Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach

This study proposes a diversified portfolio construction method based on the tail dependence between the financial assets and adopting both market prior information and the exports’ subject views. In this paper, tail‐dependence clustering was applied to divide candidate assets into different groups according to their tail dependence during the crisis period and the ARMA‐GARCH vine copula‐opinion pooling approach was applied to select the minimum Conditional Value‐at‐Risk portfolio according to the clustering results. The daily closed prices of the components of DAX 20 from 3 January 2006 to 20 December 2014 were studied to illustrate the methodology. The results reveal that more than 90% of 450 possible portfolios are modelled by D‐vine structure and Student's t‐copula dominates almost all the cases for pair copula selection. As Student's t‐copula captures the symmetric tail dependence, the 450 possible portfolios do not show stronger lower tail dependence than upper tail dependence. This study contributes by combining cluster analysis with portfolios selection. It uses vine copula to capture the dependence structure among assets. Finally, it offers a flexible method to describe market and offers a strategy to construct diversified portfolios by adding the investors’ information into portfolio selection procedure at the 1‐day forecast horizon.     

Optimal and investable portfolios: An empirical analysis with scenario optimization algorithms under crisis market prospects

This paper develops scenario optimization algorithms for the assessment of investable financial portfolios under crisis market outlooks. To this end, this research study examines from portfolio managers' standpoint the performance of optimum and investable portfolios subject to applying meaningful financial and operational constraints as a result of a financial turmoil. Specifically, the paper tests a number of alternative scenarios considering both long-only and long and short-sales positions subject to minimizing the Liquidity-Adjusted Value-at-Risk (LVaR) and various financial and operational constraints such as target expected return, portfolio trading volume, close-out periods and portfolio weights. Robust optimization algorithms to set coherent asset allocations for investment management industries in emerging markets and particularly in Gulf Cooperation Council (GCC) financial markets are developed. The results show that the obtained investable portfolios lie off the efficient frontier, but that long-only portfolios appear to lie much closer to the frontier than portfolios including both long and short-sales positions. The proposed optimization algorithms can be useful in developing enterprise-wide portfolio management models in light of the aftermaths of the most-recent financial crisis. The developed methodology and risk optimization algorithms can aid in advancing portfolio management practices in emerging markets and predominantly in the wake of the latest credit crunch.     

Capital asset pricing model in Portugal: Evidence from fractal regressions

We examine risk profiles of the Portuguese stock market index component stocks using a novel approach to the classical capital asset pricing model (CAPM). Specifically, we estimate the CAPM via fractal regressions that allow studying the marginal effects at selected scales. In this way, we can reveal whether the risk is perceived differently by market participants with different investment horizons. Apart from the analysis itself, we provide new statistical insights into the issue of separating and comparing the scale-specific effects with statistical validity. We find several stocks deviating from an expected risk perception homogeneity across investment horizons. This is true for both analysed periods, i.e. before and after the global financial crisis. There are also several stocks that changed their relationship to the market portfolio in between, which has strong implications for possible portfolio construction. The proposed methodology is not limited to financial topics but can be used in any discipline where the scale-specific marginal effects might be of interest.     

Does aggregate uncertainty explain size and value anomalies?

This paper examines the impact of aggregate uncertainty on return dynamics of size and book-to-market ratio sorted portfolios. Using VVIX as a proxy for aggregate uncertainty, and controlling for market risk, volatility risk, correlation risk and the variance risk premium, we document significant portfolio return exposures to aggregate uncertainty. In particular, portfolios that contain small and value stocks have significant and negative uncertainty betas, whereas portfolios of large and growth stocks exhibit positive and significant uncertainty betas. Using a quasi-natural experimental setting around the financial crisis, we confirm the differential sensitivity of small versus big and value versus growth portfolios to aggregate uncertainty. We posit that due to their negative uncertainty betas, uncertainty-averse investors demand extra compensation to hold small and value stocks. Our results offer an uncertainty-based explanation to size and value anomalies.     

Investment horizon effect on asset allocation between value and growth strategies

How does the optimal risk exposure of assets change as their investment horizons increase? Does this impact investment portfolio decision-making, in particular, optimal asset allocation between value and growth strategies over various investment horizons? This paper adopts a new approach to address these questions by examining portfolio allocation between value and growth stocks over various investment horizons. This new approach is based on wavelet analysis, which decomposes the returns of a particular investment strategy across multiple investment horizons. The key empirical results show that the success of pursuing the value strategy (short-selling growth stocks and going long on value stocks) is impacted by the approach used to classify value and growth stock returns. We explore two common alternatives: Fama-French versus Standard & Poor's (S&P) 500/Barra portfolios. The results using Fama-French portfolios show that as the investment horizon increases, the optimal mean allocation of investors tilts heavily away from growth stocks, particularly for lower and moderate levels of risk aversion. Interestingly, for S&P 500/Barra portfolios the allocation weights between value and growth do not vary much.     

Are Islamic finance innovations enough for investors to escape from a financial downturn? Further evidence from portfolio simulations

Does Islamic finance constitute a promising solution for the current global financial crisis and are Islamic financial innovations enough to reassure investors, stabilize financial systems and provide them with a means of escaping from financial downturns? This article addresses these questions while investigating the dynamics of Islamic and conventional stock prices over the last few years. In particular, we apply Multivariate Vector Autoregressive (VAR) tools to test the interaction between conventional and Islamic financial products, and implement the Granger causality test to specify the dependence orientation of feedback between Islamic and conventional stock prices. Our article differs from previous work on the topic in that it develops portfolio simulations to determine whether Islamic finance can supplant conventional finance by generating investment and diversification opportunities during periods of crisis. In addition, we develop optimal portfolio strategies and investment proportions for conventional and Islamic funds to ensure the best resource allocation. Our main findings are: (i) the impact of the current crisis on the Islamic finance industry is less marked than on conventional finance, (ii) investment in Islamic products generates high returns, (iii) portfolios that include Islamic products reduce systemic risk and generate significant diversification benefits, (iv) the US crisis has led to significant changes in resource allocation through changes in investment choices.     

China's liberalizing stock market,crude oil,and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach

China is the world's largest oil importer, and therefore the correlations between stock indices and highly volatile oil prices deserve close examination when investing in China's gradually liberalizing stock market. Another concern for international investors is whether safe-haven assets can reduce portfolio risks for investment in China. The paper makes two main contributions. First, we develop a novel method of examining a multivariate dependence structure by combining wavelet analysis with the vine copula model. Second, we apply the proposed methodology to study the correlations between China's liberalizing stock market, petroleum, and safe-haven assets at different frequencies. We find that the multidimensional dependence of these assets has been altered as a result of the 2008 global financial crisis. Moreover, the vine structures exhibit dependence patterns that vary over time horizons, indicating that the multidimensional dependence is sensitive to time scales.     

Measuring and Optimizing Portfolio Credit Risk: A Copula‐based Approach*

In this work, we present a methodology for measuring and optimizing the credit risk of a loan portfolio taking into account the non‐normality of the credit loss distribution. In particular, we aim at modelling accurately joint default events for credit assets. In order to achieve this goal, we build the loss distribution of the loan portfolio by Monte Carlo simulation. The times until default of each obligor in portfolio are simulated following a copula‐based approach. In particular, we study four different types of dependence structure for the credit assets in portfolio: the Gaussian copula, the Student's t‐copula, the grouped t‐copula and the Clayton n‐copula (or Cook–Johnson copula). Our aim is to assess the impact of each type of copula on the value of different portfolio risk measures, such as expected loss, maximum loss, credit value at risk and expected shortfall. In addition, we want to verify whether and how the optimal portfolio composition may change utilizing various types of copula for describing the default dependence structure. In order to optimize portfolio credit risk, we minimize the conditional value at risk, a risk measure both relevant and tractable, by solving a simple linear programming problem subject to the traditional constraints of balance, portfolio expected return and trading. The outcomes, in terms of optimal portfolio compositions, obtained assuming different default dependence structures are compared with each other. The solution of the risk minimization problem may suggest us how to restructure the inefficient loan portfolios in order to obtain their best risk/return profile. In the absence of a developed secondary market for loans, we may follow the investment strategies indicated by the solution vector by utilizing credit default swaps.     

The Influence of Different Investment Horizons on Risk Behavior

For longer investment periods, investment consultants usually recommend a larger proportion of risky assets for investor portfolios. We examine the effect of different investment horizons on investors' risk behavior. We are interested both in participants' risk perceptions and in their asset allocation behavior. We find significant underestimations of long-term risks, which lead to a higher proportion of risky assets in the long-term portfolios. Our data show that the belief in mean reversion is a potential explanation for this behavior.     

Self‐Directed Pensions: Gender,Risk, and Portfolio Choices*

In this paper, I investigate gender differences in financial risk‐taking from a new perspective, and I show that gender plays a different role across the risk distribution. To evaluate risk‐taking, I exploit portfolio choices following a reform that entitles almost the entire Swedish workforce to choose a risk profile for a part of their public‐pension contributions. The novel finding is that portfolio risk does not differ much between the men and women who choose less risky portfolios, while the men who choose risky portfolios take on significantly more risk than do the women who choose risky portfolios. The findings are robust to investors choosing the default alternative, chasing past returns, rebalancing, and different measures of risk‐taking.     

The Role of Industry Effects in Simultaneous Reversal and Momentum Patterns in One-Month Stock Returns

When stocks are ranked by returns in one month, the portfolio of loser stocks tends to outperform the portfolio of winner stocks in the subsequent month. Yet industry portfolios tend to display momentum. We develop a model of information diffusion among agents with constrained information processing ability that reconciles these well-documented phenomena. We test whether this model or the overreaction hypothesis is consistent with the data. Additionally, a trading strategy based on the model outperforms strategies based on overreaction and on industry momentum. The strategy produces abnormal returns while controlling for market–risk and the size, book value, January, momentum, and liquidity effects.     

Portfolio Composition Choice: A Behavioral Approach

This experimental study investigates portfolio composition choice for different types of financial assets and different levels of wealth. For a group of financially sophisticated executive MBA students with work experience in capital markets, the findings of this study indicate that the proportion of wealth invested in risky assets increases with wealth for all portfolio compositions examined, and increases with the degree of asset risk. This proportion is found to be as much as three times higher for common stocks than for options: For stock portfolios, it increases from 33% to 44% over the five wealth levels examined, and for options it increases from 11% to 17%. These results may imply a decreasing rel w proportions of their wealth in risky assets possess the following characteristics: they do not invest in options in real life; they sometimes buy lottery tickets; they assign a higher risk level to options than to common stocks; they are female; and they are employed.     

The winner-loser anomaly: recent evidence from Greece

This article finds evidence of significant reversals in returns over the medium term in Greek stocks. In contrast with previous research, return reversals are more pronounced for past winners, suggesting that the market overreacts to a greater extent to good news. These contrarian returns are particularly elevated when portfolios are formed using quartiles and during tranquil and bull markets. The optimum contrarian strategy involves skipping the first 6 months of the holding period and implementing the contrarian strategy for a period of 18 months, as returns exhibit continuation followed by reversal. The profitability of the contrarian investment strategy is robust to adjustments for risk and seasonalities. It is the tranquil times and not the crisis/volatile times that generates a significant and profitable contrarian strategy. The recent credit crisis and resulting stock market falls, resulted in extreme movements in some Greek stocks and testing of the contrarian strategy problematic, especially when portfolios are decile ordered. Our findings also highlight the importance of survivorship bias and also suggest that contrarian strategies that just use market beta may be ill-equipped to take into consider extreme market movements, illiquidity and short-sales constraints.     

中国股市价值反转投资策略有效性实证研究

本文以中国深沪A股股票市场为考察对象 ,分析了价值反转投资策略的有效性。作者通过实证分析发现 :在中国深沪A股股票市场上 ,以帐面价值与市场价值比 (B M)、B M GS等指标构造的价值反转投资策略可以产生显著的超额收益率 ,并且其显著程度因持有期不同而不同。接着 ,作者利用CAPM模型、Fama French三因素模型并引入了协偏度 (coskewness)和协峰度 (cokurtosis) ,构造出多风险因子模型来解释价值反转投资策略超额收益率。我们发现 :在经过传统风险因素调整后 ,价值反转投资策略效果依然明显 ;CAPM模型无法解释价值反转投资策略超额收益率 ;Fama French三因素模型对价值反转投资策略超额收益率的解释能力最为显著 ,但对于有些价值投资策略 ,在Fama French三因素基础上加上协偏度和协峰度因子后 ,模型的解释能力有所提高     

On the post-financial crisis performance of Islamic mutual funds: the case of Riyad funds

Using Riyad Capital mutual funds as a proxy for Saudi Arabian mutual funds, this paper empirically compares the risk-adjusted performance and investment style of Islamic mutual funds with that of conventional funds in the wake of the recent global financial crisis of 2009–2014. Absolute and relative risk-adjusted measures with single factor (Jensen) and multifactor (Carhart) models are applied. Our findings suggest that Islamic funds outperformed conventional funds domestically, given similar risk exposure, and produced comparable results under lower market risk globally. The results show that Islamic funds are a relatively big cap from the strong statistical significance registered on the global side as evidenced by the difference portfolio outcomes. In addition, the difference portfolios provide statistical evidence that Islamic funds are more value-oriented compared to conventional funds on both fronts. Furthermore, Islamic funds tend to slightly favour a contrarian trading investment strategy as suggested by statistically significant local portfolio value and global difference portfolios results. The results of home bias test show stronger ties by local Islamic funds to local market relative to the global proxy suggesting that domestic investors and managers favour Islamic funds over conventional funds, thus confirming a local preference for Shari’ah-compliant investments.     

Should emerging market investors buy commodities?

One reason that investors hold commodities is to receive diversification benefits. However, while an extensive set of existing studies demonstrate diversification benefits when investors hold international stocks or bonds, they are generally silent on the implications of holding commodities. Using an asset pricing framework, we investigate the benefits to investors from holding commodities, both individually and in portfolios. Generally, commodity and stock markets are integrated, although there are time-varying benefits to investors that are subject to sample period selection and investment horizon. We show that Asian investors receive positive risk adjusted returns in gold and rice markets but not in any of the other commodity markets investigated. The risk adjusted returns are time-varying: during the Asian financial crisis risk adjusted returns were negative – a penalty for investing in commodities – whereas during the global financial crisis the reverse was true and investors earned positive excess returns. The time-varying nature of the benefits that arise from diversification in commodities and their breakdown during periods of crisis, highlight the problems that investors may face when using commodities for long-term investment in addition to traditional holdings of stocks and bonds.     

Revealed preferences for portfolio selection – does skewness matter?

In this article, we consider the portfolio selection problem as a Bayesian decision problem. We compare the traditional mean–variance and mean–variance–skewness efficient portfolios. We develop bi-level programming problem to investigate the market’s preference for risk by using observed (market) weights. Numerical experiments are conducted on a portfolio formed by the 30 stocks in the Dow Jones Industrial Average. Numerical results show that the market’s preferences are better explained when skewness is included.     

When Do Opening Stock Returns Tend to be Higher?

Abstract

In this study, I make an effort to formulate a trading rule that would make use of some systematic interday patterns in individual stocks’ opening returns. I analyze intraday price data on all the stocks that were S&P 500 Index constituents during the period from 1993 to 2012. I document that if the general market direction of the previous day's opening session is controlled for, then a stock's opening return tends to be higher if, on the previous trading day, its opening return was relatively high (either positive, or higher than the same day's opening market return) and its open-to-close return was relatively low (either non-positive, or lower than or equal to the same day's open-to-close market return). Finally, for the sampling period, I construct two different investment portfolios involving a long position in the stocks on the days when, according to the findings, their opening returns are expected to be high and a short position in the stocks on the days when, according to the findings, their opening returns are expected to be low. Both portfolios are found to yield significantly positive returns, providing evidence for the practical applicability of the documented patterns in opening stock prices.     

CONDITIONAL STOCHASTIC DOMINANCE TESTS IN DYNAMIC SETTINGS

This article proposes nonparametric consistent tests of conditional stochastic dominance of arbitrary order in a dynamic setting. The novelty of these tests lies in the nonparametric manner of incorporating the information set. The test allows for general forms of unknown serial and mutual dependence between random variables and has an asymptotic distribution that can be easily approximated by simulation. This method has good finite‐sample performance. These tests are applied to determine investment efficiency between U.S. industry portfolios conditional on the dynamics of the market portfolio. The empirical analysis suggests that Telecommunications dominates the other sectoral portfolios under risk aversion.     

考虑基准资产的动态投资组合选取

职业基金经理的目标经常是希望自己的投资组合以稳定的表现能够超越所某一基准资产或组合。因此本文给出一个考虑基准资产的动态均值——方差投资组合选取模型。假设状态之间的转移遵循马氏过程,给定状态转移矩阵,可以得到对风险资产最优投入的解析表达式。此表达式表明对风险资产的投入由三项构成,前两项是不考虑基准资产时对风险资产的投入,最后一项与基准资产有关;在基准资产上的权重由基准资产收益的大小来决定,与积极投资组合管理者的风险厌恶程度无关;随着风险厌恶程度的增加,管理者会减少在风险资产上的投入。数值分析显示考虑基准资产的投资组合是一个积极的投资组合。