Asset Allocation

This study investigates the contagion effects of the 2007-2009 global financial crisis across multiple asset markets and different regions. It uses daily return data of six asset classes: stocks, bonds, commodities, shipping, foreign exchange and real estate. A robust analysis of financial contagion is provided by estimating and comparing asymmetric conditional correlations among asset markets during stable and turmoil periods. Results provide evidence on the existence of a correlated-information channel as a contagion mechanism among the U.S. stocks, real estate, commodities and emerging Brazilian bond index. The findings also support the decoupling of BRIC equity markets from the crisis, the diversification benefits of shipping and foreign exchange value of the U.S. dollar indices, and the existence of a flight to quality mechanism from risky U.S. assets to German bonds. This evidence has important implications for portfolio diversification strategies and the future work of policymakers.

Rising elderly life expectancies imply the need to accumulate sufficient savings for retirement. This paper investigates the role of recent changes in the investment menu of the Singaporean Central Provident Fund (CPF) system. Our research explores the investment patterns of CPF participants and articulates their implications for policymakers. We find that most investors use their money for housing purchase and default the remainder to the CPF investment pool. The bulk of non-housing saving sits in bank accounts paying a low return. A fraction of workers does elect outside investment products, with high-income earners and males taking more risk than low-income earners and females. Since workers who default their money to the CPF fund receive a guaranteed 2.5 % return on the Ordinary Account and 4 % on the Special Account, hurdle rates for money market and equity funds are substantial. These high hurdle rates help explain why few CPF account holders invest outside the default governm...

This working paper outlines the structural methodologies required for successful cross-border asset allocation within emerging markets, focusing on alternative investments, technology infrastructure, and real estate. It analyzes risk mitigation frameworks, jurisdictional agility, and the deployment of patient capital to maximize long-term yields while shielding portfolios from macroeconomic volatility. Through a concise examination of institutional data, current policy literature, and structural mechanics, this framework provides international wealth architects with the necessary compliance and operational insights to navigate high-growth corridors safely.

This study utilizes version 6 of the regression analysis of time series (RATS) software package to implement the estimation of the bivariate diagonal generalized autoregressive conditional heteroscedasticity (GARCH) model combined with a composite asset selection approach including two hybrid performance measures to solve 'the trade-off problem between return and risk' and 'the inconsistent results from different performance measures' in the problem of asset allocation within a group of minimum variance portfolios during the pre-COVID-19 and COVID-19 periods. Empirical results show that the optimal portfolios obtained from this approach and the assets added to a portfolio to achieve better performance differ between the pre-COVID-19 and COVID-19 periods. For instance, the optimal portfolios are the Chinese yuan-Ethereum and Bitcoin-Ethereum for the pre-COVID-19 period, but the WTI-Ethereum for the COVID-19 period. To achieve better performance, we added Ethereum to our portfolio during the pre-COVID-19 period, while WTI and Bitcoin were added during the COVID-19 period. Thus, the COVID-19 pandemic had a significant impact on the performance of asset allocation in the three markets. The proposed approaches in this study can be embedded in a computer as an asset allocation algorithm of Robo-advisers.

High levels of correlation among fi nancial assets, as well as extreme losses, are typical during crisis periods. In such situations, quantitative asset allocation models are often not robust enough to deal with estimation errors and lead to identifying underperforming investment strategies. It is an open question if in such periods, it would be better to hold diversifi ed portfolios, such as the equally weighted, rather than investing in few selected assets. In this paper, we show that alternative strategies developed by constraining the level of diversifi cation of the portfolio, by means of a regularization constraint on the sparse l q -norm of portfolio weights, can better deal with the trade-off between risk diversifi cation and estimation error. In fact, the proposed approach automatically selects portfolios with a small number of active weights and low risk exposure. Insights on the diversifi cation relationships between the classical minimum variance portfolio, risk budgeting strategies, and diversifi cation-constrained portfolios are also provided. Finally, we show empirically that the diversifi cation-constrainedbased l q -strategy outperforms state-of-art methods during crises, with remarkable out-of-sample performance in risk minimization.

The present study aims to examine the impact of two economic shocks i.e., COVID-19 and Ukraine-Russia war in the Indian equity market using 3 broad market indices and 14 sectoral indices of National Stock Exchange of India (NSE). Four events concerned with COVID-19 i.e., WHO announcement of COVID-19 as global pandemic, first lockdown in India, start of the second wave of COVID-19, peak of second wave and one event of Ukraine-Russia war have been selected for the analysis. In this study, daily stock returns have been used to compile abnormal returns and cumulative abnormal returns and event study methodology has been applied. It has been found that the selected indices show high volatility during various events, however, failed to generate abnormal returns.

Asset Pricing Theory has undergone substantial transformation since the introduction of Modern Portfolio Theory by Markowitz on 1952. Its evolution subsequently progressed through the development of Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), Intertemporal Capital Asset Pricing Model (I-CAPM), Consumption Based Capital Asset Pricing Model (C-CAPM), Sustainable Capital Asset Pricing Model (S-CAPM), and contemporary of Multifactor frameworks such as Fama-French Factor Models (FF3F, FF5F, FF6F). Although these models offer distinct theoritical perspectives, they share a common objective: to explain the relationship between risk and return more accurately. However, variations in market structures, the emergence of empirical anomalies, and the rapid growth of digital assets have challenged the explanatory power and validity of several traditional asset pricing models. Consequently, this Systematic Literature Review (SLR) aims to map the evolution of asset pricing theory, examine the theoritical fondations of major asset pricing frameworks, identify existing research gaps, and propose directions for future scholarly inquiry. The findings suggest that no single asset pricing model is capable of universally explaining variations in asset returns across all market environments. Furthermore, the rise of digital assets and advances in big data analytics highlight the needed for new generation of asset pricing theories that are more adaptive to the complexities and dynamics of contemporary financial markets.

The subject of the study is to evaluate the contribution of strategic asset allocation to the variability of Moroccan pension funds performance. The aim of the paper is to identify the role of active management factors, namely tactical allocation and security selection, in generating a performance surplus compared to strategic allocation. The relevance of the study is justified by the need to identify the sources of performance creation in order to face the commitments of Moroccan pension funds and to compensate for the decline and volatility of asset returns. The article addresses, through the use of simple linear regression methods, the relative importance of strategic asset allocation in explaining the variability of the performance of Moroccan pension funds. It introduces a scientific novelty through the use of the “performance attribution” method. The conclusions of the paper confirm the main role of strategic asset allocation, which varies according to the size of the fund, th...

This study uses an option-implied distribution as the input in asset allocation. The computation of risk-neutral densities (RND) are based on the Dow Jones Industrial Average (DJIA) index option and its constituents. Since the RNDs estimation does not incorporate risk premium, the conversion of RND into risk-world density (RWD) is required. The RWD is obtained through parametric calibration using the beta distributions. The mean, volatility, and covariance are then calculated to construct the portfolio. The performance of the portfolio is evaluated by using portfolio volatility and Sharpe ratio.

In this paper, I estimate the non-parametric optimal bond portfolio choice of a representative agent that acts optimally with respect to his/her expected utility one period forward, provided that he/she observes the ex ante liquidity signal. Using daily observations of zero-coupon Treasury and TIPS bonds yields, I construct equally-weighted returns from 2004-2012. Considering alternative measures of liquidity, I find that the liquidity differential between nominal and TIPS bonds appears to be a significant determinant of the portfolio allocation to U.S. government bonds. In fact, conditional allocations in risky assets decrease as market liquidity conditions worsen, and the effect of market liquidity decreases with the investment horizon. I also find that the bond return predictability translates into improved in-sample and out-of-sample asset allocation and performance.

Precautionary saving due to uninsurable income risk has engendered much interest because it can explain why consumption roughly tracks income over the lifecycle. However, recent …ndings suggest precautionary saving has negligible macroeconomic e¤ects. In this paper, we show that a steady-state, general-equilibrium lifecycle model can be parameterized to account for the hump-shaped lifecycle pro…le of mean consumption. As a by-product, we can then determine the contribution of precautionary saving to the capital stock for these parameters. This turns out to be sensitive to the type of borrowing frictions present. If we impose an exogenous borrowing constraint, steady-state macroeconomic variables are insensitive to simultaneous changes in the discount factor and risk aversion that preserve the equilibrium interest rate. E¤ectively, the borrowing constraint overwhelms any e¤ects of uncertainty. As aggregate precautionary saving is commonly de…ned, its dependence in this model on risk aversion has more to do with the e¤ect of intertemporal substitution. Meanwhile, an endogenous "borrowing constraint" imposed via assumptions about the income process fails to capture the properties of lifecycle consumption. Finally, if no borrowing constraint is imposed, precautionary saving will, indeed, have signi…cant e¤ects for risk aversion close to 4, and this model can better account for the lifecycle consumption pro…le than the corresponding model with borrowing constraints. Thus, while it is generally accepted that borrowing constraints and uninsurable risk are complementary frictions, in fact they are not. JEL Classi…cation: E21 Keywords: consumption hump, aggregate precautionary saving, borrowing constraints, risk aversion I would like to thank Frank Caliendo,

Este trabajo reconstruye un desplazamiento histórico y, a la vez, un cambio en las formas de gobierno económico que afecta tanto a la empresa como a la experiencia ordinaria del trabajo. El hilo conductor es doble. Por un lado, se examina cómo la corporación deja de legitimarse principalmente por su continuidad productiva y pasa a organizarse en torno a la validación bursátil, con temporalidades cada vez más cortas y con una disciplina que opera a través del precio. Por otro lado, se muestra cómo esa disciplina se vuelve operativa y exportable cuando se apoya en dispositivos de medición y verificación continua, capaces de distribuir responsabilidades y riesgos hacia individuos que deben adaptarse a señales cambiantes. En ese marco, se busca describir un mecanismo de articulación entre criterios de evaluación, dispositivos técnicos de control y subjetividades que aprenden a vivir bajo comparación permanente. La pregunta que guía el recorrido es cómo una lógica que nace y se consolida en el mundo corporativo y financiero termina reorganizando otras esferas de la vida, produciendo aislamiento, competencia cotidiana y una sensación ambigua de libertad que convive con nuevas formas de dependencia. La primera parte ordena cronológicamente el pasaje desde la empresa organizada en torno a la reinversión productiva, propia de la posguerra, hacia la primacía accionaria.

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Demographic ageing and the associated increase in the old-age dependency ratio pose
significant challenges to the long-term sustainability of pay-as-you-go (PAYG) pension systems
across Europe. Slovenia, as a post-transition economy, faces additional pressures in balancing
fiscal sustainability with adequate income protection for retirees. This paper aims to assess
the evolution of pension adequacy and sustainability in Slovenia between 1991 and 2025, with
particular emphasis on testing five research hypotheses (H1–H5) related to replacement
rates, minimum pensions, pension expenditure, and the support ratio. The study applies a
longitudinal quantitative analysis based on data from the Statistical Office of the Republic of
Slovenia (SURS) and the Pension and Disability Insurance Institute of Slovenia (ZPIZ). Key
indicators include the net replacement rate, minimum pension as a share of average wage,
pension expenditure as a percentage of gross domestic product (GDP), and the support ratio.
Comparative analysis with EU-27 benchmarks is complemented by a regression analysis,
correlation analysis, and one-sample t-tests to evaluate the proposed hypotheses. The findings
indicate a clear divergence between adequacy and sustainability. Hypotheses H1, H2, and H3
are confirmed: minimum pensions have declined relative to wages, have not kept pace with
GDP per capita, and remain significantly below the 40% adequacy threshold. In contrast, H4
and H5 are rejected: pension expenditure as a share of GDP has not increased relative to the
EU average, and the support ratio, although declining, remains above the critical threshold of
1.5. These results suggest that fiscal sustainability has been maintained, while adequacy has
weakened. The Slovenian pension system demonstrates a structural trade-off between
sustainability and adequacy. While fiscal discipline has been preserved, this has occurred at
the expense of minimum income protection. Policy implications indicate that there is room for
targeted reforms to improve pension adequacy without undermining long-term fiscal stability.

Se estudia asignaciones óptimas de clases de activo (Asset Allocation) para afiliados representativos a las AFP con diferentes plazos para jubilar. Se supone que el afiliado desearía maximizar su pensión esperada al momento de jubilar, dado un nivel de riesgo. Entonces, la pregunta es qué corresponde a Asset Allocation óptimos desde una perspectiva de largo plazo, dado que el propósito de los fondos acumulados es adquirir un pensiones. Esta pregunta no es nueva, por lo que algunos de los resultados presentados aquí son aplicaciones de conceptos existentes. Pero el problema más específico de una AFP que debe optimizar una cierta cartera de activos iniciales, más una secuencia de contribuciones a la cuenta individual, desde la perspectiva de un futuro pensionado, no ha sido resuelto, al menos planteado de esta forma, lo que da origen a algunos resultados interesantes. También puede tener novedad el cambio de perspectiva: el punto de vista de un administrador de carteras de largo plazo inserto en un país "emergente". El planteamiento del problema se resume en cambiar el numerario: tanto la rentabilidad esperada como el riesgo deben medirse en unidades de pensión futura. Esto (obviamente) implica que la moneda de referencia es la local (ajustada por inflación) y que el plazo de referencia es largo. Los instrumentos de renta fija de corto plazo son un mal hedge pues tienen baja correlación con el costo futuro de una pensión. Es de interés identificar activos que posean alta correlación con el costo de las pensiones futuras. Naturalmente, éstos corresponden principalmente a instrumentos de renta fija de largo plazo, aunque es posible que algunas clases de renta variable posean características deseables. Así, se plantea como hipótesis de trabajo que las carteras óptimas deben estar "en buena parte" constituidas por renta fija local de largo plazo ya que estos instrumentos proveen la mejor protección (hedge) existente contra variaciones adversas en el costo futuro de las pensiones. Los resultados teóricos y empíricos claramente avalan esta hipótesis, al igual que la idea de que la renta variable local tiene propiedades de protección deseables que no posee la renta variable internacional.

Robotic financial advisors (robo-advisors) have emerged as a purported low-cost and low-hassle alternative to traditional investment advisers and broker-dealers. This type of advisor assists financial institutions in employing asset-allocation models and algorithms to invest client portfolios, typically in exchange-traded funds. In this paper, we focus on reviewing the current state of the art in the provision of financial advice and discuss how regulatory agencies have interacted with aspects of robo-advising.

The equity premium puzzle is resolved by identifying the marginal investor as an unhedged entrepreneur whose labour income is a levered claim on aggregate risk. Capital-gains lock-in makes hedging prohibitively expensive, so founders optimally stay fully exposed. Under Epstein-Zin preferences with risk aversion γ = 4 and intertemporal elasticity of substitution ψ = 1.5, and using the empirical fact that the consumption volatility of stockholders is lower than their income volatility (Malloy et al., 2009), the model simultaneously delivers an equity premium of ≈ 6% and a strictly positive risk-free rate of ≈ 1%. No disasters, no unobserved latent processes, and no ad-hoc borrowing constraints are required. The theory yields a sharp, testable cross-sectional prediction linking unrealised capital gains to equity market participation.

Purpose -Stirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study. Design/methodology/approach -Methodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022. Findings -The results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions. Practical implications -In the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered. Originality/value -While limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.

As global interest rates hover near historic lows, defined benefit pension plan sponsors must grapple with the prospect of lower investment returns. We examine three levers that can enhance portfolio outcomes in a low-return world: increased contributions; reduced investment costs; and increased portfolio risk. We use portfolio simulations based on a stochastic asset class forecasting model to evaluate each lever according to two criteria: the magnitude of impact and the certainty that this impact will be realized. We show that increased contributions have the greatest and most certain impact. Reduced costs have a more modest, but equally certain impact. Increased risk can deliver a significant impact, but with the least certainty.

We provide a general framework for integration of high-frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency return volatilities and return distributions. Most procedures for modeling and forecasting financial asset return volatilities, correlations, and distributions rely on potentially restrictive and complicated parametric multivariate ARCH or stochastic volatility models. Use of realized volatility constructed from high-frequency intraday returns, in contrast, permits the use of traditional time-series methods for modeling and forecasting. Building on the theory of continuous-time arbitrage-free price processes and the theory of quadratic variation, we develop formal links between realized volatility and the conditional covariance matrix. Next, using continuously recorded observations for the Deutschemark / Dollar and Yen / Dollar spot exchange rates covering more than a decade, we find that forecasts from a simple long-memory Gaussian vector autoregression for the logarithmic daily realized volatilities perform admirably compared to a variety of popular daily ARCH and more complicated high-frequency models. Moreover, the vector autoregressive volatility forecast, coupled with a parametric lognormal-normal mixture distribution implied by the theoretically and empirically grounded assumption of normally distributed standardized returns, produces well-calibrated density forecasts of future returns, and correspondingly accurate quantile predictions. Our results hold promise for practical modeling and forecasting of the large covariance matrices relevant in asset pricing, asset allocation and financial risk management applications.

We show that the difference between the natural rate of interest and the current level of monetary policy stance, which we label Convergence Gap (CG), contains information that is valuable for bond predictability. Adding CG in forecasting regressions of bond excess returns significantly raises the R 2 , and restores countercyclical variation in bond risk premia that is otherwise missed by forward rates. Consistent with the argument that CG captures the effect of real imbalances on the path of rates, our factor has predictive ability for real bond excess returns. The importance of the gap remains robust out-of-sample and in countries other than the U.S. Furthermore, its inclusion brings significant economic gains in the context of dynamic conditional asset allocation.

Active asset allocation, also known as market timing, is controversial but potentially effective for individual investors and financial advisors. Many studies support market timing based on the relationship between the aggregate earnings yield on equities and the intermediate Treasury bond yield, known as the Fed model. Nevertheless, skeptics point to common flaws in these studies and challenge the validity of the Fed model. In general, returns from timing models are difficult to adjust for transaction costs and tax effects from short term gains and losses. In almost all cases, there is data mining from reporting results over the same period used to build the timing model. Our study addresses these concerns directly. We control the transaction costs and tax effects by focusing on funds available for retirement accounts within a Vanguard fund family allowing costless monthly transfers. We use a "risk on" or "risk off" approach rather than experiment with arbitrary cutoff rules for switching funds. We first test for the time series properties of the Fed model to build a prediction model and then apply it over a recent five-year holdout of period. Our findings show that the switching portfolio offers attractive performance compared to either of the Vanguard funds, especially with respect to enhancing upside to downside risk ratios.

Analysis of ex post returns reveals the time series properties of correlations, but ex ante correlations are required for efficient diversification. We find that a time-varying parameter model offers the best fit to ex post global equity market correlations, suggesting changing mean correlations and changing rates of adjustment back to the means. Nevertheless, we do not find improved forecast performance from time-varying parameter models in holdout periods. The added complexity of time-varying models does not translate into lower forecast errors.

A Copula-based Dynamic Conditional Correlation (DCC) model is developed to capture time-varying correlations and non-linear dependencies among financial assets, integrating Copula functions with multivariate GARCH frameworks. The model employs Sklar's theorem to separate marginal distributions from joint dependencies, enabling robust estimation of tail dependencies and dynamic correlations through maximum likelihood methods. It is applied to daily returns of equities, bonds, and commodities from 2013 to 2023, including the 2020 COVID-19 market crash, to assess risk metrics under varying market conditions. The results show that the Copula-DCC model outperforms traditional models, delivering more accurate Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) estimates with fewer backtesting violations during market stress.

We are grateful to Gita Gopinath, Philip Lane and Rich Levich for comments. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We study an economic setting in which a principal motivates a team of strategic agents to exert costly effort toward the success of a joint project. The action taken by each agent is hidden and affects the (binary) outcome of the agent's individual task in a stochastic manner. A Boolean function, called technology, maps the individual tasks' outcomes to the outcome of the whole project. The principal induces a Nash equilibrium on the agents' actions through payments that are conditioned on the project's outcome (rather than the agents' actual actions) and the main challenge is that of determining the Nash equilibrium that maximizes the principal's net utility, referred to as the optimal contract. Babaioff, Feldman and Nisan suggest and study a basic combinatorial agency model for this setting, and provide a full analysis of the AND technology. Here, we concentrate mainly on OR technologies and on series-parallel (SP) technologies, which are constructed inductively from their building blocks -the AND and OR technologies. We provide a complete analysis of the computational complexity of the optimal contract problem in OR technologies, which resolves an open question and disproves a conjecture raised by Babaioff et al. In particular, we show that while the AND case admits a polynomial time algorithm, computing the optimal contract in an OR technology is NP-hard. On the positive side, we devise an FPTAS for the OR case and establish a scheme that given any SP technology, provides a (1 + )-approximation for all but an ˆ -fraction of the relevant instances (for which a failure message is output) in time polynomial in the size of the technology and in the reciprocals of and ˆ .

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If the Black-Scholes model and its extensions were the discoveries of the 70s and 80s, then Value-at-risk (VaR) models are the darlings of the 90s. These models have many uses within an organisation; for example, a risk manager may use VaR to allocate trading limits, senior management for asset allocation and regulators set and review capital reserves for the institutions. Whatever the uses, the essence of a VaR number is to act a benchmark for measuring how 'risky' the portfolio is across different business lines and products. There are many VaR models currently on the market. Rightly or wrongly, they all try to give 'an estimate, within a given degree of confidence, of how much one can lose from one's portfolio over a given time horizon.' As an example of VaR, we may say that over the next two weeks, there is a 95% chance that we will lose no more than $10m.

This study will demonstrate, through an econometric and asset allocation approach, if and how the Chinese exchange rate regime was changing during 2015. Particularly, China to improve its exchange rate formation system implemented, during July and August 2015, three depreciation as a step toward a market-oriented exchange rate. This situation, along with the new right of the RMB to be an international currency in SDR should generate a loss of weight about the USD in the Chinese basket peg. For this reason, moving from Frankel-Wei’s basic econometric model - but with some appropriate changes - our objective is to verify if the Chinese monetary policy about the exchange rate has affected the inner balance of the Chinese basket-peg leading it towards a flexible exchange rate regime

our discussants Marty Eichenbaum and George Evans, and seminar/conference participants for helpful comments and discussions. We are indebted to Brendan Price and Fernando Yu for excellent research assistance. David Laibson acknowledges support from the NIA (P01AG005842). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

This paper analyses the 53 managerial sackings and resignations from 16 stock exchange listed English football clubs during the nine seasons between 2000/01 and 2008/09. The results demonstrate that, on average, a managerial sacking results in a post-announcement day market-adjusted share price rise of 0.3%, whilst a resignation leads to a drop in share price of 1% that continues for a trading month thereafter, cumulating in a negative abnormal return of over 8% from a trading day before the event. These findings are intuitive, and suggest that sacking a poorly performing manager may be welcomed by the markets as a possible route to better future match performance, while losing a capable manager through resignation, who typically progresses to a superior job, will result in a drop in a club's share price. The paper also reveals that while the impact of managerial departures on stock price volatilities is less clear-cut, speculation in the newspapers is rife in the build-up to such an event.

This paper analyses the 53 managerial sackings and resignations from 16 stock exchange listed English football clubs during the nine seasons between 2000/01 and 2008/09. The results demonstrate that, on average, a managerial sacking results in a post-announcement day market-adjusted share price rise of 0.3%, whilst a resignation leads to a drop in share price of 1% that continues for a trading month thereafter, cumulating in a negative abnormal return of over 8% from a trading day before the event. These findings are intuitive, and suggest that sacking a poorly performing manager may be welcomed by the markets as a possible route to better future match performance, while losing a capable manager through resignation, who typically progresses to a superior job, will result in a drop in a club's share price. The paper also reveals that while the impact of managerial departures on stock price volatilities is less clear-cut, speculation in the newspapers is rife in the build-up to such an event.

The subject of the study is to evaluate the contribution of strategic asset allocation to the variability of Moroccan pension funds performance. The aim of the paper is to identify the role of active management factors, namely tactical allocation and security selection, in generating a performance surplus compared to strategic allocation. The relevance of the study is justified by the need to identify the sources of performance creation in order to face the commitments of Moroccan pension funds and to compensate for the decline and volatility of asset returns. The article addresses, through the use of simple linear regression methods, the relative importance of strategic asset allocation in explaining the variability of the performance of Moroccan pension funds. It introduces a scientific novelty through the use of the "performance attribution" method. The conclusions of the paper confirm the main role of strategic asset allocation, which varies according to the size of the fund, the asset classes, and the risk aversion of the manager.

Gamma irradiation is a well-known method for sterilizing different foodstuffs, including fresh cow milk. Many studies witness that the low dose irradiation of milk and milk products affects the fractions of the milk protein, thus reducing its allergenic effect and make it potentially appropriate for people with milk allergy. The purpose of this study is to evaluate the relationship between the gamma radiation dose and size of the protein fractions, as potential approach to decrease the allergenic effect of the milk. In this paper, an approach for prediction of the dose in gamma irradiated products by using a Bayesian regularized neural network as a mean to save recourses for expensive electrophoretic experiments, is developed. The efficiency of the proposed neural network model is proved on data for two dairy products – lyophilized cow milk and curd.

This study develops a fuzzy multi-objective behavioral portfolio optimization model that explicitly incorporates investor risk preferences to generate feasible and psychologically coherent portfolios. The approach accounts for behavioral attitudes of risk-averse, risk-neutral, and risk-seeking investors through a tunable risk parameter (τ) and maximizes a behavioral satisfaction function across fuzzy goals for risk and return. Real-world constraints, including budget, cardinality, diversification, and sector limits, are integrated to ensure implementable solutions. The model is applied to historical data from the CAC 40 index, demonstrating adaptive portfolio allocations across behavioral scenarios while maintaining high satisfaction degrees. This framework bridges behavioral finance and fuzzy optimization, providing a practical decision-support tool for constructing portfolios aligned with investor psychology under realistic market conditions.

We discuss classes of risk measures in terms both of their axiomatic definitions and of the economic theories of choice that they can be derived from. More specifically, expected utility theory gives rise to the exponential premium principle, proposed by Gerber ), whereas Yaari's (1987) dual theory of risk can be viewed as the source of the distortion premium principle (Denneberg (1990), ). We argue that the properties of the exponential and distortion premium principles are complementary, without either of the two performing completely satisfactorily as a risk measure. Using generalised expected utility theory , we derive a new risk measure, which we call the distortion-exponential principle. This risk measure satisfies the axioms of convex measures of risk, proposed by Föllmer and Shied (2002a,b), and its properties lie between those of the exponential and distortion principles, which can be obtained as special cases.

This research seeks to provide a comprehensive picture of lifetime asset allocation in Japan. We evaluate patterns in the level and composition of assets by household type, taking account of home ownership and household claims on social security as well as financial assets and pensions. The analysis relies on a micro-data taken from the RADAR survey fielded by Nikkei, for the year 2000. The RADAR data are the only publicly available dataset to record financial asset holdings in any detail, with which we calculate housing equity as well as other forms of wealth. We supplement this with external information on pension and social security entitlements. The resulting picture attests to the importance of housing and social security in the portfolios of households approaching retirement. As well, we compare asset allocation patterns between those who are worse vs. better off, better vs. worse educated, married couples vs others, and dualearner vs. single earner couples. Our econometric analysis of asset allocation choice reinforces priors regarding Japanese lifecycle asset allocation patterns: households do invest conservatively, other than their family home; they are riskaverse in their allocation of financial assets; and they appear to over-invest in housing and life insurance, two assets which enjoy preferential bequest tax treatment. We argue that institutional, historical, and policy influences explain much of observed Japanese preferences for safe financial assets, and we offer suggestions for mechanisms that could increase household diversification.

The views expressed in this paper are those of the authors and not necessarily those of the Federal Reserve Board. We thank Eric Richards, Thomas McAndrews, and Aldo Rosas for exceptional research assistance, and Annika Sunden and Alicia Munnell for providing the age-earnings profiles used in this paper. We also thank Bill Even, David Laibson, Olivia Mitchell, Steve Utkus and seminar participants at the University of Illinois and the Federal Reserve Board for their comments and constructive suggestions.

In this work we develop an asset liability model for a swedish life insurance company, incorporating Swedish laws and regulations. A method for generating representative scenario trees from a black box model of the worlds economy is developed as well as such a black box economy model. Stochastic programming is employed to find the optimal solution to the asset allocation problem given a scenario tree. Finally the model is tested numerically, and its performance is compared to a benchmark strategy, consisting of finding the best fixed mix for a given scenario tree. We further investigate the effect of arbitrage opportunities in the tree, as well as the sensitivity of the results to adding extra stages. The long term goal of developing and testing this model is to assemble a decision support system to be used by the managers of a Swedish life insurance company.

In this work we develop,an asset liability model,for a swedish life insurance company, incorporating Swedish laws and regulations. A method for generating,representative,scenario trees from,a black box model,of the worlds economy,is developed,as well as such a black box economy,model. Stochastic programming,is employed,to find the optimal,solution to the asset allocation problem,given a scenario tree. Finally the model,is tested numerically, and its performance is compared to a benchmark strategy, consisting of finding the best fixed mix for a given scenario tree. We further investigate the effect of arbitrage opportunities in the tree, as well as the sensitivity of the results to adding,extra stages. The long term,goal of developing,and testing this model,is to assemble,a decision support system to be used by the managers,of a Swedish life insurance company. Keywords: Stochastic programming, Asset liability management. MSC 2000 subject classifications: 90C15 i Contents

We investigate whether the leveraged life cycle strategy, in which leverage is used to buy stocks when investors are young, is able to produce better retirement outcomes than other investment strategies that are currently offered by defined contribution plan providers and those suggested in the literature. Using both historical and bootstrap simulations for the period of 1900-2011 in the US, we find that the leveraged life cycle strategy has an ability to reduce risk, though this ability is relatively insignificant. Further, the leveraged life cycle strategy shows a comparative advantage over the balanced strategy. However, the leveraged life cycle strategy produces retirement outcomes inferior to conventional life cycle strategy, and demonstrates significant inferiority when compared to dynamic life cycle strategy.

This paper uses the insight that the sectors composing the economy perform differently and (to a certain extent) independently one another over the phases of the economic cycle to explore the existence of investment rules capable of exploiting such dynamics and over-perform market returns. The analysis uses three simple market-timing techniques on 41 funds of the Fidelity Select Sector family over the period January 1998-September 2003. The results indicate that each technique can exploit the pathdependency of the returns across sectors, and consistently over-perform the return of a buy-and-hold strategy. It is hoped that these results will encourage investors, investment managers, and academics to further investigate some of the heuristic models successfully used by practitioners.

Asset composition in OECD economies has undergone substantial volatility over recent decades, driven by shifts from tangible to intangible assets, financial market innovation, and increased cross-border investment. Such volatility introduces complexities in estimating analytical tax burdens, as traditional tax models often assume stable asset bases. This paper investigates the relationship between asset composition volatility and analytical tax burden estimates in advanced economies. Using a comparative and conceptual framework, the study highlights how changing shares of physical capital, financial assets, and intangible investments affect capital taxation, revenue predictability, and fiscal equity. Findings indicate that high asset composition volatility reduces the accuracy of tax burden estimates, amplifies fiscal uncertainty, and shifts the effective tax burden toward labor and consumption. The paper emphasizes the need for dynamic analytical frameworks that incorporate structural asset fluctuations.