Portfolio Returns: Downside Risk or Upside Risk: The Art and Science of Investing in Stocks

Using a sample of bank-years from 2005 to 2017, we examine the effect of internal control quality on future risk-taking and performance. We find that banks that disclose a material weakness in internal controls have higher risk-taking and worse performance in the future, including having a higher (lower) likelihood of experiencing large losses (gains). These findings suggest that weak controls increase (reduce) downside (upside) risk-taking or conversely that strong controls increase (reduce) upside (downside) risk-taking. Path analyses suggest that 22.3 to 43.7 percent of the effect of internal control quality on future performance is through risk-taking. Additionally, material weaknesses are negatively associated with total asset, loan, interest income, and non-interest income growth, suggesting that internal control quality affects both core and non-core activities of banks. Overall, results suggest that strong internal controls improve bank risk-taking, in part through asymmetrically reducing downside risk-taking while facilitating upside risk-taking, ultimately improving bank performance.

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CHARACTERISTICS OF OMEGA-OPTIMIZED PORTFOLIOS AT DIFFERENT LEVELS OF THRESHOLD RETURNS

Business Management and Education ◽

10.3846/bme.2014.235 ◽

2014 ◽

Vol 12 (2) ◽

pp. 245-265 ◽

Cited By ~ 2

Author(s):

Renaldas Vilkancas

Keyword(s):

Portfolio Optimization ◽

Risk Measures ◽

High Threshold ◽

Portfolio Performance ◽

Threshold Values ◽

Portfolio Returns ◽

Upside Risk ◽

And Performance ◽

Risk Free Rate ◽

Different Levels

There is little literature considering effects that the loss-gain threshold used for dividing good and bad outcomes by all downside (upside) risk measures has on portfolio optimization and performance. The purpose of this study is to assess the performance of portfolios optimized with respect to the Omega function developed by Keating and Shadwick at different levels of the threshold returns. The most common choices of the threshold values used in various Omega studies cover the risk-free rate and the average market return or simply a zero return, even though the inventors of this measure for risk warn that “using the values of the Omega function at particular points can be critically misleading” and that “only the entire Omega function contains information on distribution”. The obtained results demonstrate the importance of the selected values of the threshold return on portfolio performance – higher levels of the threshold lead to an increase in portfolio returns, albeit at the expense of a higher risk. In fact, within a certain threshold interval, Omega-optimized portfolios achieved the highest net return, compared with all other strategies for portfolio optimization using three different test datasets. However, beyond a certain limit, high threshold values will actually start hurting portfolio performance while meta-heuristic optimizers typically are able to produce a solution at any level of the threshold, and the obtained results would most likely be financially meaningless.

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The impact of downside risk on UK stock returns

Review of Accounting and Finance ◽

10.1108/raf-07-2017-0139 ◽

2019 ◽

Vol 18 (1) ◽

pp. 53-70

Author(s):

Fangzhou Huang

Keyword(s):

Stock Returns ◽

Financial Crises ◽

Negative Impact ◽

Positive Impact ◽

Downside Risk ◽

Content Type ◽

Portfolio Returns ◽

Time Sensitivity ◽

Window Approach ◽

The Impact

PurposeThis paper aims to investigate patterns in UK stock returns related to downside risk, with particular focus on stock returns during financial crises.Design/methodology/approachFirst, stocks are sorted into five quintile portfolios based on the relevant beta values (classic beta, downside beta and upside beta, calculated by the moving window approach). Second, patterns of portfolio returns are examined during various sub-periods. Finally, predictive powers of beta and downside beta are examined.FindingsThe downside risk is observed to have a significant positive impact on contemporaneous stock returns and a negative impact on future returns in general. In contrast, an inverse relationship between risk and return is observed when stocks are sorted by beta, contrary to the classic literature. UK stock returns exhibit clear time sensitivity, especially during financial crises.Originality/valueThis paper focuses on the impact of the downside risk on UK stock returns, assessed via a comprehensive sub-period analysis. This paper fills the gap in the existing literature, in which very few studies examine the time sensitivity in relation to the downside risk and the risk-return anomaly in the UK stock market using a long sample period.

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SCALED AND STABLE MEAN-VARIANCE-EVAR PORTFOLIO SELECTION STRATEGY WITH PROPORTIONAL TRANSACTION COSTS

Journal of Business Economics and Management ◽

10.3846/16111699.2017.1342272 ◽

2017 ◽

Vol 18 (4) ◽

pp. 561-584 ◽

Cited By ~ 1

Author(s):

Ebenezer Fiifi Emire ATTA MILLS ◽

Bo YU ◽

Jie YU

Keyword(s):

Transaction Costs ◽

Portfolio Selection ◽

Downside Risk ◽

Estimation Risk ◽

Expected Return ◽

Proportional Transaction Costs ◽

Portfolio Returns ◽

L2 Norm ◽

The Mean ◽

Mean Variance

This paper studies a portfolio optimization problem with variance and Entropic Value-at-Risk (evar) as risk measures. As the variance measures the deviation around the expected return, the introduction of evar in the mean-variance framework helps to control the downside risk of portfolio returns. This study utilized the squared l2-norm to alleviate estimation risk problems arising from the mean estimate of random returns. To adequately represent the variance-evar risk measure of the resulting portfolio, this study pursues rescaling by the capital accessible after payment of transaction costs. The results of this paper extend the classical Markowitz model to the case of proportional transaction costs and enhance the efficiency of portfolio selection by alleviating estimation risk and controlling the downside risk of portfolio returns. The model seeks to meet the requirements of regulators and fund managers as it represents a balance between short tails and variance. The practical implications of the findings of this study are that the model when applied, will increase the amount of capital for investment, lower transaction cost and minimize risk associated with the deviation around the expected return at the expense of a small additional risk in short tails.

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Is There an Intertemporal Relation between Downside Risk and Expected Returns?

Journal of Financial and Quantitative Analysis ◽

10.1017/s0022109009990159 ◽

2009 ◽

Vol 44 (4) ◽

pp. 883-909 ◽

Cited By ~ 159

Author(s):

Turan G. Bali ◽

K. Ozgur Demirtas ◽

Haim Levy

Keyword(s):

Stock Returns ◽

Value At Risk ◽

Risk Measures ◽

Downside Risk ◽

Expected Returns ◽

Significant Relation ◽

Macroeconomic Variables ◽

Portfolio Returns ◽

Risk Return ◽

Expected Stock Returns

AbstractThis paper examines the intertemporal relation between downside risk and expected stock returns. Value at Risk (VaR), expected shortfall, and tail risk are used as measures of downside risk to determine the existence and significance of a risk-return tradeoff. We find a positive and significant relation between downside risk and the portfolio returns on NYSE/AMEX/Nasdaq stocks. VaR remains a superior measure of risk when compared with the traditional risk measures. These results are robust across different stock market indices, different measures of downside risk, loss probability levels, and after controlling for macroeconomic variables and volatility over different holding periods as originally proposed by Harrison and Zhang (1999).

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Insurer’s Duty to Obtain Information under the IDD Directive – Threat or Opportunity?

Juridica International ◽

10.12697/ji.2020.29.03 ◽

2020 ◽

Vol 29 ◽

pp. 23-33

Author(s):

Olli Norros

Keyword(s):

Downside Risk ◽

Legal Systems ◽

Comprehensive Information ◽

National Jurisdiction ◽

Scope Of Application ◽

Upside Risk

Enacting Directive 2016/97, on insurance distribution (the IDD), has, inter alia, extended the scope of application of regulation, increased the requirements for expertise of the personnel of insurers and insurance intermediaries, and particularised the content of the duty to give information. One of the novelties in the IDD, with regard to the insurer’s duty to provide information, is the duty of the insurer to obtain information from the customer for enabling fulfilment of its own duty to give information. Before the IDD, the balance between the insurer’s duty to give information and the customer’s duty to become acquainted with the information received was customarily understood in many legal systems such that the insurer is obligated to supply comprehensive information on its insurance products in an understandable form while the customer bears the risk of selecting correct and sufficient insurance in reliance on the information received. In other words, the insurer is liable in respect of the information as such, but the customers accept a risk of applying the information incorrectly in their specific circumstances. This background gives rise to the following questions, examined in the article: 1) What is the legislative background of the new duty to obtain information, and what are the objectives behind it? 2) What are the consequences of neglecting this duty? 3) What is the ‘upside risk’ of the reform? That is, in what kinds of cases could the new duty improve matters? 4) What is the ‘downside risk’? In other words, might the new duty cause any problems? The article provides analysis focused on the IDD itself rather than on any national jurisdiction in which the directive has been implemented.

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A Study of Risk Spillover in the Crude Oil and the Natural Gas Markets

Global Business Review ◽

10.1177/0972150917713046 ◽

2017 ◽

Vol 18 (6) ◽

pp. 1465-1477 ◽

Cited By ~ 1

Author(s):

Dilip Kumar

Keyword(s):

Natural Gas ◽

Crude Oil ◽

Value At Risk ◽

Spillover Effects ◽

Downside Risk ◽

Natural Gas Markets ◽

Oil Markets ◽

Gas Markets ◽

Gas Market ◽

Upside Risk

This article examines the upside and downside risk spillover effects among crude oil (WTI and Brent) and Henry Hub natural gas markets. We consider value-at-risk (VaR) as a measure of risk and model both upside and downside 95 per cent, 99 per cent and 99.5 per cent VaR using various VaR approaches. The VaR models are evaluated using Christoffersen’s (1998) conditional coverage test and Lopez’s loss function approach to select the best-performing VaR model. Finally, we apply Hong, Liu and Wang’s (2009) approach to examine the upside and the downside risk spillover among crude oil and Henry Hub natural gas markets. We find significant two-way as well as one-way upside and downside risk spillover between WTI and Brent crude oil. Our results provide weak evidence of upside risk spillover from natural gas market to crude oil markets for 99.5 per cent VaR.

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