock returns in a low-volatility regime and a statistically significant impact in a high-volatility regime. We observe that oil demand shocks affect stock returns significantly more than oil supply shocks. A positive aggregate demand shock significantly increases stock returns, whereas a positive oil-specific demand shock markedly decreases stock returns. These results have important implications for policymakers and investors.     

The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: Evidence from Turkey

This paper investigates the effects of interest rate and foreign exchange rate changes on Turkish banks' stock returns using the OLS and GARCH estimation models. The results suggest that interest rate and exchange rate changes have a negative and significant impact on the conditional bank stock return. Also, bank stock return sensitivities are found to be stronger for market return than interest rates and exchange rates, implying that market return plays an important role in determining the dynamics of conditional return of bank stocks. The results further indicate that interest rate and exchange rate volatility are the major determinants of the conditional bank stock return volatility.     

An analysis of commercial bank common stock returns: 1802–97

This study creates analyses for the first time a continous index of returns on commercial bank common stocks listed in a specific market. The index is constructed from a unique set of historical data and is calculated on both a weighted and unweighted basis, first including and then excluding dividends. A measure of volatility is calculated annually.

The results indicate that the dividend component of holding period returns is very important. Including dividends, average returns were 6.0% for the century; excluding dividends, average returns were 0.1%. Excess returns were calculated using two different measures of a riskless rate of return. Cumulative excess returns for the first half of the nineteenth century were negative. Real returns were calculated, and found to be generally positive over the century. The volatility of returns was quite high during certain periods.

Examining the effects of significant economic and political events on bank common stock returns, we find that the War of 1812, the Civil War, and the National Banking System had a significant impact on bank stock returns. Several economic panics, several depressions, the First and Second Banks of the United States, the Embargo of 1807, and the Suffolk Bank had no measureable impact.     

The Relationship between Australian Mutual Fund Fees and Risk‐Adjusted Performance in Differing Economic Conditions

We find that Australian mutual fund investors should avoid high fee funds as these funds generate relatively low after‐fee risk‐adjusted returns both unconditionally and in weak economic conditions. This result is different from some of the previous findings which showed that US mutual funds with relatively high expense ratios may generate relatively higher risk‐adjusted returns during recessions relative to non‐recessions, although their unconditional alphas may be negative. We find some support for the Glode hypothesis in surviving Australian wholesale funds. High‐fee surviving Australian wholesale funds perform relatively strongly in both weak economic conditions and unconditionally. High‐fee funds in other types of Australian mutual funds generally do not perform strongly either in weak economic conditions or unconditionally. Amongst low‐fee funds, we commonly find that those that perform well unconditionally and well in weak economic conditions do charge more than those that perform well unconditionally and poorly in weak economic conditions. Amongst low‐fee funds, it is often true that those that perform poorly unconditionally but well in weak economic conditions can charge more than those that perform poorly unconditionally and poorly in weak economic conditions.