Portfolio Allocation Model Research Articles

Robust Portfolio Allocation for a Bank under Inflation

In this study, we develop a robust portfolio allocation model for a bank in an incomplete market with inflation (a non-tradeable stochastic factor). The optimality criterion of the investments is established on a functional via a modified version of the monotone mean-variance preferences. An increase in anticipated inflation will increase the interest rate, while reducing the expected net stream of dollar receipts in the loan portfolio. Eventually whilst existing loans mature and are re-negotiated (at the higher interest rate), the interest rate is earned by the bank on existing loans are locked up. Under such explicit risk aggregation paradigm, we formulate this problem as a stochastic differential game (SDG) and apply the Hamilton-Jacobi-Bellman-Isaacs (HJBI)-equation to derive the optimal investment strategy. We discuss the dynamics of myopic optimal portfolio and the intertemporal hedging demand portfolio of the optimal portfolio holdings. We describe the dynamics of the total capital ratio under Basel III regulations. Finally, we show that our solution coincides with the solution to classical Markowitz optimization problem with risk aversion coefficient depends on stochastic factor. Our results confirm that the banker’s optimal holdings and the trade-off between holding a myopically optimal portfolio and intertemporal hedging demand are determined by the derivatives of marginal utility with respect to the state variable.

A parametric bootstrap to evaluate portfolio allocation models

If the asset returns are multivariate normal and the investor knows the moments, the Mean–Variance (MV) solution provides the portfolio with the highest Sharpe ratio. However, estimation errors of the moments misalign the allocation weights, and the out-of-sample Sharpe ratio falls. The paper introduces a parametric bootstrap to estimate the predictive Sharpe ratio, the most likely Sharpe ratio that the investor would see out of sample. This Sharpe ratio is advantageous because it includes the distortions from estimation errors and the investor can see the most likely results before investing capital. The approach is quite general and one can use the approach for any portfolio allocation model that uses the moments in some way. The ex ante feature of the test is key, as the test allows the investor to see which model works best before the investors commits capital.

Cost-sensitive boosted tree for loan evaluation in peer-to-peer lending

Abstract Loan evaluation is an effective tool for credit risk assessment in the peer-to-peer (P2P) lending market. However, most of the traditional loan evaluation models assume a balanced misclassification cost, which is far from business reality and leaves opportunities for investigating the cost-sensitive modelling approaches. Moreover, few existing studies consider the special characteristics of P2P lending. In this paper, we propose a cost-sensitive boosted tree loan evaluation model by incorporating cost-sensitive learning and extreme gradient boosting (XGBoost) to enhance the capability of discriminating potential default borrowers. Therefore, a portfolio allocation model that converts the portfolio optimization problem into an integer linear programming is proposed as a decision support system for unprofessional lenders. Unlike existing studies, which mainly evaluate the model through accuracy-based metrics, this study measures the expected profitability based on the annualized rate of return (ARR) and proposes a new metric (ARR curve) reflecting the ARR over different rejection rates. Two real-world P2P lending datasets are examined, and explanatory data analysis shows that explanatory variables differ in predicting the probability of default and profitability. Experimental results reveal that the area under the ARR curve is not a considerable metric in evaluating models from a profit perspective. Conventional cost-insensitive models may even lead to negative returns, whereas the proposed loan evaluation and portfolio allocation model are the best performing methods over the two datasets in terms of profitability.

International diversification for portfolios of European fixed-income mutual funds

PurposeThe purpose of this paper is to study the scope for country diversification in international portfolios of mutual funds for the “core” EMU countries. The author uses a sample of daily returns for country indices of French, German and Italian funds to investigate the quest for international diversification. The author focuses on fixed-income mutual funds during the period of the financial market turmoil since 2007.Design/methodology/approachThe author compute optimal portfolio allocations from both unconstrained and constrained mean-variance frameworks that take as input the out-of-sample forecasts for the conditional mean, volatility and correlation of country-level indices for funds returns. The author also applies a portfolio allocation model based on utility maximization with learning about the time-varying conditional moments. The author compares the out-of-sample forecasting performance of 12 multivariate volatility models.FindingsThe author finds that there is a “core” EMU country also for the mutual fund industry: optimal portfolios allocate the largest portfolio weight to German funds, with Italian funds assigned a lower weight in comparison to French funds. This result is remarkably robust across competing forecasting models and optimal allocation strategies. It is also consistent with the findings from a utility-maximization model that incorporates learning about time-varying conditional moments.Originality/valueThis is the first study on optimal country-level diversification for a mutual fund investor focused on European countries in the fixed-income space for the turmoil period. The author uses a large array of econometric models that captures the salient features of a period characterized by large changes in volatility and correlation, and compare the performance of different optimal asset allocation models.

Maximization of Returns under an Average Value-at-Risk Constraint in Fuzzy Asset Management

A portfolio allocation model is discussed in asset management with fuzziness. By perception-based extension for fuzzy random variables, the estimation methods of asset risks are introduced. Introducing an average value-at-risk for fuzzy random variables, this paper formulates a portfolios allocation model with average value-at-risks. This paper discusses maximization of the expected return under an average value-at-risk constraint with fuzzy random variables. A numerical example is given to demonstrate the results.

Liquidity: A Review of Dimensions, Causes, Measures, and Empirical Applications in Real Estate Markets

In this article, we consider how different dimensions of liquidity have been measured in financial markets and for various forms of real estate investment. The purpose of this exercise is to establish the range of liquidity measures that could be used for real estate investments before considering which measures and questions have been investigated so far. Most measures reviewed here are applicable to public real estate, but not all can be applied to private real estate assets or funds. Use of a broader range of liquidity measures could help real estate researchers tackle issues such as quantification of illiquidity premia for the real estate asset class or different types of real estate, and how liquidity differences might be incorporated into portfolio allocation models.

Fuzzy Portfolio Allocation Models Through a New Risk Measure and Fuzzy Sharpe Ratio

A new portfolio risk measure that is the uncertainty of portfolio fuzzy return is introduced in this paper. Beyond the well-known Sharpe ratio (i.e., the reward-to-variability ratio) in modern portfolio theory, we initiate the so-called fuzzy Sharpe ratio in the fuzzy modeling context. In addition to the introduction of the new risk measure, we also put forward the reward-to-uncertainty ratio to assess the portfolio performance in fuzzy modeling. Corresponding to two approaches based on ${\rm T}_{\rm M}$ and ${\rm T}_{\rm W}$ fuzzy arithmetic, two portfolio optimization models are formulated in which the uncertainty of portfolio fuzzy returns is minimized, while the fuzzy Sharpe ratio is maximized. These models are solved by the fuzzy approach or by the genetic algorithm (GA). Solutions of the two proposed models are shown to be dominant in terms of portfolio return uncertainty compared with those of the conventional mean-variance optimization (MVO) model used prevalently in the financial literature. In terms of portfolio performance evaluated by the fuzzy Sharpe ratio and the reward-to-uncertainty ratio, the model using ${\rm T}_{\rm W}$ fuzzy arithmetic results in higher performance portfolios than those obtained by both the MVO and the fuzzy model, which employs ${\rm T}_{\rm M}$ fuzzy arithmetic. We also find that using the fuzzy approach for solving multiobjective problems appears to achieve more optimal solutions than using GA, although GA can offer a series of well-diversified portfolio solutions diagrammed in a Pareto frontier.

Portfolio Diversification and the Cross-Sectional Distribution of Foreign Investment

In this paper I explore the role of portfolio diversification in explaining the distribution of foreign investment across countries. I capture the portfolio diversification motive by a measure of country-specific riskiness, “covariance risk”, which I construct as how countries' growth rates covary with the stochastic discount factor of a representative international investor. My key new empirical finding is a strong and significant correlation between this new measure of country riskiness and foreign investment allocations. Less risky countries, i.e. countries whose growth rates are more highly correlated with the investor's stochastic discount factor, receive larger investment shares than more risky countries. I interpret this result as evidence that investors do take into account diversification opportunities, not only for portfolio investment decisions, but also for foreign direct investment decisions. My empirical results confirm the theoretical predictions of standard portfolio allocation models.

Portfolio Diversification and the Cross-Sectional Distribution of Foreign Investment

In this paper I explore the role of portfolio diversification in explaining the distribution of foreign investment across countries. I capture the portfolio diversification motive by a measure of country-specific riskiness, "covariance risk", which I construct as how countries' growth rates covary with the stochastic discount factor of a representative international investor. My key new empirical finding is a strong and significant correlation between this new measure of country riskiness and foreign investment allocations. Less risky countries, i.e. countries whose growth rates are more highly correlated with the investor's stochastic discount factor, receive larger investment shares than more risky countries. I interpret this result as evidence that investors do take into account diversification opportunities, not only for portfolio investment decisions, but also for foreign direct investment decisions. My empirical results confirm the theoretical predictions of standard portfolio allocation models.

Black swans in the brazilian stock market

This study analyzes extreme values in the daily returns of 45 Brazilian stocks between 2 January 1995 and 18 March 2009. The incidence of observations outside the range of three standard deviationsfrom the mean is at least five times greater than under the normal distribution. The occurrence of extreme values in the upper tail is 1.13 times higher than in the lower. The average of the extreme positive returns is higher than that of extreme negative returns. Half percent of the days determined the outcome of the investment. Extreme values are at least ± 7%. Investors should assess whether they will keep their holdings when returns of such magnitude occur. The characteristics of empirical distributions of stock returns favor the passive investor and the use of weight constraints in portfolio allocation models.

Identifying key players in the government-formation process: strong and dominant parties in Central and Eastern Europe

Coalition governments are the norm across Central and Eastern Europe (CEE). While a number of empirical studies have attempted to understand why certain governments form in the region there has, as yet, been no consideration of why certain parties emerge as the key players in the government-formation process. This paper uses two models to identify key actors in government formation in CEE: the dominant and central players model; and the portfolio allocation model. The results show that each of these models contributes significantly to our understanding of which parties are key actors in CEE. The key actors identified by each model are overwhelmingly likely to become members of the cabinet and provide the Prime Minister of the government. Key players are also more likely to accrue a greater share of portfolio payoffs from the coalition bargaining process as well as acquiring the most salient portfolios.

Do Inflows or Outflows Dominate? Global Implications of Capital Account Liberalization in China

This paper assesses the implications of Chinese capital account liberalization for capital flows. Stylized facts from capital account liberalization in advanced and large emerging market economies illustrate that capital account liberalization has historically generated large gross capital in- and outflows, but the direction of net flows has depended on many factors. An econometric portfolio allocation model finds that capital controls significantly dampen cross-border portfolio asset holdings. The model also suggests that capital account liberalization in China may trigger net portfolio outflows as large domestic savings seek to diversify abroad.

Optimization of Critical Systems for Robustness in a Multistate World

Critical systems are typically complex systems that are required to perform reliably over a wide range of scenarios, or multistate world. Seldom does a single system exist that performs best for all plausible scenarios. A robust solution, one that performs relatively well over a wide range of scenarios, is often the preferred choice for reduced risk at an acceptable cost. The alternative with the maximum expected utility may possess vulnerabilities that could be exploited. The best strategy is likely to be a hybrid solution. The von Neumann-Morgenstern Expected Utility Theory (EUT) would never select such a solution because, given its linear functional form, the expected utility of a hybrid solution cannot be greater than that of every constituent alternative. The continuity axiom and the independence axiom are assessed to be unrealistic for the problem of interest. Several well-known decision models are analyzed and demonstrated to be potentially misleading. The linear disappointment model modifies EUT by adding a term proportional to downside risk; however, it does not provide a mathematical basis for determining preferred hybrid solutions. The paper proposes a portfolio allocation model with stochastic optimization as a flexible and transparent method for defining choice problems and determining hybrid solutions for critical systems with desirable properties such as diversification and robustness.

Do Inflows or Outflows Dominate? Global Implications of Capital Account Liberalization in China

This paper assesses the implications of Chinese capital account liberalization for capital flows. Stylized facts from capital account liberalization in advanced and large emerging market economies illustrate that capital account liberalization has historically generated large gross capital in- and outflows, but the direction of net flows has depended on many factors. An econometric portfolio allocation model finds that capital controls significantly dampen cross-border portfolio asset holdings. The model also suggests that capital account liberalization in China may trigger net portfolio outflows as large domestic savings seek to diversify abroad.

The Return-Risk Performance——The Comparison of Asset Portfolio Performance of Institution Fund with That Based on Multifractal Detrended Fluctuation Approach

In this paper, we compare the portfolio allocation model of multifractal detrended Fluctuation approach with the modern efficient frontier model and the asset allocation model from Chinese institution fund, the risk-return performance of the multifractal detrended Fluctuation turns out to be more optimal portfolio allocation than that from chinese institution fund and the conclusions have implications for modern financial theory, it suggest that there is scope for more general multifractal portfolio selection models to be developed.

Subjective measures of risk aversion, fixed costs, and portfolio choice

The paper investigates risk preferences among different types of individuals. We use several different measures of risk preferences, including questions on choices between uncertain income streams suggested by Barsky, Juster, Kimball, and Shapiro (1997) and a number of ad hoc measures. As in Barsky et al. (1997) and Arrondel and Calvo-Pardo (2002), we first analyze individual variation in the risk aversion measures and explain them by background characteristics (both “objective” characteristics and other subjective measures of risk preference). Next we incorporate the measured risk preferences into a household portfolio allocation model, which explains portfolio shares, while accounting for incomplete portfolios and fixed costs. Our results show that a measure based on factor analysis of answers to a number of simple risk preference questions has the most explanatory power. The Barsky et al. (1997) measure has less explanatory power than this “a-theoretical” measure, suggesting that sophisticated measures based on economic theory may exceed the financial capability of respondents. Fixed costs turn out to provide an economically and statistically highly significant explanation for incomplete portfolios.

Portfolio Allocation and Policy Compromises: How and Why the Conservatives and the Liberal Democrats Formed a Coalition Government

The question of ‘who gets what?’ is one of the most interesting issues in coalition politics. Research on portfolio allocation has thus far produced some clear‐cut empirical findings: coalition parties receive ministerial posts in close proportion to the number of parliamentary seats they win. This article poses two simple questions: Why did the Conservatives and Liberal Democrats agree to form a coalition government and, secondly, did the process of portfolio allocation in the United Kingdom in 2010 reflect standard patterns of cabinet composition in modern democracies? In order to answer these questions, a content analysis of election manifestos is applied in this article in order to estimate the policy positions of the parties represented in the House of Commons. The results show that a coalition between the Tories and Lib Dems was indeed the optimal solution in the British coalition game in 2010. When applying the portfolio allocation model, it turns out that the Conservatives fulfilled the criteria of a ‘strong party’, implying that the Tories occupied the key position in the coalition game. On account of this pivotal role, they were ultimately able to capture the most important ministries in the new coalition government.

Robust portfolio allocation under discrete asset choice constraints

The mean-variance portfolio allocation model is very sensitive to estimation errors in the model parameters. Robust optimization is a technique used to incorporate the uncertainty introduced by estimation errors directly into portfolio allocation. Practitioners are often faced with complex constraints on the portfolio structure such as limits on the number of securities in the portfolio, which are modelled with discrete variables, and introduce discontinuities in the efficient frontier. This article investigates the size of discontinuities in the efficient frontiers obtained by the classical and robust mean-variance models under such discrete asset choice constraints, as well as the impact of portfolio size on the discontinuity being considered. In addition, we analyse the effects of applying discrete asset choice restrictions to the portfolio selection problem, as well as using estimated and true parameters in the computation of the classical and robust mean-variance investment strategies under discrete asset choice constraints. Computational experiments reveal reduction of the size of discontinuity when using robust optimization mean-variance models.

Portfolio Allocation or Policy Horizons? Determinants of Coalition Formation in Danish Local Government

It is widely assumed that policy considerations are important when parties form government coalitions. But if this is so, and if coalitions are negotiated in multi-dimensional policy spaces with no majority parties, then a rapid turn-over of coalitions should be observed, cf. the chaos theorem. However, we rarely witness this. Here we analyse two of the most prominent theories that address this puzzle: Laver and Shepsle's portfolio allocation model; and Warwick's policy horizon hypothesis. We do not analyse the ‘usual suspects’ (i.e. national government formations in Europe), but present a new empirical testing ground: Danish local governments. We rely on Laver and Shepsle's Winset programme to identify ‘strong parties’ in the portfolio allocation model but develop a new measure of Warwick's policy horizons that better deals with problems of multi-dimensionality. In a conditional logit analysis of survey data from 3000 local councillors, we find support for the policy horizons model, but not for the portfolio allocation model.

Why do foreigners invest in the United States?

Why are foreigners willing to invest over $2 trillion per year in the United States? This paper tests various hypotheses and finds that standard portfolio allocation models and diversification motives are poor predictors of foreign holdings of U.S. liabilities. Instead, foreigners hold greater shares of their investment portfolios in the United States if they have less developed financial markets. The magnitude of this effect decreases with income per capita. Countries that trade more with the United States also have greater portfolio shares in U.S. equity and bond markets. These results support recent theoretical work on the role of financial development in sustaining global imbalances and have important implications for whether the United States can continue to attract sufficient financing from abroad without major changes in asset prices and returns, especially in bond markets.