scholarly journals Exploring the diversification benefits of US international equity closed-end funds

2021 ◽  
Author(s):  
Jonathan Fletcher
Keyword(s):  
Portfolio Optimization ◽  
Asset Allocation ◽  
Asset Management ◽  
Sample Period ◽  
Simulation Approach ◽  
Oxford University ◽  
Out Of Sample ◽  
International Equity ◽  
Closed End Funds ◽  
Stock Portfolio

AbstractI use the simulation approach of Jobson and Korkie (J Portfolio Manag 7:70–74, 1981), combined with Michaud optimization (Michaud and Michaud, Efficient asset management: a practical guide to stock portfolio optimization and asset allocation, Oxford University Press, Oxford, 2008), to evaluate whether US international equity closed-end funds (CEF) provide out-of-sample diversification benefits. My study finds that international CEF do not provide diversification benefits across the whole sample period. However, the out-of-sample diversification benefits of international CEF do vary across economic states. I find that there are significant diversification benefits when the lagged one-month US Treasury Bill return is lower than normal, and when higher than normal, regardless of the benchmark investment universe used.

Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation.

2001 ◽  
Vol 14 (3) ◽  
pp. 901-904 ◽  
Author(s):  
Richard O. Michaud ◽  
Tongshu Ma
Keyword(s):  
Portfolio Optimization ◽  
Asset Allocation ◽  
Asset Management ◽  
Practical Guide ◽  
Stock Portfolio

scholarly journals A Network View of Portfolio Optimization Using Fundamental Information

2021 ◽  
Vol 9 ◽  
Author(s):  
Xiangzhen Yan ◽  
Hanchao Yang ◽  
Zhongyuan Yu ◽  
Shuguang Zhang
Keyword(s):  
Portfolio Optimization ◽  
Asset Allocation ◽  
Defensive Strategy ◽  
Novel Approach ◽  
Fundamental Information ◽  
Out Of Sample ◽  
Efficient Portfolios ◽  
Robust Network ◽  
Measure Of Similarity ◽  
Mean Variance

This article proposes the use of a novel approach to portfolio optimization, referred to as “Fundamental Networks” (FN). FN is an effective and robust network-based fundamental-incorporated method, and can be served as an alternative to classical mean-variance framework models. As a proxy for a portfolio, a fundamental network is defined as a set of “interconnected” stocks, among which linkages are a measure of similarity of fundamental information and are referred to asset allocation directly. Two empirical models are provided in this paper as applications of Fundamental Networks. We find that Fundamental Networks efficient portfolios are in general more mean-variance efficient in out-of-sample performance than Markwotiz’s efficient portfolios. Specifically, portfolios set for profitability goals create excess return in a general/upward trending market; portfolios targeted for operating fitness perform better in a downward trending market, and can be considered as a defensive strategy in the event of a crisis.

Out-of-sample performance of the Black-Litterman model

2021 ◽  
pp. 29-51
Author(s):  
Frieder Meyer-Bullerdiek
Keyword(s):  
Portfolio Optimization ◽  
Portfolio Management ◽  
Asset Allocation ◽  
Jel Classification ◽  
Stock Index ◽  
Out Of Sample ◽  
Weighted Portfolio ◽  
German Stock ◽  
Mean Variance Portfolio ◽  
Mean Variance

The aim of this paper is to test the out-of-sample performance of the Black Litterman (BL) model for a German stock portfolio compared to the traditional mean-variance optimized (MV) portfolio, the German stock index DAX, a reference portfolio, and an equally weighted portfolio. The BL model was developed as an alternative approach to portfolio optimization many years ago and has gained attention in practical portfolio management. However, in the literature, there are not many studies that analyze the out-of-sample performance of the model in comparison to other asset allocation strategies. The BL model combines implied returns and subjective return forecasts. In this study, for each stock, sample means of historical returns are employed as subjective return forecasts. The empirical analysis shows that the BL portfolio performs significantly better than the DAX, the reference portfolio and the equally weighted portfolio. However, overall, it is slightly outperformed by the MV portfolio. Nevertheless, the BL portfolio may be of greater interest to investors because -according to this study, where the subjective return forecasts are based on historical returns of a rather long past period of time-it could lead in most cases to lower absolute (normalized) values for the stock weights and for all stocks to smaller fluctuations in the (normalized) weights compared to the MV portfolio. JEL classification numbers: C61, G11. Keywords: Black-Litterman, Mean-variance, Portfolio optimization, Performance.

Asset Allocation Strategies and Commodities

2018 ◽  
Author(s):  
Claudio Boido
Keyword(s):  
Asset Allocation ◽  
Asset Management ◽  
Central Banking ◽  
Fixed Income ◽  
Fixed Income Securities ◽  
Asset Classes ◽  
Alternative Beta ◽  
Asset Managers ◽  
Selection Of ◽  
Allocation Strategies

As a result of the financial crisis of 2007–2008 and subsequent central banking decisions, the asset management industry changed its asset allocation choices. Asset managers are focusing their attention on the search for new asset classes by taking advantage of the new opportunities to capture risk premia with the aim of exceeding the returns given by traditional investments, including traded equities, fixed income securities, and cash. By doing so, they are trying to improve the selection of alternative assets, such as commodities that sometimes have relatively low correlations with traditional assets. The chapter begins by describing the principles of asset allocation, distinguishing between passive and active asset allocation, also focusing on beta and alternative beta. It then concentrates on how investors can gain exposure to commodities through different investment vehicles and strategies.

scholarly journals Portfolio Optimization Constrained by Performance Attribution

2021 ◽  
Vol 14 (5) ◽  
pp. 201
Author(s):  
Yuan Hu ◽  
W. Brent Lindquist ◽  
Svetlozar T. Rachev
Keyword(s):  
Portfolio Optimization ◽  
Asset Allocation ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Selection Effect ◽  
Conditional Value At Risk ◽  
Positive Role ◽  
Performance Attribution ◽  
Dow Jones Industrial Average

This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize conditional value-at-risk and investigate two performance attributes, asset allocation (AA) and the selection effect (SE), as constraints on asset weights. The test portfolio consists of stocks from the Dow Jones Industrial Average index. Values for the performance attributes are established relative to two benchmarks, equi-weighted and price-weighted portfolios of the same stocks. Performance of the optimized portfolios is judged using comparisons of cumulative price and the risk-measures: maximum drawdown, Sharpe ratio, Sortino–Satchell ratio and Rachev ratio. The results suggest that achieving SE performance thresholds requires larger turnover values than that required for achieving comparable AA thresholds. The results also suggest a positive role in price and risk-measure performance for the imposition of constraints on AA and SE.

FAST METHODS FOR LARGE-SCALE NON-ELLIPTICAL PORTFOLIO OPTIMIZATION

2014 ◽  
Vol 09 (02) ◽  
pp. 1440001 ◽  
Author(s):  
MARC S. PAOLELLA
Keyword(s):  
Portfolio Optimization ◽  
Large Scale ◽  
Asset Returns ◽  
Short Selling ◽  
Sharpe Ratio ◽  
Mixture Of Normals ◽  
Optimization Via Simulation ◽  
Fast Methods ◽  
Out Of Sample ◽  
Weighted Portfolio

Simple, fast methods for modeling the portfolio distribution corresponding to a non-elliptical, leptokurtic, asymmetric, and conditionally heteroskedastic set of asset returns are entertained. Portfolio optimization via simulation is demonstrated, and its benefits are discussed. An augmented mixture of normals model is shown to be superior to both standard (no short selling) Markowitz and the equally weighted portfolio in terms of out of sample returns and Sharpe ratio performance.

scholarly journals Cojumps and asset allocation in international equity markets

2019 ◽  
Vol 98 ◽  
pp. 1-22 ◽  
Author(s):  
Mohamed Arouri ◽  
Oussama M’saddek ◽  
Duc Khuong Nguyen ◽  
Kuntara Pukthuanthong
Keyword(s):  
Asset Allocation ◽  
Equity Markets ◽  
International Equity Markets ◽  
International Equity
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