Investment Portfolio Construction Research Articles

Comparative Analysis of Industry and Country Diversification Benefits of the Equity Portfolio

This study focuses on the construction of investment portfolios using different optimization methods (1/N, risk parity, hierarchical risk parity, mean variance) based on two ways of asset diversification—cross-country and cross-industry—and assesses their effectiveness using a number of metrics. The main research question is which approach to asset diversification turns out to be the most profitable for the investor in terms of return and risk. Research results’ degree of susceptibility of fluctuations in time is assessed by an interperiod analysis with the division of the time interval under consideration into crisis and noncrisis years. According to the results, the industry asset allocation strategy outperforms the asset allocation strategy focused on country diversification. In crisis years, these differences are amplified, but the results are highly dependent on the portfolio optimization method.

Performance comparison of multifractal techniques and artificial neural networks in the construction of investment portfolios

This work aims to compare the performance of the traditional portfolios of the S&P500, Markowitz, and Sharpe with the multifractal trend fluctuation portfolios (MF-DFA) and portfolios of artificial neural networks with Student's asymmetric probability classification (ANN-t). In this study, we use daily data for S&P500 stocks between January 18, 2018, and July 12, 2022, where we backtest return and risk metrics such as annual volatility, Value at Risk, Sharpe Ratio, Sortino Ratio, Beta, and Jensen´s Alpha. For both return and risk, we obtain the results confirming that the ANN-t technique might indicate better investment entries, which contradicts the Efficient Market Hypothesis (EMH).

Investment Portfolio Construction in the Beijing-Tianjin-Hebei Region of the CSI 300

How to construct an optimal investment portfolio has become the mainstream of research with the increasing demands of investors to preserve values and returns. This paper is based on the background of the construction of the millennium plan of Xiongan New Area and the gradual improvement of the integration of Beijing, Tianjin and Hebei. The author selects 5 stocks related to infrastructure construction in related area from CSI 300 to construct optimal investment stocks. After processing and analyzing the original data, the time series model is used to predict the future stock data, and the mean variance model is used to construct the investment portfolio to obtain the optimal Sharpe ratio. The final simulation result shows the superiority of portfolio construction with a high yield of 0.346 and the Sharpe ratio value is 2.473, which can provide a reasonable reference investment in enterprises in the Beijing-Tianjin-Hebei region. This paper has important reference value in data selection and optimization of time series model parameters.

The Numeric Characteristics of Chinese A-Share Market Index Volatility, Model Simulation, and Forecasting

This study investigates the basic numeric characteristics of Chinese A-share market index volatility (i.e., the clustering, heteroscedasticity, and jumps) from the perspective of data mining. It presents a theoretical-empirical model based on these three major characteristics and conducts a maximum likelihood estimation to study Chinese A-share market return data empirically. Results show that, in full-sample or special periods, this model calibrates the A-share index volatility well and simulates in-sample volatility better than the four major empirical models adopted to study volatility. In out-of-sample forecasts, this model performs better than the other four models on the value-at-risk dates, which are the volatile days. This model can also decompose and explain the volatility of the Chinese A-share index. On the basis of GARCH, this study revises the volatility model proposed by Maheu and extends Engle’s research framework. Thus, this model is of theoretical significance. This model’s simulation and forecast functioning can contribute to regulatory expectation management and investment portfolio construction.

Explaining mutual fund behavior through the structure‐conduct‐performance lens

AbstractThis paper examines mutual funds. These are economically important as the largest institutional investors, and form an important principal‐agent relationship as custodians of retirement savings. Despite a huge literature, there is no agreed explanation of mutual fund behavior. This analysis links mutual fund research across disciplines under the structure‐conduct‐performance paradigm (SCP), which is widely used in strategy research to explain firm actions and results. SCP explains mutual fund actions after placing the fund manager at the center of fund operations, where their conduct is driven by structure of markets and the funds management industry. Structural influences on fund managers include unpredictability of markets, the oligopolistic nature of the mutual fund industry, and disengagement of clients. As a result, funds derive income as commission on assets under management, which is sub‐optimal for clients. In addition, fund managers' conduct is driven by their homogeneity and socialization with competitors and investee firms. While the most obvious role of fund managers is construction of investment portfolios, outperformance is not their sole, or perhaps even principal, objective. The SCP lens offers insights into mutual funds of value to fund managers, investors, regulators and executives of investee firms. This paper impounds evidence from real‐world data in theory to offer an actor‐centric perspective of investment which is an archetypal practitioner driven discipline.

Формирование оптимального инвестиционного портфеля по комплексу эффективных портфелей

The paper presents the scheme for preliminary processing of historical records, provides the algorithm for historical sample length optimization, estimates expected returns and risks by prognostic models of optimal complexity, drawing on the principle of integrated decisions. The author offers a new method to generate efficient portfolios taking into account cross correlation links and construction of investment portfolio of optimal complexity based on the principle of integrated decisions.

Zero Lower Bound Monetary Policy’s Effect on Financial Asset’s Correlations

We investigate the hypothesis that zero lower bound monetary policy has an effect on the correlations of financial assets. Using an event-study approach, we evaluate the impact of the zero lower bound monetary policies of the Bank of Japan, the Bank of England, and the Federal Reserve on the bond and equity markets in Japan, the UK, the US, and the Eurozone. We evaluate the bond markets using the Japanese 10-year Sovereign bond (JGB), UK 10-year bond (Gilt), US 10-year Treasury note (T-note), and German 10-year bond (Bund). For the equity markets we use the Nikkei 225, FTSE 100, S&P 500, and Euro STOXX 600 as proxies for each regional market. We also include gold and silver as control commodities. Our analyses demonstrate significant changes not only in the evaluated assets’ correlations with each other, but also in their general behavior. This has major implications for investment portfolio construction and provides useful insight for financial service regulators and the central banks themselves in monitoring the fragility and stability of the financial system.

The Usefulness of Integrated Reports for Stock Market Investors

Abstract The huge risks associated with decisions made by key players in the capital market, i.e. investors, encourage them to explore any useful information. Therefore, stock market investors have an increasing interest in expenditures and achievements in all aspects of business activities of any corporation in which they may invest. Traditionally, they look for financial information, and increasingly for non-financial information as well, that all are about activities which are determined by and have implications to the natural environment, the society, and corporate governance (ESG). As a result, this information creates the image of Corporate Social Responsibility (CSR), and investors, who in the construction of investment portfolios take into account non-economic criteria, create Socially Responsible Investment (SRI) market. The aim of the paper is to highlight the need to satisfy market investors' expectations of CSR information by the companies listed on the stock exchange. Secondly, the aim of this paper is to indicate characteristics that make financial and non-financial information presented in Integrated Reports useful for stock market investors. As a result it has been confirmed that there is a need to produce business reports in which corporate approach to social responsibility is taken into account. Moreover, characteristics of non-financial information which are about their usefulness for investors in the process of decision-making have been identified and whether market regulators show an interest in integrated reporting has been established.

Manipulating Valid Correlation Matrices

Correlations play an important role in the construction of investment portfolios. In this research note, we explain why the manipulation of a valid correlation matrix is challenging. We also propose three methods to perform the following tasks: 1) Increase all correlations such that they converge to one in the limit. This method can be used to model unexpected high correlation values (for example, in a system crisis as experienced just recently). 2) Decrease correlations such that they shrink to zero or a minimum correlation. This procedure is needed to analyze hedged portfolios or, more generally formulated, absolute return strategies. 3) Change individual correlation values. Many times, analysts have a need to change an individual correlation to a certain value or in a certain direction. As we will see, this method is also a starting point to generate random correlations.

Corporate Risk Tolerance and Capital Allocation: A Practical Approach to Implementing an Exploration Risk Policy

Petroleum exploration companies are confronted regularly with the issue of allocating scarce capital among a set of available exploration projects, which are generally characterized by a high degree of financial risk and uncertainty. Commonly used methods for evaluating alternative investments consider the amount and timing of the monetary flows associated with a project and ignore the firm`s ability or willingness to assume the business risk of the project. The preference-theory approach combines the traditional means of project valuation, net present value (NPV) analysis, with a decision-science-based approach to risk management. This integrated model provides a means for exploration firms to measure and to manage the financial risks associated with petroleum exploration, consistent with the firm`s desired risk policy.

Programming Investment Portfolio Construction

Programming Investment Portfolio Construction