Review Article of Drèze's essays on economic decisions under uncertainty

Jacques Drèze has participated significantly in many fields of economic analysis. The book we have reviewed is limited to his main contributions to the economics of uncertainty and information. It is rich in ideas, models, and results for graduate students and researchers who are interested in this now basic dimension of economic analysis. We hope that its publication will permit the public at large to better appreciate the importance of its author's contributions.Economics Department and CRT Université de Montréal C.P. 6128. Succursale A Montréal (Québec) Canada H3C 3J7. Kenneth Arrow, Danielle Blanchard, Camille Bronsard, Leonard Dudley, Robert Gagné, Edi Karni and Françoise Shoumaker provided very useful comments on a first version of this review. Thanks are also due to Carole Laflamme for editorial assistance.     

Homemade international diversification under economic policy uncertainty

We examine how US mutual funds that invest domestically make portfolio adjustments by incorporating US-listed foreign stocks (cross-listed stocks) when faced with US market economic policy uncertainty. We document a positive association between US economic policy uncertainty and US mutual funds’ weight of cross-listed stocks, and find that the effect is concentrated in funds that mainly invest in the US domestic market. The findings are not sensitive to the instrumental variable approach, model specification, sampling, variable definition, and controlling for macro characteristics. Funds with higher weight of cross-listed foreign stocks when US economic policy uncertainty increases outperform other funds, indicating the rationality of such an investment strategy. A long-short portfolio generates 3.4% annualized abnormal return in the immediate following quarter. Our study shields light not only on the international diversification benefit of US-listed foreign stocks but also on the importance of capital market openness for domestic investors.     

First-and second-best allocations under economic and environmental uncertainty

This paper uses a micro-founded DSGE model to compare second-best optimal environmental policy, and the resulting Ramsey allocation, to first-best allocation. The focus is on the source and size of uncertainty, and how this affects optimal choices and the comparison between second- and first-best. While higher economic volatility is bad for social welfare in all cases studied, the welfare effects of higher environmental volatility depend on its size and the effectiveness of public abatement policy. The Ramsey environmental tax is pro-cyclical when there is an economic shock, while it is counter-cyclical when there is an environmental shock.     

Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model

Given that policy uncertainty shocks in the economic environment can exacerbate financial market volatility and pose financial risks, this paper utilizes a smooth transition version of the GARCH-MIDAS model to investigate the impact of different structural state changes in economic policy uncertainty (EPU) on stock market volatility. The extended model explains the nonlinear effects of the macro variables and the structural break changes in regime transitions. The empirical results confirm that the EPU indicators provide effective prediction information for stock volatility from the in-sample and out-of-sample analyses, which reveals that the smooth transition model provides an effective method for detecting the possible regime changes between stock volatility and macroeconomic uncertainty. Additionally, we further confirm that some category-specific EPU indicators also have strong smooth transition behaviour with respect to stock volatility. More important, our new model provides significant economic value to investors from a utility gain perspective. Overall, the institutional changes present in EPU play a nonnegligible and important role in stock market volatility. Accurate identification of the structural features of financial data helps investors deepen their understanding of the sources of stock market volatility.     

Welfare effects of information and rationality in portfolio decisions under parameter uncertainty

We analyse and quantify, in a financial market with parameter uncertainty and for a Constant Relative Risk Aversion investor, the utility effects of two different boundedly rational (i.e. sub-optimal) investment strategies (namely, myopic and unconditional strategies) and compare them with each other and with the utility effect of full information. We show that effects are mainly caused by full information and predictability, being the effect of learning marginal. We also investigate the saver's decision regarding whether to manage her/his portfolio personally (DIY investor) or hire, against the payment of a management fee, a professional investor and find that delegation is mainly motivated by the belief that professional advisors are, depending on investment horizon and risk aversion, either better informed (‘insiders’) or more capable of gathering and processing information, rather than possessing the ability to learn from financial data. In particular, for very short investment horizons, delegation is primarily, if not exclusively, motivated by the beliefs that professional investors are better informed.     

A game-theoretic approach to decision making under uncertainty

We discuss the problem of decision making under uncertainty. Here an action choice must be made without knowing the value of all relevant variables. The importance of decision attitude, i.e. optimistic/pessimistic, is emphasized and a unified approach for evaluating alternatives under different attitudes is discussed. We show the connection between decision making under uncertainty and competitive decision making—game theory. We then draw upon a key concept used in game theory, the association of a selection probability with each alternative rather then a decisive selection of an alternative, and apply this idea to decision making under uncertainty. Copyright © 1999 John Wiley & Sons, Ltd.     

Superreplication under model uncertainty in discrete time

We study the superreplication of contingent claims under model uncertainty in discrete time. We show that optimal superreplicating strategies exist in a general measure-theoretic setting; moreover, we characterize the minimal superreplication price as the supremum over all continuous linear pricing functionals on a suitable Banach space. The main ingredient is a closedness result for the set of claims which can be superreplicated from zero capital; its proof relies on medial limits.     

International stock return predictability under model uncertainty

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predictive variables, whereas valuation ratios perform rather poorly. Yet, predictability of market excess returns weakens substantially, once model uncertainty is accounted for. We document notable differences in the degree of in-sample and out-of-sample predictability across different stock markets. Overall, these findings suggest that return predictability is neither a uniform, nor a universal feature across international capital markets.     

Monetary policy under model and data-parameter uncertainty

Empirical Taylor rules are much less aggressive than those derived from optimization-based models. This paper analyzes whether accounting for uncertainty across competing models and (or) real-time data considerations can explain this discrepancy. It considers a central bank that chooses a Taylor rule in a framework that allows for an aversion to the second-order risk associated with facing multiple models and measurement-error configurations. The paper finds that if the central bank cares strongly enough about stabilizing the output gap, this aversion leads to significant declines in the coefficients of the Taylor rule even if the central bank's loss function assigns little weight to reducing interest rate variability. Furthermore, a small degree of aversion can generate an optimal rule that matches the empirical Taylor rule.     

Forecasting exchange rates under parameter and model uncertainty

We introduce a forecasting method that closely matches the econometric properties required by exchange rate theory. Our approach formally models (i) when (and if) predictor variables enter or leave a regression model, (ii) the degree of parameter instability, (iii) the (potentially) rapidly changing relevance of regressors, and (iv) the appropriate shrinkage intensity over time. We consider (short-term) forecasting of six major US dollar exchange rates using a standard set of macro fundamentals. Our results indicate the importance of shrinkage and flexible model selection/averaging criteria to avoid poor forecasting results.     

Portfolio optimization under model uncertainty and BSDE games

We consider robust optimal portfolio problems for markets modeled by (possibly non-Markovian) Itô–Lévy processes. Mathematically, the situation can be described as a stochastic differential game, where one of the players (the agent) is trying to find the portfolio that maximizes the utility of her terminal wealth, while the other player (“the market”) is controlling some of the unknown parameters of the market (e.g., the underlying probability measure, representing a model uncertainty problem) and is trying to minimize this maximal utility of the agent. This leads to a worst case scenario control problem for the agent. In the Markovian case, such problems can be studied using the Hamilton–Jacobi–Bellman–Isaacs (HJBI) equation, but these methods do not work in the non-Markovian case. We approach the problem by transforming it into a stochastic differential game for backward stochastic differential equations (a BSDE game). Using comparison theorems for BSDEs with jumps we arrive at criteria for the solution of such games in the form of a kind of non-Markovian analogue of the HJBI equation. The results are illustrated by examples.     

A multi‐agent‐based hybrid framework for international marketing planning under uncertainty

The increased complexity and competition in the global marketing environment present new challenges to decision‐makers. The characteristics of the international marketing planning problem are clarified in this paper. The advantages and disadvantages of relevant techniques and technologies that may be applied to deal with the planning problem are analysed. A multi‐agent‐based hybrid intelligent framework for international marketing planning and associated Internet strategy formulation is then established, with underlying techniques, technologies, software architecture and integration method outlined. In addition, a software prototype of the hybrid framework, called AgentsInternational, is created and presented, with initial evaluation results reported. Further work on this topic is also planned. Copyright © 2009 John Wiley & Sons, Ltd.     

Liquidity preference under uncertainty: A model of dynamic investment in illiquid opportunities

Whereas frictionless exchange markets provide a high degree of liquidity for financial assets, investments in real assets and productive capacity may be very costly to modify, and thus effectively irreversible in the short-run. This paper addresses the problem of an investor (individual or enterprise) who must allocate a limited resource to productive investments over time. Investment opportunities arrive in a random sequence and are irreversible in the short-run: thus investment decisions are made under uncertainty as to future opportunities (which may have to be foregone). The analysis demonstrates that a rational investor will demand a higher return on long-lasting opportunities than on those which are instantaneously reversible. The liquidity premium increases with the average duration of the non-liquid investments.     

稳字当头,把握结构性机会——商业银行如何应对疫情背景下的全球经济不确定性

当前,国内疫情得到有效控制,国外疫情正在爬坡过坎,全球金融市场震荡,经济发展面临着重大不确定性。疫情叠加全球经济放缓,对商业银行的影响主要表现为:线下业务拓展和服务受阻、信贷需求减弱、存款短期存在阶段性机会但稳存增存压力预计会逐步增加、息差收窄压力加大,中间业务收入明显下降,风险暴露逐步加快。同时也要看到,受疫情影响,财政货币政策更加积极,“新基建”四起,部分涉疫行业短期受益,疫情加快了企业运营和客户行为线上化迁徙步伐,为银行赢得再差异化竞争创造了时机。     

A risk-based approach for pricing American options under a generalized Markov regime-switching model

This paper considers a risk-based approach for pricing an American contingent claim in an incomplete market described by a continuous-time, Markov, regime-switching jump-diffusion model. We formulate the valuation problem as a stochastic differential game and use dynamic programming. Verification theorems for the Hamilton–Jacobi–Bellman–Issacs (HJBI) variational inequalities of the games are used to determine the seller's and buyer's prices and optimal exercise strategies.     

Do green bonds and economic policy uncertainty matter for carbon price? New insights from a TVP-VAR framework

Green bond shocks and economic policy uncertainty are essential factors affecting macroeconomic development and green finance. In this paper, the time-varying parameter vector autoregressive (TVP-VAR) framework is used to analyze the monthly data of China from April 2014 to March 2022 and to investigate the dynamic impact of green bond shock and economic policy uncertainty on carbon prices. The results show that economic policy uncertainty and the impact of the green bond have significant time-varying and short-term effects on carbon price. In the short term, economic policy uncertainty has a significant positive impact on carbon price most of the time, while green bond has a significant negative impact on carbon price most of the time. Meanwhile, economic policy uncertainty and the impact of green bond on carbon price in Hubei and Guangdong are heterogeneous. In addition, we also use Bayesian VAR (BVAR) model to test the robustness of the results. Based on the research results, some policy suggestions are put forward, including improving the stability of economic policies, implementing green bond support policies, and speeding up the improvement of the national unified carbon emission trading market.     

Dynamically consistent investment under model uncertainty: the robust forward criteria

We combine forward investment performance processes and ambiguity-averse portfolio selection. We introduce robust forward criteria which address ambiguity in the specification of the model, the risk preferences and the investment horizon. They encode the evolution of dynamically consistent ambiguity-averse preferences.We focus on establishing dual characterisations of the robust forward criteria, which is advantageous as the dual problem amounts to the search for an infimum whereas the primal problem features a saddle point. Our approach to duality builds on ideas developed in Schied (Finance Stoch. 11:107–129, 2007) and ?itkovi? (Ann. Appl. Probab. 19:2176–2210, 2009). We also study in detail the so-called time-monotone criteria. We solve explicitly the example of an investor who starts with logarithmic utility and applies a quadratic penalty function. Such an investor builds a dynamic estimate of the market price of risk \(\hat{\lambda}\) and updates her stochastic utility in accordance with the so-perceived elapsed market opportunities. We show that this leads to a time-consistent optimal investment policy given by a fractional Kelly strategy associated with \(\hat{\lambda}\) and with the leverage being proportional to the investor’s confidence in her estimate.