Long-term Investment Returns Research Articles

Behavioral Economics and Stock Market Decision-Making: Investor Biases and Investment Strategies

This study examines the application of behavioral economics to stock market decision-making, focusing on common cognitive biases of investors and their impact on investment decisions. Unlike the complete rationality assumed in traditional economics, behavioral economics reveals the irrational behaviors that investors exhibit when facing risks and uncertainties, such as overconfidence, loss aversion, and herd effect. By examining classical theories such as prospect theory, loss aversion, and the anchoring effect, as well as specific case studies such as the 2008 global financial crisis, this study aims to reveal how these psychological biases affect investors’ decision-making process. Further, this study examines how behavioral economics theories can be used to improve investment strategies by recommending methods such as low volatility investment strategies to help investors make more rational and effective investment choices in a complex market environment. Through in-depth analysis of the core theories and cases of behavioral economics, investors are better able to identify biases in the decision-making process, thereby optimizing their investment decisions and improving long-term investment returns.

A Novel Black-Litterman Model with Time-Varying Covariance for Optimal Asset Allocation of Pension Funds

The allocation of pension funds has important theoretical value and practical significance, which improves the level of pension investment income, achieves the maintenance and appreciation of pension funds, and resolves the pension payment risk caused by population aging. The asset allocation of pension funds is a long-term asset allocation problem. Thus, the long-term risk and return of the assets need to be estimated. The covariance matrix is usually adopted to measure the risk of the assets, while calculating the long-term covariance matrix is extremely difficult. Direct calculations suffer from the insufficiency of historical data, and indirect calculations accumulate short-term covariance, which suffers from the dynamic changes of the covariance matrix. Since the returns of main assets are highly autocorrelated, the covariance matrix of main asset returns is time-varying with dramatic dynamic changes, and the errors of indirect calculation cannot be ignored. In this paper, we propose a novel Black–Litterman model with time-varying covariance (TVC-BL) for the optimal asset allocation of pension funds to address the time-varying nature of asset returns and risks. Firstly, the return on assets (ROA) and the covariance of ROA are modeled by VARMA and GARCH, respectively. Secondly, the time-varying covariance estimation of ROA is obtained by introducing an effective transformation of the covariance matrix from short-term to long-term. Finally, the asset allocation decision of pension funds is achieved by the TVC-BL model. The results indicate that the proposed TVC-BL pension asset allocation model outperforms the traditional BL model. When the risk aversion coefficient is 1, 1.5, and 3, the Sharp ratio of pension asset allocation through the TVC-BL pension asset allocation model is 13.0%, 10.5%, and 12.8% higher than that of the traditional BL model. It helps to improve the long-term investment returns of pension funds, realize the preservation and appreciation of pension funds, and resolve the pension payment risks caused by the aging of the population.

Financing for a Sustainable Dry Bulk Shipping Industry: What Are the Potential Routes for Financial Innovation in Sustainability and Alternative Energy in the Dry Bulk Shipping Industry?

Environmental, regulatory, and economic exogenous disruptions force companies within the maritime shipping industry to become more sustainable. Financing for implementing the necessary changes is particularly challenging for these companies, considering their narrow margins. With the changes in the shipping industry being intrinsically capital-intensive, funding is a particular issue, as few institutional or individual investors can provide the capital required. This paper investigates the challenges of financing. Drawing from the theory of pecking order on debt and equity, it conceptualizes the relation between the modes of financing for the maritime shipping companies and the nature of the disruptions. Initially, we analyze the various IMO decarbonization regulations, GHG emissions, alternative fuels, and green energy. Moreover, the relationship between fleet operation and management and finance is explored. The paper provides a framework to illustrate from a financial perspective the plethora of challenges and disruptions that have troubled the industry. We then recommend more suitable funding routes for companies to gauge the proper mix of equity and debt levels, bonds, and leverage, based on the company’s characteristics, such as size or ESG performance, as analyzed via the lens of corporate financing, along with the nature of the disruption, such as high inflation or geopolitical conflicts. In more detail, the paper focuses on key environmental, social, and governance (ESG) drivers both in the short-term and the long-term within the dry bulk shipping industry: impact investing and ESG factors are driving new investment opportunities and contributing to risk mitigation and long-term investment returns. The most pressing financial and economic questions of the time are wildly extended equity and bond valuations, inflation, and the conundrum most central banks face. Given these uncertainties, from an investment perspective for equity markets, the risk/return outlook for risk assets is skewed to the downside, making a cautious approach prudent for maritime shipping companies.

Long-Term Investing and the Frequency of Investment Decisions

This article analyzes the impact of the frequency of investment decisions on long-term investment results. Long-term investment returns are shown to be a nonlinear function of skill, transaction costs, volatility, and frequency. The author uses compound returns to show the minimum skill level that is required to result in a positive expected return after costs and shows the skill level required to outperform the buy-and-hold investor. These can be high for markets that have high transaction costs per unit of volatility. The optimum frequency of investment decisions is derived as that frequency that maximizes the expected terminal value of wealth. Empirical estimates from the US equity and fixed-income markets show that this optimum frequency is considerably different between these markets, even when the investor has an equal amount of skill in each. The author also shows how long-horizon value-at-risk varies with the frequency of investment decision-making. <b>TOPICS:</b>Wealth management, equity portfolio management, fixed-income portfolio management, risk management, portfolio construction, performance measurement <b>Key Findings</b> ▪ The author derives the success rate that is required to result in a positive expected return after cost and applies it to directional strategies in the US equity and fixed-income markets. For fixed income, the investor requires a success rate of more than 51%, regardless of the frequency of those decisions. For directional strategies in the US equity market, this minimum success rate varies more with frequency, but it is higher than 53%. ▪ The optimum frequency of investment decisions is derived as that frequency that maximizes expected terminal wealth. The article shows that this frequency is equal to skill times volatility over costs, squared. Because neither of these parameters is likely to be constant through time, the optimum frequency of investment decision-making is also likely to change through time, which has important implications for how an investment process is to be structured. Empirical estimates show very different results for different markets. ▪ Even for highly skilled investment processes, downside risk is meaningful when frequency is low. Downside risks are meaningfully lower only for high-skill investment processes at high frequency. This is an important consideration for investors who place high importance on downside risks at long investment horizons.

Incorporating simulated annealing algorithm in the Weibull distribution for valuation of investment return of Malaysian property development sector

In this study, a simulated annealing algorithm(SAA) has been incorporated in the Weibull Distribution (WD) for Valuation of Investment Return. The purpose is to examine the behaviour of investment's attractiveness in the Malaysian property development sector (MPDS) for a long-term investment period. The research intends is to produce parameters estimates of the WD using MIRR data extracted from the financial report of MPDS for 5 years investment period. The shape parameter of the WD reflects the effectiveness in maximizing the investment performance on MPDS with lower returns and is represented as the slope of the fitted line on a Weibull probability plot. The estimated results obtained using the Simulated annealing algorithm (SAA) has been compared with Differential Evolution (DE) and other existing estimation methods in terms of root mean square error (R-MSE) and coefficient of determination (R-Square). The findings revealed that Weibull distribution parameters estimated via Simulated annealing algorithm have good agreement with parameters estimated via Differential Evolution (DE) and other existing methods based on the transformed MIRR data from the MPDS. The study is expected to provide an overview of the investment behaviour for the long-term investment return in the MPDS. Therefore, SAA in estimating the WD parameters can serve as a good alternative approach for the assessment of the investment potential using MIRR data. The study will be extended to accommodate the growth rate arising from the financial data such as investment growth and insurance claim data.

RECEPTIVENESS OF GOLD ACCUMULATION PROGRAM IN MALAYSIA: AN EMPIRICAL INVESTIGATION

Gold is credence as an essence of deluxe and wealth in the sight of humankind. History has witnessed that gold is one of the best high long-term investment returns. In Malaysia's context, gold investments are broken down into three (3) offerings. These include physical gold investments, gold investment accounts or gold savings accounts and blockchains for improved financial returns of the prospective gold investors or gold investors itself. Public Gold strengthens the emerging popularity of gold investment accounts in Malaysia through the offering of Gold Accumulation Program (GAP) as one of the gold investment account platforms for investors to diversify their investments. Through this facility, investors are hassle-free to invest and keep their gold with Shariah-based products. However, to what extent do people in East Malaysia are willing to perform in Gold Accumulation Program? It remains unexplored in the body of knowledge that warrants the undertaking of the current study to void the gap. This topic is of utmost importance. The significance of investing in Gold Accumulation Program (GAP) can solve the issues of Muslim investors. They are previously might be investing in forbidden forms of gold investments, which are non-Shariah compliant outlets. By all means, the current study examines the receptiveness of retail investors in performing the GAP in East Malaysia, where some deliberations of critical factors are brought into play.

Real liquidity and banking

In an economy where banks take numeraire goods, so called money, as deposits, money allows depositors suffering preference shocks to withdraw from banks prematurely without liquidation of real investment. If real liquidity, defined as the real value of the monetary base, is low, the amount of payment liquidity, constrained by the velocity of money, limits the short-term price level of investment goods before banks can settle their long-term loan contracts. This leads to an attractive nominal long-term investment return and over-investment. Allowing for inside money, that is, bank deposits, to be used for payment can improve social welfare but cannot fully resolve the liquidity shortage problem as the short-term interest rate offered by banks is constrained by the threat of bank runs. In the presence of systemic liquidity shocks, the price-adjustment mechanism cannot take full effects with insufficient payment liquidity, which can lead to non-zero profits for banks. Exchanging investment goods for numeraire goods through international trade can improve social welfare.

Aggregate risk and efficiency of mutual funds

Abstract This paper studies the welfare properties of mutual funds in a Diamond–Dybvig economy with two sources of aggregate risk: (i) shocks to long-term investment returns; and (ii) shocks to aggregate liquidity demand. Mutual funds are inefficient when the long-term investment is risky. Mutual funds improve upon autarky by introducing a wedge between the market and technological rates of return. However, the wedge distorts the decisions of consumers not facing liquidity shocks, and the resulting equilibrium is inefficient. If only aggregate liquidity demand is subject to shocks, mutual funds can implement the social optimum (even when liquidity demand is not directly observable) by means of a price-contingent dividend policy.

The ETF 'Fee War'

Despite widely publicized fee reductions, we find that average ETF expense ratios have remained relatively steady during the last 15 years. Even though thousands of new funds have entered the market, the arrival of most ETF sponsors into a narrowly defined area does not generally lead to lower fees for competing funds. Given the impact of fees on long-term investment returns, investors should examine all of the available opportunities before choosing specific funds. Furthermore, as objectives for newer ETFs become increasingly specialized, investors must also carefully consider whether the benefits of targeted strategies justify their higher prices.

中国蓝筹股的长期股权投资回报

中国蓝筹股的长期股权投资回报

Research on the Renewable Energy Industry Financing Efficiency Assessment and Mode Selection

In recent years, environmental issues are attracting widespread attention by various countries around the world. In this context, the renewable energy industry has become a stimulus point for economic development and has great potential for development. Renewable energy industry financing is difficult due to its characteristics of high risk and long-term investment returns, and relying on existing financing channels make it present a glut of excess capacity. It is key to realize resource optimal allocation, solve overcapacity phenomenon and select the valid financing mode. This paper used Bloomberg New Energy Finance (BNEF) data and the data envelopment analysis (DEA) method to analyze the financing efficiency different parts of the global renewable energy industry and different ways of financing. It could be found that although the financing efficiency showed a trend of increasing year by year, the financing efficiency of each industry presented generally weak DEA efficiency, the comprehensive financing efficiency of wind power industry was higher. The article also found that the financing efficiency of project financing and Research and Development (R&amp;D) were relatively high, and the equity market and venture capital and private equity were less efficient. The results of this paper play an important role in the overall financing status cognizance of the renewable energy industry and give suggestions about valid financing mode choice.

Long-Term Sources of Investment Returns and a Simple Way to Enhance Equity Returns

Investment return from equities is comprised of four components: dividend yield, inflation, real growth in business value, and change in valuation multiples. However, we show that over the long-term investment return from equities is derived primarily from underlying growth in business values. We propose that an investment process that successfully identifies businesses with the ability to grow business value at above average rates, will result in superior investment returns.

The promotion of domestic grid-connected photovoltaic electricity production through social learning

An effective social learning process which enhances public understanding of photovoltaic installations in residential dwellings and the economic instruments used by governments to encourage investment in this form of energy is regarded as an important component of implementing renewable energy policy in Australia. The development of social learning was explored in deliberative workshops conducted in 2005 and 2012 in New South Wales, Australia. Participants had informed discussion of the operation of photovoltaic panels and how such panels could be integrated into domestic building structure and the economic instruments used by their State and Federal governments to encourage the installation of grid-connected photovoltaic systems. Their attitudes to the technology and investment were surveyed at the end of the workshops. The participants expressed favourable attitudes toward the design, reliability and environmental benefits of such technology and positive attitudes towards the building integration of such panels. However, despite this, the participants were unwilling to invest in this technology, primarily because in 2005 they perceived the financial benefits of doing so as being marginal and in 2012 they were framing investment decisions in terms of reductions in tariff rates since 2010 rather than current returns. Social learning principles can provide a range of benefits for communication and decision making in the informed promotion of grid-connected photovoltaic technology. Public perceptions and citizens’ investment decisions should move beyond framing decisions relative to subsidy levels to consider long-term investment returns. Retailers and installers of residential photovoltaic systems in Australia are encouraged to promote the option of building-integrated panels given favourable preferences shown for such technology.

How Well Do Stock Prices Reflect Intrinsic Values?

A legendary fund manager champions the importance of low-cost, diversified portfolios, with dividend yields and earnings growth as the key sources of long-term investment returns. The ownership of mutual fund management companies by financial conglomerates creates an agency conflict that does not serve the interests of shareholders. The growing proliferation of investment “products” is one example of the incentives that drive fund managers to increase assets under management, revenues, and profits as well as to keep management fees and fund expenses at the highest possible levels.

Advancing Strategic Asset Allocation in aMulti-Factor World

Strategic asset allocation is arguably one of the most important, yet least advanced, aspects of investing. The authors present a new approach to strategic asset allocation that leverages the idea that long-term investment returns derive from multiple distinct sources that they call “return-generating factors.” Their approach addresses four key shortcomings of traditional approaches: First, their multi-factor model helps better understand the important sources of return in today’s complex investment universe, generating a substantial increase in estimation precision across asset classes and providing investors with a new way to think about portfolio diversification. Second, their robust portfolio optimization methodology seeks to explicitly account for the uncertainties inherent in the estimates of expected returns, delivering well-diversified portfolios with superior risk?return characteristics. Third, the factor-based risk analytics better capture the true characteristics of asset returns, such as fat tails and increased correlations at times of crises, allowing the authors to more-accurately model the downside risks of portfolios. Finally, the factor-based simulation technique accounts for the impact of different economic conditions (e.g., low interest rates) on future portfolio returns, resulting in more-precise, forward-looking projections.

The Norwegian Government Pension Fund: Ethics Over Efficiency

The Norwegian Government Pension Fund Global has an explicit mission to integrate long-term investment return objectives with an ambitious ethical commitment. This approach has drawn praise among Western policymakers. However, we contend that the ethical investment policy of the Norwegian Government Pension Fund Global presents a paradox, as the manner in which the country applies its ethical criteria to investment management transgresses best practice as we define it. As a result, we believe that Norway has chosen to discount functional efficiency in favor of exerting a “fundamental social perspective”. This may have unfavorable consequences in the long run. Nonetheless, we recognize the current approach is the source of the public and political legitimacy the Fund enjoys today.

Modelling long-term investment returns via Bayesian infinite mixture time series models

This paper introduces the class of Bayesian infinite mixture time series models first proposed in Lau & So (2004) for modelling long-term investment returns. It is a flexible class of time series models and provides a flexible way to incorporate full information contained in all autoregressive components with various orders by utilizing the idea of Bayesian averaging or mixing. We adopt a Bayesian sampling scheme based on a weighted Chinese restaurant process for generating partitions of investment returns to estimate the Bayesian infinite mixture time series models. Instead of using the point estimates, as in the classical or non-Bayesian approach, the estimation in this paper is performed by the full Bayesian approach, utilizing the idea of Bayesian averaging to incorporate all information contained in the posterior distributions of the random parameters. This provides a natural way to incorporate model risk or uncertainty. The proposed models can also be used to perform clustering of investment returns and detect outliers of returns. We employ the monthly data from the Toronto Stock Exchange 300 (TSE 300) indices to illustrate the implementation of our models and compare the simulated results from the estimated models with the empirical characteristics of the TSE 300 data. We apply the Bayesian predictive distribution of the logarithmic returns obtained by the Bayesian averaging or mixing to evaluate the quantile-based and conditional tail expectation risk measures for segregated fund contracts via stochastic simulation. We compare the risk measures evaluated from our models with those from some well-known and important models in the literature, and highlight some features that can be obtained from our models.

The Importance of Asset Allocation

A commonly held view is that the normal long-term allocation to stocks, bonds, and cash is of “overwhelming” importance in determining long-term investment returns. This view understates the importance of factors such as cost, market timing, and security selection in determining investment outcomes. The author demonstrates this point by examining the return implications of a set of scenarios representing choices and circumstances found in the real world of investing.

Safeguarding Your Retirement Fund

the continuing wild gyrations of interest rates, which cause swings in bond prices, are evidence of a higher level of instability. Given the current environment, faculty members should consider becoming more involved in the oversight of their personal retirement funds. The rate of long-term investment return on such funds can have a significant impact on future financial security and the resulting quality of life for faculty members in retirement. Some individuals are quick to point out that TIAA-CREF has served them well in the past and they see no need to become personally involved in the complex world of investments. However, TIAA-CREF has itself responded to the new environment in which we find our-

The Dimensions of Analysis: A Critical Review

THE process of selecting individual securities, and particularly common stocks, for investment portfolios has several dimensions. But while the basic structure of the portfolio selection process is fairly well established, considerable controversy seems to exist as to the means by which these dimensions should be implemented. It is our purpose to review critically a few major areas of conflict currently extant in investment analysis. Hopefully, this might enable practicing analysts to identify more clearly the issues involved and the possible implications of the alternative points of view. For example, it is generally agreed that the process should be oriented to and conditioned by specific portfolio objectives, such as growth, income requirements, quality limitations, and diversification targets. But as these matters are essentially in the domain of overall portfolio strategy rather than security analysis per se, they are regarded as outside the scope of this review. However, it might be noted that considerable controversy currently exists in this area as to the usefulness of computer programs to suggest and delineate the characteristics of efficient or optimum portfolios. It is my tentative opinion that existing models for portfolio structures are likely to be of very limited practical use as they seem to involve some highly questionable assumptions in order to obtain required quantifications, such as that the entire spectrum of risk factors can be adequately measured by the relative price volatility of individual issues. A second crucial dimension of security selection is concerned with appraising the potential economic values (primarily prospective earnings and dividend flows and the risks surrounding their achievement) embodied in the industries and related companies that appear eligible to meet the portfolio requirements. The content of most of the literature, as well as of our series of C.F.A. examinations, suggests that mastery of this broad area is considered to be of prime importance to the professional development of financial analysts and portfolio managers. And rightly so. For while the random walk theory of security prices may be convincing with respect to the problem of obtaining short-term trading results, this theory does not conflict with the proposition that long-term investment returns will largely be a function of the long-term economic performance of particular industries and companies. Although the concept that investment results are likely to be heavily related to corporate performance in a long-term sense is generally accepted, some recent contributions to the field have alleged that the implementation methodology should be completely revolutionized. For example, Lerner and Carleton allege that a critical investigation of the past financial statements to reveal potential problems of consistency and comparability of reported income and balance sheet data can be largely discarded because accounting and disclosure standards have improved to the point where the underlying data require no critical review.' Moreover, they allege that financial risk factors no longer require appraisal because of the greatly improved stability features of the economy; in lieu thereof, they suggest elegant mathematical techniques to develop the theoretical effects of assumed patterns of various management decisions and economic data on security values.2 However, the empirical evidence would suggest that these allegations are seriously in error. Largely because of recurrent tinkering with the tax rules for national economic policy reasons, a strong case can be