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Relevant bibliographies by topics / Portfolio allocation, co-variance, co-skewness and co-kurtosis

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Journal articles

Academic literature on the topic 'Portfolio allocation, co-variance, co-skewness and co-kurtosis'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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Journal articles on the topic "Portfolio allocation, co-variance, co-skewness and co-kurtosis"

1

Chaudhary, Rashmi, Dheeraj Misra, and Priti Bakhshi. "Conditional relation between return and co-moments – an empirical study for emerging Indian stock market." Investment Management and Financial Innovations 17, no. 2 (2020): 308–19. http://dx.doi.org/10.21511/imfi.17(2).2020.24.

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Due to many theoretical and practical shortcomings of the traditional CAPM model, this study aims at analyzing the CAPM with possible extensions. The analysis aims to know the empirical soundness of Conditional Higher Moment CAPM in emerging India’s capital market. The sample consists of 69 company’s daily stock price data from April 2004 to March 2019 from NSE 100. Panel data analysis is used on 21 cross-sections. The overall results show that when both up and down markets are incorporated separately, all three moments, namely, co-variance, co-skewness, and co-kurtosis, are priced during the

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2

Khan, Kanwal Iqbal, Syed M. Waqar Azeem Naqvi, Muhammad Mudassar Ghafoor, and Rana Shahid Imdad Akash. "Sustainable Portfolio Optimization with Higher-Order Moments of Risk." Sustainability 12, no. 5 (2020): 2006. http://dx.doi.org/10.3390/su12052006.

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Sustainable economic growth and development of stock market plays an important role in diversifying the investment opportunities that can be assessed accordingly. However, a true diversification in portfolio is impossible without inclusion of higher-order moments, skewness and kurtosis. However, the risk-taking behavior of investors is modelled with the help of higher-order moments of risk. Therefore, this study is intended to construct optimal portfolios and efficient frontiers with the inclusion of higher-order moments of risk. The findings show that optimized portfolios with inclusion of sk

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3

DA FONSECA, JOSÉ, MARTINO GRASSELLI, and FLORIAN IELPO. "HEDGING (CO)VARIANCE RISK WITH VARIANCE SWAPS." International Journal of Theoretical and Applied Finance 14, no. 06 (2011): 899–943. http://dx.doi.org/10.1142/s0219024911006784.

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In this paper, we quantify the impact on the representative agent's welfare of the presence of derivative products spanning covariance risk. In an asset allocation framework with stochastic (co)variances, we allow the agent to invest not only in the stocks but also in the associated variance swaps. We solve this optimal portfolio allocation program using the Wishart Affine Stochastic Correlation framework, as introduced in Da Fonseca, Grasselli and Tebaldi (2007): it shares the analytical tractability of the single-asset counterpart represented by the [36] model and it seems to be the natural

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Mounir, Amine Mohammed. "Prudence and temperance in portfolio selection with Shariah-compliant investments." International Journal of Islamic and Middle Eastern Finance and Management 14, no. 4 (2021): 753–66. http://dx.doi.org/10.1108/imefm-07-2019-0292.

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Purpose This paper aims to explore the impact of Sharīʿah-compliant stocks on other investor risk preferences beyond the risk aversion, namely, prudence and temperance. Design/methodology/approach This paper uses the non-parametric model data envelopment analysis with the shortage function as a measure of performance. The model uses three specifications considering skewness and kurtosis that describe according to expected utility theory, prudence and temperance. Findings Results show that first, efficient portfolios consist mainly of conventional stocks in the three-model specification. Second

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5

Bt Abdul Halima, Nurfadhlina, Dwi Susanti, Alit Kartiwa, and Endang Soeryana Hasbullah. "Abnormal Portfolio Asset Allocation Model: Review." International Journal of Business, Economics, and Social Development 1, no. 1 (2020): 46–54. http://dx.doi.org/10.46336/ijbesd.v1i1.18.

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It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where

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Caldeira, João Frois, and Marcelo Savino Portugal. "Estratégia Long-Short, Neutra ao Mercado, e Index Tracking Baseadas em Portfólios Cointegrados." Brazilian Review of Finance 8, no. 4 (2010): 469. http://dx.doi.org/10.12660/rbfin.v8n4.2010.1534.

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The traditional models to optimize portfolios based on mean-variance analysis aim to determine the portfolio weights that minimize the variance for a certain return level. The covariance matrices used to optimize are difficult to estimate and ad hoc methods often need to be applied to limit or smooth the mean-variance efficient allocations recommended by the model. Although the method is efficient, the tracking error isn’t certainly stationary, so the portfolio can get distant from the benchmark, requiring frequent re-balancements. This work uses cointegration methodology to devise two quantit

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7

Georgescu, Irina, and Jani Kinnunen. "How the Investor’s Risk Preferences Influence the Optimal Allocation in a Credibilistic Portfolio Problem." Journal of Systems Science and Information 7, no. 4 (2019): 317–29. http://dx.doi.org/10.21078/jssi-2019-317-13.

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Abstract A classical portfolio theory deals with finding the optimal proportion in which an agent invests a wealth in a risk-free asset and a probabilistic risky asset. Formulating and solving the problem depend on how the risk is represented and how, combined with the utility function defines a notion of expected utility. In this paper the risk is a fuzzy variable and the notion of expected utility is defined in the setting of Liu’s credibility theory. Thus, the portfolio choice problem is formulated as an optimization problem in which the objective function is a credibilistic expected utilit

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8

Füss, Roland, and Felix Schindler. "Diversifikationsvorteile verbriefter Immobilienanlagen in einem Mixed-Asset-Portfolio." Perspektiven der Wirtschaftspolitik 12, no. 2 (2011): 170–91. http://dx.doi.org/10.1111/j.1468-2516.2011.00362.x.

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AbstractThis article examines whether international investors benefit from adding real estate investment trusts (REITs) to a mixed asset portfolio consisting of global stocks, bonds, hedge funds, and commodities. Previous literature has shown that REITs provide a strong co-movement with direct real estate in the long run. We therefore test the diversification potential of international REITs within the strategic asset allocation. Using the Johansen cointegration technique, we show that there is no long-term co-movement between REITs and the other asset classes in the period from January 1990 t

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Tronzano, Marco. "Safe-Haven Assets, Financial Crises, and Macroeconomic Variables: Evidence from the Last Two Decades (2000–2018)." Journal of Risk and Financial Management 13, no. 3 (2020): 40. http://dx.doi.org/10.3390/jrfm13030040.

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This paper focuses on three “safe haven” assets (gold, oil, and the Swiss Franc) and examines the impact of recent financial crises and some macroeconomic variables on their return co-movements during the last two decades. All financial crises produced significant increases in conditional correlations between these asset returns, thus revealing consistent portfolio shifts from more traditional towards safer financial instruments during turbulent periods. The world equity risk premium stands out as the most relevant macroeconomic variable affecting return co-movements, while economic policy unc

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10

Oliva, I., and R. Renò. "Optimal portfolio allocation with volatility and co-jump risk that Markowitz would like." Journal of Economic Dynamics and Control 94 (September 2018): 242–56. http://dx.doi.org/10.1016/j.jedc.2018.05.004.

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