scholarly journals Grading Investment Diversification Options in Presence of Non-Historical Financial Information

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 692
Author(s):  
Clara Calvo ◽  
Carlos Ivorra ◽  
Vicente Liern ◽  
Blanca Pérez-Gladish
Keyword(s):  
Risk Measure ◽  
Statistical Information ◽  
Expected Returns ◽  
Financial Assets ◽  
Expected Return ◽  
Additional Information ◽  
Subjective Risk ◽  
The Impact ◽  
Statistical Risk ◽  
Reduction Index

Modern portfolio theory deals with the problem of selecting a portfolio of financial assets such that the expected return is maximized for a given level of risk. The forecast of the expected individual assets’ returns and risk is usually based on their historical returns. In this work, we consider a situation in which the investor has non-historical additional information that is used for the forecast of the expected returns. This implies that there is no obvious statistical risk measure any more, and it poses the problem of selecting an adequate set of diversification constraints to mitigate the risk of the selected portfolio without losing the value of the non-statistical information owned by the investor. To address this problem, we introduce an indicator, the historical reduction index, measuring the expected reduction of the expected return due to a given set of diversification constraints. We show that it can be used to grade the impact of each possible set of diversification constraints. Hence, the investor can choose from this gradation, the set better fitting his subjective risk-aversion level.

scholarly journals How leverage can improve performance

2020 ◽  
Vol 83 ◽  
pp. 01031
Author(s):  
Miroslav Kmeťko ◽  
Eduard Hyránek
Keyword(s):  
Risk Premium ◽  
Expected Returns ◽  
Tax Rates ◽  
Expected Return ◽  
Tax Rate ◽  
Equity Ratio ◽  
Risk Free Rate ◽  
The Cost ◽  
Managed Portfolios ◽  
The Impact

One of the best-known Capital Asset Pricing Model (CAP/M) provides us with a methodology for measuring the relationship between the risk premium and the impact of leverage on expected returns. However, this model is not used only to value the cost of capital but also to evaluate the performance of managed portfolios. We will test how the expected return changes in percent by changing the debt-equity ratio and the tax rate based on following assumptions: market return 7%, risk-free rate of return 1% and beta 1.2. These assumptions will be constant and we will change the debt-equity ratio and tax rate. Based on these results, it is clear that the change in profitability varies, in relation to the change of the DE ratio by one tenth. As for changes I n tax rates, changes in expected profitability are not entirely in direct proportion to these changes.

scholarly journals CVaR Robust Mean-CVaR Portfolio Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Maziar Salahi ◽  
Farshid Mehrdoust ◽  
Farzaneh Piri
Keyword(s):  
Portfolio Optimization ◽  
Asset Allocation ◽  
Risk Measure ◽  
Optimization Technique ◽  
Large Error ◽  
Data Uncertainty ◽  
Final Decision ◽  
Estimation Risk ◽  
Expected Return ◽  
The Impact

One of the most important problems faced by every investor is asset allocation. An investor during making investment decisions has to search for equilibrium between risk and returns. Risk and return are uncertain parameters in the suggested portfolio optimization models and should be estimated to solve the problem. However, the estimation might lead to large error in the final decision. One of the widely used and effective approaches for optimization with data uncertainty is robust optimization. In this paper, we present a new robust portfolio optimization technique for mean-CVaR portfolio selection problem under the estimation risk in mean return. We additionally use CVaR as risk measure, to measure the estimation risk in mean return. To solve the model efficiently, we use the smoothing technique of Alexander et al. (2006). We compare the performance of the CVaR robust mean-CVaR model with robust mean-CVaR models using interval and ellipsoidal uncertainty sets. It is observed that the CVaR robust mean-CVaR portfolios are more diversified. Moreover, we study the impact of the value of confidence level on the conservatism level of a portfolio and also on the value of the maximum expected return of the portfolio.

scholarly journals Immunization Strategies for Funding Multiple Inflation-Linked Retirement Income Benefits

Risks ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 60
Author(s):  
Cláudia Simões ◽  
Luís Oliveira ◽  
Jorge M. Bravo
Keyword(s):  
Interest Rate ◽  
Yield Curve ◽  
Risk Measure ◽  
Management Strategies ◽  
Interest Rate Risk ◽  
Insurance Companies ◽  
Retirement Income ◽  
Investment Strategies ◽  
Immunization Strategies ◽  
The Impact

Protecting against unexpected yield curve, inflation, and longevity shifts are some of the most critical issues institutional and private investors must solve when managing post-retirement income benefits. This paper empirically investigates the performance of alternative immunization strategies for funding targeted multiple liabilities that are fixed in timing but random in size (inflation-linked), i.e., that change stochastically according to consumer price or wage level indexes. The immunization procedure is based on a targeted minimax strategy considering the M-Absolute as the interest rate risk measure. We investigate to what extent the inflation-hedging properties of ILBs in asset liability management strategies targeted to immunize multiple liabilities of random size are superior to that of nominal bonds. We use two alternative datasets comprising daily closing prices for U.S. Treasuries and U.S. inflation-linked bonds from 2000 to 2018. The immunization performance is tested over 3-year and 5-year investment horizons, uses real and not simulated bond data and takes into consideration the impact of transaction costs in the performance of immunization strategies and in the selection of optimal investment strategies. The results show that the multiple liability immunization strategy using inflation-linked bonds outperforms the equivalent strategy using nominal bonds and is robust even in a nearly zero interest rate scenario. These results have important implications in the design and structuring of ALM liability-driven investment strategies, particularly for retirement income providers such as pension schemes or life insurance companies.

News and Idiosyncratic Volatility: The Public Information Processing Hypothesis*

2020 ◽  
Author(s):  
Robert F Engle ◽  
Martin Klint Hansen ◽  
Ahmet K Karagozoglu ◽  
Asger Lunde
Keyword(s):  
Information Processing ◽  
Public Information ◽  
Selection Procedure ◽  
Autoregressive Process ◽  
Return Volatility ◽  
Market Outcomes ◽  
The Public ◽  
Additional Information ◽  
Financial News ◽  
The Impact

Abstract Motivated by the recent availability of extensive electronic news databases and advent of new empirical methods, there has been renewed interest in investigating the impact of financial news on market outcomes for individual stocks. We develop the information processing hypothesis of return volatility to investigate the relation between firm-specific news and volatility. We propose a novel dynamic econometric specification and test it using time series regressions employing a machine learning model selection procedure. Our empirical results are based on a comprehensive dataset comprised of more than 3 million news items for a sample of 28 large U.S. companies. Our proposed econometric specification for firm-specific return volatility is a simple mixture model with two components: public information and private processing of public information. The public information processing component is defined by the contemporaneous relation with public information and volatility, while the private processing of public information component is specified as a general autoregressive process corresponding to the sequential price discovery mechanism of investors as additional information, previously not publicly available, is generated and incorporated into prices. Our results show that changes in return volatility are related to public information arrival and that including indicators of public information arrival explains on average 26% (9–65%) of changes in firm-specific return volatility.

The Price of Predictability: Estimating Inconsistency Premiums in Social Interactions

2021 ◽  
pp. 014616722199853
Author(s):  
Judith Gerten ◽  
Michael K. Zürn ◽  
Sascha Topolinski
Keyword(s):  
Risk Premium ◽  
Psychological Research ◽  
Expected Value ◽  
Decision Makers ◽  
Expected Returns ◽  
Expected Return ◽  
Total N ◽  
Financial Decision ◽  
Variance Risk ◽  
Risky Option

For financial decision-making, people trade off the expected value (return) and the variance (risk) of an option, preferring higher returns to lower ones and lower risks to higher ones. To make decision-makers indifferent between a risky and risk-free option, the expected value of the risky option must exceed the value of the risk-free option by a certain amount—the risk premium. Previous psychological research suggests that similar to risk aversion, people dislike inconsistency in an interaction partner’s behavior. In eight experiments (total N = 2,412) we pitted this inconsistency aversion against the expected returns from interacting with an inconsistent partner. We identified the additional expected return of interacting with an inconsistent partner that must be granted to make decision-makers prefer a more profitable, but inconsistent partner to a consistent, but less profitable one. We locate this inconsistency premium at around 31% of the expected value of the risk-free option.

OPTIMAL REINSURANCE FROM THE VIEWPOINTS OF BOTH AN INSURER AND A REINSURER UNDER THE CVAR RISK MEASURE AND VAJDA CONDITION

2021 ◽  
pp. 1-29
Author(s):  
Yanhong Chen
Keyword(s):  
Loss Function ◽  
Value At Risk ◽  
Numerical Study ◽  
Risk Measure ◽  
Convex Combination ◽  
Weighting Factor ◽  
Loss Functions ◽  
Conditional Value At Risk ◽  
Optimal Reinsurance ◽  
The Impact

ABSTRACT In this paper, we study the optimal reinsurance contracts that minimize the convex combination of the Conditional Value-at-Risk (CVaR) of the insurer’s loss and the reinsurer’s loss over the class of ceded loss functions such that the retained loss function is increasing and the ceded loss function satisfies Vajda condition. Among a general class of reinsurance premium principles that satisfy the properties of risk loading and convex order preserving, the optimal solutions are obtained. Our results show that the optimal ceded loss functions are in the form of five interconnected segments for general reinsurance premium principles, and they can be further simplified to four interconnected segments if more properties are added to reinsurance premium principles. Finally, we derive optimal parameters for the expected value premium principle and give a numerical study to analyze the impact of the weighting factor on the optimal reinsurance.

scholarly journals Optimization of Financial Asset Neutrosophic Portfolios

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1162
Author(s):  
Marcel-Ioan Boloș ◽  
Ioana-Alexandra Bradea ◽  
Camelia Delcea
Keyword(s):  
Capital Market ◽  
Financial Risk ◽  
Financial Asset ◽  
Financial Assets ◽  
Portfolio Risk ◽  
Financial Return ◽  
Additional Information ◽  
Triangular Numbers ◽  
The Capital Market

The purpose of this paper was to model, with the help of neutrosophic fuzzy numbers, the optimal financial asset portfolios, offering additional information to those investing in the capital market. The optimal neutrosophic portfolios are those categories of portfolios consisting of two or more financial assets, modeled using neutrosophic triangular numbers, that allow for the determination of financial performance indicators, respectively the neutrosophic average, the neutrosophic risk, for each financial asset, and the neutrosophic covariance as well as the determination of the portfolio return, respectively of the portfolio risk. There are two essential conditions established by rational investors on the capital market to obtain an optimal financial assets portfolio, respectively by fixing the financial return at the estimated level as well as minimizing the risk of the financial assets neutrosophic portfolio. These conditions allowed us to compute the financial assets’ share in the total value of the neutrosophic portfolios, for which the financial return reaches the level set by investors and the financial risk has the minimum value. In financial terms, the financial assets’ share answers the legitimate question of rational investors in the capital market regarding the amount of money they must invest in compliance with the optimal conditions regarding the neutrosophic return and risk.

scholarly journals Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences

2020 ◽  
Vol 11 ◽  
Author(s):  
Kenichiro Imai ◽  
Kenta Nakai
Keyword(s):  
Amino Acid ◽  
Subcellular Localization ◽  
Amino Acid Sequences ◽  
Additional Information ◽  
Sorting Signals ◽  
Specific Alternative ◽  
Cell Type Specific ◽  
Future Direction ◽  
The Impact ◽  
New Algorithms

At the time of translation, nascent proteins are thought to be sorted into their final subcellular localization sites, based on the part of their amino acid sequences (i.e., sorting or targeting signals). Thus, it is interesting to computationally recognize these signals from the amino acid sequences of any given proteins and to predict their final subcellular localization with such information, supplemented with additional information (e.g., k-mer frequency). This field has a long history and many prediction tools have been released. Even in this era of proteomic atlas at the single-cell level, researchers continue to develop new algorithms, aiming at accessing the impact of disease-causing mutations/cell type-specific alternative splicing, for example. In this article, we overview the entire field and discuss its future direction.

Toward functional proteomics of alveolar macrophages

2005 ◽  
Vol 288 (4) ◽  
pp. L585-L595 ◽  
Author(s):  
Haifeng M. Wu ◽  
Ming Jin ◽  
Clay B. Marsh
Keyword(s):  
Alveolar Macrophages ◽  
Large Scale ◽  
Cell Types ◽  
Mononuclear Phagocyte ◽  
Detection Sensitivity ◽  
Current Status ◽  
Blood Monocytes ◽  
Protein Patterns ◽  
Additional Information ◽  
The Impact

Alveolar macrophages (AM) belong to a phenotype of macrophages with distinct biological functions and important pathophysiological roles in lung health and disease. The molecular details determining AM differentiation from blood monocytes and AM roles in lung homeostasis are largely unknown. With the use of different technological platforms, advances in the field of proteomics have made it possible to search for differences in protein expression between AM and their precursor monocytes. Proteome features of each cell type provide new clues into understanding mononuclear phagocyte biology. In-depth analyses using subproteomics and subcellular proteomics offer additional information by providing greater protein resolution and detection sensitivity. With the use of proteomic techniques, large-scale mapping of phosphorylation differences between the cell types have become possible. Furthermore, two-dimensional gel proteomics can detect germline protein variants and evaluate the impact of protein polymorphisms on an individual's susceptibility to disease. Finally, surface-enhanced laser desorption and ionization (SELDI) time-of-flight mass spectrometry offers an alternative method to recognizing differences in protein patterns between AM and monocytes or between AM under different pathological conditions. This review details the current status of this field and outlines future directions in functional proteomic analyses of AM and monocytes. Furthermore, this review presents viewpoints of integrating proteomics with translational topics in lung diseases to define the mechanisms of disease and to uncover new diagnostic and therapeutic targets.

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