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Applying Intangible Criteria in Multiple-Criteria Optimization Problems
Published in Sarah Ben Amor, Adiel Teixeira de Almeida, João Luís de Miranda, Emel Aktas, Advanced Studies in Multi-Criteria Decision Making, 2019
Difficulties in applying various objectives may stem from situations in which definitions are ambiguous and allow for different interpretations. Let us demonstrate this by the examples related to the problem of choosing an optimal investment portfolio. Consider two criteria used in evaluating investment portfolios: (1) the expected return and (2) the level of diversification. Analysts and decision makers may disagree on probability distributions; nevertheless, once certain assumptions are agreed on, it becomes possible to measure the expected return. On the other hand, the level of diversification represents a different challenge because there is no exact, universally accepted way to define it as a measurable characteristic. Examples of expected return and diversification demonstrate the distinction between tangible and intangible, measurable and not measurable.
Risk and Return
Published in Bijan Vasigh, Ken Fleming, Liam Mackay, Foundations of Airline Finance, 2018
Bijan Vasigh, Ken Fleming, Liam Mackay
A similar methodology can be used to determine the expected return of an individual stock or portfolio. Expected return is the return that an individual expects in a future period. Since expected return is a projection of the future, the actual return of a stock can vary considerably Additionally, the expected return of the same security can vary based upon one’s beliefs, projections, knowledge, and skill. One methodology for calculating expected return is to assign varying probabilities of an expected annual return. For instance, consider a stock (Table 4.3) with different expected returns based upon the state of the economy Additionally, one has varying probabilities of the state of the economy Based on these factors, the expected return of the stock can be calculated.
Decision Making Under Uncertainty
Published in Charles Yoe, Principles of Risk Analysis, 2019
Now we turn to decision making with probabilities and begin with the expected value approach. If probabilistic information regarding the states of nature is available, we may use the expected value (EV) approach, see Table 19.4. The expected return for each decision is calculated by summing the products of the payoff under each state of nature and the probability of that state of nature occurring. The decision with the best expected return is chosen.
Distributionally robust optimization with multivariate second-order stochastic dominance constraints with applications in portfolio optimization
Published in Optimization, 2023
Shuang Wang, Liping Pang, Hua Guo, Hongwei Zhang
In this section, we apply the DROMSSD model to the portfolio problems. We consider a specific portfolio problem with nonlinear transaction cost where short-selling is allowed to examine our DROMSSD model. Let denote the rate of return from investment on stock i and denote the capital invested in the stock i for . Let a denote the unit transaction cost. The total return rate from the investment of the m stocks is and the total return with transaction costs is , where we write ξ for and x for . We consider the situation where the investors are risk-averse and the purpose of investors is to find a portfolio strategy maximizing the expected return. In the rest of this paper, we consider that where is the benchmark strategy and is a given vector in . First, we give a convex formulation of DROMSSD model (10).
Stock market reactions of maritime shipping industry in the time of COVID-19 pandemic crisis: an empirical investigation
Published in Maritime Policy & Management, 2022
Md Rajib Kamal, Mohammad Ashraful Ferdous Chowdhury, Md. Mozaffar Hosain
The event study begins with regression of stock returns on market returns to establish the parameters for estimating expected stock returns (fair values). The difference between actual stock return and its expected return is then calculated as an abnormal return. This return ought to be zero of every semi-strong structure-efficient market, inferring that market prices are equivalent to fair value. We are keen to observe whether abnormal returns exist encompassing the decided event time frames. Therefore, to find abnormal returns, we first calculate the actual return of each stock for each trading date. The expected return is the projected return on an investment based on historic performance combined with predicted market trends. We start with the following market model (Consolandi et al. 2008):
Risk-adjusted discount rates and the present value of risky nonconventional projects
Published in The Engineering Economist, 2020
Anastasia N. Blaset Kastro, Nikolay Yu Kulakov
One of the basic concepts in finance is risk/return tradeoff, meaning that higher expected returns are associated with greater risk and vice versa. However, this concept is related to investors and it does not correspond to the borrowers’ intention and should therefore be reformulated for them. To derive a rule for adjusting the discount rate for risky negative cash flows, let us use the approach suggested by Miles and Choi (1979). Suppose Firm A is to make an uncertain payment of E(CF1) dollars to Firm B at the end of the current period. Moreover, as an additional operation, Firm B made a certain payment CF0 to Firm A at the beginning of the current period. In other words, Firm B invests funds or makes a “long sale”, and Firm A takes out a loan or makes a “short sale”.