Capital Allocation Research Articles

Multiagent-based deep reinforcement learning framework for multi-asset adaptive trading and portfolio management

The highly dynamic nature of stock markets has motivated researchers to propose various supervised learning models to assist investors to optimize financial performance. Machine learning models have been used to predict price trends, and approaches have been proposed for portfolio management. However, these studies focus on only one kind of financial issue, and the methods proposed exhibit poor generalizability. We address these problems with a multi-agent portfolio adaptive trading framework based on reinforcement learning to create an automated trading system with the best trading strategy that can be achieved by long-short situation judgment and adaptive capital allocation. We use the TD3 algorithm in the multi-agent algorithm to mitigate the overestimation and overfitting exhibited by traditional value functions and improve training stability. Experimental results show that the proposed framework outperforms single-agent reinforcement learning algorithms while achieving more stable returns.

Does Digital Inclusive Finance Help County Level Governance in the Five Provinces of Northwest China, from the Perspective of Economic Resilience?

The sustainable development of a country requires stable funds to reshape and restore its economy, something which cannot be separated from the support of financial services. Digital financial inclusion, with its inclusive and extensive features, has provided a new impetus for economic development and governance. Based on the panel data of 193 counties in 5 provinces of northwest China from 2014 to 2021, this paper uses a bi-directional fixed effect model, an intermediary effect model and a threshold effect model in order to test digital inclusive finance and county-level economic resilience, and to explore the internal correlation details. The results show that digital inclusive finance will significantly enhance the economic resilience of the five northwestern provinces by improving capital allocation efficiency, enhancing entrepreneurship and employment vitality, and reducing pollution emissions. In addition, there is a double threshold effect between capital allocation efficiency and employment vitality, in which the threshold effect of capital allocation efficiency presents a progressively increasing state, and in which the threshold effect of entrepreneurship and employment vitality presents a state of fluctuating increase. Therefore, China needs to further improve the digital inclusive financial environment in its northwest; continue and deepen the significant functions of digital inclusive finance in resource allocation efficiency, entrepreneurship and employment vitality, and environmental protection; and provide guidance for solving regional imbalances and promoting national sustainable development.

Volatility Spillover Benefits of the Hang Seng Index and Shanghai Composite Index: A Vector Autoregressive (VAR) Model and Granger Causality Test Analysis

This study aims to explore the volatility spillover benefits between two major stock markets in Hong Kong and Shanghai, namely the Hang Seng Index and the Shanghai Composite Index. Empirical analysis is conducted using a Vector Autoregressive (VAR) model and Granger causality test based on daily return data from 2013 to 2023. The research finds a significant volatility interaction between the Hang Seng Index and the Shanghai Composite Index, which is more pronounced during periods of global economic instability. Impulse response analysis reveals that positive shocks in Hang Seng Index lead to increased volatility in the short term for the Shanghai Composite Index but gradually weaken to a weak negative effect in the long term. Conversely, positive shocks in the Shanghai Composite Index have a short-term inhibitory effect on the Hang Seng Index but transform into a weak promoting effect in the long term. These findings have important implications for investors and policymakers in risk management, forecasting future stock market trends, and capital allocation.

Financial Development and the Capital Flow Allocation Puzzle in Developing Asia

ABSTRACT Using a panel regression approach across 13 developing Asian economies from 1996Q1 to 2019Q4, this paper examines the extent of financial development as a transmission channel for mediating the “allocation puzzle” in capital flows. This puzzle pertains to why capital seems to flow to economies with lower rather than higher productivity growth. We find that while portfolio equity and debt investment flows are negatively related to total factor productivity (TFP) in developing Asia, thereby contradicting the predictions of traditional neoclassical growth models, financial development significantly mitigates this effect. This is particularly the case at earlier stages of financial development and convergence towards a frontier. For foreign direct investment, although we find that there is no direct allocation puzzle in developing Asia, financial development can hamper the stimulatory effect of TFP for highly financially developed economies given diminishing marginal returns.

Public sector and human capital: on the mechanics of economic development

This paper proposes a theory about the allocation of human capital along the development process that helps to understand the controversial impact of this variable in growth regressions. We build a model in which human capital is allocated to three activities: production, tax collection (bureaucracy), and public education. At the first stage of development, countries have low effective tax rates because tax collection requires human capital, which is scarce. As countries accumulate human capital throughout the transition, the effective tax rate rises, diverting human capital from production to bureaucracy and public education. Consequently, at this stage, human capital has a weak impact on production, even when the human capital allocation is efficient. Furthermore, disparities in institutional quality may diminish the correlation between human capital and GDP.

Pengaruh ESG terhadap Kinerja Perusahaan: Moderasi Board Gender Diversity

Company performance is a metric in assessing the level of success of a company in a certain period. to maintain good company performance, companies need to manage core business, namely building good relationships with stakeholders. For investors as stakeholders, the availability of information presented by the company is very important to decide on the right capital allocation and avoid the risks that occur. With the encouragement from the government and investors as stakeholders, more and more companies want to provide a clear picture of corporate practices and responsibilities, one of which is by disclosing environmental, social and corporate governance (ESG) aspects. The purpose of this study to provide empirical evidence regarding the influence of ESG on company performance, provide empirical evidence regarding the role of board gender diversity on the influence of ESG on the performance of companies listed on the Stock Exchange in Indonesia and Germany in 2018-2022. The sampling technique in this study was purposive sampling. Data was taken from Thomsonreuters and this study used panel data regression analysis with STATA 17. The results of this study found that ESG has no effect on company performance in Indonesia. The results of further research found that ESG has a negative effect on company performance in Germany. This study found that board gender diversity plays a role in encouraging ESG activities to improve firm performance in Germany.

A BRIEF STUDY ON STOCK MARKET

The Indian stock market has undergone a remarkable transformation over its century-long history, emerging as a dynamic and sophisticated financial ecosystem that plays a pivotal role in driving the nation's economic growth. With securities traded on prominent exchanges like the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE), the market serves as a vital platform for capital allocation and investment. Regulated by the Securities and Exchange Board of India (SEBI), it exhibits inclusivity, welcoming a diverse spectrum of participants, from retail investors to institutional funds. Despite facing challenges such as volatility and regulatory compliance, the Indian stock market remains resilient, offering ample opportunities for wealth creation and economic development. Through a comprehensive exploration of its historical evolution, regulatory framework, market participants, and performance metrics, this report aims to provide valuable insights for investors and stakeholders, shedding light on emerging trends and opportunities in the Indian financial landscape.

Singapore’s Temasek Model and State Asset Management in China

Since the late 1970s, Singapore has been an important policy reference for China. Some Chinese policymakers viewed Temasek, its government holding company, as a model for state asset management. They studied Singapore’s approach, but ultimately chose a different institutional design when establishing the State-Owned Assets Supervision and Administration Commission (SASAC) in 2003. China’s engagement with Temasek subsequently concentrated on corporate governance, specifically boards of directors in state-owned enterprises (SOEs). Yet despite the Temasek model’s appeal, its influence in China was limited by the far greater size and indebtedness of the state sector; the weaker role of firm performance in asset and capital allocation; SOEs’ numerous social and welfare functions; lack of willingness to augment firm autonomy; and divergent interpretations of the Temasek model and its reference value. “Policy collage” by Chinese policymakers explains the existence of formal similarities between China and advanced capitalist economies without fundamental convergence in function.

Impact of green finance on carbon emissions and spatial spillover effects: Empirical evidence from China

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance.

Financial constraints of ASEAN firms: Impact alleviation by ESG pillars

The purpose of this study is to examine whether ESG plays a positive moderating role in the negative relationship between financial constraint, the Kaplan-Zingales (KZ) and Whited and Wu (WW) indexes, and firm performance: Return of Asset (ROA) and Return of Equity (ROE). This study uses information from the Thomas Refinitiv database, which covers the Association of Southeast Asian Nations (ASEAN-5): Indonesia, Malaysia, Singapore, Thailand, and the Philippines non-financial firms from 2011 to 2019. Fixed-effects (FE) are used as the baseline model, and random-effects (RE) act as the robustness of methods. The results show that the main effect of financial constraints is to act as an obstacle to firm performance. However, the marginal effects of financial constraints can be improved in the presence of ESG. Firms with a high ESG score are better at alleviating the adverse impact of financial constraints as compared to those with a low ESG score. When the ESG score is further broken down into three sub-pillar dimensions, the S-score is of the greatest magnitude in its moderating role in the ESG breakdown. The findings have important implications: effective financial support and the source of funding from the government are crucial to supporting firm performance. ESG-compliant strategies should also be formulated to encourage ESG disclosure, which leads to increased capital allocation efficiency. The firms should be stringent on S-score, which helps drive the company as employees respond by giving their best. Governments and firms need to deploy ESG guidelines in order to succeed in thriving competitive firm performances.

The Tail Mean–Variance optimal capital allocation under the extended skew-elliptical distribution

In this paper we introduce a novel Tail Mean-Variance (TMV) model intended to optimize capital allocation in financial decision-making. The TMV model has many intriguing properties, such as considering the variability and tail risk of the loss function simultaneously. We specifically consider the multivariate extended skew-elliptical (ESE) distributions, which are widely applicable in financial and insurance data modeling. Additionally, we explore the probabilistic properties of the multivariate extended skew-elliptical (ESE) distributions and present explicit formulas for the TMV model within this distribution. Finally, a numerical example is provided to illustrate the results.

A Case Study Examining the Effects of Corporate Social Responsibility on the Financial Performance of Iraqi Commercial Banks

The study examines the relationship between corporate social responsibility (CSR) and financial performance in leading Iraqi banks. Data was collected from company websites and reports, and regression analysis was used to examine the relationship between variables. The findings suggest that banks should evaluate their CSR strategies, align with corporate values and societal needs, and consider sustainability and long-term impact. Collaboration among banks and stakeholders can lead to more impactful initiatives. Stabilizing net profits through operational efficiency improvement, risk management, and new revenue streams is crucial for sustained profitability. Strategies to enhance profitability include diversifying revenue streams, optimizing capital allocation, and optimizing operational efficiency.

IPO suspensions and labor employment decisions: Evidence from China

The Chinese regulator occasionally suspends all initial public offerings (IPOs) to maintain stability in the capital markets and facilitate capital market reform. These suspensions temporarily prevent firms that have obtained IPO approval from going public. We hypothesize that this suspension-induced listing delay influences firms’ labor employment decisions. Consistent with this argument, we find that a suspension-induced listing delay is associated with an increase in labor costs, both in terms of total and average employee payments. This positive relationship is more pronounced for human capital-intensive firms and non-state-owned enterprises. We also find that there is an increase in employment and employee turnover for firms facing suspension-induced listing delays. Moreover, IPO suspensions result in lower labor productivity and firm performance. Overall, our results indicate that government policy uncertainty leads firms to incur high labor costs and reduces capital allocation efficiency.

Research on the Optimal Strategy of Investment Portfolio Based on Markowitz Model

Nowadays, investment is becoming increasingly common. Under the globalization of the economy, investors are given more investment opportunities and choices. Investors need to select excellent assets and allocate the selected asset portfolio on weight during the investment process. The mean-variance model proposed by Markowitz plays an important guiding role in investment and risk management. This model can effectively evaluate investors portfolio risk and return decisions and significantly impact their decision-making choices. This study uses the data of the annual average return and variance from 11 risky assets and 1 risk-free asset in about 20 years to construct an investment portfolio in a fixed group based on the Markowitz Model. The study calculates the changes in the allocation of the maximum Sharpe ratio and the minimum variance portfolios under three different constraints and one condition with the addition of risk-free assets, respectively, and then analyzes changes in the outcome of data. The capital allocation lines are introduced to analyze the outcome of an investment portfolio with risk-free assets. Compared with the changes from three constraints, reasons are explained why these changes happen under three constraints. Then, the above limitations are taken as a premise, and the study proposes recommendations for the optimal investment portfolio selection for different investors according to the investment cycle, the preference of investors based on the situation of different investors, and market constraints. The study guides investors future investment decisions.

Can public data availability affect stock price crash risk? Evidence from China

In the era of the digital economy, data has emerged as a critical factor of production. The exploration of methods to unlock the economic value inherent in the vast reservoirs of public data held by the government has now begun to draw the attention of scholars. However, little research has considered this issue from the perspective of financial market stability. Leveraging the staggered establishment of public data open platforms (PDOPs) across different cities of China and employing the staggered difference-in-differences (DID) model, we find that the establishment of PDOPs significantly decrease local firms' stock price crash risk (SPCR). Our results remain valid after various robustness tests, such as placebo tests, entropy balancing analysis, alternative measures of SPCR, as well as alternative difference-in-differences (DID) estimators. Furthermore, additional evidence suggests that the observed effects are driven by two mechanisms: improved operating performance and enhanced external monitoring. The former mechanism reduces the generation of bad news within firms, while the latter restricts managers' ability to hoard bad news. Further research findings show that the motivation of management to withhold bad news and the nature of firms' property rights are important factors affecting the relationship between public data availability and SPCR. Overall, our findings suggest that government can help improve capital market resource allocation efficiency by supplying public data to market participants.

Uncertainty and international fund flows: A cross-country analysis

This paper investigates the impacts of uncertainty on international portfolio allocation decisions and returns across 27 countries. Using panel structural vector autoregressive analysis, a positive link between both country-level and global uncertainty with equity fund flows is uncovered, highlighting the role of investor sentiment in capital allocation decisions. Findings also support the portfolio rebalancing theory, revealing the negative influence of past returns on fund flows. Results show that the VIX demonstrates a positive association with fund flows, particularly during periods of elevated global uncertainty. Moreover, this research analyzes differences between developed and emerging markets in their sensitivity to uncertainty shocks.

Dynamic capital allocation with reallocation cost

Traditional static capital allocation incurs significant reallocation costs over periods due to drastic fluctuations. We propose a new framework for dynamic capital allocation with time-varying capital constraints that incorporates reallocation costs. We obtain an analytical solution in a recursive form and demonstrate its admirable performance through simulations. The solution compromises between static allocation and expected future risk structure and strikes a balance between addressing current risk profiles and adjustment costs. It successfully provides an effective allocation tool while preserving stability.

Analysis and Reflection on Investment Status of Innovative Drugs in China

At present, China's innovative drug support policies and market volume are good, but China's innovative drug research and development(R&D) success rate and market share still need to be improved. This is related to the unreasonable investment direction of innovative drugs and the low utilization efficiency of R&D resources. Therefore, the objective of this paper is to evaluate China's present state of investment in innovation drugs and explore how to promote the effectiveness and sustainability of innovative drug investment. Through data analysis, this paper found that the scale and frequency of investment and financing of innovative drugs in China are declining. The problem with China's innovative drug investment is that the valuation of hot projects is too high, the allocation of funds is unreasonable, the investment is not in line with the actual needs of the industry, and only the pursuit of short-term returns. Given the various problems in China's innovative drug investment, the government needs to create a long-term stable environment for the innovative drug investment market and prudently formulate relevant policies to strike a balance between stimulating the market and regulating the market. Entrepreneurs should choose the direction of R&D according to their areas of expertise combined with cutting-edge scientific research progress rather than adjusting the direction of R&D to cater to the preferences of investment institutions. Investment institutions should avoid risks caused by unreasonable capital allocation by strengthening the layout of the pre-investment track and prudently carrying out project valuation analysis.

Oil price uncertainty and excess value of diversification

PurposeThis study examines the value implications of oil price uncertainty for investors in diversified firms using a sample of 922 USA firms from 2001 to 2019.Design/methodology/approachOur study employs a panel dataset to examine the value implications of oil price uncertainty for diversified firm investors. We consider several alternative specifications to account for unobserved factors and measurement errors that could potentially bias our results. In particular, we use alternative measures of the excess value of diversified firms and oil price uncertainty, additional control variables, fixed-effects models, the Oster test, impact threshold for confounding variable (ITCV) analysis, two-stage least square instrumental variable (2SLS-IV) analysis and the system-GMM model.FindingsWe find that the excess value of diversified firms, relative to a benchmark portfolio of single-segment firms, increases with high oil price uncertainty. The impact of oil price uncertainty is asymmetric, as corporate diversification is value-increasing for diversified firm investors only when the volatility is due to positive oil price changes and amidst supply-driven oil price shocks. The excess value increases irrespective of diversified firms’ financial constraints and oil usage. Diversified firms become conservative in their internal capital allocations with high oil price uncertainty. Such conservatism is value-increasing for diversified firm investors, as it supports higher performance in response to oil price uncertainty.Originality/valueOur study has three important implications: first, they are relevant to investors in understanding the portfolio value implications of oil price uncertainty. Second, they are helpful for firm managers while comprehending the value-relevant implications of internal capital allocations. Finally, our findings are policy relevant in the context of the future of diversified firms in developed markets.

Capital Allocation Analysis based on Markowitz Model and Index Model

In finance, the question of how best to invest money to make more money is not an easy one. Some academics and hands-on practitioners have studied into this field for decades. This article delves into this issue, with a special focus on a detailed analysis of various investment plans. To get a better idea of which plan is better in a given situation, this paper dug through a bunch of data that included ten different company stocks from various industries, as well as daily revenue data for the S&P 500 over a 20-year history. This paper mainly looked at two key investment plans: the Markowitz model and the Index model. This paper did some simple math and theoretical research, and then this paper used the capabilities of Excel to help us find the best solution. And the analysis specially adopted a monthly summary method, minimized the complexity of the data on a horizon. And the study critically evaluating investment strategies within real-world constraints such as Regulation T, arbitrary "box" constraints, and scenarios involving no short positions or exclusion of broad indices.The finding shows that the performance of the assets chosen by Markowitz is better than Index Model under the given circumstances, which indicates the more complex model and addition data could probably provide a better result. This dissertation aims to contribute significantly to the field of finance by enhancing the understanding of portfolio management strategies, thus aiding in informed decision-making in the ever-evolving financial landscape.