• Title/Summary/Keyword: Portfolio selection

Search Result 108, Processing Time 0.021 seconds

A Study on Dynamic Asset Allocation Strategy for Optimal Portfolio Selection

  • Lee, Hojin
    • East Asian Economic Review
    • /
    • v.25 no.3
    • /
    • pp.310-336
    • /
    • 2021
  • We use iterative numerical procedures combined with analytical methods due to Rapach and Wohar (2009) to solve for the dynamic asset allocation strategy for optimal portfolio demand. We compare different optimal portfolio demands when investors in each country have different access to overseas and domestic investment opportunities. The optimal dynamic asset allocation strategy without foreign investment opportunities leads domestic investors in Korea, Hong Kong, and Singapore to allocate more funds to domestic bonds than to domestic stocks. However, the U.S. investors allocate more wealth to domestic stocks than to domestic bonds. Investors in all countries short bills at a low level of risk aversion. Next, we investigate dynamic asset allocation strategy when domestic investors in Korea have access to foreign markets. The optimal portfolio demand leads investors in Korea to allocate most resources to domestic bonds and foreign stocks. On the other hand, the portfolio weights on foreign bonds and domestic stocks are relatively low. We also analyze dynamic asset allocation strategy for the investors in the U.S., Hong Kong, and Singapore when they have access to the Korean markets as overseas investment opportunities. Compared to the results when the investors only have access to domestic markets, the investors in the U.S. and Singapore increase the portfolio weights on domestic stocks in spite of the overseas investment opportunities in the Korean markets. The investors in the U.S., Hong Kong, and Singapore short domestic bills to invest more than initial funds in risky assets with a varying degree of relative risk aversion coefficients without exception.

Selection Model of System Trading Strategies using SVM (SVM을 이용한 시스템트레이딩전략의 선택모형)

  • Park, Sungcheol;Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
    • /
    • v.20 no.2
    • /
    • pp.59-71
    • /
    • 2014
  • System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

FUZZY RISK MEASURES AND ITS APPLICATION TO PORTFOLIO OPTIMIZATION

  • Ma, Xiaoxian;Zhao, Qingzhen;Liu, Fangai
    • Journal of applied mathematics & informatics
    • /
    • v.27 no.3_4
    • /
    • pp.843-856
    • /
    • 2009
  • In possibility framework, we propose two risk measures named Fuzzy Value-at-Risk and Fuzzy Conditional Value-at-Risk, based on Credibility measure. Two portfolio optimization models for fuzzy portfolio selection problems are formulated. Then a chaos genetic algorithm based on fuzzy simulation is designed, and finally computational results show that the two risk measures can play a role in possibility space similar to Value-at-Risk and Conditional Value-at-Risk in probability space.

  • PDF

A Model for Project Selection of Information System (정보시스템 프로잭트의 선택원리)

  • 지원철
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.10 no.1
    • /
    • pp.79-83
    • /
    • 1985
  • This purpose of this study is to suggest a tentative model for project selection of information system. In constructing a mathematical model, quantification of decision criteria is tried to lessen difficulties of measuring benefits of information system project. Suggested model enables us to select projects in the context of portfolio and information system policy.

  • PDF

Shrinkage Model Selection for Portfolio Optimization on Vietnam Stock Market

  • NGUYEN, Nhat;NGUYEN, Trung;TRAN, Tuan;MAI, An
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.7 no.9
    • /
    • pp.135-145
    • /
    • 2020
  • This paper provides the practical application of a linear shrinkage framework on Vietnam stock market. The cumulative data points observed in this analysis are 468 weeks from January 2011 to December 2019. All the companies listed on Ho Chi Minh City Stock Exchange (HOSE), except the companies under two years period from Initial Public Offering (IPO), are considered. The cumulative number of stocks picked is therefore 350 companies. The VNINDEX, which is the Vietnam Stock Index, is used as a reference index for shrinking to a single-index model. The empirical results show that the shrinkage of covariance matrix for portfolio optimization gives the promising results for the investors on Vietnam stock market. The shrinkage method helps the investors to produce the optimal portfolio in the sense of having higher profit with lower levels of risk compared to the portfolio of the traditional SCM method. Moreover, the portfolio turnover of shrinkage method is always kept at low magnitudes, and this makes the shrinkage portfolios save much transaction costs and reduce the liquidity risks in the trading process. In addition, the ability of shrinkage method in making profit is once again confirmed by the Alpha coefficient that achieves a high positive value.

PORTFOLIO CHOICE UNDER INFLATION RISK: MARTINGALE APPROACH

  • Lim, Byung Hwa
    • Journal of the Chungcheong Mathematical Society
    • /
    • v.26 no.2
    • /
    • pp.343-349
    • /
    • 2013
  • The optimal portfolio selection problem under inflation risk is considered in this paper. There are three assets the economic agent can invest, which are a risk free bond, an index bond and a risky asset. By applying the martingale method, the optimal consumption rate and the optimal portfolios for each asset are obtained explicitly.

A CONSUMPTION, PORTFOLIO AND RETIREMENT CHOICE PROBLEM WITH NEGATIVE WEALTH CONSTRAINTS

  • ROH, KUM-HWAN
    • Journal of the Chungcheong Mathematical Society
    • /
    • v.33 no.2
    • /
    • pp.293-300
    • /
    • 2020
  • In this paper we study an optimal consumption, investment and retirement time choice problem of an investor who receives labor income before her voluntary retirement. And we assume that there is a negative wealth constraint which is a general version of borrowing constraint. Using convex-duality method, we provide the closed-form solutions of the optimization problem.

Mean-shortfall portfolio optimization via sorted L-one penalized estimation (슬로프 방식을 이용한 평균-숏폴 포트폴리오 최적화)

  • Haein Cho;Seyoung Park
    • The Korean Journal of Applied Statistics
    • /
    • v.37 no.3
    • /
    • pp.265-282
    • /
    • 2024
  • Research in the area of financial portfolio optimization, with the dual goals of increasing expected returns and reducing financial risk, has actively explored various risk measurement indicators. At the same time, the incorporation of various penalty terms to construct efficient portfolios with limited assets has been investigated. In this study, we present a novel portfolio optimization formula that combines the mean-shortfall portfolio and the SLOPE penalty term. Specifically, we formulate this optimization expression, which differs from linear programming, by introducing new variables and using the alternating direction method of multipliers (ADMM) algorithms. Through simulations, we validate the automatic grouping property of the SLOPE penalty term within the proposed mean-shortfall portfolio. Furthermore, using the model introduced in this paper, we propose and evaluate four different types of portfolio compositions relevant to real-world investment scenarios through empirical data analysis.

Two essays on the economics of Kye(契)

  • Oh, Kwan-Chi
    • Journal of the Korean Statistical Society
    • /
    • v.3 no.1
    • /
    • pp.31-57
    • /
    • 1974
  • The economic behavior of individuals' selection of particular kye and positions in a kye is based upon choice criteria. The selection of a kye or a position in a kye is not the same as an investor's portfolio selection. A kye member combines in varying degrees the characteristics of both a borrower and a lender of funds. In the following sections we shall first propose choice criteria for borrowers and lenders of funds, then we will try to test various hypotheses derived from the choice criteria by empirical data.

  • PDF

Optimal Portfolio Selection in a Downside Risk Framework (하방위험을 이용한 위험자산의 최적배분)

  • Hyung, Nam-Won;Han, Kyu-Sook
    • The Korean Journal of Financial Management
    • /
    • v.24 no.3
    • /
    • pp.133-152
    • /
    • 2007
  • In this paper, we examine a portfolio selection model in which a safety-first investor maximizes expected return subject to a downside risk constraint. We use the Value-at-Risk as the downside risk measure. We exploit the fact that returns are fat-tailed, and use a semi-parametric method suggested by Jansen, Koedijk and de Vries(2000). We find a more realistic asset allocation than the one suggested by the literature based on the traditional mean-variance framework. For the robustness check, we provide empirical analyses using empirical quantiles. The results highlight that for optimal portfolio selection involving downside risks that are far in the tails of the distribution, our mean-VaR model with a fat-tailed distribution is superior.

  • PDF