Liability driven investment with alternative assets: Evidence from Brazil

We study the portfolio choice problem for an asset-liability investor who invests in stocks, equity mutual funds, government bonds, short term interest, hedge funds, listed real estate, and commodities futures available in Brazil. Inflation and real interest play as important risk sources. We estimate the asset classes and liabilities time-varying conditional covariance structure using an asymmetric multivariate dynamic conditional correlation GARCH model and compare the asset-liability portfolio's global minimum variance allocation with Brazilian pension funds' market portfolio. The conditional covariance structure provides insights about the complex dynamic relationships between the asset classes and liabilities. We find that some (though not all) Brazilian alternative assets render strong diversification and liabilities hedging benefits for asset-liability investors. There are significant strategic asset allocation differences between the market portfolio and the liability driven portfolio as given by our model. We, therefore, question the Brazilian pension funds' allocation.     

Learning from evaluation by peer team: a case study of a family counselling organization

This qualitative study explores how employees learn from Team Primacy Concept‐based employee evaluation and how they use the feedback in performing their jobs. Team Primacy Concept‐based evaluation is a type of multirater evaluation. The distinctive characteristic of such evaluation is its peer feedback component during which the employee's performance is discussed by peers in a face‐to‐face team setting. The study used Kolb's experiential learning model to describe the process by which employees learn from Team Primacy Concept‐based employee evaluation and the ways in which they use the knowledge to improve their job performance. The study found eight major dimensions that highlight employee learning as a result of the employees' engagement in the process of Team Primacy Concept‐based evaluation.     

Option Pricing When Jump Risk Is Systematic1

This paper generalizes the Merton jump-diffusion option pricing model to the case in which jump risk cannot be eliminated in the market portfolio. the option pricing formula is obtained using a general equilibrium asset pricing model. Since jump risk is systematic, the correlation of the underlying stock's jump with the market portfolio's jump affects the option price.     

Diversification potential of Asian frontier,BRIC emerging and major developed stock markets: A wavelet-based value at risk approach

This study examines the portfolio risk and the co-movements between each of the BRIC emerging and South Asian frontier stock markets and each of the major developed stock markets (U.S., UK and Japan), using the wavelet squared coherence approach as well as the wavelet-based Value at Risk (VaR) method. The results show that the co-movements and diversification benefits between these markets vary over time and across frequencies. Additionally, the co-movements are intensified in the wake of the recent global financial crisis (GFC) and the Eurozone sovereign debt crisis (ESDC). More precisely, the wavelet-based VaR ratio indicates that including a BRIC or a South Asian (particularly Pakistan and Sri Lanka at both the short- and long-term) stock market in a portfolio of the developed stock markets reduces the resulting portfolio's VaR. Specifically, adding China in the medium term to this portfolio reduces risk in the pre- and during both the GFC and ESDC periods. By assigning optimal weights to the different market assets in the portfolio formulation, the analysis thus has implications for international investors.     

Instructional skills for on‐the‐job training and experiential learning: an empirical study of Japanese firms

Despite the effectiveness of on‐the‐job training (OJT), few systematic empirical studies have been conducted on how OJT trainers instruct trainees in firms. The primary goal of this study was to investigate the characteristics of the trainer's instructional skills for OJT using survey data collected from 715 employees covering 22 firms. Results indicate that excellent OJT trainers use four types of instructional skills: (1) stretching trainee objectives, (2) monitoring their progress, (3) providing positive feedback, and (4) promoting reflection on results. The findings suggest that excellent OJT trainers facilitate trainees' experiential learning by promoting deliberate practice and reflective practice. Theoretical and managerial implications are also discussed.     

Using animated agents in learner‐controlled training: the effects of design control

Animated agents have the potential to increase engagement and learning during online training by acting as personalized tutors. However, little is known about the conditions that make these agents most effective. In this study, 183 e‐learners completed a Microsoft Excel training course. Approximately half were assigned an agent with predetermined features. The others were allowed to choose their agent's appearance, personality, feedback style or all of the above features. Offering multiple choices increased learning. Unexpectedly, choice of feedback style alone decreased self‐efficacy. Choosing the agent's appearance increased self‐efficacy and the number of training modules completed. Overall, this study expands the learner control literature, identifying a new form of learner control that has some beneficial effects on knowledge acquisition.     

Daily outfit satisfaction: the effects of self and others' evaluation on satisfaction with what I wear today

This study investigated the satisfaction of the outfit which an individual chose to wear for the day by examining how self and others' evaluations influenced the outfit satisfaction and the intention to re‐wear. In addition, moderator variables (body satisfaction and body surveillance) that affected the effect of the evaluative factors upon satisfaction and behavioural intention were also examined. An online‐survey was conducted and the sample size used in the analysis was 349 in total. Using SPSS 18.0 and AMOS 18.0, structural equation modeling analysis and one‐way analysis of variance were implemented for hypothesis testing. The results showed that self‐evaluation as a perception of appropriateness of the outfit for that day and others' positive feedback increases outfit satisfaction. Appropriateness perception also had a significant impact on the intention to re‐wear. However, feedback from others on one's outfit did not have a significant direct effect on behavioural intention. Three‐way ANOVA was performed to verify the impact the feedback from others, body satisfaction, and body surveillance had on the respondent's intention to re‐wear, and a three‐way interaction effect was statistically significant. While individuals with high body satisfaction were likely to be confident about their appearance overall, the feedback from others did not impact their satisfaction. Individuals with low body satisfaction were influenced by others' feedback on their outfit. Individuals with high levels of body surveillance who sensitively monitored others' feedback especially displayed decreased intention to re‐wear when feedback from others on their outfit was negative. This research contributed to the deeper understanding of consumer's clothing behaviour at the post‐purchase stage. Enhanced understanding of lasting satisfaction and benefits pursued throughout the time while using the product would be essential in developing consumer‐centric marketing strategies.     

The effects of training design,individual characteristics and work environment on transfer of training

This study aims to gain insight into some of the factors that determine the transfer of training to the work context. The present research examined the relationship between three types of predictors on transfer of training, including training design, individual characteristics and work environment. Data was collected at two points in time from 182 employees in a large grocery organization. The results indicated that transfer design, performance self‐efficacy, training retention and performance feedback were significantly related to transfer of training. Contrary to expectation, supervisory support was not significantly related to transfer of training. These results suggest that in order to enhance transfer of training, organizations should design training that gives trainees the ability to transfer learning, reinforces the trainee's beliefs in their ability to transfer, ensures the training content is retained over time and provides appropriate feedback regarding employee job performance following training activities.     

Trading co‐integrated assets with price impact

Executing a basket of co‐integrated assets is an important task facing investors. Here, we show how to do this accounting for the informational advantage gained from assets within and outside the basket, as well as for the permanent price impact of market orders (MOs) from all market participants, and the temporary impact that the agent's MOs have on prices. The execution problem is posed as an optimal stochastic control problem and we demonstrate that, under some mild conditions, the value function admits a closed‐form solution, and prove a verification theorem. Furthermore, we use data of five stocks traded in the Nasdaq exchange to estimate the model parameters and use simulations to illustrate the performance of the strategy. As an example, the agent liquidates a portfolio consisting of shares in Intel Corporation and Market Vectors Semiconductor ETF. We show that including the information provided by three additional assets (FARO Technologies, NetApp, Oracle Corporation) considerably improves the strategy's performance; for the portfolio we execute, it outperforms the multiasset version of Almgren–Chriss by approximately 4–4.5 basis points.     

Leadership training and organizational learning climate: Measuring influences based on a field experiment in education

Research considering the effects of leadership training and development is underresearched. However, leadership behaviour can generate greater levels of performance and satisfaction. In this study, the effect of a group reflective learning programme for school leaders is examined. The study questions whether leadership development, using a group reflective learning programme that focuses on coaching skills, can influence teacher perceptions of the organizational learning climate. Gaining a deeper insight in factors influencing organizational learning climate is important because organizational learning climate is associated with job motivation, job satisfaction, positive working conditions and the optimizing of training outcomes. Hence, a positive organizational learning climate can contribute to organizational performance, in the case of primary education delivering quality education to pupils. Based on a sample of 289 teachers, it turned out that school leaders’ participation in the group reflective learning programme resulted in a significant increase of teachers’ perceptions of the organizational learning climate. The results are inspiring for scholars, policy makers and practitioners.     

Does the More Risk‐Averse Investor hold a Less Risky Portfolio?*

We study the suitability of using absolute risk aversion as a measure of willingness to take risk in the Arrow–Debreu portfolio framework. We define a global measure of risk for the Arrow–Debreu portfolio, which is measured by the sensitivity of an individual's Arrow–Debreu portfolio payoff to the change in the market return. We call this measure ‘conservatism’ and show that the concept of ‘more conservative’ is stronger than that of ‘more risk‐averse.’ A higher absolute risk aversion is only necessary but not sufficient to induce a less risky Arrow–Debreu portfolio. Our results not only challenge the well‐accepted notion that a more risk‐averse investor holds a less risky portfolio, but also suggest a stronger measure – conservatism – for evaluating the riskiness of portfolio.     

Retail investors and financial advisors: New evidence on trust and advice taking heuristics

This paper investigates factors that influence trust and advice taking among retail investors when consulting with financial advisors and making real-world portfolio decisions. The data reveal that non-expert retail investors trust their advisors a lot. Trust formation appears to be well described by a simple heuristic that relies substantially on the advisor's communication style when deciding how much to trust and delegate investment decisions. Portfolio decisions appear to depend more on investors' perceptions about the investor–advisor relationship than on the risk and return characteristics of investments comprising the portfolio choice set. This evidence supports Pentland's (2008) “honest signals” as a more powerful mechanism underlying investor trust than standard metrics based on past performance. Trust and advice-taking heuristics can be interpreted as well adapted to the environment of the non-profit bank cooperatives in which they are observed, implying that trusting based on simple honest signals, although vulnerable to exploitation, can be interpreted as ecologically rational. Features of the investor's environment typical of non-profit cooperative banks imply that the heuristics investors use can perform rather well without requiring investment experience or financial sophistication, which most investors in our sample are well aware they lack.     

A study focusing on American expatriates’ learning in host countries

This study examines the learning process and situations while expatriates are living and working in a foreign country. The survey was conducted on 70 American expatriates via individual e‐mails and the World Wide Web. The study found that expatriates gained the culture of their host country through reflective learning. Cross‐cultural training programs should be examined based on expatriates’ actual needs. Finally, several learning situations that would be helpful in reducing expatriates’ cultural difficulties are: previous cross‐cultural experience, language competency, long‐term relationships with the host people, and information about the host country originating from the home country as well as the host country.     

Networks and the Dynamics of Firms' Export Portfolio: Evidence for Mexico

We use network analysis tools to identify communities in the web of exporters' destinations. Our network‐based community measure is purely outcome based, it captures multilateral rather than bilateral dependence across countries, and it can be calculated at the industry level. Next, we use our network‐based community measure as predictor of additional countries chosen by firms expanding their export destination portfolio. Using data on Mexican new exporters, the probability of choosing a new export destination doubles if it belongs to the same community of any of the firm's previous destinations. The introduction of the network‐based community variable improves the accuracy of the model up to 19 per cent relative to a model that only includes gravity variables. Industry‐specific communities and general communities play similar roles in determining the dynamics of Mexican exporters' country portfolio.     

Returns to alliance portfolio diversity: The relative effects of partner diversity on firm's innovative performance and productivity

This study considers the impact of diversification in types of technological alliances, resulting in alliance portfolio diversity, on various dimensions of a firm's performance, as they relate to exploration and exploitation. Using a large panel of innovative firms in the Netherlands, this study shows that partner type diversity in a firm's alliance portfolio has an inverted U-shaped relationship with productivity and radical innovative performance and a positive relationship with incremental innovative performance. Moreover, the results suggest that a lower level of diversity is needed to achieve an optimal level of productivity compared to radical innovative performance, whereas for incremental innovative performance a higher level of portfolio diversity appears to give the best performance.     

Critical success factors determining performance of cross‐border acquisition: Evidence from the African telecom market

This study investigates the factors affecting Bharti Airtel's cross‐border postacquisition performance in an African market. This study describes the relationships among various factors such as technical capability, affiliated firm's absorptive capacity, and organizational learning capabilities, which determine the successful operations of the Zain acquisition deal in South Africa. This paper adopts a qualitative approach to identify factors that influence the postacquisition performance. Seven factors are identified based on the literature. Consequently, it has become a necessity to encapsulate these factors in suitable proportions. In this study, we have developed a total interpretive structural modeling (TISM) to analyze the postacquisition performance of Bharti Airtel in South Africa. Our research has highlighted six dynamic factors (organizational learning capability, knowledge management, technology capability, technology relatedness, acquirer's absorptive capacity, and national culture difference) that affect the firm's postacquisition performance. The interpretive structural model (ISM) and total interpretive structural model for postacquisition performance are built‐up. The developed TISM will support academics and practitioners to develop their understanding of acquisition performance of parent companies in the context of telecom business in the South African market.     

A NOTE ON THE QUANTILE FORMULATION

Many investment models in discrete or continuous‐time settings boil down to maximizing an objective of the quantile function of the decision variable. This quantile optimization problem is known as the quantile formulation of the original investment problem. Under certain monotonicity assumptions, several schemes to solve such quantile optimization problems have been proposed in the literature. In this paper, we propose a change‐of‐variable and relaxation method to solve the quantile optimization problems without using the calculus of variations or making any monotonicity assumptions. The method is demonstrated through a portfolio choice problem under rank‐dependent utility theory (RDUT). We show that this problem is equivalent to a classical Merton's portfolio choice problem under expected utility theory with the same utility function but a different pricing kernel explicitly determined by the given pricing kernel and probability weighting function. With this result, the feasibility, well‐posedness, attainability, and uniqueness issues for the portfolio choice problem under RDUT are solved. It is also shown that solving functional optimization problems may reduce to solving probabilistic optimization problems. The method is applicable to general models with law‐invariant preference measures including portfolio choice models under cumulative prospect theory (CPT) or RDUT, Yaari's dual model, Lopes' SP/A model, and optimal stopping models under CPT or RDUT.     

A Combination Rule for Portfolio Selection with Transaction Costs

We propose a new portfolio rule for portfolio selection problems in the presence of transaction costs. The new portfolio rule is formed by combining an extant portfolio rule with the no‐rebalancing portfolio rule, which specifies the current portfolio weights before rebalancing as the desired portfolio weights. The new portfolio rule can be applied into most extant portfolio rules. Simulation and out‐of‐sample evidence show that the new portfolio rule can greatly improve portfolio performance, in comparison with the extant portfolio rules to be combined.     

When to sell an asset amid anxiety about drawdowns

We consider risk‐averse investors with different levels of anxiety about asset price drawdowns. The latter is defined as the distance of the current price away from its best performance since inception. These drawdowns can increase either continuously or by jumps, and will contribute toward the investor's overall impatience when breaching the investor's private tolerance level. We investigate the unusual reactions of investors when aiming to sell an asset under such adverse market conditions. Mathematically, we study the optimal stopping of the utility of an asset sale with a random discounting that captures the investor's overall impatience. The random discounting is given by the cumulative amount of time spent by the drawdowns in an undesirable high region, fine‐tuned by the investor's personal tolerance and anxiety about drawdowns. We prove that in addition to the traditional take‐profit sales, the real‐life employed stop‐loss orders and trailing stops may become part of the optimal selling strategy, depending on different personal characteristics. This paper thus provides insights on the effect of anxiety and its distinction with traditional risk aversion on decision making.     

BOUNDING WRONG‐WAY RISK IN CVA CALCULATION

A credit valuation adjustment (CVA) is an adjustment applied to the value of a derivative contract or a portfolio of derivatives to account for counterparty credit risk. Measuring CVA requires combining models of market and credit risk to estimate a counterparty's risk of default together with the market value of exposure to the counterparty at default. Wrong‐way risk refers to the possibility that a counterparty's likelihood of default increases with the market value of the exposure. We develop a method for bounding wrong‐way risk, holding fixed marginal models for market and credit risk and varying the dependence between them. Given simulated paths of the two models, a linear program computes the worst‐case CVA. We analyze properties of the solution and prove convergence of the estimated bound as the number of paths increases. The worst case can be overly pessimistic, so we extend the procedure by constraining the deviation of the joint model from a baseline reference model. Measuring the deviation through relative entropy leads to a tractable convex optimization problem that can be solved through the iterative proportional fitting procedure. Here, too, we prove convergence of the resulting estimate of the penalized worst‐case CVA and the joint distribution that attains it. We consider extensions with additional constraints and illustrate the method with examples.