scholarly journals Binary Beetle Antennae Search Algorithm for Tangency Portfolio Diversification

2021 ◽  
Vol 13 (1) ◽  
pp. 44-50
Author(s):  
Vasilios N. Katsikis ◽  
Spyridon D. Mourtas
Keyword(s):  
Nonlinear Programming ◽  
Evolutionary Algorithms ◽  
Capital Market ◽  
Search Algorithm ◽  
Efficient Frontier ◽  
Portfolio Diversification ◽  
Cardinality Constraint ◽  
Market Portfolio ◽  
Real World Datasets ◽  
Intercept Point

The tangency portfolio, also known as the market portfolio, is the most efficient portfolio and arises from the intercept point of the Capital Market Line (CML) and the efficient frontier. In this paper, a binary optimal tangency portfolio under cardinality constraint (BOTPCC) problem is defined and studied as a nonlinear programming (NLP) problem. Because such NLP problems are widely approached by heuristic, a binary beetle antennae search algorithm is employed to provide a solution to the BTPSCC problem. Our method proved to be a magnificent substitute to other evolutionary algorithms in real-world datasets, based on numerical applications and computer simulations.

scholarly journals Diversification of Time-Varying Tangency Portfolio under Nonlinear Constraints through Semi-Integer Beetle Antennae Search Algorithm

AppliedMath ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 63-73
Author(s):  
Vasilios N. Katsikis ◽  
Spyridon D. Mourtas
Keyword(s):  
Nonlinear Programming ◽  
Real World ◽  
Capital Market ◽  
Search Algorithm ◽  
Efficient Frontier ◽  
Intersection Point ◽  
Time Varying ◽  
Nonlinear Constraints ◽  
Evolutionary Methods ◽  
Real World Datasets

In finance, the most efficient portfolio is the tangency portfolio, which is formed by the intersection point of the efficient frontier and the capital market line. This paper defines and explores a time-varying tangency portfolio under nonlinear constraints (TV-TPNC) problem as a nonlinear programming (NLP) problem. Because meta-heuristics are commonly used to solve NLP problems, a semi-integer beetle antennae search (SIBAS) algorithm is proposed for solving cardinality constrained NLP problems and, hence, to solve the TV-TPNC problem. The main results of numerical applications in real-world datasets demonstrate that our method is a splendid substitute for other evolutionary methods.

A Critical Analysis of Selected Public and Private Mutual Fund Schemes in India

2019 ◽  
Vol 118 (8) ◽  
pp. 28-34
Author(s):  
Dr. V. Murali Krishna ◽  
Dr T. Hima Bindu ◽  
Dr. Ravikumar Gunakala
Keyword(s):  
Mutual Funds ◽  
Capital Market ◽  
Mutual Fund ◽  
Portfolio Diversification ◽  
Financial Intermediaries ◽  
Public And Private ◽  
Fund Managers ◽  
Fixed Base ◽  
Banking Institutions ◽  
Different Levels

Mutual Fund Industry is one of the emerged dominant financial intermediaries in Indian Capital Market. The main objective of investing in a mutual fund is to diversify risk. Though the mutual fund invests in diversified portfolio, the fund managers take different levels of risk in order to achieve the schemes objectives. Mutual funds allow portfolio diversification and relative risk management through collection of funds from the savers/investors, the same investing in equity and debt stocks. This type of invested funds is managed by professional experts called as fund managers Funds are categorized as income should fixed base in India are a kind of mutual fund which makes investment in debt securities that have been issued to the corporate, banking institutions and to government in general

scholarly journals Evolutionary Algorithms for Constrained Parameter Optimization Problems

1996 ◽  
Vol 4 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Zbigniew Michalewicz ◽  
Marc Schoenauer
Keyword(s):  
Nonlinear Programming ◽  
Evolutionary Algorithms ◽  
Evolutionary Computation ◽  
Numerical Optimization ◽  
Optimization Problems ◽  
Optimization Techniques ◽  
Test Cases ◽  
Nonlinear Constraints ◽  
Nonlinear Programming Problem ◽  
General Nonlinear Programming

Evolutionary computation techniques have received a great deal of attention regarding their potential as optimization techniques for complex numerical functions. However, they have not produced a significant breakthrough in the area of nonlinear programming due to the fact that they have not addressed the issue of constraints in a systematic way. Only recently have several methods been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; however, these methods have several drawbacks, and the experimental results on many test cases have been disappointing. In this paper we (1) discuss difficulties connected with solving the general nonlinear programming problem; (2) survey several approaches that have emerged in the evolutionary computation community; and (3) provide a set of 11 interesting test cases that may serve as a handy reference for future methods.

scholarly journals State Variable Effects in Graphical Event Models

2020 ◽  
Author(s):  
Debarun Bhattacharjya ◽  
Dharmashankar Subramanian ◽  
Tian Gao
Keyword(s):  
Real World ◽  
Continuous Time ◽  
Point Processes ◽  
Temporal Dynamics ◽  
Search Algorithm ◽  
State Variables ◽  
Discrete State ◽  
State Variable ◽  
Event Models ◽  
Real World Datasets

Many real-world domains involve co-evolving relationships between events, such as meals and exercise, and time-varying random variables, such as a patient's blood glucose levels. In this paper, we propose a general framework for modeling joint temporal dynamics involving continuous time transitions of discrete state variables and irregular arrivals of events over the timeline. We show how conditional Markov processes (as represented by continuous time Bayesian networks) and multivariate point processes (as represented by graphical event models) are among various processes that are covered by the framework. We introduce and compare two simple and interpretable yet practical joint models within the framework with relevant baselines on simulated and real-world datasets, using a graph search algorithm for learning. The experiments highlight the importance of jointly modeling event arrivals and state variable transitions to better fit joint temporal datasets, and the framework opens up possibilities for models involving even more complex dynamics whenever suitable.

scholarly journals Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit

2020 ◽  
Author(s):  
Mengying Zhu ◽  
Xiaolin Zheng ◽  
Yan Wang ◽  
Qianqiao Liang ◽  
Wenfang Zhang
Keyword(s):  
Financial Markets ◽  
Transaction Costs ◽  
Portfolio Selection ◽  
Financial Engineering ◽  
Side Information ◽  
Cardinality Constraint ◽  
Real World Datasets ◽  
Online Portfolio ◽  
Online Portfolio Selection ◽  
Practical Constraints

Online portfolio selection (OLPS) is a fundamental and challenging problem in financial engineering, which faces two practical constraints during the real trading, i.e., cardinality constraint and non-zero transaction costs. In order to achieve greater feasibility in financial markets, in this paper, we propose a novel online portfolio selection method named LExp4.TCGP with theoretical guarantee of sublinear regret to address the OLPS problem with the two constraints. In addition, we incorporate side information into our method based on contextual bandit, which further improves the effectiveness of our method. Extensive experiments conducted on four representative real-world datasets demonstrate that our method significantly outperforms the state-of-the-art methods when cardinality constraint and non-zero transaction costs co-exist.

Information Asymmetry And The Role Of Foreign Investors In Daily Transactions During The Crisis; A Study Of Herding In The Indonesian Stock Exchange

2016 ◽  
Vol 32 (1) ◽  
pp. 269-288 ◽  
Author(s):  
Ishak Ramli ◽  
Sukrisno Agoes ◽  
Ignatius Roni Setyawan
Keyword(s):  
Information Asymmetry ◽  
Capital Market ◽  
Stock Exchange ◽  
Efficient Frontier ◽  
Herding Behavior ◽  
Lower Intensity ◽  
Foreign Investors ◽  
Global Investors ◽  
European Economies

The purpose of this study is to prove that there was herding behavior by domestic investors following that of foreign investors in the Indonesian Capital Market (IDX) and that the herding was influenced by information asymmetry. It began when global investors undertook international diversification to the IDX because the returns on their portfolios were not on the efficient frontier during the crisis and because of the low correlation between Indonesia’s economy and the American and European economies. Utilizing the IDX daily transaction data during the years 2009-2011, the herding behavior of domestic investors, which followed that of foreign investors, was tested by Lakonishok models as was the influence of information asymmetry on the herding. It was found that the herding behavior in the IDX occurred in buy, sell or entire herdings (buy and sell). There were 0.40 to 0.55 buy herdings and 0.20 to 0.40 sell herdings during the crisis in 2008 and 2009. Buy herding then continued in 2010 onwards, although with lower intensity (0.05 to 0.20); however, sell herding decreased dramatically, and there has been almost no sell herding since then. Nevertheless, domestic investors did then sell in the opposite strategy, which was to sell when foreign investors tended to buy. Subsequent findings demonstrated that herding occurred with the influence of information asymmetry between domestic and foreign investors.

A Study on the Strategic Application of Abnormal Risk-Return Relationship

2017 ◽  
Vol 25 (3) ◽  
pp. 339-367
Author(s):  
Youngmin Choi ◽  
Bohyun Yoon
Keyword(s):  
Capital Market ◽  
Efficient Frontier ◽  
Investment Strategies ◽  
Traditional Concept ◽  
Period Analysis ◽  
Empirical Results ◽  
Risk Return ◽  
High Return ◽  
Before And After ◽  
Preliminary Study

This paper focuses on the strategic application based on the empirical results of risk-return relationship against the classical concept. Empirical analysis from domestic data, we verify that the traditional concept-‘high risk, high return’ relationship are maintained, however, we confirm the falling pattern in the highest total volatility group. Even though we implies double sorting method to control the well known systematic factor such as BM and size, we still confirm such abnormal risk-return relationship. Furthermore, we perform sub-period analysis before and after the liberalization of Korean capital market and we find such abnormal risk-return relationship is appeared after the liberalization. Based on our empirical results, we establish and verify the new benchmark that evenly allocate highest volatility portfolio to sub-volatility portfolio. Under the new benchmark, we confirm the expansion of the efficient frontier and the improvement of Sharpe ratio. We believe that our results provide an applicability research of smart beta strategy and new benchmark based on such strategy. We expect our research to be used as preliminary study to overcome the era of “new normal” and to reform the investment strategies correspond to segmentation of benchmark.

scholarly journals Capital Market Theories: Market Efficiency Versus Investor Prospects

2012 ◽  
Vol 11 (8) ◽  
pp. 849
Author(s):  
Kathleen Hodnett ◽  
Heng-Hsing Hsieh
Keyword(s):  
Market Efficiency ◽  
Behavioral Finance ◽  
Capital Market ◽  
Asset Allocation ◽  
Efficient Market Hypothesis ◽  
Capital Asset Pricing ◽  
Arbitrage Pricing Theory ◽  
Market Portfolio ◽  
Pricing Theory

This paper reviews the development of capital market theories based on the assumption of capital market efficiency, which includes the efficient market hypothesis (EMH), modern portfolio theory (MPT), the capital asset pricing model (CAPM), the implications of MPT in asset allocation decisions, criticisms regarding the market portfolio and the development of the arbitrage pricing theory (APT). An alternative school of thought proposes that investors are irrational and that their trading behaviors are driven by psychological biases such as greed and fear. Prospect theory and the role of behavioral finance that describe investment decisions in imperfect capital markets are presented to contrast the Utopian assumption of perfect market efficiency. The paper concludes with the argument of Hirshleifer (2001) that heuristics are shared by investors and asset prices may not reflect their long-term intrinsic values as indicated by efficient capital market theories.

scholarly journals Fundamental Indexes As Proxies For Mean-Variance Efficient Portfolios

2014 ◽  
Vol 30 (6) ◽  
pp. 1929
Author(s):  
Kathleen Hodnett ◽  
Geare Botes ◽  
Khumbudzo Daswa ◽  
Kimberly Davids ◽  
Emmanuel Che Fongwa ◽  
...  
Keyword(s):  
Firm Value ◽  
Efficient Frontier ◽  
Expected Returns ◽  
Market Capitalization ◽  
Weighted Index ◽  
Market Portfolio ◽  
Index Approach ◽  
Efficient Portfolios ◽  
Market Indexes ◽  
Mean Variance

Mean-variance efficiency was first explained by Markowitz (1952) who derived an efficient frontier comprised of portfolios with the highest expected returns for a given level of risk borne by the investor. The assumed mean-variance efficiency of the market portfolio along with the fact that it is capitalization-weighted underlies the rationale for market indexes being constructed by market capitalization weights (Mar, Bird, Casavecchia and Yeung, 2009). The pioneers of the fundamental index approach to investing, Arnott, Hsu and Moore (2005), however differ, and argue that market capitalization-weighted indexes are not mean-variance efficient due to their price-sensitivity, which leads to the overweighting of overvalued stocks and the underweighting of undervalued stocks, creating a return drag. The authors constructed an index weighted by fundamental determinants of firm value such as earnings, book value and revenue, proving that their fundamentally weighted index causes the return drag inherent in capitalization-weighted indexes to disappear. The aim of this paper is to discuss the evidence for and the arguments against fundamentally-weighted indexes as proxies for mean-variance efficient portfolios. We conclude that since the market cap-weighted index is only mean-variance efficient given the efficiency of the market, whilst the fundamental index incurs higher turnover, and may contain a value bias, its resistance to investor overreaction makes it a more valid mean-variance efficient proxy in an inefficient market.

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