scholarly journals Estratégia Long-Short, Neutra ao Mercado, e Index Tracking Baseadas em Portfólios Cointegrados

2010 ◽  
Vol 8 (4) ◽  
pp. 469
Author(s):  
João Frois Caldeira ◽  
Marcelo Savino Portugal
Keyword(s):  
Ad Hoc ◽  
Tracking Error ◽  
Covariance Matrices ◽  
Return Level ◽  
Index Tracking ◽  
Optimal Portfolios ◽  
The Mean ◽  
Efficient Allocations ◽  
Mean Variance ◽  
Tracking Portfolios

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 quantitative strategies: index tracking and long-short market neutral. We aim to design optimal portfolios acquiring the asset prices’ co-movements. The results show that the devise of index tracking portfolios using cointegration generates goods results, replicating the benchmark’s return and volatility. The long-short strategy generated stable returns under several market circumstances, presenting low volatility.

scholarly journals Optimal omega-ratio portfolio performance constrained by tracking error

2020 ◽  
Vol 17 (3) ◽  
pp. 263-280
Author(s):  
Wade Gunning ◽  
Gary van Vuuren
Keyword(s):  
Recent Work ◽  
Tracking Error ◽  
Sharpe Ratio ◽  
Main Axis ◽  
Portfolio Performance ◽  
Optimal Portfolios ◽  
Investment Style ◽  
The Mean ◽  
Omega Ratio ◽  
Mean Variance

The mean-variance framework coupled with the Sharpe ratio identifies optimal portfolios under the passive investment style. Optimal portfolio identification under active investment approaches, where performance is measured relative to a benchmark, is less well-known. Active portfolios subject to tracking error (TE) constraints lie on distorted elliptical frontiers in return/risk space. Identifying optimal active portfolios, however defined, have only recently begun to be explored. The Ω – ratio considers both down and upside portfolio potential. Recent work has established a technique to determine optimal Ω – ratio portfolios under the passive investment approach. The authors apply the identification of optimal Ω – ratio portfolios to the active arena (i.e., to portfolios constrained by a TE) and find that while passive managers should always invest in maximum Ω – ratio portfolios, active managers should first establish market conditions (which determine the sign of the main axis slope of the constant TE frontier). Maximum Sharpe ratio portfolios should be engaged when this slope is > 0 and maximum Ω – ratios when < 0.

scholarly journals Mean-Variance Portfolio Selection with Tracking Error Penalization

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1915
Author(s):  
William Lefebvre ◽  
Grégoire Loeper ◽  
Huyên Pham
Keyword(s):  
Portfolio Selection ◽  
Tracking Error ◽  
Efficient Frontier ◽  
Minimum Variance ◽  
Sharpe Ratio ◽  
Portfolio Strategy ◽  
The Mean ◽  
Mean Variance Portfolio ◽  
Mean Variance ◽  
Variance Criterion

This paper studies a variation of the continuous-time mean-variance portfolio selection where a tracking-error penalization is added to the mean-variance criterion. The tracking error term penalizes the distance between the allocation controls and a reference portfolio with same wealth and fixed weights. Such consideration is motivated as follows: (i) On the one hand, it is a way to robustify the mean-variance allocation in the case of misspecified parameters, by “fitting" it to a reference portfolio that can be agnostic to market parameters; (ii) On the other hand, it is a procedure to track a benchmark and improve the Sharpe ratio of the resulting portfolio by considering a mean-variance criterion in the objective function. This problem is formulated as a McKean–Vlasov control problem. We provide explicit solutions for the optimal portfolio strategy and asymptotic expansions of the portfolio strategy and efficient frontier for small values of the tracking error parameter. Finally, we compare the Sharpe ratios obtained by the standard mean-variance allocation and the penalized one for four different reference portfolios: equal-weights, minimum-variance, equal risk contributions and shrinking portfolio. This comparison is done on a simulated misspecified model, and on a backtest performed with historical data. Our results show that in most cases, the penalized portfolio outperforms in terms of Sharpe ratio both the standard mean-variance and the reference portfolio.

Optimal Index Tracking Under Transaction Costs and Impulse Control

1998 ◽  
Vol 01 (03) ◽  
pp. 315-330 ◽  
Author(s):  
I. R. C. Buckley ◽  
R. Korn
Keyword(s):  
Transaction Costs ◽  
Optimal Strategy ◽  
Impulse Control ◽  
Tracking Error ◽  
Management Problem ◽  
Index Tracking ◽  
Cash Management ◽  
Proportional Transaction Costs ◽  
Control Techniques ◽  
Mean Variance

We apply impulse control techniques to a cash management problem within a mean-variance framework. We consider the strategy of an investor who is trying to minimise both fixed and proportional transaction costs, whilst minimising the tracking error with respect to an index portfolio. The cash weight is constantly fluctuating due to the stochastic inflow and outflow of dividends and liabilities. We show the existence of an optimal strategy and compute it numerically.

The Impact of Financial Crises on the Asset Allocation: Classical Theory Versus Behavioral Theory

2019 ◽  
Vol 32 (2) ◽  
pp. 218-236
Author(s):  
Amen Aissi Harzallah ◽  
Mouna Boujelbene Abbes
Keyword(s):  
Financial Crisis ◽  
Risk Aversion ◽  
Asset Allocation ◽  
Global Financial Crisis ◽  
Optimal Portfolio ◽  
Optimal Portfolios ◽  
The Mean ◽  
Degree Of Risk ◽  
The Impact ◽  
Mean Variance

The aim of this article is to compare the portfolio optimization generated by the behavioral portfolio theory (BPT) and the mean variance theory (MVT) by investigating the impact of the global financial crisis on the asset allocation. We use data from the Canadian Stock Exchange over the 2002–2015 period. By comparing both approaches, we show that for any level of aspiration and admissible failure, the BPT optimal portfolio will always contain a part of the mean–variance frontier. Thus, in the case of higher degree of risk aversion induced by typical BPT investors, the security set is located on the upper right of the Markowitz frontier. However, even if the optimal portfolios of MVT and BPT may coincide, MVT investors associated with an extremely low degree of risk aversion will not systematically choose BPT optimal portfolios. Our results also indicate the period of financial crisis generate huge losses in MVT portfolio values that implies a lower expected return and a higher level of risk. Furthermore, we point out the absence of the BPT optimal portfolio when potential losses are higher during the 2008 global financial crisis. JEL: G11, G17, G40

scholarly journals A new media optimizer based on the mean-variance model

2007 ◽  
Vol 27 (3) ◽  
pp. 427-456 ◽  
Author(s):  
Pedro Jesus Fernandez ◽  
Marcelo de Souza Lauretto ◽  
Carlos Alberto de Bragança Pereira ◽  
Julio Michael Stern
Keyword(s):  
New Media ◽  
Ad Hoc ◽  
Media Planning ◽  
Full Generality ◽  
Variance Model ◽  
Novel Approach ◽  
The Media ◽  
The Mean ◽  
Set Up ◽  
Mean Variance

In the financial markets, there is a well established portfolio optimization model called generalized mean-variance model (or generalized Markowitz model). This model considers that a typical investor, while expecting returns to be high, also expects returns to be as certain as possible. In this paper we introduce a new media optimization system based on the mean-variance model, a novel approach in media planning. After presenting the model in its full generality, we discuss possible advantages of the mean-variance paradigm, such as its flexibility in modeling the optimization problem, its ability of dealing with many media performance indices - satisfying most of the media plan needs - and, most important, the property of diversifying the media portfolios in a natural way, without the need to set up ad hoc constraints to enforce diversification.

scholarly journals Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores

2019 ◽  
Vol 23 (10) ◽  
pp. 4323-4331 ◽  
Author(s):  
Wouter J. M. Knoben ◽  
Jim E. Freer ◽  
Ross A. Woods
Keyword(s):  
Time Series ◽  
Coefficient Of Variation ◽  
Ad Hoc ◽  
Model Performance ◽  
Technical Note ◽  
Mean Flow ◽  
Model Adequacy ◽  
Robust Model ◽  
The Mean ◽  
Adequacy Assessment

Abstract. A traditional metric used in hydrology to summarize model performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41 indicate that a model improves upon the mean flow benchmark – even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment.

scholarly journals How Does the Cause of Infantile Hemiparesis Influence Other Conditioning Factors? A Preliminary Study in a Spanish Population

Children ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 323
Author(s):  
Rocío Palomo-Carrión ◽  
Rita Pilar Romero-Galisteo ◽  
Helena Romay-Barrero ◽  
Inés Martínez-Galán ◽  
Cristina Lirio-Romero ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Cross Sectional Study ◽  
Motor Dysfunction ◽  
Sensory Loss ◽  
Speech Impairments ◽  
Cross Sectional ◽  
Conditioning Factors ◽  
Age Of Diagnosis ◽  
The Mean ◽  
Preliminary Study

Infantile hemiparesis may be associated with significant morbidity and may have a profound impact on a child’s physical and social development. Infantile hemiparesis is associated with motor dysfunction as well as additional neurologic impairments, including sensory loss, mental retardation, epilepsy, and vision, hearing, or speech impairments. The objective of this study was to analyze the association between the cause of infantile hemiparesis and birth (gestational age), age of diagnosis, and associated disorders present in children with infantile hemiparesis aged 0 to 3 years. An observational and cross-sectional study was performed. A simple and anonymous questionnaire was created ad hoc for parents of children diagnosed with infantile hemiparesis aged between 0 and 3 years about the situation regarding the diagnosis of hemiparesis, birth, cause of hemiparesis, and presence of other associated disorders. Perinatal stroke (60.1%) was the most common cause of hemiparesis, and the most typical associated disorder was epilepsy (34.2%), with the second largest percentage in this dimension corresponding to an absence of associated disorders (20.7%). The most frequent birth was “no premature” (74.1%). The mean age of diagnosis of infantile hemiparesis was registered at 8 months (IQR: 0–36). Knowing the possible association between different conditioning factors and the cause of infantile hemiparesis facilitates the prevention of severe sequelae in children and family, implementing an early comprehensive therapeutic approach in children with infantile hemiparesis.

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