The Impact of Volatility Targeting

2018 ◽  
Keyword(s):  
Sharpe Ratio ◽  
Leverage Effect ◽  
Left Tail ◽  
Risk Parity ◽  
Asset Classes ◽  
Equity Portfolios ◽  
Sharpe Ratios ◽  
Tail Events ◽  
The Impact ◽  
Extreme Returns

Recent studies show that volatility-managed equity portfolios realize higher Sharpe ratios than portfolios with a constant notional exposure. The authors show that this result only holds for risk assets, such as equity and credit, and they link this finding to the so-called leverage effect for those assets. In contrast, for bonds, currencies, and commodities, the impact of volatility targeting on the Sharpe ratio is negligible. However, the impact of volatility targeting goes beyond the Sharpe ratio: It reduces the likelihood of extreme returns across all asset classes. Particularly relevant for investors, left-tail events tend to be less severe because they typically occur at times of elevated volatility, when a target-volatility portfolio has a relatively small notional exposure. We also consider the popular 60–40 equity–bond balanced portfolio and an equity–bond–credit–commodity risk parity portfolio. Volatility scaling at both the asset and portfolio level improves Sharpe ratios and reduces the likelihood of tail events.

The performance of the Broad Based Black Economic Empowerment compliant listed property firms in South Africa

2016 ◽  
Vol 34 (1) ◽  
pp. 3-26 ◽  
Author(s):  
Omokolade Akinsomi ◽  
Katlego Kola ◽  
Thembelihle Ndlovu ◽  
Millicent Motloung
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Stock Exchange ◽  
Sharpe Ratio ◽  
Economic Empowerment ◽  
Content Type ◽  
Black Economic ◽  
Black Economic Empowerment ◽  
The Government ◽  
The Impact

Purpose – The purpose of this paper is to examine the impact of Broad-Based Black Economic Empowerment (BBBEE) on the risk and returns of listed and delisted property firms on the Johannesburg Stock Exchange (JSE). The study was investigated to understand the impact of Black Economic Empowerment (BEE) property sector charter and effect of government intervention on property listed markets. Design/methodology/approach – The study examines the performance trends of the listed and delisted property firms on the JSE from January 2006 to January 2012. The data were obtained from McGregor BFA database to compute the risk and return measures of the listed and delisted property firms. The study employs a capital asset pricing model (CAPM) to derive the alpha (outperformance) and beta (risk) to examine the trend amongst the BEE and non-BEE firms, Sharpe ratio was also employed as a measurement of performance. A comparative study is employed to analyse the risks and returns between listed property firms that are BEE compliant and BEE non-compliant. Findings – Results show that there exists differences in returns and risk between BEE-compliant firms and non-BEE-compliant firms. The study shows that BEE-compliant firms have higher returns than non-BEE firms and are less risky than non-BEE firms. By establishing this relationship, this possibly affects the investor’s decision to invest in BEE firms rather than non-BBBEE firms. This study can also assist the government in strategically adjusting the policy. Research limitations/implications – This study employs a CAPM which is a single-factor model. Further study could employ a multi-factor model. Practical implications – The results of this investigation, with the effects of BEE on returns, using annualized returns, the Sharpe ratio and alpha (outperformance), results show that BEE firms perform better than non-BEE firms. These results pose several implications for investors particularly when structuring their portfolios, further study would need to examine the role of BEE on stock returns in line with other factors that affect stock returns. The results in this study have several implications for government agencies, there may be the need to monitor the effect of the BEE policies on firm returns and re-calibrate policies accordingly. Originality/value – This study investigates the performance of listed property firms on the JSE which are BEE compliant. This is the first study to investigate listed property firms which are BEE compliant.

A comparison of minimum variance and maximum Sharpe ratio portfolios for mainstream investors

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anja Vinzelberg ◽  
Benjamin Rainer Auer
Keyword(s):  
Minimum Variance ◽  
Sharpe Ratio ◽  
Optimization Techniques ◽  
Estimation Methods ◽  
Content Type ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Out Of Sample ◽  
Asset Classes

PurposeMotivated by the recent theoretical rehabilitation of mean-variance analysis, the authors revisit the question of whether minimum variance (MinVar) or maximum Sharpe ratio (MaxSR) investment weights are preferable in practical portfolio formation.Design/methodology/approachThe authors answer this question with a focus on mainstream investors which can be modeled by a preference for simple portfolio optimization techniques, a tendency to cling to past asset characteristics and a strong interest in index products. Specifically, in a rolling-window approach, the study compares the out-of-sample performance of MinVar and MaxSR portfolios in two asset universes covering multiple asset classes (via investable indices and their subindices) and for two popular input estimation methods (full covariance and single-index model).FindingsThe authors find that, regardless of the setting, there is no statistically significant difference between MinVar and MaxSR portfolio performance. Thus, the choice of approach does not matter for mainstream investors. In addition, the analysis reveals that, contrary to previous research, using a single-index model does not necessarily improve out-of-sample Sharpe ratios.Originality/valueThe study is the first to provide an in-depth comparison of MinVar and MaxSR returns which considers (1) multiple asset classes, (2) a single-index model and (3) state-of-the-art bootstrap performance tests.

Die Investition in Fine Wine unter Diversifikations- und Kostengesichtspunkten

2018 ◽  
Author(s):  
Thomas Nahmer
Keyword(s):  
Sharpe Ratio ◽  
Government Bond ◽  
Bond Index ◽  
World Government ◽  
Us Dollar ◽  
Sharpe Ratios

Dieses Papier untersucht die Sinnhaftigkeit von Fine Wine als Alternatives Investment unter besonderer Berücksichtigung der Kosten eines Fine Wine Investments. Ist Fine Wine zur weiteren Diversifizierung und damit zur Verbesserung des Risikio-Return-Profils von global in Aktien und Anleihen investierenden Portfolios geeignet? Die Analyse erfolgt in einem ersten Schritt auf Indexbasis und in einem zweiten Schritt auf Basis von realen Investitions-möglichkeiten. Die Referenzwährungen sind der US-Dollar und der Euro. Für die Indexbetrachtung werden auf der Aktienseite der MSCI-World-Index und für die Anleihen der JPM-World-Government-Bond-Index verwendet. Bei den Daten für die Investition in Fine Wine liegt der Fokus auf dem Liv-ex-50-Index der im Jahre 1999 gegründeten Londoner Weinbörse Liv-ex. Bei der realen Investition werden für die Datenanalyse bei Aktien und Anleihen Indexfonds verwendet. Da es für die Investition in Fine Wine keinen Indexfonds gibt, wird der Liv-ex-50-Index inklusive aller Kosten einer realen Investition berechnet. Es werden verschiedene Portfoliozusammensetzungen verglichen. Zum einen wird ein Portfolio aus 50% Aktien und 50% Anleihen einem Portfolio aus 45% Aktien, 45% Anleihen und 10% Fine Wine gegenübergestellt. Zum an-deren wird ein Portfolio aus 25% Aktien und 75% Anleihen gegen ein Portfolio aus 20% Aktien, 70% Anleihen und 10% Fine Wine gemessen. Als Vergleichsmaßstab werden die annualisierte Rendite, die Standardabweichung sowie das Sharpe-Ratio der jeweiligen Portfolios berechnet. Die Ergebnisse für die genannten Zeiträume sind ernüchternd. Die Beimischung von Fine Wine führt auf Indexebene lediglich zu einer leichten Verbesserung der annualisierten Rendite aber zu einer markanten Erhöhung des Risi-kos. Bei der Betrachtung der realen Investition kommen die hohen Kosten eines Investments in Fine Wine zum Tragen. Die annualisierte Rendite ist im Vergleich zu den Portfolios ohne Beimischung von Fine Wine niedriger bei gleichzeitig höheren Risikowerten. Lediglich bei der Betrachtung auf Indexbasis in Euro kann bei einem Portfolio eine leichte Verbesserung der Sharpe-Ratio verzeichnet werden. Bei der Betrachtung nach Kosten führt in allen Fällen die Beimischung von Fine Wine zu einer Verschlechterung der Sharpe-Ratios.

scholarly journals Risk Return Performance of Bitcoin and Alternative Investment Assets in Mixed Asset Portfolios in the Years 2018 to 2020

2021 ◽  
Vol 129 ◽  
pp. 03006
Author(s):  
David Elferich
Keyword(s):  
Statistical Analysis ◽  
Financial Crisis ◽  
Value Added ◽  
Financial Industry ◽  
Paired Sample ◽  
Risk Return ◽  
Efficiency Theory ◽  
Asset Classes ◽  
The Impact ◽  
Institutional Finance

Research background: Since the financial crisis in 2008, numerous other cryptocurrencies have established themselves in the financial industry alongside Bitcoin. Although the validity of the user cases is still lacking, Bitcoin is already being used extensively in the institutional finance sector, among others. Here, the comparison of Bitcoin to other asset classes in mixed portfolio structures must be taken into account. According to the latter, far-reaching areas of investigation emerge by adding Bitcoin in the evaluation of risk-return ratios of mixed portfolio weightings. Purpose of the article: The objective of this paper is to examine, within the framework of Harry Markowitz’s efficiency theory, the impact of including Bitcoin as an investment asset for the risk-return ratios of mixed portfolio structures. Methods: The statistical analysis is based, among other things, on paired sample tests, where the return and volatility values are tested for significant differences in the selected test values. Findings & Value added: The statistical investigations show that the introduction of Bitcoin leads to advantageous return structures, but at the same time to significantly increased volatility values of the examined portfolio constellations. Setting a regional focus of the investment assets in the investigations led to a simplified evaluation basis and at the same time offers the scientific space for further investigations.

scholarly journals Risk-adjusted return, fund manager efficacy, and fund characteristics – An inquiry

2021 ◽  
Author(s):  
Riyazahmed K
Keyword(s):  
Regression Analysis ◽  
Mutual Funds ◽  
Fund Performance ◽  
Sharpe Ratio ◽  
Information Ratio ◽  
Fund Manager ◽  
Data Set ◽  
Dependent Variables ◽  
Corpus Size ◽  
The Impact

Abstract In this study, I examine the risk-adjusted return of mutual funds in India. A data set of 4220 mutual funds is used for the analysis. Sharpe ratio, a metric of risk-adjusted return (Sharpe, 1994) and Information ratio, a metric of outperformance than a fund’s benchmark (Goodwin, 1998) were analyzed. Regression analysis is used to estimate the impact of fund characteristics like fund category, fund type, fund access type, corpus size on the dependent variables i.e., Sharpe Ratio and the Information Ratio. All the funds underperformed in both the Sharpe ratio and Information ratio. Liquid funds found worst. Fund type and corpus size do not impact fund performance. Fund access type was found to be significant on fund performance. The results add to the literature by examining the post-pandemic period.

The Impact of Covid-19 on the Performances and Risks of the U.S. Energy ETF and Equity Portfolios

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Irene Wei Kiong Ting ◽  
Qian Long Kweh ◽  
Ikhlaas Gurrib ◽  
Mohammad Nourani
Keyword(s):  
Equity Portfolios ◽  
The Impact ◽  
The U.S

Dynamics of capital controls: panel evidence from Asia

2020 ◽  
Vol 47 (2) ◽  
pp. 242-263
Author(s):  
Biplab Kumar Guru ◽  
Inder Sekhar Yadav
Keyword(s):  
Capital Flows ◽  
Capital Controls ◽  
Substitution Effect ◽  
Capital Flight ◽  
Empirical Examination ◽  
Content Type ◽  
Asian Economies ◽  
Asset Classes ◽  
The Impact ◽  
Gross Capital Flows

PurposeThis study empirically examines the effect of capital controls on the volume and composition of capital flows at aggregated as well as at disaggregated level by different asset classes such as debt, FDI, equity, and derivatives.Design/methodology/approachSeveral dynamic panel SYS-GMM models are employed on two sets of unique data on cross-border capital flows and capital control index along with control variables at aggregated and disaggregated level by different asset classes during 1995–2015 for a sample of 31 Asian economies.FindingsEconometric findings suggest that higher capital controls effectively reduce gross capital flows. The reduction in gross capital flows is largely found to be on account of effectiveness of controls on equity flows. However, the impact of controls on overall debt and derivative flows is found to be insignificant. Further, it was found that an increase in direct capital controls disaggregated by inflow and outflow categories significantly reduced the inflow of debt and equity + FDI flows and outflow of equity + FDI and derivative flows. Finally, the study did not find any substitution effect (due to indirect controls) and net effect on capital flows.Practical implicationsResults of such empirical examination may enable governments in respective countries to pursue prudent and rational capital controls as a shield against capital flight and shock transmission.Social implicationsPreventing capital flight through effective controls has macroeconomic benefits such as maintaining stability in income, growth, interest rate, exchange rate, and employment levels for the society.Originality/valueThe primary contribution of the study is the analysis of effectiveness of capital controls disaggregated by different asset categories such as debt, equity, FDI, and derivatives using two unique recent data sets for a large sample of Asian economies.

ASSET CORRELATIONS IN TURBULENT MARKETS AND THE IMPACT OF DIFFERENT REGIMES ON ASSET MANAGEMENT

2011 ◽  
Vol 28 (01) ◽  
pp. 1-23 ◽  
Author(s):  
GERMAN BERNHART ◽  
STEPHAN HÖCHT ◽  
MICHAEL NEUGEBAUER ◽  
MICHAEL NEUMANN ◽  
RUDI ZAGST
Keyword(s):  
Risk Aversion ◽  
Asset Management ◽  
Value At Risk ◽  
Conditional Value At Risk ◽  
Dependence Structure ◽  
The Us ◽  
The Mean ◽  
Asian Market ◽  
Asset Classes ◽  
The Impact

In this article, the dependence structure of the asset classes stocks, government bonds, and corporate bonds in different market environments and its implications on asset management are investigated for the US, European, and Asian market. Asset returns are modelled by a Markov-switching model which allows for two market regimes with completely different risk-return structures. Using major stock indices from all three regions, calm and turbulent market periods are identified for the time period between 1987 and 2009 and the correlation structures in the respective periods are compared. It turns out that the correlations between as well as within the asset classes under investigation are far from being stable and vary significantly between calm and turbulent market periods as well as in time. It also turns out that the US and European markets are much more integrated than the Asian and US/European ones. Moreover, the Asian market features more and longer turbulence phases. Finally, the impact of these findings is examined in a portfolio optimization context. To accomplish this, a case study using the mean-variance and the mean-conditional-value-at-risk framework as well as two levels of risk aversion is conducted. The results show that an explicit consideration of different market conditions in the modelling framework yields better portfolio performance as well as lower portfolio risk compared to standard approaches. These findings hold true for all investigated optimization frameworks and risk-aversion levels.

scholarly journals BAYESIAN ESTIMATION OF ASYMMETRIC JUMP-DIFFUSION PROCESSES

2014 ◽  
Vol 09 (03) ◽  
pp. 1450008 ◽  
Author(s):  
SAMUEL J. FRAME ◽  
CYRUS A. RAMEZANI
Keyword(s):  
Bayesian Estimation ◽  
Portfolio Choice ◽  
Stock Prices ◽  
Asset Returns ◽  
Jump Diffusion ◽  
Empirical Literature ◽  
Leverage Effect ◽  
Parameter Estimates ◽  
Price Process ◽  
The Impact

The hypothesis that asset returns are normally distributed has been widely rejected. The literature has shown that empirical asset returns are highly skewed and leptokurtic. The affine jump-diffusion (AJD) model improves upon the normal specification by adding a jump component to the price process. Two important extensions proposed by Ramezani and Zeng (1998) and Kou (2002) further improve the AJD specification by having two jump components in the price process, resulting in the asymmetric affine jump-diffusion (AAJD) specification. The AAJD specification allows the probability distribution of the returns to be asymmetrical. That is, the tails of the distribution are allowed to have different shapes and densities. The empirical literature on the "leverage effect" shows that the impact of innovations in prices on volatility is asymmetric: declines in stock prices are accompanied by larger increases in volatility than the reverse. The asymmetry in AAJD specification indirectly accounts for the leverage effect and is therefore more consistent with the empirical distributions of asset returns. As a result, the AAJD specification has been widely adopted in the portfolio choice, option pricing, and other branches of the literature. However, because of their complexity, empirical estimation of the AAJD models has received little attention to date. The primary objective of this paper is to contribute to the econometric methods for estimating the parameters of the AAJD models. Specifically, we develop a Bayesian estimation technique. We provide a comparison of the estimated parameters under the Bayesian and maximum likelihood estimation (MLE) methodologies using the S&P 500, the NASDAQ, and selected individual stocks. Focusing on the most recent spectacular market bust (2007–2009) and boom (2009–2010) periods, we examine how the parameter estimates differ under distinctly different economic conditions.

Sharpe Ratios and Alphas in Continuous Time

2004 ◽  
Vol 39 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Lars Tyge Nielsen ◽  
Maria Vassalou
Keyword(s):  
Continuous Time ◽  
Sharpe Ratio ◽  
Continuous Time Model ◽  
Time Model ◽  
Time Performance ◽  
Optimal Portfolio Selection ◽  
Dynamic Portfolio ◽  
Sharpe Ratios ◽  
The One ◽  
Riskless Asset

AbstractThis paper proposes modified versions of the Sharpe ratio and Jensen's alpha, which are appropriate in a simple continuous-time model. Both are derived from optimal portfolio selection. The modified Sharpe ratio equals the ordinary Sharpe ratio plus half of the volatility of the fund. The modified alpha also differs from the ordinary alpha by a second-moment adjustment. The modified and the ordinary Sharpe ratios may rank funds differently. In particular, if two funds have the same ordinary Sharpe ratio, then the one with the higher volatility will rank higher according to the modified Sharpe ratio. This is justified by the underlying dynamic portfolio theory. Unlike their discrete-time versions, the continuous-time performance measures take into account that it is optimal for investors to change the fractions of their wealth held in the fund vs. the riskless asset over time.

Sign in / Sign up

Export Citation Format

Share Document