Turning an Asset-Liability Problem into an Investment Portfolio Problem

2012 ◽  
Author(s):  
Yaniv Zaks ◽  
Zinoviy Landsman
Keyword(s):  
Investment Portfolio ◽  
Portfolio Problem

scholarly journals Apie eksperimentinį investavimo strategijų tyrimą realiose ir virtualiose fi nansų rinkose

2013 ◽  
Vol 65 ◽  
pp. 103-110
Author(s):  
Jonas Mockus ◽  
Igor Katin ◽  
Joana Katina
Keyword(s):  
Mean Absolute Error ◽  
Absolute Error ◽  
Investment Strategies ◽  
Individual Investor ◽  
Investment Portfolio ◽  
Acceptable Risk ◽  
The Real ◽  
Portfolio Problem ◽  
The Mean

Darbo tikslas yra įvertinti įvairias investavimo strategijas pagal jų pelningumą realiose ir virtualiose fi nansų rinkose. Darbe aprašytas atnaujintas fi nansų rinkos modelis, analizuojami eksperimentinių skaičiavimų rezultatai. On the experimental investigation of investment strategies in the real and virtual fi nancial marketsJonas Mockus, Igor Katin, Joana Katina SummaryThe optimal fi nancial investment (Portfolio) problem was investigated by leading fi nancial organizations and scientists. The aim of these works was to defi ne the optimal diversifi cation of the assets depending on the acceptable risk level.The aim of the paper is to evaluate different investment strategies in the real and virtual fi nancial markets. This aim is the new element of the proposed simulation system since optimization is performed in the space of investment strategies; both daily and long-term. A number of different investment strategies are presented, including the ones based on the Modern Portfolio Theory (MPT).The simulated investment procedures include different prediction methods. The methods that minimize the mean absolute error (MAE) are added to the traditional ones that minimize the least squares error (MSE). The results of the virtual fi nancial market are compared with historical data.The model is designed as a tool to represent the behavior of an individual investor which wants to predict how the expected profi t depends on different investment strategies using different forecasting methods of real and virtual stocks.

scholarly journals Research on intelligent algorithms for solving portfolio problems

2021 ◽  
Vol 336 ◽  
pp. 09017
Author(s):  
Hongwei Wang ◽  
Lin Huo ◽  
Jinhao Feng
Keyword(s):  
Stock Market ◽  
Mathematical Optimization ◽  
Optimization Methods ◽  
Multiple Constraints ◽  
Investment Portfolio ◽  
Intelligent Algorithms ◽  
The Real ◽  
Inertia Weight ◽  
Portfolio Problem ◽  
Sine Cosine Algorithm

Investment is a behavior of coexistence of the benefits and risks. In the context of rich asset types, an effective investment portfolio can help investors obtain stable returns and diversify risks. In reality, portfolio problems often contain multiple constraints and objectives that cannot be effectively solved by traditional mathematical optimization methods. This paper proposes a hybrid beetle antennae search sine cosine algorithm based on non-linear inertia weight. Experiments are performed on five portfolio problem datasets in the real stock market. The results show that the proposed algorithm is effective and has some performance advantages in solving portfolio problems.

scholarly journals Investment Portfolio, Democratic Accountability, Poverty and Income Inequality Nexus in Pakistan: A Way to Social Sustainability

2021 ◽  
Vol 13 (11) ◽  
pp. 6411
Author(s):  
Muhammad Shahid Hassan ◽  
Haider Mahmood ◽  
Muhammad Ibrahim Saeed ◽  
Tarek Tawfik Yousef Alkhateeb ◽  
Noman Arshed ◽  
...  
Keyword(s):  
Income Inequality ◽  
Social Sustainability ◽  
Data Availability ◽  
Democratic Accountability ◽  
Investment Portfolio ◽  
Economic Activities ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Short Run

Institutions help to streamline the economic activity-related procedures, where government intervention might be involved. Institutions also play a significant role in social sustainability. The findings using the Autoregressive Distributed Lag approach to cointegration for the period from 1984–2019 reveal that investment portfolio and democratic accountability reduce poverty in Pakistan both in the long and short run. Moreover, democratic accountability helps to reduce income inequality, but the investment portfolio’s role is not significant. The literacy rate helps to reduce income inequality, and inflation increases poverty and income inequality. The remittances increase income inequality, and urbanization increases poverty. To eradicate poverty and income inequality, the governments should be accountable for their actions to the general public while they remain in power. If they do not deliver as per their manifestoes, they will not be reelected in the next election. Moreover, there is a dire need to redefine the role of an investment portfolio to reduce the risk of investment. So, investments would increase economic activities and could reduce poverty and income inequality. This study contributes to the literature by inquiring about the role of the investment portfolio and democratic accountability in social sustainability by reducing poverty and income inequality. This study only considers Pakistan’s economy due to limitations of poverty data availability in other countries. The scope could further be broadened by accessing data for a wider Asia region to test the role of the investment portfolio and democratic accountability to reduce poverty and income inequality.

scholarly journals OPTIMAL CONTROL OF THE DECUMULATION OF A RETIREMENT PORTFOLIO WITH VARIABLE SPENDING AND DYNAMIC ASSET ALLOCATION

2021 ◽  
pp. 1-34
Author(s):  
Peter A. Forsyth ◽  
Kenneth R. Vetzal ◽  
Graham Westmacott
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Retirement Savings ◽  
Allocation Strategy ◽  
Investment Portfolio ◽  
Dynamic Asset Allocation ◽  
Dynamic Strategy ◽  
Prior Literature ◽  
Weighted Combination ◽  
Over Time

Abstract We extend the Annually Recalculated Virtual Annuity (ARVA) spending rule for retirement savings decumulation (Waring and Siegel (2015) Financial Analysts Journal, 71(1), 91–107) to include a cap and a floor on withdrawals. With a minimum withdrawal constraint, the ARVA strategy runs the risk of depleting the investment portfolio. We determine the dynamic asset allocation strategy which maximizes a weighted combination of expected total withdrawals (EW) and expected shortfall (ES), defined as the average of the worst 5% of the outcomes of real terminal wealth. We compare the performance of our dynamic strategy to simpler alternatives which maintain constant asset allocation weights over time accompanied by either our same modified ARVA spending rule or withdrawals that are constant over time in real terms. Tests are carried out using both a parametric model of historical asset returns as well as bootstrap resampling of historical data. Consistent with previous literature that has used different measures of reward and risk than EW and ES, we find that allowing some variability in withdrawals leads to large improvements in efficiency. However, unlike the prior literature, we also demonstrate that further significant enhancements are possible through incorporating a dynamic asset allocation strategy rather than simply keeping asset allocation weights constant throughout retirement.

scholarly journals Portfolio optimization under dynamic risk constraints: Continuous vs. discrete time trading

2018 ◽  
Vol 35 (1-2) ◽  
pp. 1-21
Author(s):  
Imke Redeker ◽  
Ralf Wunderlich
Keyword(s):  
Discrete Time ◽  
Risk Measure ◽  
Time Discretization ◽  
Optimal Investment ◽  
Portfolio Performance ◽  
Dynamic Risk ◽  
Portfolio Problem ◽  
Risk Constraint ◽  
Infrequent Trading ◽  
Dynamic Programming Equations

AbstractWe consider an investor facing a classical portfolio problem of optimal investment in a log-Brownian stock and a fixed-interest bond, but constrained to choose portfolio and consumption strategies that reduce a dynamic shortfall risk measure. For continuous- and discrete-time financial markets we investigate the loss in expected utility of intermediate consumption and terminal wealth caused by imposing a dynamic risk constraint. We derive the dynamic programming equations for the resulting stochastic optimal control problems and solve them numerically. Our numerical results indicate that the loss of portfolio performance is not too large while the risk is notably reduced. We then investigate time discretization effects and find that the loss of portfolio performance resulting from imposing a risk constraint is typically bigger than the loss resulting from infrequent trading.

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