What drives asymmetric dependence structure of asset return comovements?

We examine the determinants of return comovements of three different asset classes and provide critical insights on the key macroeconomic and non-macroeconomic factors which drive the asset return comovements during economic contraction and expansion regimes. We show that amongst the macroeconomic factors, interest rate and inflation have significant effect on the return comovements during the economic contraction regime whilst risk aversion significantly affects the return comovements during the economic expansion regime. The non-macroeconomic factors, output uncertainty, bond illiquidity and depth of recession contribute significantly in explaining the variations of return comovements for all asset pairs during both economic contraction and expansion periods except for real estate-based portfolios. Our results are robust to alternative model specification that uses regime switching MGARCH model.     

What is the impact of wealth shocks on asset allocation?

I test the assumption of constant relative risk aversion using U.S. macroeconomic data and analyse the role of wealth shocks in generating transitory changes in asset portfolio composition. I show that the risky asset share exhibits cyclical behavior and it is significantly (and positively) affected by unexpected variation in wealth. Therefore, the empirical evidence suggests that risk aversion is counter-cyclical. I also find that the portfolio share of housing wealth falls when the agent is faced with a positive wealth shock, i.e. housing is a hedge against unfavorable wealth fluctuations. Finally, considering a variety of wealth definitions, the results show that: (i) wealth effects are stronger for direct holdings of risky assets than for indirect holdings, which highlights that investors do not typically trade some assets such as pension or mutual funds; (ii) although significant, wealth effects on asset allocation are mainly temporary as agents quickly rebalance the asset portfolio composition (i.e. there is weak evidence of inertia or slow adjustment in asset allocation); and (iii) changes in expected returns partially explain the variation in risky asset allocation.     

Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective

It is often suggested that through a judicious choice of predictors that track business cycles and market sentiment, simple vector autoregressive (VAR) models could produce optimal strategic portfolio allocations that hedge against the bull and bear dynamics typical of financial markets. However, a distinct literature exists that shows that nonlinear econometric frameworks, such as Markov switching (MS), are also natural tools to compute optimal portfolios in the presence of stochastic good and bad market states. In this paper we examine whether simple VARs can produce portfolio rules similar to those obtained under MS, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those typical of nonlinear models for a long-horizon investor with constant relative risk aversion. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (net of transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks. We also compute the improvement in realized performance that may be achieved adopting more complex MS models and report this may be substantial in the case of regime switching ARCH.     

How does the choice of Value-at-Risk estimator influence asset allocation decisions?

Considering the growing need for managing financial risk, Value-at-Risk (VaR) prediction and portfolio optimisation with a focus on VaR have taken up an important role in banking and finance. Motivated by recent results showing that the choice of VaR estimator does not crucially influence decision-making in certain practical applications (e.g. in investment rankings), this study analyses the important question of how asset allocation decisions are affected when alternative VaR estimation methodologies are used. Focusing on the most popular, successful and conceptually different conditional VaR estimation techniques (i.e. historical simulation, peak over threshold method and quantile regression) and the flexible portfolio model of Campbell et al. [J. Banking Finance. 2001, 25(9), 1789–1804], we show in an empirical example and in a simulation study that these methods tend to deliver similar asset weights. In other words, optimal portfolio allocations appear to be not very sensitive to the choice of VaR estimator. This finding, which is robust in a variety of distributional environments and pre-whitening settings, supports the notion that, depending on the specific application, simple standard methods (i.e. historical simulation) used by many commercial banks do not necessarily have to be replaced by more complex approaches (based on, e.g. extreme value theory).     

Is local bias a cross-border phenomenon? Evidence from individual investors’ international asset allocation

Extant literature consistently documents that investors tilt their domestic equity portfolios towards regionally close stocks (local bias). We hypothesize that individual investors’ local bias is not limited to the domestic sphere but instead also determines their international investment decisions. Our results confirm the presence of a cross-border local bias. Specifically, we show (i) that the stockholdings of individual investors living within regional proximity to a foreign country display a significantly lower foreign investment bias towards investment opportunities in that country and (ii) that this drop in foreign investment bias levels is disproportionately driven by investments in regionally close neighbor-country companies. The impact of cross-border local bias on investors’ bilateral foreign equity investments is economically significant and holds even after controlling for previously identified explanations of international asset allocation.     

The real effect of banking crises: Finance or asset allocation effects? Some international evidence

This paper analyzes whether the decline in economic growth that follows a banking crisis occurs because of a reduction in the amount of credit available (finance effect) or a worsening in the allocation of investable resources (asset allocation effect). We use a sample of more than 2500 industrial firms in 18 developed and developing countries that experienced 19 systemic banking crises between 1989 and 2007. The results indicate that banking crises negatively affect firms’ intangible investments, which intensifies the economic downturn. The negative growth effect produced by the worsening of the investment allocation is stronger in countries with highly developed financial systems and institutions.     

How do valuations impact outcomes of asset sales with heterogeneous bidders?

Differences among bidder type-specific outcomes of asset sales are theoretically related to differences in bidders’ valuations and participation. The lead application to quantify these relations is takeover auctions: bidders are classified into strategic and financial, and bids are available. I structurally estimate valuations from all bids. The positive difference in premiums between strategic and financial acquirers is driven by the difference in dispersions of valuations (e.g., strategic bidders’ synergies are more dispersed) and the set of auction participants. The difference in average valuations is relatively unimportant. My approach can help explain outcomes of asset sales, even in settings with limited bidder data.     

Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?

The Shanghai International Energy Exchange (INE) facilitates both local and international investment in Chinese petrochemical-related stocks through local crude oil futures. This study investigates whether the Chinese emerging market can better aid investors' risk hedging and asset allocation compared to two major international developed markets–the Brent and West Texas Intermediate (WTI) crude oil futures markets—and examines the pairwise risk hedging effects and multi-asset allocation performance of INE and petrochemical-related stocks. The results show that INE has higher hedge effectiveness than Brent and WTI under pairwise hedging. Further, in multi-asset allocation, the portfolios containing INE outperform other portfolios. Overall, INE results in a better diversification effect and volatility reduction than the use of WTI crude oil futures to construct multi-asset allocation with Chinese petrochemical-related stocks. However, INE performance is inferior to Brent's in terms of constructing portfolios with oil or energy stocks. Finally, our results are robust to the five factors proposed by Fama and French (2015) in asset pricing.     

Value-at-risk capital requirement regulation,risk taking and asset allocation: a mean–variance analysis

In this study, the mean–variance framework is employed to analyze the impact of the Basel value-at-risk (VaR) market risk regulation on the institution's optimal investment policy, the stockholders’ welfare, as well as the tendency of the institution to change the risk profile of the held portfolio. It is shown that with the VaR regulation, the institution faces a new regulated capital market line, which induces resource allocation distortion in the economy. Surprisingly, only when a riskless asset is available does VaR regulation induce the institution to reduce risk. Otherwise, the regulation may induce higher risk, accompanied by asset allocation distortion. On the positive side, the regulation implies an upper bound on the risk the institution takes and it never induces the firm to select an inefficient portfolio. Moreover, when the riskless asset is available, tightening the regulation always increases the amount of maintained eligible capital and decreases risk.     

The optimal asset allocation of the main types of pension funds: a unified framework

The existing literature deals with the optimal investment strategy of defined benefit (DB) or defined contribution (DC) pension plans. This article’s objective is to compare the optimal policies of different types of pension plans. This is done by first defining an original framework, which is based on the distinction between the nature of the guarantee—which can be internal or external—offered by or to a pension fund. This framework allows to establish links between optimization programs of DC, DB and targeted money purchase schemes. The case of an internal guarantee appears as a standard portfolio insurer’s problem. The second kind of guarantee, not analyzed in the literature yet with regard to the resulting optimal policy, is characterized by the existence of an option in the final wealth definition. Four funds are present in the internal guarantee optimal allocation: the speculative component, the preference independent guarantee- and contribution-hedge terms and the preference dependent state variable-hedge fund. The external guarantee program, solved with an original method using the principles of standard options theory, yields an optimal policy incorporating the delta of the option embodied in the final wealth definition. The conclusion is that the resulting optimal portfolio policy becomes riskier.

Strategic timing of earnings announcements?

Using firm‐specific regressions, I show that earnings response coefficient differ across firms. However, there is no evidence of differential earnings response coefficient to a certain earnings announcement time. By switching to a different announcement time from its preferred time, a firm does not gain a softer market reaction. I compare research results from a firm‐specific method and from a pooled time‐series and cross‐sectional method and demonstrate that they differ significantly due to large heterogeneity across firms. I suggest that researchers should adopt a firm‐specific approach to avoid misleading results and to achieve improved estimations.     

What lies behind the asset growth effect?

This study finds that changes in total factor productivity (TFP) serve as one of the drivers behind the asset growth effect. Firms increase (decrease) assets when there is an increase (decrease) in TFP. And increases (decreases) in TFP also cause corresponding increases (decreases) in earnings and returns. Subsequently, changes in TFP reverse, which also reverse earnings and returns, leading to the observed asset growth effect. Our results are robust to sorting using the Fama-French five-factor model and momentum factor, and its asset pricing implications, using low-high spread asset growth portfolios with correspondingly low-high spread TFP changes.     

Do subjective expectations explain asset pricing puzzles?

The structural uncertainty model with Bayesian learning, advanced by Weitzman (AER 2007), provides a framework for gauging the effect of structural uncertainty on asset prices and risk premiums. This paper provides an operational version of this approach that incorporates realistic priors about consumption growth volatility, while guaranteeing finite asset pricing quantities. In contrast to the extant literature, the resulting asset pricing model with subjective expectations yields well-defined expected utility, finite moment generating function of the predictive distribution of consumption growth, and tractable expressions for equity premium and risk-free return. Our quantitative analysis reveals that explaining the historical equity premium and risk-free return, in the context of subjective expectations, requires implausible levels of structural uncertainty. Furthermore, these implausible prior beliefs result in consumption disaster probabilities that virtually coincide with those implied by more realistic priors. At the same time, the two sets of prior beliefs have diametrically opposite asset pricing implications.     

Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?

This study examines whether geopolitical risk (GPR) exhibits an ability to forecast crude oil volatility from a time-varying transitional dynamics perspective. Unlike previous studies that assume an oversimplification of the fixed transition probabilities for crude oil volatility, we develop an asymmetric time-varying transition probability Markov regime switching (AS-TVTP-MS) GARCH model. In-sample estimated results show that GPR yields strong evidence of regime switching behavior on crude oil volatility and that the negative shocks of GPR result in greater effects on switching probabilities than positive shocks. Out-of-sample results indicate that the AS-TVTP-MS GARCH model containing the GPR index outperforms other models, suggesting that the consideration of GPR information and time-varying regime switching together results in superior predictive performance. Moreover, the predictability of oil volatility is further verified to be economically significant in the framework of portfolio allocation. In addition, our results are robust to various settings.     

Do capital flows change domestic credit allocation?

Since the 1990s, domestic bank credit has been reallocated away from lending to non-financial business and toward households. An expanding literature discusses negative effects on growth and stability of this change in credit allocation. We research its drivers. We hypothesize that if foreign capital flows into economies with few investment opportunities, it may substitute for domestic bank lending to non-financial business, so that bank balance sheets become more dominated by household lending. In GMM estimations on data for 36 economies over 1990–2011, we find evidence consistent with this mechanism. Foreign capital inflows into the non-bank sector (but not into the bank sector) are associated with lower shares of business lending in domestic bank portfolios. The association is weaker in economies with more investment opportunities, whether proxied by investment shares, current account surpluses, or EMU membership. Our results highlight the importance of sectoral destination in determining the effects of capital flows.     

Dynamic asset–liability management in a Markov market with stochastic cash flows

This paper provides a general model to investigate an asset–liability management (ALM) problem in a Markov regime-switching market in a multi-period mean–variance (M–V) framework. Emphasis is placed on the stochastic cash flows in both wealth and liability dynamic processes, and the optimal investment and liquidity management strategies in achieving the M–V bi-objective of terminal surplus are evaluated. In this model, not only the asset returns and liability returns, but also the cash flows depend on the stochastic market states, which are assumed to follow a discrete-time Markov chain. Adopting the dynamic programming approach, the matrix theory and the Lagrange dual principle, we obtain closed-form expressions for the efficient investment strategy. Our proposed model is examined through empirical studies of a defined contribution pension fund. In-sample results show that, given the same risk level, an ALM investor (a) starting in a bear market can expect a higher return compared to beginning in a bull market and (b) has a lower expected return when there are major cash flow problems. The effects of the investment horizon and state-switching probability on the efficient frontier are also discussed. Out-of-sample analyses show the dynamic optimal liquidity management process. An ALM investor using our model can achieve his or her surplus objective in advance and with a minimum variance close to zero.     

Strategic Management Thinking and Practice in the Public Sector: A Strategic Planning for All Seasons?

This paper explores how strategic management thinking manifests itself in strategic management practice in the public sector. Mintzberg's framework of ten strategic management schools of thought is chosen for mapping strategic management thinking. The paper analyses a convenience sample of 35 strategic management processes, observation of an agency's strategy reformulation process and interviews of managers in the public sector in Norway for informing the discussion. Strategic planning is heavily criticised in some of the business strategy literature. The analysis indicates that strategic management in the public sector extensively uses strategic planning, bundled with certain other schools of thought, despite tendencies to downplay formal, mechanistic planning in contemporary strategic management theory.     

Do different streams of capital flows affect asset prices differently?

This paper explores the impact of six types of gross capital flows (debt, equity, and banking gross inflows and outflows) on two dimensions: (1) extreme episodes of surges, stops, flights, and retrenchments, and (2) the probability of boom-busts in ASEAN-4 asset markets for the period 1993–2018. To this end, we first decompose gross capital inflows and outflows from Balance of Payments 5 and 6 and show that ASEAN-4 is largely dominated by portfolio flows and a relatively small magnitude of banking flows. However, when we link this decomposition to the extreme episodes, our findings show banking flows are volatile enough to cause greater occurrences of flight and retrenchment episodes while volatile debt flows tend to lead to surge and stop episodes. In the second part, we construct asset price index for ASEAN-4 that can detect boom-busts periods with a minimal noise-to-signal ratio eight quarters ahead. We use heteroscedasticity panel probit and ordinal generalized linear models to show that fundamental variables and banking inflows are statistically significant at increasing likelihood of boom-busts in asset markets. These two findings highlight that although largest percentage of capital flows come through debt and equity markets, the banking channel is of paramount importance in causing extreme episodes of flight and retrenchment as well as boom-busts of asset markets.     

An evaluation of conditional multi-factor models in active asset allocation strategies: an empirical study for the German stock market

This paper examines the out-of-sample performance of asset allocation strategies that use conditional multi-factor models to forecast expected returns and estimate the future variance and covariance. We find that strategies based on conditional multi-factor models outperform strategies based on unconditional multi-factor models, and do better than a passive buy-and-hold strategy. However, a strategy that uses the sample mean as a return forecast is superior. We also find that the estimation of the covariance matrices based on the conditional and unconditional multi-factor models does not improve the performance of the active asset allocation strategy relative to the incorporation of the historical covariance matrices. These results are fairly robust to different estimation approaches, as well as to the impact of transaction costs and the consideration of upper and lower bounds for the portfolio weights.