Journal articles: 'Risk and Return'

1

Gambeta, Vaughn, and Roy Kwon. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization." Journal of Risk and Financial Management 13, no. 10 (October 4, 2020): 237. http://dx.doi.org/10.3390/jrfm13100237.

Full text

Abstract:

This paper formulates a relaxed risk parity optimization model to control the balance of risk parity violation against the total portfolio performance. Risk parity has been criticized as being overly conservative and it is improved by re-introducing the asset expected returns into the model and permitting the portfolio to violate the risk parity condition. This paper proposes the incorporation of an explicit target return goal with an intuitive target return approach into a second-order-cone model of a risk parity optimization. When the target return is greater than risk parity return, a violation to risk parity allocations occurs that is controlled using a computational construct to obtain near-risk parity portfolios to retain as much risk parity-like traits as possible. This model is used to demonstrate empirically that higher returns can be achieved than risk parity without the risk contributions deviating dramatically from the risk parity allocations. Furthermore, this study reveals that the relaxed risk parity model exhibits advantageous traits of robustness to expected returns, which should not deter the use of expected returns in risk parity model.

APA, Harvard, Vancouver, ISO, and other styles

2

Miller, Kent D., and Michael J. Leiblein. "Corporate Risk-Return Relations: Returns Variability Versus Downside Risk." Academy of Management Journal 39, no. 1 (February 1996): 91–122. http://dx.doi.org/10.5465/256632.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Miller, K. D., and M. J. Leiblein. "CORPORATE RISK-RETURN RELATIONS: RETURNS VARIABILITY VERSUS DOWNSIDE RISK." Academy of Management Journal 39, no. 1 (February 1, 1996): 91–122. http://dx.doi.org/10.2307/256632.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Huang, Wei, Qianqiu Liu, S. Ghon Rhee, and Liang Zhang. "Return Reversals, Idiosyncratic Risk, and Expected Returns." Review of Financial Studies 23, no. 1 (March 25, 2009): 147–68. http://dx.doi.org/10.1093/rfs/hhp015.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Aslanidis, Nektarios, Charlotte Christiansen, and Christos S. Savva. "Quantile Risk–Return Trade-Off." Journal of Risk and Financial Management 14, no. 6 (June 3, 2021): 249. http://dx.doi.org/10.3390/jrfm14060249.

Full text

Abstract:

We investigate the risk–return trade-off on the US and European stock markets. We investigate the non-linear risk–return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk–return trade-off is significantly positive at the upper tail (0.9 quantile), where the upper tail is large positive excess returns. The positive trade-off is as expected from asset pricing models. For the lower tail (0.1 quantile), that is for large negative stock returns, the trade-off is significantly negative. Additionally, for the median (0.5 quantile), the risk–return trade-off is insignificant. These results are recovered for the US industry portfolios and for Eurozone stock market portfolios.

APA, Harvard, Vancouver, ISO, and other styles

6

Odutola Omokehinde, Joshua. "Mutual funds behavior and risk-adjusted performance in Nigeria." Investment Management and Financial Innovations 18, no. 3 (September 9, 2021): 277–94. http://dx.doi.org/10.21511/imfi.18(3).2021.24.

Full text

Abstract:

The paper investigates the behavior of mutual funds and their risk-adjusted performance in the financial markets of Nigeria between April 2016 and May 31, 2019, using descriptive statistics, as well as CAPM, Jensen’s alpha, and other risk-adjusted portfolio performance measures such as Sharpe and Treynor ratios, as well as Fama decomposition of return. The descriptive tests revealed that 80.77% of the funds were superior to market returns, while 13.46% were riskier. The market and the fund returns behaved abnormally with asymptotic and leptokurtic characteristics as their skewness and kurtosis varied from the normal requirements. Diagnostically, the normality test by Jacque-Berra showed that the return was not normally distributed at a 1% significance level. The market was more aggressive relative to the funds. The average risk-free rate was 6.75% above the market’s return. The risk-adjusted portfolio returns measured by Sharpe and Treynor ratios showed that 67.31% of the funds underperformed the market compared to 40.38% that outperformed the market using Jensen’s alpha. Fama decomposition of return revealed that the fund managers are risk-averse with 48% superior selection ability and rationally invested over 85% of investors’ funds in schemes with fixed income securities at a given risk-free return that cushioned the negative effects of the systematic and idiosyncratic risks and consequently threw the total returns into positive territories. Overall, the fund managers possessed 52% of inferior selection abilities that only earned 33% of superior risk-adjusted returns and hence, failed to achieve the desired diversification in the relevant period.

APA, Harvard, Vancouver, ISO, and other styles

7

Cochrane, John H., and Monika Piazzesi. "Bond Risk Premia." American Economic Review 95, no. 1 (February 1, 2005): 138–60. http://dx.doi.org/10.1257/0002828053828581.

Full text

Abstract:

We study time variation in expected excess bond returns. We run regressions of one-year excess returns on initial forward rates. We find that a single factor, a single tent-shaped linear combination of forward rates, predicts excess returns on one-to five-year maturity bonds with R2 up to 0.44. The return-forecasting factor is countercyclical and forecasts stock returns. An important component of the return-forecasting factor is unrelated to the level, slope, and curvature movements described by most term structure models. We document that measurement errors do not affect our central results.

APA, Harvard, Vancouver, ISO, and other styles

8

BAYAT, Fikret, and Şule Yüksel YİĞİTER. "COMPARISON OF DOWN-SIDE RISK MEASUREMENTS AND MODERN PORTFOLIO THEORY: THE EXAMPLE OF BORSA ISTANBUL." Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 13, no. 25 (June 29, 2022): 1–23. http://dx.doi.org/10.36543/kauiibfd.2022.001.

Full text

Abstract:

The concept of risk entered the portfolio world with the work of Harry Markowitz. By considering risk and return together, Markowitz accepts the return distribution symmetrically to create optimal portfolios so that investors can obtain the least risk (variance) and the highest return. When the return distribution is symmetrical, variance can give accurate results as an indicator of risk. But what if the returns show an asymmetrical distribution, can this be the case? Based on this question, the purpose of our research is to compare the portfolio return, risk and covariances of 10 different stocks traded in BIST100 between 1.1.2011-31.4.2021 according to Modern Portfolio theory and Downside risk criteria. In our study, it has been found that Modern Portfolio does not diversify sufficiently, creates portfolios from stocks with high return-risk features, and when the returns do not show a symmetrical distribution, it is insufficient. On the contrary, it has been understood that portfolios created against downside risk measures contain less risk and that more accurate results can be achieved with downside risk measures in asymmetric return distribution.

APA, Harvard, Vancouver, ISO, and other styles

9

Shaw, Frances, Fergal O’Brien, and Finbarr Murphy. "European Corporate Credit Returns: A Risk Return Analysis." International Review of Business Research Papers 11, no. 1 (March 2015): 11–24. http://dx.doi.org/10.21102/irbrp.2015.03.111.02.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Marston, Felicia, and Robert S. Harris. "Risk and Return: A Revisit Using Expected Returns." Financial Review 28, no. 1 (February 1993): 117–37. http://dx.doi.org/10.1111/j.1540-6288.1993.tb01341.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Živkov, Dejan, Boris Kuzman, and Jonel Subić. "Measuring the risk-adjusted performance of selected soft agricultural commodities." Agricultural Economics (Zemědělská ekonomika) 68, No. 3 (March 17, 2022): 87–96. http://dx.doi.org/10.17221/298/2021-agricecon.

Full text

Abstract:

In this paper, we used several elaborate return-to-risk methods to investigate the risk-adjusted performances of five soft commodities. Regarding only the level of risk, we found that cocoa had the highest risk of losses, followed by orange juice. Cotton and coffee had the lowest risk of losses. However, according to the return-to-risk output, cotton was the worst asset in which to invest because it had negative average returns. In contradistinction, sugar had a relatively high risk of losses but also the highest average returns, which put it in the first place according to the Sharpe, Sortino and modified Sharpe ratios. Although orange juice had the second-worst downside risk performance, it came in second place according to the return-to-risk ratio because it had relatively high average returns.

APA, Harvard, Vancouver, ISO, and other styles

12

Liang, Priscilla. "Explaining the Risk/Return Mismatch of the MSCI China Index: A Systematic Risk Analysis." Review of Pacific Basin Financial Markets and Policies 10, no. 01 (March 2007): 63–80. http://dx.doi.org/10.1142/s0219091507000982.

Full text

Abstract:

This study examines a risk/return mismatch of the MSCI China Index, which has offered investors low returns and high volatility, yet remains a favorite within the global investors' portfolio. The paper suggests several insights, both from behavioral and traditional finance perspectives, to explain this mismatch. An international risk decomposition model is applied to separate the total risk of China's index return into global systematic risks, regional systematic risks and country specific risks. It suggests the index's lower than average systematic risk might be one of the explanations for its risk/return mismatch. The study also finds that the China Index's systematic risks, both global and regional, have been increasing, but more so at the global level.

APA, Harvard, Vancouver, ISO, and other styles

13

Shum, Wai Cheong, and Gordon Y. N. Tang. "Risk-Return Characteristics." Chinese Economy 43, no. 5 (September 2010): 15–31. http://dx.doi.org/10.2753/ces1097-1475430502.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Goldberg, Lisa R., and Ola Mahmoud. "Risk without return." Journal of Investment Strategies 2, no. 2 (March 2013): 111–20. http://dx.doi.org/10.21314/jois.2013.018.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Mountain, Julie. "Risk and return." Nursery World 2019, no. 10 (May 13, 2019): 30–33. http://dx.doi.org/10.12968/nuwa.2019.10.30.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Armour, Phillip G. "Return at risk." Communications of the ACM 53, no. 9 (September 2010): 23–25. http://dx.doi.org/10.1145/1810891.1810902.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Aladangady, Aditya, Etienne Gagnon, Benjamin K. Johannsen, and William B. Peterman. "Macroeconomic Implications of Inequality and Income Risk." Finance and Economics Discussion Series 2021, no. 072 (November 18, 2021): 1–49. http://dx.doi.org/10.17016/feds.2021.073.

Full text

Abstract:

We explore the long-run relationship between income risk, inequality, and the macroeconomy in an overlapping-generations model in which households face uncertain streams of labor income and returns on their savings. To manage those risks, households can apportion their savings to a bond, whose return is safe and identical across households, and a productive asset, whose return is uncertain and can differ persistently across households. We find that greater polarization in households’ labor income and returns on their savings generally accentuates households’ demand for risk-free assets and the compensation they require for bearing risk, leading to higher measured income and wealth inequality, a lower risk-free real interest rate, and higher risk premiums. These findings suggest that the factors behind the observed rise in inequality over the past few decades might have contributed to the observed fall in the risk-free real interest rate and widening gap between the risk-free real interest rate and the rate of return on capital. We also find that the magnitude of the decline in the risk-free real interest rate and offsetting rise in risk premiums depend importantly on the source of income polarization, with the effects being especially large when greater inequality is caused by increased dispersion in returns on risky assets. Thus, the macroeconomic implications not only depend on the amount of inequality, but also the source of this inequality.

APA, Harvard, Vancouver, ISO, and other styles

18

Kazem Ebrahimi, Seyed, Ali Bahrami Nasab, and Mehdi Karim. "Evaluating the effect of accruals quality, investments anomaly and quality of risk on risk premium (return) of stock of listed companies in Tehran Stock Exchange." Problems and Perspectives in Management 14, no. 3 (September 15, 2016): 296–306. http://dx.doi.org/10.21511/ppm.14(3-si).2016.01.

Full text

Abstract:

Nowadays, reaching to economic goals in any society requires public participation, which is only the result of people participation. Investment in stock market is one of people participation methods. So, awareness from stock return and its affecting factors is one of anxieties of investors and owners of shares. In this research, authors evaluate the effective factors on stock return using Fama and French models. So, authors study the effect of some factors including accruals quality, anomalies of investments, size factor, market’s risk premium factor, and book equity to market equity factor, on stock’s risk premium which is representative of stock returns, in 70 listed companies in Tehran stock exchange from 20 March 2003 to 20 March 2014. Results showed that accruals quality and quality of risk have meaningful effect on risk premium, which is representative of stock returns. Results also show that investment anomaly has no meaningful effect on risk premium and, consequently, on stock returns. Keywords: accruals quality, investments anomaly, risk premium, return diversity, stock returns, quality of earnings, discretionary accruals, systematic risk. JEL Classification: M41, G12, G14

APA, Harvard, Vancouver, ISO, and other styles

19

Penman, Stephen H., and Julie Lei Zhu. "Accounting Anomalies, Risk, and Return." Accounting Review 89, no. 5 (April 1, 2014): 1835–66. http://dx.doi.org/10.2308/accr-50799.

Full text

Abstract:

ABSTRACT This paper investigates whether so-called anomalous returns predicted by accounting numbers reflect normal returns for risk or abnormal returns. It does so via a model showing how accounting numbers inform about normal returns if pricing were rational. The model equates expected returns to expectations of earnings and earnings growth, so that any variable that forecasts earnings and earnings growth also indicates the required return if the market prices those outcomes as risky. The empirical results confirm that many accounting anomaly variables (such as accruals, asset growth, and investment) forecast forward earnings and growth, and in the same direction in which they forecast returns. While the lack of an agreed-upon asset pricing model for required returns rules out definitive conclusions, the paper provides both a framework and supporting empirical results indicating that the observed “anomalous” returns associated with accounting numbers are consistent with rational pricing.

APA, Harvard, Vancouver, ISO, and other styles

20

Chauvet, Marcelle, and Simon Potter. "NONLINEAR RISK." Macroeconomic Dynamics 5, no. 4 (September 2001): 621–46. http://dx.doi.org/10.1017/s1365100501023082.

Full text

Abstract:

This paper analyzes the joint time-series properties of the level and volatility of expected excess stock returns. An unobservable dynamic factor is constructed as a nonlinear proxy for the market risk premia with its first moment and conditional volatility driven by a latent Markov variable. The model allows for the possibility that the risk–return relationship may not be constant across the Markov states or over time. We find an overall negative contemporaneous relationship between the conditional expectation and variance of the monthly value-weighted excess return. However, the sign of the correlation is not stable, but instead varies according to the stage of the business cycle. In particular, around the beginning of recessions, volatility rises substantially, reflecting great uncertainty associated with these periods, while expected return falls, anticipating a decline in earnings. Thus, around economic peaks there is a negative relationship between conditional expectation and variance. However, toward the end of a recession expected return is at its highest value as an anticipation of the economic recovery, and volatility is still very high in anticipation of the end of the contraction. That is, the risk–return relation is positive around business-cycle troughs. This time-varying behavior also holds for noncontemporaneous correlations of these two conditional moments.

APA, Harvard, Vancouver, ISO, and other styles

21

Soni, Rashmi. "Designing a Portfolio Based On Risk and Return of Various Asset Classes." International Journal of Economics and Finance 9, no. 2 (January 11, 2017): 142. http://dx.doi.org/10.5539/ijef.v9n2p142.

Full text

Abstract:

Every investor’s dream is to maximize return with minimum risk. Since this is practically impossible, the target is to optimize the risk and return. Different asset classes perform differently at different points of time. The performance is affected by the business as well as other local and global macroeconomic parameters. Crude oil, real estate, gold etc. have given very high returns previously but have turned unattractive in recent times. Equity market has over a long term returned handsome benefits but is highly volatile and hence fraught with risks. The risk free investments like fixed, on the other hand, fall in the low-risk low-return category. The purpose of this study is to analyze the returns of various asset classes and correlate these with their risk characteristics in order to verify whether there is always a positive relation between risk and return across all asset classes and to find out the portfolio mix of the various asset classes corresponding to the desired return and risk.

APA, Harvard, Vancouver, ISO, and other styles

22

Won, Jin Woo, Wooyong Jung, Seung Heon Han, Sungmin Yun, and Bonsang Koo. "What Enables a High-Risk Project to Yield High Return from a Construction Contractor’s Perspective?" Sustainability 11, no. 21 (October 27, 2019): 5971. http://dx.doi.org/10.3390/su11215971.

Full text

Abstract:

“High risk high return” is a general rule in the overall industry; however, high-risk projects in the construction industry frequently fail to yield a high return. In order to achieve a sustainable business in the international construction market, contractors require an average to high return yield under high-risk conditions. This study aims to reveal what risk factors and risk management performance enables high-risk projects to yield high returns. The study investigated 124 international construction projects by Korean contractors and classified them into four groups: high-risk high-return (HH), high-risk low-return (HL), low-risk high-return (LH), and low-risk low-return (LL). The study found that risk assessment accuracy was the most important trigger in discriminating between high return projects (HH, LH) and low return projects (HL, LL), whereas risk mitigation performance showed little difference between high return and low return projects. In addition, the contingency amount did not significantly affect project return in HL, LH, and LL projects, but HH projects showed a positive relation between contingency and predicted risk amount. This article contributes to recognizing the differences between high return and low return projects and provides insights for practitioners into the relation between risk management performance and high returns in different risk conditions.

APA, Harvard, Vancouver, ISO, and other styles

23

Mahdavi, Mahnaz. "Risk-Adjusted Return When Returns Are Not Normally Distributed." Journal of Alternative Investments 6, no. 4 (March 31, 2004): 47–57. http://dx.doi.org/10.3905/jai.2004.391063.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Amaroh, Siti, and Chanif Nasichah. "Risk-Return Analysis on Optimum Portfolio Selection of Islamic Stocks." Equilibrium: Jurnal Ekonomi Syariah 9, no. 1 (June 4, 2021): 65. http://dx.doi.org/10.21043/equilibrium.v9i1.9433.

Full text

Abstract:

<p><em>This study aims to determine the optimum portfolio category and analyze the risk-return on a formed portfolio. Data was taken from eighteen listed companies indexed by Jakarta Islamic Index during 2015-2018. Stock returns are calculated based on the closing price at the end of each month in the period. Sharia Certificate of Bank Indonesia is a proxy of risk-free return, while the market return is measured by the value of the Jakarta Islamic Index. Stocks are sorted by the value of excess return to beta (ERB) from highest to lowest, and to obtain optimal stock portfolio candidates, and the ERB value must be compared with the cut-off rate value. Seven issuers qualify for forming the optimum portfolio of shares. The results show that the optimum portfolio return is greater than the expected return and the expected risk-free return. When compared between individual stock returns and portfolio stock returns, some individual stocks provide higher returns than portfolio returns. However, the risk of individual shares was also higher than the risk of the portfolio. This finding proves that risk can be reduced optimally in Islamic stocks selection by forming an optimum portfolio.</em></p>

APA, Harvard, Vancouver, ISO, and other styles

25

Howe, Thomas S., and Ralph A. Pope. "Risk, Return, And Diversification Of Specialty Mutual Funds." Journal of Applied Business Research (JABR) 9, no. 4 (September 27, 2011): 45. http://dx.doi.org/10.19030/jabr.v9i4.5992.

Full text

Abstract:

This study examines the risk, return, and diversification of specialty mutual funds compared to traditional mutual funds. Until recently, lack of data has precluded examination of the performance of a number of categories of specialty funds. Over the period studied, specialty funds as a whole appeared to earn returns comparable to those of traditional equity mutual funds. On the other hand, most categories of specialty funds were found to have greater total risk and retain significantly more unsystematic risk than traditional equity mutual funds.

APA, Harvard, Vancouver, ISO, and other styles

26

Machdar, Nera Marinda. "THE EFFECT OF CAPITAL STRUCTURE, SYSTEMATIC RISK, AND UNSYSTEMATIC RISK ON STOCK RETURN." Business and Entrepreneurial Review 14, no. 2 (November 20, 2016): 149. http://dx.doi.org/10.25105/ber.v14i2.1148.

Full text

Abstract:

The purpose of study was to analyze the effect of capital structure, systematic risk on stock return. The model proposed was evaluated using SPSS statistics 22. Samples in this study are public firms listed on the Indonesian stock Exchange with LQ 45 Index for period 2009-2012. The result of this study showed that (1) The variable of capital structure, systematic risk and unsytematic risk together have a positive influence on stock return; (2) The capital structure has a positive and significant impact on stock return; (3) The systematic risk (beta) has a negative effect on stock return; and (4) The unsystematic risk has a negative effect on stock return. The limitations of this study were as follows: (1) The number of sample used in this study is small, so the result might not be able to describe the overall companies; (2) The study was only investigated the sample firm from manufacturing sector with LQ45 Index; (3) The study calculated stock returns without considering the risks. Therefore, it was necessary to manner. Subsequent research suggested that (1) The number of samples shoulds be increased; (2) The sample of companies in the industry should be expanded; (3) The stock return by calculating the risk adjusted return should be considered.

APA, Harvard, Vancouver, ISO, and other styles

27

Punj, Dr Shruti. "Risk and Return Analysis of Selected Flexi Cap Mutual Funds." International Journal of Multidisciplinary Research and Analysis 05, no. 10 (October 15, 2022): 2763–71. http://dx.doi.org/10.47191/ijmra/v5-i10-25.

Full text

Abstract:

Mutual funds are considered by the investors as an ideal investment for people who are not having huge sum of money and wish to invest in a portfolio of stocks wherein the share price is quite high. The investors may or may not be aware about the ways investment could be done in stock market and there are different investment options which are available in the market based on a different risk and return. Flexi cap mutual funds offerfund managers a freedom for investing across themes/ sectors and market capitalizations. In Flexi Cap mutual funds, the fund managers could invest on the basis of outlook of market. These schemes generally recommended to the moderate investors for creating wealth over long time period. This study is based on the evaluation of risk and return of different flexi cap mutual funds and compares the performance of these funds so as to find the best flexi cap fund based on different measures of return and risk. Based on the average of the monthly returns, though it is negative, the lowest average negative return is of Aditya Birla and Parag Parikh Flexi Cap mutual funds. The maximum times the highest return has been of Parag Parikh Flexi Cap mutual fund during different quarters. Based on the average Annual return, highest return is of Parag Parikh Flexi Cap mutual fund, followed by UTI Flexi Cap fund, SBI Flexi Cap fund, PGIM Flexi Cap fund and Aditya Birla Flexi Cap mutual fund.

APA, Harvard, Vancouver, ISO, and other styles

28

Chen, Menggen. "Risk-return tradeoff in Chinese stock markets: some recent evidence." International Journal of Emerging Markets 10, no. 3 (July 20, 2015): 448–73. http://dx.doi.org/10.1108/ijoem-06-2012-0058.

Full text

Abstract:

Purpose – The purpose of this paper is to pay more attention to four different research questions at least. One is that this study intends to explore the changes of the risk-return relationship over time, because the institutions and environment have changed a lot and might tend to influence the risk-return regime in the Chinese stock markets. The second question is whether there is any difference for the risk-return relationship between Shanghai and Shenzhen stock markets. The third question is to compare the similarities and dissimilarities of the risk-return tradeoff for different frequency data. The fourth question is to compare the explanation power of different GARCH-M type models which are all widely used in exploring the risk-return tradeoff. Design/methodology/approach – This paper investigates the risk-return tradeoff in the Chinese emerging stock markets with a sample including daily, weekly and monthly market return series. A group of variant specifications of GARCH-M type models are used to test the risk-return tradeoff. Additionally, some diagnostic checks proposed by Engle and Ng (1993) are used in this paper, and this will help to assess the robustness of different models. Findings – The empirical results show that the dynamic risk-return relationship is quite different between Shanghai and Shenzhen stock markets. A positive and statistically significant risk-return relationship is found for the daily returns in Shenzhen Stock Exchange, while the conditional mean of the stock returns is negatively related to the conditional variance in Shanghai Stock Exchange. The risk-return relationship usually becomes much weaker for the lower frequency returns in both markets. A further study with the sub-samples finds a positive and significant risk-return trade-off for both markets in the second stage after July 1, 1999. Originality/value – This paper extends the existing related researches about the Chinese stock markets in several ways. First, this study uses a longer sample to investigate the relationship between stock returns and volatility. Second, this study estimates the returns and volatility relationship with different frequency sample data together. Third, a group of variant specifications of GARCH-M type models are used to test the risk-return tradeoff. In particular, the author employs the Component GARCH-M model which is relatively new in this line of research. Fourth, this study investigates if there is any structural break affecting the risk-return relationship in the Chinese stock markets over time.

APA, Harvard, Vancouver, ISO, and other styles

29

Graf, Stefan, Lena Haertel, Alexander Kling, and Jochen Ruß. "THE IMPACT OF INFLATION RISK ON FINANCIAL PLANNING AND RISK-RETURN PROFILES." ASTIN Bulletin 44, no. 2 (February 4, 2014): 335–65. http://dx.doi.org/10.1017/asb.2014.1.

Full text

Abstract:

AbstractThe importance of funded private or occupational old-age provision is expected to increase due to demographic changes and the resulting problems for government-run pay-as-you-go systems. Clients and advisors therefore need reliable methodologies to match offered products with clients' needs and risk appetite. In Graf et al. (2012), the authors have introduced a methodology based on stochastic modeling to properly assess the risk-return profiles — i.e. the probability distribution of future benefits — of various old-age provision products. In this paper, we additionally consider the impact of inflation on the risk-return profile of old-age provision products. In a model with stochastic interest rates, stochastic inflation and equity returns including stochastic equity volatility, we derive risk-return-profiles for various types of existing unit-linked products with and without embedded guarantees and especially focus on the difference between nominal and real returns. We find that typical “rule of thumb” approximations for considering inflation risk are inappropriate and further show that products that are considered particularly safe by practitioners because of nominal guarantees may bear significant inflation risk. Finally, we propose product designs suitable to reduce inflation risk and investigate their risk-return profile in real terms.

APA, Harvard, Vancouver, ISO, and other styles

30

Cao Mai Phuong, Lai. "Bowman's risk-return relationship: Empirical evidence in a frontier market." Investment Management and Financial Innovations 19, no. 2 (June 3, 2022): 191–200. http://dx.doi.org/10.21511/imfi.19(2).2022.16.

Full text

Abstract:

This paper investigates whether there exists a Bowman paradox on the relationship between risk-return for Vietnamese firms. Data in the annual audited financial statements from 2017 to 2020 of 727 enterprises listed on the Vietnamese stock market are used in this study. The data set is divided into two different groups based on the reference point, which is the average return of the whole market and by industry. Correlation analysis and ordinary least square regression according to cross sectional data were performed in this study. After controlling for size, debt-to-total assets, and debt-to-equity ratios, the research results show that the risk-return relationship of the two groups of firms is mixed and can be explained by prospect theory. There exists Bowman's paradox for a group of firms whose return is below the reference point, these firms tend to seek risk versus return, so their risk-return relationship is negative. In contrast, this relationship is positive for the group of firms whose returns are above the reference point, or which tend to avoid risk. The slope coefficient of the group of enterprises below the reference point compared to the rest of enterprises is 2.5:1, which correctly reflects the ratio of the risk-seeking area to the risk-avoiding area in prospect theory.

APA, Harvard, Vancouver, ISO, and other styles

31

Kalev, Petko S., Konark Saxena, and Leon Zolotoy. "Coskewness Risk Decomposition, Covariation Risk, and Intertemporal Asset Pricing." Journal of Financial and Quantitative Analysis 54, no. 1 (December 21, 2018): 335–68. http://dx.doi.org/10.1017/s0022109018000637.

Full text

Abstract:

We develop an intertemporal asset pricing model where cash-flow news, discount-rate news, and their second moments are priced by the market. This model generalizes the market-return decomposition framework, showing that intertemporal considerations imply a decomposition of squared market returns (coskewness risk). Our model accounts for 68% of the return variation across portfolios sorted by size, book-to-market ratio, momentum, investment, and profitability for a modern U.S. sample period. Further, our findings highlight the importance of covariation risk, that is, the risk of simultaneous unfavorable shocks to cash flows and discount rates, in understanding equity risk premia.

APA, Harvard, Vancouver, ISO, and other styles

32

Lioui, Abraham, and Patrice Poncet. "Misunderstanding risk and return?" Finance 32, no. 2 (2011): 91. http://dx.doi.org/10.3917/fina.322.0091.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Wanger, Ralph. "Risk, Return, and Regulation." CFA Institute Magazine 28, no. 4 (December 2017): 28–29. http://dx.doi.org/10.2469/cfm.v28.n4.9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Malkiel, Burton G., and Yexiao Xu. "Risk and Return Revisited." Journal of Portfolio Management 23, no. 3 (April 30, 1997): 9–14. http://dx.doi.org/10.3905/jpm.1997.409608.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Castex, Gonzalo. "College risk and return." Review of Economic Dynamics 26 (October 2017): 91–112. http://dx.doi.org/10.1016/j.red.2017.03.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Bellini, Fabio, Roger J. A. Laeven, and Emanuela Rosazza Gianin. "Robust return risk measures." Mathematics and Financial Economics 12, no. 1 (June 1, 2017): 5–32. http://dx.doi.org/10.1007/s11579-017-0188-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Ang, Andrew, and Jun Liu. "Risk, return, and dividends." Journal of Financial Economics 85, no. 1 (July 2007): 1–38. http://dx.doi.org/10.1016/j.jfineco.2007.01.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Bell, David E. "Risk, Return, and Utility." Management Science 41, no. 1 (January 1995): 23–30. http://dx.doi.org/10.1287/mnsc.41.1.23.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Campbell, John Y. "Understanding Risk and Return." Journal of Political Economy 104, no. 2 (April 1996): 298–345. http://dx.doi.org/10.1086/262026.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Henkel, Joachim. "The Risk-Return Fallacy." Schmalenbach Business Review 52, no. 4 (October 2000): 363–73. http://dx.doi.org/10.1007/bf03396625.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Gurrib, Ikhlaas, Firuz Kamalov, and Elgilani E. Alshareif. "High Frequency Return and Risk Patterns in U.S. Sector ETFs during COVID-19." International Journal of Energy Economics and Policy 12, no. 5 (September 27, 2022): 441–56. http://dx.doi.org/10.32479/ijeep.13030.

Full text

Abstract:

This study investigates intraday patterns in the eleven sectors of the United States (U.S.). Key contributions are (i) risk and return patterns at specific trading periods on the New York Stock Exchange (NYSE), (ii) whether a specific day return model can predict the next 15-minute positive return, and (iii) the impact of the first vaccination rollout in the U.S. on intraday Exchange-Traded-Funds (ETF) returns. Time-dependent regressions capture risk and return relationships, decision trees in machine learning compare return models, and impulse responses capture the effect of the 2019 coronavirus (COVID-19) vaccine rollout in U.S. 15-minute Standard & Poor’s Depository Receipts (SPDR) Select Sector ETF data is used over 12th March 2020-23rd February 2021. Findings support sector ETF returns fluctuate the most in the first and last 15 minutes. Average returns in the first 15 minutes are the highest, converging to near zero as the trading session continues. Overnight returns contribute the most to volatility. U-shaped patterns into both return and risk exist, especially on Mondays. Mondays and Fridays have the most significant positive returns 15 minutes after the open. Prediction scores using an all-return model were superior to any specific day return model. The first vaccination rollout has a positive effect only in energy, technology, and financial sector ETFs, however with a short-lasting effect on ETFs returns.

APA, Harvard, Vancouver, ISO, and other styles

42

Jeong, Wan-Ho, and Chan-Pyo Kook. "Stock Return Volatility and Corporate Credit Risk." Journal of Derivatives and Quantitative Studies 20, no. 1 (February 29, 2012): 1–40. http://dx.doi.org/10.1108/jdqs-01-2012-b0001.

Full text

Abstract:

In order to reinforce traditional credit indicators such as credit rate or financial ratio, many financial market data; such as the stock prices or their returns are used to evaluate corporate credit risk. Even though many structural models, which are using stock returns and their volatilities, are used to measure credit risk, empirical studies to find out how to measure desirable stock return volatility or which interval data is better for measuring the volatility are not enough. So, we tried to find out empirical evidences of following two questions. First, whether stock return volatility could be used as a timely indicator for credit events, such as bankruptcy or credit rate change. Second, which measure and which interval data are the best to calculate stock return volatility for credit indicator. We have reached the following empirical conclusions based on recent Korean stock market data. First, stock return volatility could be useful for early warning of credit events, because the volatility showed meaningful increase before the credit event. Second, 90~150 daily stock return data are useful to measure the volatility. Short-term data, less than 90 days are too sensitive to market circumstances and they easily increase without any credit level change. On the contrary, volatilities based on long-term data, more than 150 days are too smooth to use as a timely credit indicator. Third, in aspect of the measure of volatility, realized volatility which assume the averages of short-term stock returns are ‘zero’ is more efficient than traditional standard deviation. Those conclusions are based on recent Korean stock market data, so further robustness test should be followed.

APA, Harvard, Vancouver, ISO, and other styles

43

Bertelli, Anthony M., and Peter John. "Public Policy Investment: Risk and Return in British Politics." British Journal of Political Science 43, no. 4 (December 7, 2012): 741–73. http://dx.doi.org/10.1017/s0007123412000567.

Full text

Abstract:

This article sets out and tests a theory of public policy investment – how democratic governments seek to enhance their chances of re-election by managing a portfolio of policy priorities for the public, analogous to the relationship between investment manager and client. Governments choose policies that yield returns the public values; and rebalance their policy priorities later to adjust risk and stabilize return. Do the public reward returns to policy capital or punish risky policy investments? The article investigates whether returns to policy investment guide political management and statecraft. Time-series analyses of risk and return in Britain 1971–2000 reveal that risk and return on government policy portfolios predict election outcomes, and that returns, risk profiles and the uncertainty in public signals influence the prioritization of policies.

APA, Harvard, Vancouver, ISO, and other styles

44

Hui, Eddie C. M., and Ziyou Wang. "IDIOSYNCRATIC RISK AND SPILLOVER EFFECT IN REIT RETURNS." International Journal of Strategic Property Management 22, no. 6 (November 12, 2018): 457–70. http://dx.doi.org/10.3846/ijspm.2018.6271.

Full text

Abstract:

Nowadays, idiosyncratic risk has substantial impacts on the risk control of portfolio construction. However, little research has been done on the spillover effect of idiosyncratic risk from global markets in REIT returns. A risk-return model is developed to examine the effects of idiosyncratic risk and its spillover on the short-run dynamics of REIT returns in 10 major REIT markets between 2001 and 2014. Variance decomposition provides evidence that idiosyncratic risk exceeds market risk most of the time. The risk-return models demonstrate that the spillover effect of idiosyncratic risk globally played a more significant role than idiosyncratic risk in the return dynamics during the subprime mortgage crisis. Furthermore, we analyse the asymmetric responses of volatility in REIT returns. The results show that the Netherlands is the most strongly preferred market in terms of earning excess returns, while the US market is unique in that the idiosyncratic risk and spillover effect tend to enlarge the fluctuations in REIT returns.

APA, Harvard, Vancouver, ISO, and other styles

45

Mohanty, Sunil K., Roar Aadland, Sjur Westgaard, Stein Frydenberg, Hilde Lillienskiold, and Cecilie Kristensen. "Modelling Stock Returns and Risk Management in the Shipping Industry." Journal of Risk and Financial Management 14, no. 4 (April 9, 2021): 171. http://dx.doi.org/10.3390/jrfm14040171.

Full text

Abstract:

We estimate the impact of macroeconomic risk factors on shipping stock returns, using a quantile regression (QR) model. We regress the excess return of a portfolio for the container, dry bulk, chemical/gas, oil tanker, and diversified shipping sectors on the world market portfolio excess return, volatility index, and changes in the oil price, exchange rate, and interest rate. The sensitivities of stock returns to the risk factors differ across quantiles and shipping segments and are found to be significant for the volatility index, world market portfolio return, exchange rate, and changes in long-term interest rate with variation over quantiles. This provides evidence of asymmetric and heterogeneous dependence between stock returns and certain macroeconomic risk variables. The results of the study also suggest that standard OLS regression is inadequate to uncover the risk-return relation.

APA, Harvard, Vancouver, ISO, and other styles

46

Huang, Yin-Yin, I.-Fei Chen, Chien-Liang Chiu, and Ruey-Chyn Tsaur. "Adjustable Security Proportions in the Fuzzy Portfolio Selection under Guaranteed Return Rates." Mathematics 9, no. 23 (November 25, 2021): 3026. http://dx.doi.org/10.3390/math9233026.

Full text

Abstract:

Based on the concept of high returns as the preference to low returns, this study discusses the adjustable security proportion for excess investment and shortage investment based on the selected guaranteed return rates in a fuzzy environment, in which the return rates for selected securities are characterized by fuzzy variables. We suppose some securities are for excess investment because their return rates are higher than the guaranteed return rates, and the other securities whose return rates are lower than the guaranteed return rates are considered for shortage investment. Then, we solve the proposed expected fuzzy returns by the concept of possibility theory, where fuzzy returns are quantified by possibilistic mean and risks are measured by possibilistic variance, and then we use linear programming model to maximize the expected value of a portfolio’s return under investment risk constraints. Finally, we illustrate two numerical examples to show that the expected return rate under a lower guaranteed return rate is better than a higher guaranteed return rates in different levels of investment risks. In shortage investments, the investment proportion for the selected securities are almost zero under higher investment risks, whereas the portfolio is constructed from those securities in excess investments.

APA, Harvard, Vancouver, ISO, and other styles

47

Korteweg, Arthur. "Risk Adjustment in Private Equity Returns." Annual Review of Financial Economics 11, no. 1 (December 26, 2019): 131–52. http://dx.doi.org/10.1146/annurev-financial-110118-123057.

Full text

Abstract:

This article reviews empirical methods to assess risk and return in private equity. I discuss data and econometric issues for fund-level, deal-level, and publicly traded partnerships data. Risk-adjusted return estimates vary substantially by method, time period, and data source. The weight of evidence suggests that, relative to a similarly risky investment in the stock market, the average venture capital (VC) fund earned positive risk-adjusted returns before the turn of the millennium, but net-of-fee returns have been zero or even negative since. Average leveraged buyout (BO) investments have generally earned positive risk-adjusted returns both before and after fees, compared with a levered stock portfolio. Based on an expanded set of risk factors from the literature, VC resembles a small-growth investment, while BO loads mostly on value. I also discuss the empirical evidence on liquidity and idiosyncratic volatility risks.

APA, Harvard, Vancouver, ISO, and other styles

48

Putri, Dwiana Sanjaya, and Nusa Muktiadji. "Analisis Portfolio Optimal Pada Beberapa Perusahaan LQ-45 Komparasi Pendekatan Markowits Dan Model Indeks Tunggal." Jurnal Ilmiah Manajemen Kesatuan 5, no. 1 (July 16, 2018): 33–43. http://dx.doi.org/10.37641/jimkes.v5i1.24.

Full text

Abstract:

In order to minimize the risk, every investor will diverse their investments in a portfolio. This research will form two portfolios, containing three stocks with the highest return and the lowest risks, and with the dividend for the last five years. The two methods used are Single Index Model and Markowitz. Single Index Model involving market in its process while Markowitz only considering the correlation between each stocks. Later will be shown, that both methods’ results are the same for both returns (Individual stocks and portofolio), and a slightly different result with the portofolio’s risks. This proves that the correlation between stocks are also involving in the market. Alam Sutera Realty (ASRI), AKR Corporindo (AKRA), and Global Mediacom (BMTR) are chosen as they have the highest return since 2010, while Astra Agro Lestari (AALI), Adhi Wijaya (ADHI), and Bank Negara Indonesia (BBNI), are chosen for its lowest risk for the last five years. The portfolio A’s returns, calculated with Markowitz method is 45.7% and the risk is 33.78%, and the single index model results for return is exactly the same, 45.7% while the risk is slightly different, 35.8%. The portfolio B’s return, calculated with Markowitz method is 20.7% and the risk is 27.67%, and the single index model’s result for return is exactly the same, 20.7% while the risk is slightly different, 28.24%.

APA, Harvard, Vancouver, ISO, and other styles

49

Hong, Min-Goo, and Kook-Hyun Chang. "Jump Risk and Heteroscedasticity of KOSPI200 Intra-day Returns." Journal of Derivatives and Quantitative Studies 23, no. 2 (May 31, 2015): 243–64. http://dx.doi.org/10.1108/jdqs-02-2015-b0004.

Full text

Abstract:

This study examines whether KOSPI200 intra-day return has jump risk and heteroscedasticity and we compare the estimation result of intra-day return and that of daily return. The sample covers from January 2, 2004 to July 31, 2014. We use 30-minute intervals for measuring KOSPI200 intra-day return. It seems this study finds the importance of the consideration of the intra-day data in Korean Stock Market. While some of the parameters of the daily returns for the jump are not significant, but those of intra-day returns are significant over the sample period. Also, the intra-day volatility has shown U-shaped or reverse J-shaped curve. In particular the pattern of intra-day volatility seems to come from the jump risk, which is interpreted as the information inflow in the market.

APA, Harvard, Vancouver, ISO, and other styles

50

Barinov, Alexander. "Analyst Disagreement and Aggregate Volatility Risk." Journal of Financial and Quantitative Analysis 48, no. 6 (December 2013): 1877–900. http://dx.doi.org/10.1017/s002210901400009x.

Full text

Abstract:

AbstractThe paper explains why firms with high dispersion of analyst forecasts earn low future returns. These firms beat the capital asset pricing model in periods of increasing aggregate volatility and thereby provide a hedge against aggregate volatility risk. The aggregate volatility risk factor can explain the abnormal return differential between high- and low-disagreement firms. This return differential is higher for firms with abundant real options, and this fact can be explained by aggregate volatility risk. Aggregate volatility risk can also explain why the link between analyst disagreement and future returns is stronger for firms with high short-sale constraints.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Risk and Return'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles