Disentangling the drivers of renewable energy investments: The role of behavioral factors

The scope of this study is to investigate the main determinants of renewable energy investments in Greece. For this reason, we build an appropriate framework to infer the decision‐making process in the renewable energy sources (RES). The main drivers are then categorized under two groups as economic, and behavioral ones. In the next stage, we rely on binomial (logit and probit) and quantile regression analysis to estimate the impact of these factors on investment decisions towards RES. Our findings indicate that investors who gain better access to knowledge and exhibit a more positive attitude towards the contribution of artificial intelligence (AI) on the RES industry have a higher share of renewables in their portfolio. We argue that these investors are willing to invest a higher amount in the RES industry today. At the same time, quantile regression models illustrate that this relationship is nonmonotonic (i.e., inverted U shaped curve), arguing that positive attitudes towards the contribution of behavioral factors on RES are not adequate to encourage investments after crossing a certain point (threshold). Based on the empirical findings, we argue that the message to policymakers and government officials is to promote a faster penetration of low carbon technologies to achieve sustainable economic and social growth.     

Predictability of stock returns and asset allocation under structural breaks

This paper adopts a new approach that accounts for breaks to the parameters of return prediction models both in the historical estimation period and at future points. Empirically, we find evidence of multiple breaks in return prediction models based on the dividend yield or a short interest rate. Our analysis suggests that model instability is a very important source of investment risk for buy-and-hold investors with long horizons and that breaks can lead to a negative slope in the relationship between the investment horizon and the proportion of wealth that investors allocate to stocks. Once past and future breaks are considered, an investor with medium risk aversion reduces the allocation to stocks from close to 100% at short horizons to 10% at the five-year horizon. Welfare losses from ignoring breaks can amount to several hundred basis points per year for investors with long horizons.     

Corbelled Domes in Two and Three Dimensions: The Treasury of Atreus

Before the development of the true dome, many ancient cultures used the technique of corbelling to roof spaces. Recently, a series of related statistical models have been proposed in the literature for explaining how corbelled domes might have been constructed. The most sophisticated of these models is based on a piecewise linear structure, with an unknown number of changepoints, to guide the building process. This model is analyzed by the reversible jump Markov Chain Monte Carlo (MCMC) technique. All models considered to date have been two-dimensional, that is, they have taken a single cross section through the dome; even when more extensive data, in the form of measurements on multiple slices through the dome, have been available, these have been averaged together for the purposes of analysis. In this paper, we extend the two-dimensional analysis to a three-dimensional analysis, that takes full advantage of the data collected by the archaeologists and of the rotational symmetries inherent in the structure.We also explore ways of graphically presenting the results from a complex, reversible jump MCMC implementation, in order to check convergence, good mixing, and appropriate exploration of the (high dimensional and varying dimension) parameter space. The model and the graphical techniques are demonstrated on the Treasury of Atreus in Mycenae, Greece, one of the finest extant examples of the corbelling method.     

Transaction Costs and Nonlinear Adjustment Towards Equilibrium in the US Treasury Bill Market

This paper uses nonlinear error correction models to study yield movements in the US Treasury Bill Market. Nonlinear error correction arises because portfolio adjustment is an ‘on-off’ process, which occurs only when disequilibrium in the bill market is large enough to induce investors to incur the transaction costs associated with buying/selling bills. This, together with heterogeneity of transaction costs, implies that the strength of aggregate error correction depends on both the distribution of costs and the extent of disequilibrium in the market. Smooth transition models are used to describe an aggregate adjustment process which is strong when the market is distant from equilibrium, but becomes weaker as the market approaches equilibrium. Linearity tests indicate that the types of nonlinearities that would be induced by transactions costs are statistically significant, and estimated models which incororate these nonlinearities outperform their linear counterparts, both in sample and out of sample.     

机构投资者资产配置方法研究

资产配置在当今证券投资管理过程中具有重要作用,本文首先阐述资产配置的理论基础,介绍资产配置“自上而下"的过程,然后综述资产配置的主要模型并进行比较分析,提出当今机构投资者比较适宜应用的资产配置模型。     

Application of Multilevel Models to Structured Repeated Measurements

The linear mixed-effects model has been widely used for the analysis of continuous longitudinal data. This paper demonstrates that the linear mixed model can be adapted and used for the analysis of structured repeated measurements. A computational advantage of the proposed methodology is that there is no extra burden on the analyst since any software for linear mixed-effects models can be used to fit the proposed models. Two data sets from clinical psychology are used as motivating examples and to illustrate the methods.     

Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances

We propose a new class of models specifically tailored for spatiotemporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, that is, SARAR(1, 1), by exploiting the recent advancements in score‐driven (SD) models typically used in time series econometrics. In particular, we allow for time‐varying spatial autoregressive coefficients as well as time‐varying regressor coefficients and cross‐sectional standard deviations. We report an extensive Monte Carlo simulation study in order to investigate the finite‐sample properties of the maximum likelihood estimator for the new class of models as well as its flexibility in explaining a misspecified dynamic spatial dependence process. The new proposed class of models is found to be economically preferred by rational investors through an application to portfolio optimization.     

A quantitative perspective of Porter's industry forces framework for investment analysis

Porter's industry forces framework is an important tool for external analysis of firms, but its qualitative nature presents numerous limitations to be used in investment analysis. This study introduces a quantitative perspective of the framework using financial information proxies. This allows investors to gauge the external factors quantitatively and to gain enhanced framework usability. In order to test its validity, the correlation movements of our quantitative perspective have been analysed. For demonstration of enhanced usability, our quantitative perspective, alongside machine learning models, was used to predict business performances. The empirical results indicate that our quantitative perspective of the framework corroborates with its original definition and that it exhibits enhanced usability than the original framework.     

An analytical solution for the robust investment-reinsurance strategy with general utilities

In financial markets, different investors have different attitudes or preferences on the investment policies and reinsurance problems. For investors with different investment utilities, how to provide an optimal investment strategy is not only a very hard problem, but also an urgent problem to be solved. In this paper, we derive an analytical solution for the optimal allocation problem of investment-reinsurance with general-form utility function. The general utility function allows for varying relative risk aversion coefficient, which is an important feature in finance theory. However, obtaining analytical solutions for general utility function has been difficult or impossible. The solution presented in this paper is constructed through the homotopy analysis method (HAM) and written in the form of a Taylor series expansion. The fully nonlinear Hamilton–Jacobi–Bellman (HJB) equation is decomposed into an infinite series of linear PDEs, which can be solved analytically. In the end, three examples are presented to illustrate the convergence and accuracy of the method, it also demonstrates that different risk reference investors have different investment-reinsurance strategies.     

‘Nobody is perfect’: Asset pricing and long-run survival when heterogeneous investors exhibit different kinds of filtering errors

In this paper we analyze an economy with two heterogeneous investors who both exhibit misspecified filtering models for the unobservable expected growth rate of the aggregated dividend. A key result of our analysis with respect to long-run investor survival is that there are degrees of model misspecification on the part of one investor for which there is no compensation by the other investor's deficiency. The main finding with respect to the asset pricing properties of our model is that the two dimensions of asset pricing and survival are basically independent. In scenarios when the investors are more similar with respect to their expected consumption shares, return volatilities can nevertheless be higher than in cases when they are very different.     

基于CAPM的国际投资分析

随着经济全球化发展,国际投资日益多元化,因此,如何选择国际投资方式成为众多投资者的关注目标。文章以崭新的视角,采用评价证券组合的资本资产理论来对跨国并购进行分析论证,对跨国并购的溢出效应进行量化分析,帮助决策者进行判断。     

The international firms as new entrants to the statutory audit market: an empirical analysis of auditor selection in Greece, 1993 to 1997

This paper investigates choice of statutory auditor in Greece in the five years subsequent to the 1992 liberalization of the audit market. We analyse auditor choices by 205 companies which, by 1997, represented almost 90% of companies listed on the Athens Stock Exchange. We find that the level of shareholdings by foreign shareholders is positively associated with choice of a Big Six versus any other auditor both immediately after liberalization in 1993 and still in 1997, indicative of the role of the Big Six in providing audit credibility in the eyes of international investors. In addition, Big Six auditors strengthened their position in the finance sector and, outside the finance sector, among larger companies over the period studied. We also find that in both 1993 and 1997 Big Six firms were distinguished specifically from the second-tier international firms, consistent with the view that, in post-liberalization Greece, companies by their choice of auditor appear to be distinguishing Big Six firms from all others but not between second-tier international firms and local auditors. These findings shed light on the hitherto unresearched area of which companies Big Six auditors target in order to gain market share when they are new entrants in an environment radically changed by regulatory reform. In addition the research extends the auditor name brand reputation debate by its finding that, in post-liberalization Greece, second-tier international firms appear to be distinguished from the Big Six but not from the local audit firms.     

Strong Consistency of the Maximum Likelihood Estimator in Generalized Linear and Nonlinear Mixed-Effects Models

Generalized linear and nonlinear mixed-effects models are used extensively in biomedical, social, and agricultural sciences. The statistical analysis of these models is based on the asymptotic properties of the maximum likelihood estimator. However, it is usually assumed that the maximum likelihood estimator is consistent, without providing a proof. A rigorous proof of the consistency by verifying conditions from existing results can be very difficult due to the integrated likelihood. In this paper, we present some easily verifiable conditions for the strong consistency of the maximum likelihood estimator in generalized linear and nonlinear mixed-effects models. Based on this result, we prove that the maximum likelihood estimator is consistent for some frequently used models such as mixed-effects logistic regression models and growth curve models.     

Tax effects in the dutch bond market

In this paper an analysis of the Dutch bond market is made. The technique used is linear programming. Given the fact that coupon income and capital gains are taxed differently and that some investors are tax-exempt in the Netherlands, it is shown that there are overpriced bonds in the market. This is as can be expected. But it is found that there are bonds that a rational investor would never hold in his portpolio, whatever the tax rate the investor has to pay on coupon income. Given the fact that the Dutch bond market is very illiquid for some bonds, an analysis of the effects of bid-ask spreads is made. It is shown that the effect of these spreads cannot explain the existence of bonds that are overpriced. It is not clear where these remaining overpricings stem from.     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.     

The costs of suboptimal dynamic asset allocation: General results and applications to interest rate risk, stock volatility risk, and growth/value tilts

The recent theoretical asset allocation literature has derived optimal dynamic investment strategies in various advanced models of asset returns. But how sensitive is investor welfare to deviations from the theoretically optimal strategy? Will unsophisticated investors do almost as well as sophisticated investors? This paper develops a general theoretical framework for answering such questions and applies it to three specific models of interest rate risk, stochastic stock volatility, and mean reversion and growth/value tilts of stock portfolios. Among other things, we find that growth/value tilts are highly valuable, but the hedging of time-varying stock risk premia is less important.     

Revisiting dividend yield dynamics and returns predictability: Evidence from a time-varying ESTR model

Since the bubble of the late 1990s the dividend yield appears non-stationary indicating the breakdown of the equilibrium relationship between prices and dividends. Two lines of research have developed in order to explain this apparent breakdown. First, that the dividend yield is better characterised as a non-linear process and second, that it is subject to mean level shifts. This paper jointly models both of these characteristics by allowing non-linear reversion to a changing mean level. Results support stationarity of this model for eight international dividend yield series. This model is than applied to the forecast of monthly stock returns. Evidence supports our time-varying non-linear model over linear alternatives, particularly so on the basis of an out-of-sample R-squared measure and a trading rule exercise. More detailed examination of the trading rule measure suggests that investors could obtain positive returns, as the model forecasts do not imply excessive trading such that costs would not outweigh returns. Finally, the superior performance of the non-linear model largely arises from its ability to forecast negative returns, whereas linear models are unable to do.     

Canonical forms and tests of hypotheses Part II: Multivariate mixed linear models

Abstract  In the literature on multivariate analysis of variance, exact test procedures are restricted to linear models with fixed effects only. In this paper tests are presented for multivarite linear hypotheses with respect to mixed models, which constitude a generalization of (univariate) regular models described by R oebruck (1982). Furthermore it is shown, that the matrices, which are used to compute the test statistics, can be derived from the univariate "sums of squares" in the same manner as in the case of fixed models. The applicability of this theory is demonstrated by two examples.     

Auditor realignment and 8−K disclosures—Usefulness for investor decision making

This study extends prior studies on auditor changes by testing (1) whether investors react to 8-K disclosures, and (2) the probability of investors anticipating a potential switch. The study includes 136 firms that both switched and did not switch auditors. It is hypothesized that investors would find it difficult to ascertain the true motives behind auditor changes. Event methodology and logit analysis are used. The results indicate a negative drift in abnormal returns prior to the switch, followed by significant positive abnormal returns on the day of the switch, and a positive drift after the switch.     

Herding behavior in the cryptocurrency market during COVID-19 pandemic: The role of media coverage

This paper examines herding behavior in the cryptocurrency market during the COVID-19 pandemic using daily data and based on static and regime-switching models. Furthermore, we investigate whether herding behavior is affected by the coronavirus media coverage. Based on a sample of the top-43 cryptocurrencies in terms of market capitalization between 2013 and 2020, we find significant evidence of herding for the entire sample period only during high volatility state. Moreover, during the COVID-19 crisis, results suggest that investors in the cryptocurrency market follow the consensus. Finally, the impact of coronavirus media coverage is significant on herding among investors, explaining such behavior in the cryptocurrency market during the COVID-19 crisis. Our findings explain herding determinants that may help investors avoid such comportment, mainly during the crisis.