Spillovers and diversification potential of bank equity returns from developed and emerging America

We examine the network spillovers, portfolio allocation characteristics and diversification potential of bank returns from developed and emerging America. We draw our results by applying a directional spillover index, the tail-event driven network (TENET) and nonlinear portfolio optimization methods on bank returns. We find that the spillovers and connectedness among banks from emerging America are noticeably smaller than those among banks from developed America. The largest emerging market spillover transmitters and receivers are the banks from Brazil, followed by the banks from Chile. The largest developed market spillover transmitter is JP Morgan Chase. The connectedness among banks from developed America is dominated by the banks from the USA, relative to those from Canada. The total connectedness of the emerging market banks is more intensified than that of the banks from developed America due to the effect of the COVID-19 pandemic. The portfolio optimization shows that in developed America, the largest banks from the USA are the largest risk contributors to total portfolio risk, whereas the banks from Canada contribute the least risk. In emerging America, the banks from Brazil contribute the most risk to total portfolio risk while the banks from Peru and one bank from Colombia contribute the least risk. The portfolio of banks from emerging America offers greater diversification potential and lower total portfolio allocation risk.     

Lessons from naïve diversification about the risk-reward trade-off

Studies of naïve diversification show that average total portfolio risk declines asymptotically as number of stocks increases. Recent work shows that a significant amount of idiosyncratic risk remains, even for portfolios with large numbers of stocks. The corresponding shocks are non-trivial. For example, more than half of all equal-weighted portfolios with 100 stocks have better than a 16 percent chance of an annual shock at least as large as about half of the annualized mean excess return on the U.S. total stock market index over July 1963–June 2018. I perform a simulation analysis of portfolio reward-to-risk as well as the components of total portfolio risk. On average, investors do not appear to be rewarded for exposure to non-systematic risk. The cross-sectional distribution of the true Sharpe ratio rises and its dispersion shrinks significantly as the number of stocks in the portfolio increases, whereas the cross-sectional distribution of the true non-systematic risk falls and its dispersion shrinks significantly as the number of stocks in the portfolio increases. This pattern appears regardless of the true asset pricing model for generating security returns, the portfolio weighting method, or specification of security alphas.     

Corporate tax,financial leverage,and portfolio risk

We examine the theoretical implications of corporate income tax for a risky portfolio in a aggregate-endowment economy. In this model, corporate income tax affects the portfolio risk associated with the rebalancing motive during market clearance. An asset is defined as a portfolio of stocks and bonds whose portfolio weights are similar to financial leverage. Corporate tax can decrease after-tax consumption from dividends (increase leverage) and increase the tax shield that increases dividends (decrease leverage). Changes in dividends are responsible for the correlation between expected dividend growth and consumption growth and, thus, affect stock pricing and returns. Overall, the model is characterized by tax-induced portfolio risk associated with financial leverage.     

Measuring Credit Risk of a Bank's Corporate Loan Portfolio Using Advanced Internal Ratings Base Approach

Abstract

The use of technical and advanced approaches in the measurement of credit risk of banks' portfolios has nowadays become a very hot issue. The most recent technical report issued by the Basel Committee in May 2003 has concentrated heavily on the measurement of credit risk using either foundation or advanced Internal Ratings Base (IRB) approaches. This empirical research study attempts to measure credit risk of a bank's corporate loan portfolio, including firms from 10 different Turkish sectors. The monthly observations of the total amount of corporate loans and the total amount of corporate loans at default across various sectors are downloaded from the web page of Central Bank of Turkey (CBT) in a period of 1999-2002. This period covers 47 monthly observations since CBT has captured sectoral corporate loans beginning of 1999. Therefore, the observed sectoral default rates are needed to be simulated to obtain a nicely shaped distribution. Monte Carlo simulation is applied for 1,000 times. Based on the simulated default rates, the expected sectoral default rates are computed. Next, a credit quality rating scale is fitted into sectoral default rates distributions. Finally, the sectoral weights in the whole loan portfolio are multiplied by the expected sectoral default rates matrix, considering cross-sectoral correlations to get the total amount of the bank's credit risk and capital requirement. It is assumed that sectoral monthly default rates are a good representative of the default risk of a sample bank's corporate loan portfolio since no publicly available data on any particular bank's corporate loan portfolio composition exists. Nevertheless, this research may be a good application for measuring the credit risk of banks' corporate loan portfolios using advanced IRB approach.     

Investors' carbon risk exposure and their potential for shareholder engagement

This article examines the exposure to and management of carbon risks of different investor types. Considering the dual role as portfolio manager and partial owner, we analyze carbon risk for investors both in terms of exposure to portfolio values and in terms of responsibility as shareholder of carbon-intensive firms. We show that among various investor types, the preference for holding carbon-intensive stocks differs substantially, even when considering traditional investment decision parameters. In particular, it is governments whose portfolio values are most threatened by a carbon risk exposure of 49%, but at the same time, they prefer larger ownership shares in polluting firms. In contrast, individual investors, investment advisors, and mutual funds avoid holding stakes in these firms, while revealing only a moderate exposure of their assets to carbon risk. In view of the Paris Agreement, which includes the consistent steering of financial flows towards a low carbon transformation of the economy, our study provides policymakers with important implications regarding the coverage and effects of respective regulations. By identifying the ownership structures of carbon-intensive firms and respective owners' portfolio compositions, we also offer implications for further research on portfolio decarbonization and shareholders' influence of corporate carbon management.     

The Effectiveness of Portfolio Risk Diversification: An Additive Approach by Project Replication

This article proposes a probabilistic approach to project operational risk and project portfolio risk diversification. The analysis rests on a fundamental distinction between a fractional and an additive approach for constructing portfolios. Since the additive approach excludes variance as a measure of risk, the project's operational risk is defined by its probability of loss. Paradoxically, the effectiveness of any firm's portfolio risk diversification process will be negatively related to the operational risk of its representative project. We also present the conditions under which risk management and efficiency management can contribute to the firm's strategic imperative of lowering its operational risk.     

公司风险视角下上市国企管理层股权激励研究

在允许国有控股上市公司实施股权激励的背景下,考察了其不同种类风险与经营者股权激励强度的关系。先界定了风险的类型,再通过构建基于风险的两种股权激励模型,并进一步推导得出：若国有上市企业的管理层不能（可以）买卖公司以外的市场证券组合时,其最优股权激励强度与公司特别性风险成反向变化关系,而与公司整体性风险的相关关系不确定（无关）,这为正在实践中摸索的国有上市企业管理层股权激励合同的设计提供了进一步的理论建议。     

Portfolio optimization based on GARCH-EVT-Copula forecasting models

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-$t$ and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-$t$ copulas, are best at reducing the portfolio risk.     

Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors

This paper presents a dynamic portfolio credit model following the regulatory framework, using macroeconomic and latent risk factors to predict the aggregate loan portfolio loss in a banking system. The latent risk factors have three levels: global across the entire banking system, parent-sectoral for the intermediate loan sectors and sector-specific for the individual loan sectors. The aggregate credit loss distribution of the banking system over a risk horizon is generated by Monte Carlo simulation, and a quantile estimator is used to produce the aggregate risk measure and economic capital. The risk contributions of the individual sectors and risk factors are measured by combining the Hoeffding decomposition with the Euler capital allocation rule. For the U.S. banking system, we find that the real GDP growth rate, the global and sector-wide frailty risk factors and their spillovers significantly affect loan defaults, and the impacts of the frailty factors are not only economy-wide but also sector-specific. We also find that the frailty risk factors make more significant risk contributions to the aggregate portfolio risk than the macroeconomic factors, while the macroeconomic factors help to improve the accuracy and efficiency of the credit risk forecasts.     

Risk decomposition,estimation error,and naïve diversification

How to achieve adequate diversification is important in portfolio construction. Efficient markets should not reward an investor for taking on risk that can be diversified away. Hence, when minimizing risk exposure, investors need to measure what part of total portfolio risk is systematic and what part can be diversified away. I examine several methods for decomposing total portfolio risk into systematic and diversifiable components and then carry out simulations to compare cross-sectional distributions of estimated and true risk as number of stocks increases in portfolios constructed using naïve diversification. Ordinary least squares estimators of diversifiable risk are relatively robust, and their cross-sectional distributions closely track the cross-sectional distributions of the corresponding true diversifiable risk. Other proposed estimators of diversifiable risk as well as all estimators of systematic risk have cross-sectional dispersion much greater than the corresponding true risk although, with one exception, bias is small. Results are relatively robust to the choice of method for generating market returns and to the underlying asset pricing model but not to random security betas. The simulation analysis also shows that risk and magnitude of shocks due to diversifiable risk are not negligible, even for 300-stock portfolios.     

基于高阶矩风险防范的银行资产负债组合优化模型研究——以A银行为例

资产负债管理能力是现代商业银行的基本能力,其核心在于风险控制和价值创造。商业银行资产负债组合优化是现代商业银行信贷管理框架中的核心内容,它对于保持银行资产流动性、安全性和赢利性的＂三性＂的最佳组合、优化配置资源、提高银行的生存能力和竞争能力,具有重要的现实意义。本文通过以贷款组合的VaR约束控制贷款组合的二阶矩,即控制了资产组合的风险;以贷款组合收益率的偏度约束控制贷款组合的三阶矩,即控制了贷款组合收益率发生总体损失的可能性;以组合收益率的峰度约束控制贷款组合的四阶矩,即减少了组合收益率发生极端损失的可能性,建立了资产分配的收益率均值-方差-偏度-峰度模型。     

Portfolio Risk Management and Its Contribution to Project Portfolio Success: An Investigation of Organization,Process, and Culture

Previous research has found supporting evidence of a positive relationship between project risk management and project success, but literature on how risk management is applied to and integrated with project portfolios has been scarce. Based on a literature review, a comprehensive conceptual model is developed, which highlights the three components of portfolio risk management: organization, process, and culture. This study investigates their linkage to portfolio success, mediated through risk management quality, and, therefore, provides principles for more effective portfolio risk management. The developed framework can be used for further empirical research on the influence of portfolio risk management and its success.     

Value-at-Risk (VaR) Computations Under Various VaR Models and Stress Testing

SUMMARY

Bank for International Settlements (BIS) proposes that all banks calculate and report amount of market risk they incur and allocate sufficient amount of capital starting at the beginning of year 2002. BIS also suggests that value-at-risk (VaR) models in computing market risk should be used. The Turkish Bank Regulation and Supervision Agency already required all Turkish banks to compute and periodically report market risk and reserve adequate amount of capital since January, 2002. This study mimics an average trading marketable securities portfolio subject to market risk of the four largest Turkish banks. The publicly available quarterly financial reports of year 2001 for Isbank, Garanti, Yapi Kredi and Akbank are examined, and a mimicking portfolio composition is determined as bond investments; 60% in Turkish currency (TRL), 20% in American dollar (USD) and 20%in Euro (EUR). The VaR amounts of the mimicking portfolio are computed by applying Historical Simulation, Monte Carlo Simulation, Delta-Normal and Standard Methods. Finally, stress test is applied for each of the models by using crisis scenarios. The Turkish financial crises of November 2000 and February 2001 are simulated as stress scenarios. The results of stress testing reveal that all methods except standard method can stand the crisis in November 2000, but none of the models can stand the crisis in February 2001.     

Selecting balanced portfolios of R&D projects with interdependencies: A Cross-Entropy based methodology

The intensive growth of technology makes firms rely on research and development (R&D) activities in order to adapt to technology changes in an ever-changing and uncertain environment. Due to R&D budget constraints and limited resources, firms are often forced to select a subset of all candidate projects by means of project portfolio selection techniques mitigating the corresponding risks and enhancing the overall value of portfolio. Projects' interdependencies and types were rarely considered in existing models of R&D portfolio selection that may result in selecting wrong projects. This flaw hinders the projects alignment with corporate objectives and strategy and leads to excessive risk and missing the promised values. In this paper, a balanced set of R&D project evaluation criteria was proposed. Next, to construct R&D project portfolio, a 0–1 nonlinear mathematical programming method for balancing portfolio values and risks was proposed, in which research projects' interdependencies, types and other constraints were all considered. Finally, a Cross-Entropy algorithm was developed to solve the proposed model and results were reported. The algorithm proved to be very effective in terms of solution quality and computational time. The proposed algorithm especially suits large scale instances while exact approaches are doomed to fail.     

Optimal portfolios when variances and covariances can jump

We analyze the optimal portfolio choice in a multi-asset Wishart-model in which return variances and correlations are stochastic and subject to jump risk. The optimal portfolio is characterized by the positions in stock diffusion risk, variance-covariance diffusion risk, and jump risk. We find that including jumps in the second moments changes the optimal positions and particularly variance-covariance hedging demands significantly. Erroneously omitting these jumps gives rise to substantial model risk. Furthermore, variance-covariance jump risk can have a significant impact on potential utility gains when the market is completed by adding derivatives. As a robustness check, we compare our results to those obtained for other parametrizations of Wishart-models from the literature as well as to various single-asset models.     

Diversified behavioral portfolio as an alternative to Modern Portfolio Theory

The traditional mean–variance approach has been complemented by alternative theories that use risk measures different from standard deviation of returns or involve additional distributional features of returns like skewness and kurtosis. We propose a portfolio choice model that combines different distributional characteristics of the returns in the decision-making making process, considering preferences of investors which are modeled as non-statistical uncertainties of investors using fuzzy theory. We use 20 stocks of the S&P500 from January 2013 to December 2017. We assess the obtained portfolios’ performance, and the diversified behavioral portfolios outperform than the mean–variance portfolio. This methodological proposal can be seen as a strong managerial tool to make investment portfolio decisions.     

Network structure,portfolio diversification and systemic risk

We investigate the effect of portfolio diversification on banking systemic risk, where the network effect is incorporated. We analyze three kinds of interbank networks, namely, random networks, small-world networks and scale-free networks. We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types. First, systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock. Second, in the case of the systemic shock, systemic risk reduces with the increases of the level of portfolio diversification. Third, banking systems with scale-free network structures are the most stable, and those with small-world network structures are the most vulnerable.     

Limitations of portfolio diversification through fat tails of the return Distributions: Some empirical evidence

This study investigates the level of risk due to fat tails of the return distribution and the changes of tail fatness (TF) through portfolio diversification. TF is not eliminated through portfolio diversification, and, interestingly, the positive tail has declining fatness until a certain level is reached, while the negative tail has rising fatness. This indicates that fat tails are highly relevant to common factors on systematic risk and that the relevance of common factors is higher for the negative tail compared to the positive tail. In the portfolio diversification effect, the declining fatness of the positive tail further reduces risk, but the rising fatness of the negative tail does not contribute to this effect. The asymmetry between the fatness of the positive and negative tails in the return distribution corresponds to the asymmetry of the trade-off relationship between loss avoidance and profit sacrifice that is expected as a consequence of portfolio diversification. Investors use portfolio diversification to reduce their risk of suffering high losses, but following this strategy means sacrificing high-profit potential. Our study provides empirical confirmation for the practical limitation of portfolio diversification and explains why investors with diversified portfolios suffer high losses from market crashes. An examination of the Northeast Asian stock markets of China, Japan, Korea, and Taiwan show identical results.     

A model of international asset pricing under imperfect commodity arbitrage

This paper examines the effect of imperfect international commodity arbitrage (i.e., violation of the law of one price), modeled as the existence of non-traded goods, on the structure of purchasing power risk, optimal portfolio rules of the risk-averse investors and the equilibrium yield relationship among assets. The major results of the paper include: (i) There are two separate sources of purchasing power risk, i.e., relative price risk and inflation risk; relative price risk is specific to the country in which the investor resides. (ii) In a world of n countries, investors may hold n + 1 hedge portfolios as vehicles to hedge against purchasing power risk; facing different relative prices, investors residing in different countries display divergent portfolio behavior. (iii) In equilibrium, investors are compensated in terms of excess return for bearing not only the systematic world market risk but also the systematic inflation and relative price risks.     

A dynamic autoregressive expectile for time-invariant portfolio protection strategies

“Constant proportion portfolio insurance” is a popular technique among portfolio insurance strategies: the risky part of a portfolio is reallocated with respect to market conditions, via a fixed parameter (the multiple), guaranteeing a predetermined floor. We propose here to use a conditional time-varying multiple as an alternative. We provide the main properties of the conditional multiples for some mainstream cases, including discrete-time rebalancing and an underlying risk asset driven by the Lévy process, while evaluating conditional and unconditional gap risks. Finally, we evaluate the use of a dynamic autoregressive expectile model for estimating the conditional multiple in such a context.