scholarly journals Sampling methods for investment portfolio formulation procedure at increased market volatility

2021 ◽  
Vol 43 ◽  
pp. 74-93
Author(s):  
Mateusz Dzicher ◽  
◽  
◽  
Keyword(s):  
Sampling Methods ◽  
Empirical Distribution ◽  
Investment Decision ◽  
Optimal Solution ◽  
Statistical Simulation ◽  
Jel Classification ◽  
Optimization Techniques ◽  
Market Volatility ◽  
Investment Portfolio ◽  
Investment Decision Making

Aim/purpose–In this paper, a market volatility-robust portfolio composition frame-work under the modified Markowitz’s approach with the use of sampling methods is developed in order to improve the allocation efficiency for a portfolio of financial in-struments formulation procedure at an increased market volatility.Design/methodology/approach–In order to overcome the risk of not receiving an optimal solution to the portfolio optimization (suboptimal outcomes of attribution of weights in allocation procedures) the developed model, first, implements the rationale that financial markets largely feature two states, i.e., quiescent (non-crisis; low market volatility) periods that are occasionally interspersed with stress (crisis; high market volatility) periods and, second, relies on many input samples of rates of return, either from an empirical distribution or a theoretical distribution (mitigating estimation risk). All computational results are reported for publicly available historical daily data sets on selected Polish blue-chip securities. Findings–Not only did the presented method produce more diversified allocation, but also successfully minimized the unfavorable effects of increased market volatility by providing less risky portfolios in comparison to Newton’s method, typically used for optimization under portfolio theory.Research implications/limitations–The research emphasized that in order to get a more diversified investment portfolio it is crucial to outdo the limitations of a single sample approach (utilized in Markowitz’s model) which may on some occasions be statistically biased. Thus it was proved that sampling methods allow to obtain a less concentrated and volatile allocation which contributes the investment decision-making. However, the current research focused solely on publicly available input data of particular securities. In this manner, an additional analysis can be prepared for other jurisdic-tions and asset classes. There can also be considered a use of other than variance risk measures.Originality/value/contribution–The suggested framework contributes to existing methods a wide array of quantitative data analysis and simulation tools for composing an unique approach that directly addresses the task of minimizing the adverse implications of increased market volatility that, in consequence, pertains to knowledgeable attributing of investment portfolio proportions of either individual or institutional investors. The prepared method is also proved to hold demanded computational quality and, important-ly, the capacity for further development. Keywords: investment decisions, optimization techniques, portfolio selection, statistical simulation methods. JEL Classification: C150, C610, G110

The Need to Decarbonise Buildings: Reasons, Challenges and Objectives

2021 ◽  
Vol 39 (3) ◽  
Author(s):  
Paloma Taltavull ◽  
Raúl Pérez ◽  
Francisco Juárez
Keyword(s):  
Investment Decision ◽  
Decision Making Process ◽  
Investment Portfolio ◽  
Energy Characteristics ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Investment Decision Making ◽  
The Cost ◽  
The Eu

The article addresses the relevance of the real estate sector in climate change control through the decarbonisation of buildings. It presents a case study of an investment portfolio artificially constructed from randomly selected buildings in different Spanish cities and with different uses, evaluated in terms of their structural and energy characteristics. The CRREM tool is used to evaluate the decarbonisation horizon of the buildings between 2018 and 2050, their total emissions and their cost, in relation to the maximum allowed in the agreements signed by the EU in Paris (COP21). From this calculation, an assessment is provided of when buildings will become energetically stranded (energy obsolete) assets and the cost of carbon emitted above permitted levels. These calculations lend transparency to the investment decision-making process facing building owners in the EU over the next 30 years.

scholarly journals Performance Evaluation of Stock Markets

2017 ◽  
Author(s):  
Alina Kvietkauskienė ◽  
Raimonda Martinkutė-Kaulienė
Keyword(s):  
Performance Evaluation ◽  
Stock Markets ◽  
Investment Decision ◽  
Three Dimension ◽  
Investment Portfolio ◽  
Market Selection ◽  
Investment Return ◽  
Investment Decision Making ◽  
Sustainable Investment ◽  
Selection For

The authors concentrate their attention on the performance evaluation of stock markets. The markets evaluation and selection is the important part of investment decision making. In order to develop a conceptual framework for investment decisions in financial markets, it is important to establish a logical model for market selection. The main purpose of the article – to propose the scheme of stock market evaluation and selection for investment portfolio formation. The authors propose the scheme, according to that, it is possible to analyse the issue of the market value and to select markets that may potentially generate a sustainable investment return for investor, taking into account that sustainable investment return is the stable investment return for a long period. According to the analysis of selected stock markets and their evaluation using three-dimension utility function, the authors identified the most stable markets to investors for investment portfolio formation.

Is fair value information relevant to investment decision-making: Evidence from the Australian agricultural sector?

2018 ◽  
Vol 43 (4) ◽  
pp. 555-574 ◽  
Author(s):  
Li Yu (Colly) He ◽  
Sue Wright ◽  
Elaine Evans
Keyword(s):  
Agricultural Sector ◽  
Investment Decision ◽  
Empirical Support ◽  
Accounting Standards ◽  
Fair Value ◽  
Cash Flows ◽  
Jel Classification ◽  
Fair Value Accounting ◽  
Operating Cash Flows ◽  
Investment Decision Making

Despite major accounting standards boards worldwide continuing to use fair value extensively, academic evidence on the relevance of fair value accounting has focused on financial assets. This study breaks new ground to provide the first empirical evidence for the agricultural sector on the relevance of fair value accounting. It examines the forecasting power of the fair value of biological assets for future operating cash flows. Using all agribusinesses listed in Australia, where fair value accounting was first implemented in the agricultural sector, we find that fair value of biological assets does not provide incremental forecasting power for future operating cash flows, whether market-determined prices or managerially estimated value is used. The findings of this study provide empirical support for the call by Elad and Herbohn in 2011 for the International Accounting Standards Board (IASB) to revisit the implementation of fair value accounting in the agricultural sector. JEL Classification: G14, G38, M41, Q18

scholarly journals A Conceptual Framework for Transportation Infrastructure Resilience Optimization

10.29007/rqnf ◽  
2020 ◽  
Author(s):  
Shantanu Kumar ◽  
Mohammed Hashem Mehany
Keyword(s):  
Quantitative Research ◽  
Critical Infrastructure ◽  
Investment Decision ◽  
Investment Decisions ◽  
Optimal Solution ◽  
The United States ◽  
Transportation Infrastructure ◽  
Infrastructure Projects ◽  
Cascading Effects ◽  
Investment Decision Making

Limited financial resources and increased demand for transportation infrastructure maintenance and rehabilitation have complicated investment decision making in recent decades. Additionally, the cascading effects of disasters on critical infrastructure combined with insufficient funding for rehabilitation projects have intensified the situation. Meanwhile, infrastructure resiliency has emerged as a major solution to this problem and research efforts are currently implementing resilience concepts in current and future transportation infrastructure projects. Individual research studies have created models to assess investment decisions related to recovery and other facets of resilience (e.g., adaptability and robustness). However, most of these efforts have been fragmented and none have been applied on a standardized basis or been applicable to fit a standard system for infrastructure resiliency measures over different infrastructure projects (e.g. transportation) around the United States. This quantitative research builds on the Envision standardized rating system’s resilience section to explore the possibilities of investment decisions influenced by adopting different resilience strategies. The novel optimization model uses mathematical modeling to assess various combinations of resilience strategies under budget constraints to find an optimal solution. The model has been successful in providing results based on user-defined priorities for cost and resilience.

Foresight for stock market volatility – a study in the Indian perspective

foresight ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Jitendra Kumar Dixit ◽  
Vivek Agrawal
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Investment Decision ◽  
Market Volatility ◽  
Future Research ◽  
Stock Market Volatility ◽  
Content Type ◽  
Constant Variance ◽  
Investment Decision Making

Purpose Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be measured through the generalized autoregressive conditional heteroscedasticity family models and that will give an insight for investment decision-making. Design/methodology/approach Daily data of the closing value of Bombay Stock Exchange (BSE) (Sensex) and National Stock Exchange (NSE) (Nifty) from April 1, 2011 to March 31, 2017 is collected through the web-portal of BSE (www.bseindia.com) and NSE (www.nseindia.com) for the analysis purpose. Findings The outcome of the study suggested that P-GARCH model is most suitable to predict and forecast the stock market volatility for both the markets. Research limitations/implications Future research can be extended to other stock market segments and sectoral indices to explore and forecast the volatility to establish a trade-off between risk and return. Originality/value The results of previous studies available are not conducive to this research, and very limited scholarly work is available in the Indian context, so required to be re-explored to identify the appropriate model to predict market volatility.

Predictability of Return Volatility Across Different Emerging Capital Markets: Evidence from Asia

2017 ◽  
Vol 6 (2) ◽  
pp. 157-177 ◽  
Author(s):  
Thushari N. Vidanage ◽  
Fabrizio Carmignani ◽  
Tarlok Singh
Keyword(s):  
Econometric Model ◽  
Investment Decision ◽  
Jel Classification ◽  
Policy Formation ◽  
Return Volatility ◽  
Investment Decision Making ◽  
Forecasting Performance ◽  
Out Of Sample ◽  
Egarch Model ◽  
Emerging Capital Markets

The importance of return volatility forecasts in policy formation and investment decision-making in emerging countries is growing considerably. However, from an operational perspective, there is no consensus in the literature on which econometric model has the best forecasting performance. To shed new light on this issue, this article compares forecasting models for a selected group of emerging Asian economies: India, Malaysia, Pakistan, Sri Lanka, Singapore and Thailand. Model’s performance is tested using both in-sample and out-of-sample forecasting methods. It is found that a relatively simple asymmetric EGARCH model clearly outperforms other models. JEL Classification: G12, G17

Investment Decision Making

2017 ◽  
pp. 1-23
Author(s):  
Aleksandar Šević ◽  
Srđan Marinković
Keyword(s):  
Decision Making ◽  
Common Knowledge ◽  
Investment Decision ◽  
Market Equilibrium ◽  
Pricing Model ◽  
Investment Portfolio ◽  
Body Of Knowledge ◽  
Capital Assets ◽  
Investment Decision Making ◽  
Intellectual Traditions

This chapter is a review of different approaches academics take to find right answers on the question how investors' community makes decisions on optimal portfolio of securities and how this process converges toward capital market equilibrium. Authors will try to reconcile the approaches that come from different intellectual traditions. The authors start with the Capital Assets Pricing Model (hereafter CAPM). For decades long the model has been a cornerstone of modern finance literature and a guide for investment decision making. The model assumes that the choice of investment portfolio is directed toward optimization between statistically defined risk and observable return of a universe of available investments, in the setting of rational and homogeneous agents where information is common knowledge. The rigidity of CAPM assumptions led to a plethora of studies where some of those assumptions are relaxed. An important breakthrough to the extant body of knowledge has been made by the introduction of the asymmetric information in the decision-making process.

Investment Decision Making

2020 ◽  
pp. 1498-1521
Author(s):  
Aleksandar Šević ◽  
Srđan Marinković
Keyword(s):  
Decision Making ◽  
Common Knowledge ◽  
Investment Decision ◽  
Market Equilibrium ◽  
Pricing Model ◽  
Investment Portfolio ◽  
Body Of Knowledge ◽  
Capital Assets ◽  
Investment Decision Making ◽  
Intellectual Traditions

This chapter is a review of different approaches academics take to find right answers on the question how investors' community makes decisions on optimal portfolio of securities and how this process converges toward capital market equilibrium. Authors will try to reconcile the approaches that come from different intellectual traditions. The authors start with the Capital Assets Pricing Model (hereafter CAPM). For decades long the model has been a cornerstone of modern finance literature and a guide for investment decision making. The model assumes that the choice of investment portfolio is directed toward optimization between statistically defined risk and observable return of a universe of available investments, in the setting of rational and homogeneous agents where information is common knowledge. The rigidity of CAPM assumptions led to a plethora of studies where some of those assumptions are relaxed. An important breakthrough to the extant body of knowledge has been made by the introduction of the asymmetric information in the decision-making process.

scholarly journals A STUDY ON IMPACT OF BEHAVIOURAL FINANCE ON INVESTMENT DECISION OF SINGLE PARENTS IN SOUTH ASIAN COUNTRIES

2021 ◽  
Vol 6 (2) ◽  
pp. 16-37
Author(s):  
Kannadas Sendilvelu ◽  
Manita Deepak Shah
Keyword(s):  
South Asian ◽  
Risk Taking ◽  
Investment Decision ◽  
Single Parent ◽  
Jel Classification ◽  
Asian Countries ◽  
Behavioural Finance ◽  
Investment Decision Making ◽  
The Impact ◽  
Second Chance

The purpose of this study is to find out the possible impact of behavioural finance on the investment decision of a single parent. As being an earning/working single parent who usually does not have other possible sources in their family, the decision which they take must be a reliable one and cannot afford to get a second chance. In the study, this study is also one of an effort to assess the impact of behavioural biases in the investment decision-making of a single parent. A questionnaire is designed and responses are collected from 203 respondents who prefer to invest where the level of risk is either low or moderate and are more concerned about losses in their investment than substantial gain. Also, most of the respondents were investing in order to meet some specific purpose, for their retirement plan as well as to educate their children. This study concludes by stating that investors’ risk-taking capacity is dependent on their level of income and the sources of income. Although every Individual is subject to some biases, they tend to think more rational way than an average investor in many ways as they know about their requirements and the investment they make. JEL Classification Codes: G40, G41.

The role of affective reactions on investment decision-making

2007 ◽  
Author(s):  
Enrico Rubaltelli ◽  
Giacomo Pasini ◽  
Rino Rumiati ◽  
Paul Slovic
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Affective Reactions ◽  
Investment Decision Making
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