scholarly journals Returns to Low Risk Investment Strategy

2017 ◽  
Vol 6 (01) ◽  
pp. 2-15 ◽  
Author(s):  
Shilpa Girish Peswani
Keyword(s):  
High Risk ◽  
Stock Exchange ◽  
Risk Measures ◽  
Risk Measure ◽  
Investment Strategy ◽  
Low Risk ◽  
Total Risk ◽  
Excess Returns ◽  
Benchmark Portfolio ◽  
The Difference

The paper studies the low risk anomaly in the Indian market using entire National Stock Exchange (NSE) as sample from January 2001 to June 2016. It provides evidence that low risk portfolio sorted for total risk, systematic risk as well as unsystematic risk individually for the large cap, mid cap, small cap and the entire NSE universe give higher returns to the investor as compared to high risk portfolio. The difference of returns from low risk portfolio versus high risk portfolio is positive as well as economically and statistically significant for all the risk measures. The results also prove that low risk portfolio investing strategy returns outperform the benchmark portfolio. Using either total volatility, idiosyncratic volatility or beta as a risk measure in stocks, the low risk portfolio gives higher returns even after controlling for the well-known size, value and momentum factors. The excess returns are the highest for low risk portfolio sorted for volatility of large cap stocks. Most of the low risk portfolios consists of growth and winner stocks. In conclusion, the low risk portfolio investment strategy is independent of size and gives positive excess returns as compared to high risk portfolio in the Indian stock market.

scholarly journals The Volatility Effect: Evidence from India

2016 ◽  
Vol 5 (1) ◽  
pp. 12 ◽  
Author(s):  
Mayank Joshipura ◽  
Nehal Joshipura
Keyword(s):  
Standard Deviation ◽  
High Risk ◽  
Stock Market ◽  
Empirical Evidence ◽  
Risk Measures ◽  
Benchmark Portfolio ◽  
Beta Effect ◽  
High Volatility ◽  
The Difference ◽  
Indian Stock Market

We offer empirical evidence that stocks with low volatility earn higher risk-adjusted returns compared to high volatility stocks in the Indian stock market. The annualised excess returns for the low and high volatility decile portfolios amount to 11.40% and 1.30%, respectively, over the period January 2001 to June 2015. The difference of returns is statistically and economically significant for both low and high-risk stocks. Using risk measures of standard deviation and beta, the volatility effect remains after controlling for size, value and momentum. We uncover that the volatility effect is not statistically significant after controlling for beta effect. Our evidence for volatility effect is not dominated by small and illiquid stocks. Our results show that the low volatility portfolio outperforms benchmark portfolio not only in down market but also in up market conditions.

scholarly journals Modified Mean-Variance Risk Measures for Long-Term Portfolios

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 111
Author(s):  
Hyungbin Park
Keyword(s):  
Risk Measures ◽  
Risk Measure ◽  
Investment Strategy ◽  
Stochastic Volatility Model ◽  
Heston Model ◽  
Volatility Model ◽  
Variance Risk ◽  
Investment Portfolios ◽  
Mean Variance

This paper proposes modified mean-variance risk measures for long-term investment portfolios. Two types of portfolios are considered: constant proportion portfolios and increasing amount portfolios. They are widely used in finance for investing assets and developing derivative securities. We compare the long-term behavior of a conventional mean-variance risk measure and a modified one of the two types of portfolios, and we discuss the benefits of the modified measure. Subsequently, an optimal long-term investment strategy is derived. We show that the modified risk measure reflects the investor’s risk aversion on the optimal long-term investment strategy; however, the conventional one does not. Several factor models are discussed as concrete examples: the Black–Scholes model, Kim–Omberg model, Heston model, and 3/2 stochastic volatility model.

scholarly journals Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes

2021 ◽  
Author(s):  
Andreas Fritsche ◽  
Robert Wagner ◽  
Martin Heni ◽  
Kostantinos Kantartzis ◽  
Jürgen Machann ◽  
...  
Keyword(s):  
High Risk ◽  
Lifestyle Intervention ◽  
Low Risk ◽  
Liver Fat ◽  
Liver Fat Content ◽  
Randomized Controlled ◽  
The Difference ◽  
Prevention Of Diabetes

Lifestyle intervention (LI) can prevent type 2 diabetes, but response to LI varies depending on risk subphenotypes. We tested if prediabetic individuals with low risk benefit from conventional LI and individuals with high risk benefit from an intensification of LI in a multi-center randomized controlled intervention over 12 months with 2 years follow up. 1105 prediabetic individuals based on ADA glucose criteria were stratified into a high- and low-risk phenotype, based on previously described thresholds of insulin secretion, insulin sensitivity and liver fat content. Low-risk individuals were randomly assigned to conventional LI according to the DPP protocol or control (1:1), high-risk individuals to conventional or intensified LI with doubling of required exercise (1:1). A total of 908 (82%) participants completed the study. In high-risk individuals, the difference between conventional and intensified LI in post-challenge glucose change was -0.29 mmol/l [CI:-0.54;-0.04], p=0.025. Liver fat (-1.34 percentage points [CI:-2.17;-0.50], p=0.002) and cardiovascular risk (-1.82[CI:-3.13-0.50],p=0.007) underwent larger reductions with intensified than with conventional LI. During a follow up of 3 years, intensified compared to conventional LI had a higher probability to normalize glucose tolerance (p=0.008). In conclusion, it is possible in high-risk individuals with prediabetes to improve glycemic and cardiometabolic outcomes by intensification of LI. Individualized, risk-phenotype-based LI may be beneficial for the prevention of diabetes.

scholarly journals Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes

2021 ◽  
Author(s):  
Andreas Fritsche ◽  
Robert Wagner ◽  
Martin Heni ◽  
Kostantinos Kantartzis ◽  
Jürgen Machann ◽  
...  
Keyword(s):  
High Risk ◽  
Lifestyle Intervention ◽  
Low Risk ◽  
Liver Fat ◽  
Liver Fat Content ◽  
Randomized Controlled ◽  
The Difference ◽  
Prevention Of Diabetes

Lifestyle intervention (LI) can prevent type 2 diabetes, but response to LI varies depending on risk subphenotypes. We tested if prediabetic individuals with low risk benefit from conventional LI and individuals with high risk benefit from an intensification of LI in a multi-center randomized controlled intervention over 12 months with 2 years follow up. 1105 prediabetic individuals based on ADA glucose criteria were stratified into a high- and low-risk phenotype, based on previously described thresholds of insulin secretion, insulin sensitivity and liver fat content. Low-risk individuals were randomly assigned to conventional LI according to the DPP protocol or control (1:1), high-risk individuals to conventional or intensified LI with doubling of required exercise (1:1). A total of 908 (82%) participants completed the study. In high-risk individuals, the difference between conventional and intensified LI in post-challenge glucose change was -0.29 mmol/l [CI:-0.54;-0.04], p=0.025. Liver fat (-1.34 percentage points [CI:-2.17;-0.50], p=0.002) and cardiovascular risk (-1.82[CI:-3.13-0.50],p=0.007) underwent larger reductions with intensified than with conventional LI. During a follow up of 3 years, intensified compared to conventional LI had a higher probability to normalize glucose tolerance (p=0.008). In conclusion, it is possible in high-risk individuals with prediabetes to improve glycemic and cardiometabolic outcomes by intensification of LI. Individualized, risk-phenotype-based LI may be beneficial for the prevention of diabetes.

scholarly journals Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes

2021 ◽  
Author(s):  
Andreas Fritsche ◽  
Robert Wagner ◽  
Martin Heni ◽  
Kostantinos Kantartzis ◽  
Jürgen Machann ◽  
...  
Keyword(s):  
High Risk ◽  
Lifestyle Intervention ◽  
Low Risk ◽  
Liver Fat ◽  
Liver Fat Content ◽  
Randomized Controlled ◽  
The Difference ◽  
Prevention Of Diabetes

Lifestyle intervention (LI) can prevent type 2 diabetes, but response to LI varies depending on risk subphenotypes. We tested if prediabetic individuals with low risk benefit from conventional LI and individuals with high risk benefit from an intensification of LI in a multi-center randomized controlled intervention over 12 months with 2 years follow up. 1105 prediabetic individuals based on ADA glucose criteria were stratified into a high- and low-risk phenotype, based on previously described thresholds of insulin secretion, insulin sensitivity and liver fat content. Low-risk individuals were randomly assigned to conventional LI according to the DPP protocol or control (1:1), high-risk individuals to conventional or intensified LI with doubling of required exercise (1:1). A total of 908 (82%) participants completed the study. In high-risk individuals, the difference between conventional and intensified LI in post-challenge glucose change was -0.29 mmol/l [CI:-0.54;-0.04], p=0.025. Liver fat (-1.34 percentage points [CI:-2.17;-0.50], p=0.002) and cardiovascular risk (-1.82[CI:-3.13-0.50],p=0.007) underwent larger reductions with intensified than with conventional LI. During a follow up of 3 years, intensified compared to conventional LI had a higher probability to normalize glucose tolerance (p=0.008). In conclusion, it is possible in high-risk individuals with prediabetes to improve glycemic and cardiometabolic outcomes by intensification of LI. Individualized, risk-phenotype-based LI may be beneficial for the prevention of diabetes.

scholarly journals Marginal Decomposition of Risk Measures

2006 ◽  
Vol 36 (2) ◽  
pp. 375-413
Author(s):  
Gary G. Venter ◽  
John A. Major ◽  
Rodney E. Kreps
Keyword(s):  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Directional Derivative ◽  
Component Composition ◽  
Capital Allocation ◽  
Directional Derivatives ◽  
Total Risk ◽  
Business Decision ◽  
Marginal Risk

The marginal approach to risk and return analysis compares the marginal return from a business decision to the marginal risk imposed. Allocation distributes the total company risk to business units and compares the profit/risk ratio of the units. These approaches coincide when the allocation actually assigns the marginal risk to each business unit, i.e., when the marginal impacts add up to the total risk measure. This is possible for one class of risk measures (scalable measures) under the assumption of homogeneous growth and by a subclass (transformed probability measures) otherwise. For homogeneous growth, the allocation of scalable measures can be accomplished by the directional derivative. The first well known additive marginal allocations were the Myers-Read method from Myers and Read (2001) and co-Tail Value at Risk, discussed in Tasche (2000). Now we see that there are many others, which allows the choice of risk measure to be based on economic meaning rather than the availability of an allocation method. We prefer the term “decomposition” to “allocation” here because of the use of the method of co-measures, which quantifies the component composition of a risk measure rather than allocating it proportionally to something.Risk adjusted profitability calculations that do not rely on capital allocation still may involve decomposition of risk measures. Such a case is discussed. Calculation issues for directional derivatives are also explored.

scholarly journals Performance comparison between Islamic and conventional stocks: evidence from Pakistan's equity market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Munazza Jabeen ◽  
Saba Kausar
Keyword(s):  
Stock Prices ◽  
Stock Exchange ◽  
Equity Market ◽  
Performance Comparison ◽  
Parametric Estimation ◽  
Total Risk ◽  
Excess Returns ◽  
Content Type ◽  
Practical Implications ◽  
Non Parametric

PurposeThis paper aims to examine the performance of Islamic and conventional stocks listed at the Pakistan Stock Exchange by using both parametric and non-parametric approaches. The motivation is to do risk-return analysis of Islamic stock prices and conventional stock prices.Design/methodology/approachIt uses various measures of performance, e.g. Sharpe ratio, Treynor ratio, Jensen's alpha, beta, generalized auto-regressive conditional heteroskedasticity and stochastic dominance. Using the Karachi Meezan Index-30 (KMI-30) and the Karachi Stock Exchange Index-30 (KSE-30) as proxies for Islamic and conventional stock prices, respectively, it examines the performance of Islamic and conventional stocks. The daily data of KMI-30 and KSE-30, covering period from June 9, 2009 to June 20, 2020 are used.FindingsThe results show that the overall KMI-30 outperforms the KSE-30. The returns of the KMI-30 are greater than the KSE-30. However, the risk and volatility of the KMI-30 and KSE-30 are similar. Further, the KMI-30 has higher excess returns per unit of total risk than the KSE-30. But both indexes have similar excess returns per unit of systematic risk. Moreover, the KMI-30 returns have stochastically dominance over the KSE-30 returns. These results reveal that the Islamic index performs better than the conventional index.Practical implicationsThe findings provide several practical implications in financial and investment decisions making by investors, managers and policymakers such as strategies for asset allocation and investment. Further, in risk management, it provides guidance for allocating portfolios and managing risk. The investment in Islamic stocks may mitigate potential risk within asset portfolios.Originality/valueThis research is unique in its approach to the analysis of the performance comparison of conventional and Islamic stock by using comprehensive parametric and non-parametric estimation techniques. Such research has not been undertaken in the Pakistan's equity market since.

scholarly journals Analisis Perbedaan Return Portofolio Saham Dengan Metode Beta Historis Dengan Beta Akuntansi

2019 ◽  
Vol 15 (2) ◽  
pp. 211
Author(s):  
Lestari Lestari ◽  
Atty Erdiana
Keyword(s):  
High Risk ◽  
Stock Returns ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Statistical Test ◽  
High Rate ◽  
The Difference ◽  
The Right ◽  
Portfolio Structure

This study has the right to select securities that have a high risk of being included in the portfolio structure. High-security securities will offer a high rate of return. Portfolios by choosing high-risk securities that are advantageously seen from the investor's perspective.The object of this study is the Indonesian Stock Exchange. The data needed are price data for the Composite Stock Price Index (CSPI) from 2014 to 2017. The analysis of the technique used is beta estimation as a measure of risk with the historical beta method. While the analysis to test the difference in stock returns with historical beta and accounting accounts using the Paired Sample T statistical test. The results are that there are no differences in stock returns with historical beta and accounting beta from companies that go public on the Indonesia Stock Exchange (IDX).

scholarly journals A Comparative Study of Fundamental and Technical Analysis on Private Sector Banks

2022 ◽  
pp. 127-130
Author(s):  
Dr. S. Kamalasaravanan ◽  
Dr. M. Bhuvaneswari ◽  
Ms. V. Kanimozhi ◽  
Mr. S. Saravanan
Keyword(s):  
High Risk ◽  
Private Sector ◽  
Comparative Study ◽  
Stock Exchange ◽  
Technical Analysis ◽  
Low Risk ◽  
Private Bank ◽  
Risk And Return ◽  
Book Value ◽  
Pe Ratio

All investment is the allocation of money to assets that are expected to yield some gain over a period of time. One of the best high risk and return investments was buying shares in stock exchange. Through these fundamental and technical analysis helps to reduce the risk. The fundamental analysis is used to understand the trend and growth of the economic, industry and company. For this analysis investor used many tools like EPS, PE ratio, Book value, ROE, etc. The technical analysis is used to understand price moment of the stocks and index. For this analysis investor used many tools like Trend, Support and Resistance, RSI, MACD, etc. From this study investors can able to understand and find low risk stocks in Nifty Private Bank. There is no analysis tools and strategy to find the risk free stock. This analysis helps to find the profitable stocks in Nifty Private Bank.

scholarly journals Behavioral finance: the analysis of investor behavior based on belief and feeling and the investor rationality towards LQ 45 stocks

2018 ◽  
Vol 15 (1) ◽  
pp. 292-298
Author(s):  
Etty Indriani ◽  
Cahyani Tunggal Sari
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Behavioral Finance ◽  
Significant Relationship ◽  
Stock Exchange ◽  
Low Risk ◽  
Investor Behavior ◽  
Average Return ◽  
High Return ◽  
The Relationship

This research analyzes behavioral finance, especially the behavior of investors in Yogyakarta, Indonesia Region. The performance of investor behavior is examined based on the LQ 45 stocks return on Indonesia Stock Exchange and questionnaires that are spread out to five securities agents in Yogyakarta.The performance of LQ 45 stocks return is compared to the questionnaire analysis in the “Belief” part at the first and second stages. The first result shows that LQ 45 stocks are profitable. It can be seen from the average return of the stocks that it has positive value and is statistically identical with the LQ 45 index return. This result is in line with the investors’ opinion that LQ 45 stocks are profitable. The second result shows that most of LQ 45 stocks are profitable and give high return. But, this result is also contrary to the opinion of investors towards traditional finance paradigm that investors still believe “high risk – high return, low risk – low return”. Although most of LQ 45 stocks are considered as low risk stocks, many investors prefer to choose LQ 45 stocks. It means that the traditional finance paradigm has weakness. It is proven that investors sometimes act irrationally.The third and fourth stages of the study are aimed to analyze the relationship between feeling and belief towards frequency of transaction each day based on the questionnaire using regression analysis. The result shows that there is significant relationship between feeling and frequency of transaction each day.

Sign in / Sign up

Export Citation Format

Share Document