Return-Risk Evaluation of Investments

2020 ◽  
pp. 161-177
Author(s):  
Paul Weirich

In finance, a common way of evaluating an investment uses the investment’s expected return and the investment’s risk, in the sense of the investment’s volatility, or exposure to chance. A version of this method derives from a general mean-risk evaluation of acts, under the assumption that only money, risk, and their sources matter. Although the method does not require a measure of risk, finance investigates measures of risks to assist evaluations of risks. An investment creates possible returns, and the variance of the probability distribution of their utilities is a measure of the investment’s risk. This measure neglects some factors affecting an investment’s risk, and so is satisfactory only in special cases. Another measure of risk is known as value-at-risk, or VAR. It also neglects some factors affecting an investment’s risk, and so should be restricted to special cases.

2019 ◽  
Vol 181 (2) ◽  
pp. 473-507 ◽  
Author(s):  
E. Ruben van Beesten ◽  
Ward Romeijnders

Abstract In traditional two-stage mixed-integer recourse models, the expected value of the total costs is minimized. In order to address risk-averse attitudes of decision makers, we consider a weighted mean-risk objective instead. Conditional value-at-risk is used as our risk measure. Integrality conditions on decision variables make the model non-convex and hence, hard to solve. To tackle this problem, we derive convex approximation models and corresponding error bounds, that depend on the total variations of the density functions of the random right-hand side variables in the model. We show that the error bounds converge to zero if these total variations go to zero. In addition, for the special cases of totally unimodular and simple integer recourse models we derive sharper error bounds.


2001 ◽  
Vol 04 (03) ◽  
pp. 535-543
Author(s):  
ANDREAS DE VRIES

A connection between the notion of information and the concept of risk and return in portfolio theory is deduced. This succeeds in two steps: A general moment-return relation for arbitrary assets is derived, thereafter the total expected return is connected to the Kullback-Leibler information. With this result the optimization problem to maximize the expected return of a portfolio consisting of n subportfolios by moment variation under a given value-at-risk constraint is solved. This yields an ansatz to price information.


Author(s):  
TUNCER ŞAKAR CEREN ◽  
MURAT KÖKSALAN

We study the effects of considering different criteria simultaneously on portfolio optimization. Using a single-period optimization setting, we use various combinations of expected return, variance, liquidity and Conditional Value at Risk criteria. With stocks from Borsa Istanbul, we make computational studies to show the effects of these criteria on objective and decision spaces. We also consider cardinality and weight constraints and study their effects on the results. In general, we observe that considering alternative criteria results in enlarged regions in the efficient frontier that may be of interest to the decision maker. We discuss the results of our experiments and provide insights.


2013 ◽  
Vol 43 (2) ◽  
pp. 189-212 ◽  
Author(s):  
Gordon E. Willmot ◽  
Jae-Kyung Woo

AbstractWe discuss a class of counting distributions motivated by a problem in discrete surplus analysis, and special cases of which have applications in stop-loss, discrete Tail value at risk (TVaR) and claim count modelling. Explicit formulas are developed, and the mixed Poisson case is considered in some detail. Simplifications occur for some underlying negative binomial and related models, where in some cases compound geometric distributions arise naturally. Applications to claim count and aggregate claims models are then given.


2009 ◽  
Vol 54 (183) ◽  
pp. 119-138 ◽  
Author(s):  
Milica Obadovic ◽  
Mirjana Obadovic

This paper presents market risk evaluation for a portfolio consisting of shares that are continuously traded on the Belgrade Stock Exchange, by applying the Value-at-Risk model - the analytical method. It describes the manner of analytical method application and compares the results obtained by implementing this method at different confidence levels. Method verification was carried out on the basis of the failure rate that demonstrated the confidence level for which this method was acceptable in view of the given conditions.


2018 ◽  
Vol 979 ◽  
pp. 012094 ◽  
Author(s):  
Dedy Dwi Prastyo ◽  
Dwi Handayani ◽  
Soo-Fen Fam ◽  
Santi Puteri Rahayu ◽  
Suhartono ◽  
...  

2018 ◽  
Vol 5 (1) ◽  
pp. 63-72
Author(s):  
I Nyoman Nugraha Ardana P ◽  
Desi Prapita Sari ◽  
Nurul Suryawati

Penelitian ini berjudul “Analisis Risiko Kredit Angsuran Sistem Fidusia Pada PT. Pegadaian (Persero) Cabang Praya Lombok Tengah”. Tujuan Penelitian ini adalah untuk mengetahui bagaimana tingkat risiko kredit angsuran sistem fidusia yang dihadapi oleh Pegadaian Cabang Praya Lombok Tengah selama lima tahun terakhir yaitu dari tahun 2012 sampai dengan 2016.Pengumpulan data yang dilakukan adalah metode studi kasus. Jenis penelitian yang digunakan adalah penelitian deskriptif, dalam hal ini bagian yang akan dijelaskan/dideskripsikan adalah tingkat risiko kredit angsuran sistem fidusia pada Pegadaian Cabang Praya Lombok Tengah. Variabel yang yang digunakan dalam penelitian ini terdiri dari Nilai Risiko (Value at Risk/VaR), Hasil Ekspektasi (Expected Return), Risiko Kredit (Total Risk).Berdasarkan hasil analisis data dengan menggunakan VaR, maka hipotesispenelitian yang menyatakan tingkat risiko kredit angsuran sistem fidusia yang dihadapi oleh Pegadaian Cabang Praya Lombok Tengah tergolong tinggi dapat dibuktikan. Pernyataan ini didukung oleh temuan penelitian, yaitu nilai kerugian maksimum yang dihadapi Pegadaian Cabang Praya Lombok Tengah pada tahun 2016 dengan tingkat keyakinan 99 persen adalah sebesar Rp.115.317.868, dimana nilai relatifnya sebesar 14,19 persen masih lebih besar jika dibandingkan dengan annual interest sebesar 13,80 persen


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