The Behaviour of Banking Stocks During the Financial Crisis and Recessions. Evidence from Changes‐in‐Changes Panel Data Estimations

This paper examines the impact of the financial crisis and economic recessions on bank shares compared to the overall stock market index for 18 OECD countries from 1993 to 2015. The empirical methodology utilizes the changes‐in‐changes approach. We compare and contrast the returns of the banking stock price index (treatment group) in each country with their general stock price index (control group), which experiences smaller changes. Our results suggest that bank returns on average perform significantly worse than that of the general stock price index during recessions. In addition, we also find significantly greater volatility in bank share returns.     

年轻高管与企业股价崩盘风险：来自“代理冲突观”的证据*

在企业纷纷实施高管年轻化战略的背景下，本文从股价崩盘风险的视角分析和检验了年轻高管风险偏好的经济后果及其作用机理。本文基于“个体认知观”和“代理冲突观”展开理论推演，采用中国沪深A股非金融上市公司的数据，检验发现，年轻高管会显著加剧企业未来的股价崩盘风险，且这种影响主要存在于民营企业，在国有企业并不显著。进一步针对具体作用机制的检验发现，年轻高管在投资决策中选择了更多能迅速提升个人收益的风险性投资项目，但在不能迅速提升个人收益的风险性投资项目上与年长高管没有显著差异。同时，年轻高管对股价崩盘风险的加剧效应仅仅存在于高管在上市公司领取薪酬的样本企业，且更高的独立董事比例能显著抑制年轻高管的股价崩盘风险加剧效应。这表明，年轻高管个体认知层面的风险偏好被其追求个人私利最大化的代理冲突所扭曲，进而为年轻高管风险偏好的“代理冲突观”提供了实证证据。     

年轻高管与企业股价崩盘风险：来自“代理冲突观”的证据*

在企业纷纷实施高管年轻化战略的背景下，本文从股价崩盘风险的视角分析和检验了年轻高管风险偏好的经济后果及其作用机理。本文基于“个体认知观”和“代理冲突观”展开理论推演，采用中国沪深A股非金融上市公司的数据，检验发现，年轻高管会显著加剧企业未来的股价崩盘风险，且这种影响主要存在于民营企业，在国有企业并不显著。进一步针对具体作用机制的检验发现，年轻高管在投资决策中选择了更多能迅速提升个人收益的风险性投资项目，但在不能迅速提升个人收益的风险性投资项目上与年长高管没有显著差异。同时，年轻高管对股价崩盘风险的加剧效应仅仅存在于高管在上市公司领取薪酬的样本企业，且更高的独立董事比例能显著抑制年轻高管的股价崩盘风险加剧效应。这表明，年轻高管个体认知层面的风险偏好被其追求个人私利最大化的代理冲突所扭曲，进而为年轻高管风险偏好的“代理冲突观”提供了实证证据。     

Oil price risk in the Spanish stock market: An industry perspective

This study examines the sensitivity of the Spanish stock market at the industry level to movements in oil prices over the period 1993–2010, paying special attention to the presence of endogenously determined structural changes in the relationship between oil price changes and industry equity returns. The empirical results show that the degree of oil price exposure of Spanish industries is rather limited, although significant differences are found across industries. The oil price sensitivity is very weak in the 1990s, a period of fairly stable and low oil prices. Instead, the link between crude oil and stock prices seems to have increased during the 2000s, becoming primarily positive. This evidence highlights the key role played by aggregate demand-side oil price shocks associated with the global real economic activity in the link between oil price fluctuations and the Spanish stock market.     

New Evidence on Psychology and Stock Returns

This article provides econometric evidence on the importance of psychological considerations for aggregate stock price fluctuations. To this end, a novel measure of stock market sentiment, dubbed the Net Psychology Index (NPI), based on information contained in Bloomberg News's end-of-the-day stock market reports, is confronted with a battery of multivariate empirical analyses. Results suggest that NPI is statistically different from popular sentiment proxies within the literature. NPI exhibits predictive power, increasing stock returns in the short run with this impact dissipating in the medium term. NPI does not exhibit asymmetric effects on returns for size- and momentum-related portfolios. A trading strategy based on NPI generates a statistically significant positive monthly return. Recursive out-of-sample fit analyses report a lower standard deviation of forecasting errors for NPI-based returns models versus competing accounts.     

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.     

Morocco and the US Free Trade Agreement: A specific factors model with unemployment and energy imports

This paper examines the impact in Morocco of its pending free trade agreement with the US in a specific factors model with unemployment and energy imports. Projected price scenarios across eight industries lead to adjustments in outputs, energy imports, rural wages, urban wages, and the unemployment rate. The model predicts substantial adjustments for reasonable price scenarios. Rural wages fall unless agriculture is subsidized. Unemployment, assumed inversely related to output, is sensitive to price changes. Factor substitution only affects the degree of output adjustments. Adjustments in capital returns lead to industrial investment and subsequent long run output adjustments.     

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.     

Oil prices and stock returns: nonlinear links across sectors

We present evidence of an asymmetric relationship between oil prices and stock returns. The two regime multivariate Markov switching vector autoregressive (MSVAR) model allow us to capture the state shifts in the relationship between regional stock markets and sectors. Results suggest that oil price risk is significantly priced in the sample used. The impact is asymmetric with respect to market phases, and regimes have been associated with world economic, social and political events. Our study also suggests asymmetric responses of sector stock returns to oil price changes and different transmission impacts depending on the sector analyzed. There is a high causality from oil to sectors like Industrials and Oil & Gas. Companies inside the Utilities sector were more able to hedge against oil price increases between 2007 and 2012. Historical crisis events between 1992–1998 and 2003–2007 do not seem to have affected the relationship between oil and sector stock returns, given the higher probability of remaining smoother. For all sectors there seems to be a turn back to stability from 2012 onwards. Finally, investors gain more through portfolio diversification benefits built across, rather than within sectors.     

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).     

Risk in supply response: an econometric application

The impact of risk aversion on supply response is empirically estimated for selected field crops in California. As indicators of risk aversion the following surrogate variables are used: variance of past prices and yields, adjusted price to reflect the role of government support price over the market price and the dummy variables indicating price expectations. In general, the econometric estimates show a negative impact of risk aversion measured by the surrogate variables and this has implications for welfare gains resulting from price support policies aimed at stabilization.     

Global idiosyncratic risk moments

We investigate a global cross-sectional relation between idiosyncratic risk moments and expected stock returns by suggesting three global idiosyncratic volatility, skewness, and kurtosis risk factors. We also suggest two global small minus big and high minus low risk proxies for estimating return residuals of the test assets from a global asset pricing model. To perform robustness checks, we suggest other four global risk factors of momentum, leverage, bid-ask spread, and liquidity. We find a significant negative relation between stock portfolio returns and the global moments, and the cross section of stock returns reflects a significant negative price of risk for global idiosyncratic skewness (?0.13%) and idiosyncratic volatility (?1.85%) and a positive and significant price of risk for global idiosyncratic kurtosis. We find that our suggested risk factors are key drivers of risk premia in stock market and are robust to various checks. These factors also can forecast the gross domestic product growth over the sample period.     

DYNAMICS BETWEEN NORTH AMERICAN AND EUROPEAN AGRICULTURAL FUTURES PRICES DURING TURMOIL AND FINANCIALIZATION

North American and European agricultural futures markets faced significant changes in recent years, i.e., the financialization which originated in the USA, the increase of futures trading in Europe and the recent price turmoils in international commodity markets. We analyse the long‐ and short‐run dynamics between North American and European agricultural futures prices during these institutional changes. The empirical results show that the US markets lead in terms of price transmissions and volatility spillovers. US markets, however, predominantly react to deviations from the long‐run equilibrium which indicates a rising impact of European agricultural markets on a global scale.     

China’s competition and the export price strategies of developed countries

This paper analyzes the impact of Chinese competition on developed countries’ export prices. The empirical application is on Italy, one of the main European manufacturing exporters with exports at high risk of competition from China. Our results show that, following China’s entry into the WTO, the price strategies of Italian firms has been affected. While in general the increasing Chinese export competition resulted in an upgrading of products exported, the impact has been different according to the sector and technological level. The incentives to upgrade have been stronger for low technology sectors, where competition is tougher and varieties of products sold lower. To highlight quality differentials, and isolate the effects on the different segments of the distribution of Italy’s export prices, we run quantile regressions. We find that are mainly those products sold at low prices to face a strong pressure to upgrade.     

上证180指数的GARCH族模型仿真研究——对上证300指数的间接实证建模分析

本文旨在运用GARCH族模型对即将作为股指期货标的物——上证300指数进行间接实证建模研究。本文使用上证180指数研究上证300指数具有可行性。分析结果表明:上海股市股价波动确实存在显著的GARCH效应和冲击持久效应,并存在较弱的杠杆效应;收益率条件方差序列是平稳的,模型具有可预测性,GARCH-M(1,1)模型可以很好地拟合与预测上证180指数。该仿真模型可以较好地实现点对点的长期高精度预测,克服了传统预测模型只能进行短期预测的缺陷。这不仅对于投资者规避风险,开拓利润空间,而且对于我国资本市场的稳健发展,都具有重要的理论与实践指导意义。     

Gold and silver manipulation: What can be empirically verified?

The issue of gold and silver price manipulation, in particular price suppression, is examined. We use a mixture of normal approach to decompose the returns into abnormal and control samples. Price suppression is a form of market manipulation of the runs type, where longer negative runs with lower returns than expected would be observed. To explore whether this form of manipulation can be empirically detected the length of runs and the total return observed during a run were computed for modelled abnormal and control clusters in gold and silver. In both metals the proportion of negative runs in the abnormal cluster is greater than the proportion of negative runs in the control cluster. In both cases the average return for negative runs is significantly lower in the abnormal cluster than in the control cluster. When average returns over positive runs are compared the abnormal group has significantly higher expected returns than the control group. Given the short maximum run lengths in the abnormal cluster and the fact that positive runs have significantly higher average returns in the abnormal cluster than in the control cluster, it is likely that that the high volatility associated with the abnormal cluster is the driver of the results presented in this study, as opposed to manipulation.     

Assessing the impacts of oil price fluctuations on stock returns in emerging markets

This paper investigates the effects of oil price shocks on stock market returns in emerging countries. It differs from previous works in three main aspects: i) we distinguish three groups of countries, the largest net-oil importing countries, the moderately oil-dependent countries, and the largest net-oil exporting countries; ii) The potential influence of bullish and bearish market conditions on the causal relationship between oil and stock returns is controlled for in our analysis; iii) The empirical investigation is based on an analysis of long-term correlation and a conditional multifactor pricing model. Using data from twenty-five emerging countries, our results suggest that oil price risk is significantly priced in emerging markets, and that the oil impact is asymmetric with respect to market phases.     

COMPETITIVE LONG RUN INDUSTRY EQUILIBRIUM AND FACTOR-PRICE UNCERTAINTY*

In this paper we have considered competitive long run industry equilibrium with factor-price uncertainty. We discussed the long run equilibrium output of firms with risk neutrality, output price and their responses to changes in uncertainty, factor price and industry demand. In the first part of this paper we have derived a result that, given risk neutrality, the firms operate at proper capacity, i.e. where expected long run marginal cost is equal to expected long run average cost, as shown in the case of output-price uncertainty. This result is, however, different from that obtained from Sheshinski and Dréze (1976). From the comparative static analysis we first discovered that even under risk neutrality factor-price uncertainty affects the long run industry equilibrium: that is, a mean preserving increase in uncertainty leads firm's to enter the industry, because they can decrease expected long run costs as the variability of factor price increases. Consequently, output price goes down. In contrast, firm size is kept invariable in response to its increase as long as the cost function is separable, i.e. the separability of the cost function holds when production functions are the Cobb-Douglas and CES types used commonly in empirical work, although firm size might, generally, be affected by the increase. It is an interesting fact that firm size and industry size will express different responses to a change in risk. The result that the long run industry equilibrium with cost uncertainty is explicitly affected is a sharp contrast to the result under output-price uncertainty and provides a new aspect for understanding about the behaviour of the industry with uncertainty. Secondly, increased factor-price causes the number of firms in the industry to decline and output price to rise. In addition, firm's size will expand with its increase if that factor is inferior, while the effect on firm size is ambiguous if it is normal. The firm's output, i.e. firm size, is, however, kept constant if the cost function is separable. Thirdly, the long run equilibrium output of the firm remains intact but the number of firms increases as industry demand rises. This result holds, regardless of the firm's attitude towards risk. Finally, we find throughout the paper that the functional form of the cost function plays a significant role in determining the behaviour of the industry with factor-price uncertainty.     

U.S. industry-level returns and oil prices

This paper empirically investigates and provides further support for the oil price effect documented in Driesprong et al. (2008) in the U.S. industry-level returns. We find that oil price predictability is concentrated in a relatively small number of industry-level returns, the relevant measure for a study of the oil effect is percentage change in oil spot prices, and changes in oil futures prices have virtually no prediction power for industry-level returns. With percentage changes in oil spot prices as the predictor, approximately one fifth of industry returns are oil-predictable. We detect a two trading weeks delay in reaction to oil price changes which is consistent with the Hong and Stein (1996) underreaction hypothesis. These results are robust to various alternative specifications, and are shown to be unrelated to time-varying risk premia. Moreover, we demonstrate that trading strategies based on the oil effect generate superior gains in comparison with buy-and-hold strategy in the presence of reasonable trading costs.     

Smart fund managers? Stupid money?

Abstract .  We develop a model of mutual fund manager investment decisions near the end of quarters. We show that when investors reward better performing funds with higher cash flows, near quarter-ends a mutual fund manager has an incentive to distort new investment toward stocks in which his fund holds a large existing position. The short-term price impact of these trades increase the fund's reported returns. Higher returns are rewarded by greater subsequent fund inflows which, in turn, allow for more investment distortion the next quarter. Because the price impact of trades is short term, each subsequent quarter begins with a larger return deficit. Eventually, the deficit cannot be overcome. Thus, our model leads to the empirically observed short-run persistence and long-run reversal in fund performance. In doing so, our model provides a consistent explanation of many other seemingly contradictory empirical features of mutual fund performance.