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A growing number of investors in recent years has focused on environmental, social and governance (ESG) factors in carrying out investment activities and the COVID-19 pandemic has only driven such trends of ESG investing at an accelerated rate. Many studies have examined the relationship between ESG scores and corporate financial performance, along with the effectiveness of ESG portfolios. This paper discusses various approaches to incorporate ESG factors into a portfolio optimisation and critically compares and contrasts the efficacy of these approaches on the Dow Jones Industrial Average constituents. It finds that thematic investing appears to be the best performer. In addition, it is also found that there is no evidence that ESG portfolios underperform the market. [ABSTRACT FROM AUTHOR]

This paper studies multiscale stochastic volatility models of financial asset returns. It specifies two components in the log-volatility process and allows for leverage/asymmetric effects from both components while return innovation terms follow a heavy/fat tailed Student t distribution. The two components are shown to be important in capturing persistent dependence in return volatility, which is often absent in applications of stochastic volatility models which incorporate leverage/asymmetric effects. The models are applied to asset returns from a foreign currency market and an equity market. The model fits are assessed, and the proposed models are shown to compare favorably to the one-component asymmetric stochastic volatility models with Gaussian and Student t distributed innovation terms. [ABSTRACT FROM AUTHOR]

This article proposes a general framework of a Markov Switching GARCH model with a mixture of truncated Gaussian to model asset returns with price limits in China. Theoretically, while retaining many convenient statistical properties of the Gaussian distribution, the proposed model also assumes a flexible time-varying volatility structure to accommodate the feature of the return data under price restrictions in China, such as the clusters near the bounds (due to the 'bound effect'). Empirically, we apply the model to eight representative stocks from Shanghai and Shenzhen stock markets in China. Lastly, we find that our proposed model dominates the conventional volatility models in terms of Value-at-Risk measures. [ABSTRACT FROM AUTHOR]

This study investigates the development and sustainability of a firm's information technology (IT) capability reputation from an IT executive's standpoint. Building on institutional theory, we argue that IT executives will try to achieve external legitimacy (i.e., project an image of superior IT capability to external stakeholders) in the hope that the top management team and board members will reciprocate by elevating the internal legitimacy of IT executives. Firms that develop such a culture of reciprocity with their IT executives are more likely to sustain their IT capability reputation. Econometric results based on panel data for 1,326 large U.S. firms from a wide spectrum of industries over a 13-year period (1997-2009) validate these predictions. More specifically, we find that IT executives with greater structural power (e.g., higher job titles) or IT-related expert power (e.g., IT-related education or experience) are more likely to attract public recognition for their firm's IT capability. Firms that build such an IT capability reputation are more likely to promote their IT executives, and IT executives who are promoted are more likely to stay longer with their firms. This continuity in IT strategic leadership is positively associated with the firm's ability to sustain its IT capability reputation. Our findings have important practical implications related to a firm's IT reputation strategy as well as the motivation and career of IT executives. Firms wanting to develop and sustain their IT capability reputation would do well to foster the creation of a cycle of positive reciprocity with their IT executives. IT executives hoping to increase their power within their firm's top management team and improve the legitimacy of the firm's IT organization need to project an image of IT superiority to external stakeholders. [ABSTRACT FROM AUTHOR]

Organizations seek to differentiate themselves in the marketplace by deploying information technology (IT) to develop dynamic IT capabilities and resist competitors' attempts to imitate or improve these capabilities. While this strategy has been justified on the grounds that dynamic IT capabilities are durably heterogeneous, there does not seem to be empirical evidence supporting or refuting this assumption. This study empirically validates the assumption of durable heterogeneity of dynamic organizational IT capability (ITC) due to path dependence. We capture ITC heterogeneity by introducing a framework in which firms try to achieve ITC leadership in their industry and we propose that durable ITC heterogeneity can be attributed to path dependence, and hence, it can be tested using Heckman's true state dependence of ITC leadership status. Using random and fixed effect dynamic logit models, we investigate true state dependence of ITC leadership on a sample of large U.S. firms. The results, which are robust to alternative sample, dependent, and control variable specifications, show that achieving ITC leadership is a true state-dependent process, suggesting durable heterogeneity of ITC due to path dependence. The study contributes to the dynamic capabilities literature and has important managerial implications. The proposed framework for conceptualizing durable resource heterogeneity due to path dependence is general and versatile, thus providing a foundation for future research on dynamic capabilities. The findings provide empirical evidence to confirm that ITC is durably heterogeneous and should be managed as a potential source of competitive advantage. [ABSTRACT FROM AUTHOR]

This paper tests the prediction of the permanent income hypothesis (PIH) that news about future income induce a revision in consumption equal to the revision in permanent income. We use time-series data from 48 contiguous U.S. states to perform the test. The empirical results provide some support for the PIH across states. [ABSTRACT FROM AUTHOR]

This paper proposes a variant of a threshold stochastic conditional duration (TSCD) model for financial data at the transaction level. It assumes that the innovations of the duration process follow a threshold distribution with a positive support. In addition, it also assumes that the latent first-order autoregressive process of the log conditional durations switches between two regimes. The regimes are determined by the levels of the observed durations and the TSCD model is specified to be self-excited. A novel Markov-Chain Monte Carlo method (MCMC) is developed for parameter estimation of the model. For model discrimination, we employ deviance information criteria, which does not depend on the number of model parameters directly. Duration forecasting is constructed by using an auxiliary particle filter based on the fitted models. Simulation studies demonstrate that the proposed TSCD model and MCMC method work well in terms of parameter estimation and duration forecasting. Lastly, the proposed model and method are applied to two classic data sets that have been studied in the literature, namely IBM and Boeing transaction data. [ABSTRACT FROM AUTHOR]

This paper discusses the management of climate change risks for equity investments and presents a scenario-based framework for building sustainable portfolios under the climate change scheme. An empirical analysis is first performed using historical price data to show the inferior risk-adjusted performance of the carbon-intensive industries in the North American stock market, which supplements evidence from existing literature in the market's gradual pricing of the climate change risk. Risk management modules are devised with subjective top-level constraints to achieve comprehensive coverage of the key aspects of climate change: risk exposures are measured by carbon intensities, while the risk impacts are quantified through equity return impact scenarios derived from climate change paths under Integrated Assessment Models. A model for quantifying stranded asset risk is also presented. Results from these modules formulate the joint posterior return distribution of the stocks that are used to construct the mean-variance optimal portfolio. [ABSTRACT FROM AUTHOR]

This paper conducts simulation-based comparison of several stochastic volatility models with leverage effects. Two new variants of asymmetric stochastic volatility models, which are subject to a logarithmic transformation on the squared asset returns, are proposed. The leverage effect is introduced into the model through correlation either between the innovations of the observation equation and the latent process, or between the logarithm of squared asset returns and the latent process. Suitable Markov Chain Monte Carlo algorithms are developed for parameter estimation and model comparison. Simulation results show that our proposed formulation of the leverage effect and the accompanying inference methods give rise to reasonable parameter estimates. Applications to two data sets uncover a negative correlation (which can be interpreted as a leverage effect) between the observed returns and volatilities, and a negative correlation between the logarithm of squared returns and volatilities. [ABSTRACT FROM AUTHOR]

This article focuses on simulation-based inference for the time-deformation models directed by a duration process. In order to better capture the heavy tail property of the time series of financial asset returns, the innovation of the observation equation is subsequently assumed to have a Student-tdistribution. Suitable Markov chain Monte Carlo (MCMC) algorithms, which are hybrids of Gibbs and slice samplers, are proposed for estimation of the parameters of these models. In the algorithms, the parameters of the models can be sampled either directly from known distributions or through an efficient slice sampler. The states are simulated one at a time by using a Metropolis-Hastings method, where the proposal distributions are sampled through a slice sampler. Simulation studies conducted in this article suggest that our extended models and accompanying MCMC algorithms work well in terms of parameter estimation and volatility forecast. [ABSTRACT FROM AUTHOR]

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of the mean equation follows a threshold distribution in which the mean innovation switches between two regimes. In our model, the threshold is treated as an unknown parameter. We show that the proposed threshold SV model can not only capture the time-varying volatility of returns, but can also accommodate the asymmetric shape of conditional distribution of the returns. Parameter estimation is carried out by using Markov chain Monte Carlo methods. For model selection and volatility forecast, an auxiliary particle filter technique is employed to approximate the filter and prediction distributions of the returns. Several experiments are conducted to assess the robustness of the proposed model and estimation methods. In the empirical study, we apply our threshold SV model to three return time series. The empirical analysis results show that the threshold parameter has a non-zero value and the mean innovations belong to two separately distinct regimes. We also find that the model with an unknown threshold parameter value consistently outperforms the model with a known threshold parameter value. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper extends stochastic conditional duration (SCD) models for financial transaction data to allow for correlation between error processes and innovations of observed duration process and latent log duration process. Suitable algorithms of Markov Chain Monte Carlo (MCMC) are developed to fit the resulting SCD models under various distributional assumptions about the innovation of the measurement equation. Unlike the estimation methods commonly used to estimate the SCD models in the literature, we work with the original specification of the model, without subjecting the observation equation to a logarithmic transformation. Results of simulation studies suggest that our proposed models and corresponding estimation methodology perform quite well. We also apply an auxiliary particle filter technique to construct one-step-ahead in-sample and out-of-sample duration forecasts of the fitted models. Applications to the IBM transaction data allow comparison of our models and methods to those existing in the literature. [ABSTRACT FROM PUBLISHER]

ABSTRACT This paper proposes Markov chain Monte Carlo methods to estimate the parameters and log durations of the correlated or asymmetric stochastic conditional duration models. Following the literature, instead of fitting the models directly, the observation equation of the models is first subjected to a logarithmic transformation. A correlation is then introduced between the transformed innovation and the latent process in an attempt to improve the statistical fits of the models. In order to perform one-step-ahead in-sample and out-of-sample duration forecasts, an auxiliary particle filter is used to approximate the filter distributions of the latent states. Simulation studies and application to the IBM transaction dataset illustrate that our proposed estimation methods work well in terms of parameter and log duration estimation. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper extends the stochastic conditional duration model first proposed by Bauwens and Veredas (2004) by imposing mixtures of bivariate normal distributions on the innovations of the observation and latent equations of the duration process. This extension allows the model not only to capture various density shapes of the durations but also to easily accommodate a richer dependence structure between the two innovations. In addition, it applies an estimation methodology based on the empirical characteristic function. Empirical applications based on the IBM and Boeing transaction data are provided to assess and illustrate the performance of the proposed model and the estimation method. One interesting empirical finding in this paper is that there is a significantly positive correlation under both the contemporaneous and lagged intertemporal dependence structures for the IBM and Boeing duration data. [ABSTRACT FROM AUTHOR]

This article considers risk measures constructed under a discrete mixture-of-normal distribution on the innovations of a GARCH model with time-varying volatility. The authors use an approach based on a continuous empirical characteristic function to estimate the parameters of the model using several daily foreign exchange rates' return data. This approach, compared to the likelihood-based approach, has several important advantages as a method for estimating this type of models; in particular, the characteristic function, unlike its likelihood function counterpart, is always uniformly bounded over the model-parameter space due to the Fourier transformation. To evaluate VaR and expected shortfall measures obtained from alternative specifications, the authors construct several evaluation criteria, such as the number of violations and the sum square of violations. Based on these criteria, the authors find that both the VaR and expected shortfall measures obtained from the proposed model outperform those obtained from other competing models. [ABSTRACT FROM AUTHOR]

This paper utilizes relatively unexplored Canadian provincial-level data to investigate an old but still relevant question in macroeconomics as to whether consumption responds to income innovations in a manner consistent with the stochastic implications of the permanent income hypothesis (PIH). The empirical results obtained do not appear to be in accord with the PIH. Instead, consumption's response to income innovations is found to be much weaker than that predicted by PIH; in particular, the response displays an asymmetric pattern in the sense that it is much stronger for negative than positive income innovations. We interpret this evidence of asymmetry as indicative of the presence of liquidity constraints in provincial households. [ABSTRACT FROM AUTHOR]

This paper presents a stylized exchange rate pass-through model of crude oil price formation for the purpose of understanding the price reactions of OPEC Member Countries to changes in the exchange rate of the US dollar against major currencies and the prices of other Members. Our empirical results suggest that, in response to changes in the exchange rate, exporting countries tend to adjust their prices to secure a stable international purchasing power of oil revenues and to avoid suppressing market demand and losing market share. [ABSTRACT FROM AUTHOR]

Using Canadian data, the consumption-based asset pricing model is studied, defined in terms of nondurable and durable goods consumption. A two-stage estimation procedure is used, which takes account of the presence of common stochastic trends in the forcing processes. This method yields more reasonable estimates of the preference parameters than the previous studies did, and the asset-pricing equation is not rejected by the data. Moreover, the preference specification adopted in this paper allows a number of useful economic information to be obtained. The additive separability assumption and the Cobb-Douglas functional form of the utility function are ruled complements in the sense of Edgeworth and Pareto. [ABSTRACT FROM AUTHOR]

This paper proposes a simple, partial equilibrium model for studying an individual's migration decisions. It shows that an individual may choose to delay migration when the condition appears to be favorable, giving rise to the “waiting” behavior observed in the data. Using a closed-form solution, it also examines how the duration of the waiting is affected by a number of economic factors such as the risks associated with the wages in regions of origin and destination, the individual's attitude toward risk, etc. [ABSTRACT FROM AUTHOR]

In this study we examine the stability of long-run broad money demand in Japan. In contrast to previous studies of Japanese broad money demand, we use a series of tests designed specifically to test for structural instability in the presence of I(1) processes. According to these tests, the Japanese broad money demand function appears to be stable over a period of financial innovation and deregulation. JEL Classification Numbers: E41, C22. [ABSTRACT FROM AUTHOR]

Examines the theoretical, empirical and public policy implications of the proportion of females in the establishment level in Canada. Characteristics of the gender wage gap; Implications of employment equity policy; Individual level and wage equations used; Use of the model of statistical discrimination.

The paper is concerned with identifying useful indicators of the probability of currency crises in Indonesia, Malaysia, the Philippines, South Korea and Thailand over a period of 22 years, where a currency crisis is defined as a large and infrequent devaluation of a local currency. The leading crisis indicators include international and domestic factors; but they are dominated by the leading indicators from the financial sector, such as the ratio of short-term debt to foreign reserves, the ratio of M2 to foreign reserves, and the indicator representing a regional contagion effect. This result is interpreted as pointing to external illiquidity together with adverse shifts in the market sentiment as the likely catalyst for the 1997-98 East Asia crisis. [ABSTRACT FROM AUTHOR]

Examines the results of a study by Mercenier and Sekkat on the willingness of a monetary authority in an open economy to stabilize exchange rates. Approach for examining the results; Extension of observations beyond the year 1970; Estimation of the parameters of the linear quadratic model under rational expectations.

The hypothesis of market efficiency is typically rejected by standard variance-bounds tests which assume stationary asset prices. A number of researchers, however, argue that tests used in previous studies are inappropriate since asset prices appear to be generated by nonstationary processes. In this paper, we propose a regression-based variance-bounds test that is valid when the asset price is an integrated process. We apply this test to annual U. S. data over the 1889 to 1985 sample period using measures of the perfect-foresight price constructed from a nonlinear asset-pricing equation that allows for a stochastic discount parameter. The results suggest that the data appear consistent with a version of the efficient-market hypothesis detailed in this paper. [ABSTRACT FROM AUTHOR]

This paper discusses how conditional heteroskedasticity models can be estimated efficiently without imposing strong distributional assumptions such as normality. Using the generalized method of moments (GMM) principle, we show that for a class of models with a symmetric conditional distribution, the GMM estimates obtained from the joint estimating equations corresponding to the conditional mean and variance of the model are efficient when the instruments are chosen optimally. A simple ARCH(1) model is used to illustrate the feasibility of the proposed estimation procedure. [ABSTRACT FROM AUTHOR]

In this paper, we examine the idea that a general model of consumption should allow for the direct effect of government expenditures in a two-good permanent-income model. We show, given an assumed preference specification, that there is a cointegration restriction implied by an intraperiod first-order condition of the model. This restriction leads to a linear deterministic cointegration relation between government spending, private consumption, and their relative price that is supported by the data. Using this restriction to recover the preference parameters, we estimate the intraperiod elasticity of substitution for both government and private consumption to be about 0.9. Overall, we find consistent empirical evidence in support of our model. [ABSTRACT FROM AUTHOR]

Considers a general permanent-income model in which a fraction of consumers in the economy is liquidity constrained using the Canadian evidence. Consumption growth rate for these individuals; Interest-rate coefficient predicted to be smaller in the presence of liquidity constraints; Structural changes over the sample period, which are associated with the 1982 recession.

This paper investigates whether there are variants of the permanent income model that are consistent with seasonally unadjusted quarterly postwar Canadian data. The analysis is based on a misspecification-test equation which nests the standard permanent income model. The results obtained are somewhat unfavourable to the permanent-income hypothesis. The same results also apply to more general models in which the real interest rate is time-varying and the utility function is non-separable in consumption and the stock of durable goods. [ABSTRACT FROM AUTHOR]

This paper estimates and tests several versions of the consumption-based asset pricing model extended to allow for time-nonseparable preferences and/or liquidity constraint proxies, using Canadian aggregate data. It is found that a habit-persistence effect uncovered in the time-nonseparable preference model is due to the model's misspecification and that liquidity constraints have significant effects on an individual's intertemporal consumption behaviour. [ABSTRACT FROM AUTHOR]

The article presents an empirical investigation into the permanent income hypothesis taking evidence from the Canadian data. The objective of the paper is to investigate whether aggregate consumption in postwar Canada shares similar features to the findings for the U.S. Recently, researchers J.Y. Campbell and G.N. Mankiw (CM) have demonstrated that most empirical findings in the aggregate consumption literature can be explained by a simple model in which some fraction of income accrues to individuals who consume their current income each period and the remainder accrues to individuals whose consumption behaviour is predicted by the consumption-based asset pricing model. For the U.S. data, researchers report that the fraction of income going to current income consumers is in the range of 35 to 50%. The paper departs on several points from CM study in which the first-order condition is linearized by essentially assuming that the joint distribution of asset returns and consumption is conditionally lognormal and homoscedastic.