Investment Portfolio Research Articles

The pension system of Kazakhstan: savings analysis, review of investment portfolio and prospects for profitability increase

The article considers the pension system of the Republic of Kazakhstan as the most important element of the system of social protection of the population and a major investment player in the market, which is responsible for the safety of pension savings of the population. Consequently, it is necessary to constantly monitor the quality of pension provision and financial sustainability of the pension system in order to ensure the adequacy of pension payments to maintain a decent standard of living for pensioners, taking into account the inflation rate in the country. Thus, it is necessary to carefully assess the possible consequences of investment decisions in order to prevent the depreciation of pension system participants' savings. The pension system is an important element for ensuring the stability of the country's population. It forms the foundation of social security for citizens, creating financial security for them during the period of disability or retirement. Due to demographic changes in the country, the pension system is being reformed, which in turn affects financial stability in the Republic of Kazakhstan. The article presents a number of key roles and functions within the pension system, analyzes the volume of pension savings and the number of individual pension accounts in the cities of national importance, presents the structure of the investment portfolio of the PAs of the Unified Accumulative Pension Fund (UAPF), which are under the trust management of the NBRK, in the context of financial instruments. Proposals on how to increase investment income have been developed.

Cross-Market Volatility Dynamics Among Crude Oil and South Asian Emerging Markets During the COVID-19 Pandemic.

The COVID-19 pandemic had profound impacts on the global economy, initially triggering a severe economic downturn due to widespread lockdowns, this outbreak generated various economic shocks, a major one being the oil price crash. A brief understanding of how this pandemic is affecting the financial markets, empirical analysis is done on three financial markets. Three stock exchange markets are selected from emerging markets in South Asia (Pakistan, China, and India). The world crude oil market is selected as a reference, to how it transmits volatility to South Asian markets during the COVID-19 period. We employ a bivariate BEKK-GARCH model for analyzing the volatility spillover from November 19, 2019, to March 31, 2021. All markets show negative coefficients with the oil market, indicating that the previous day’s shocks in oil prices reduce today's stock market volatility, with significant values for India and Pakistan. China has a negative coefficient while the rest of the two markets show a positive and significant coefficient means past volatilities in the stock market decrease today’s oil market volatility, likely indicating a reactive or adaptive market behavior to stock volatility. Generally, oil price changes have a significant impact on these markets, with both immediate effects (via ARCH terms) and persistent effects (via GARCH terms). The study's findings offer valuable insights for policymakers, as they help identify the direction of spillovers among interconnected economies. Additionally, portfolio investors can use this information to effectively allocate weights to different asset classes when making investment decisions.

Hedging political risk in international portfolios

We show that internationally diversified portfolios carry sizeable political risk premia and expose investors to tail risk. We obtain political efficient frontiers with and without hedging political risk using a portfolio selection model for skewed distributions and develop a new asymptotic inference test to compare portfolio performance. Politically hedged portfolios outperform a broad market index and the equally weighted portfolio for US, Eurozone, and Japanese investors. Political risk hedging is not subsumed by currency hedging, and the diversification gains of politically hedged portfolios persist under currency hedging and transaction cost frictions. Hedging political risk induces equity home bias but does not fully explain the puzzle.

Portfolio optimization by enhanced LinUCB

We study portfolio optimization through reinforcement learning, employing the contextual LinUCB approach to build an investment portfolio with changing market conditions. Contextual information enhances the LinUCB technique recommendation process, maximizing the efficacy of the model and the cumulative return. The recommendation criteria are to achieve the maximum level of confidence regarding the uncertainty surrounding the upward trend of asset returns within the pool of assets. Employing stocks from the Chinese A-share market, Hong Kong market, and US market as empirical tests, our findings demonstrate that the proposed model consistently outperforms the benchmark indices in our backtesting process.

Dynamic DeFi-G7 stock markets interactions and their potential role in diversifying and hedging strategies

AbstractThis study examines the link between stocks and decentralized finance (DeFi) in terms of returns and volatility. Major G7 exchange-traded funds (ETFs) and various highly traded DeFi assets are considered to ensure the robustness of the empirical experiment. Specifically, this study applies the vector autoregression generalized autoregressive conditional heteroskedasticity (VAR-GARCH) model to examine the information transmission of these two markets on a two-way basis and the dynamic conditional correlation (DCC)-GARCH model to assess the bivariate correlation structure between each DeFi and ETF pair. The volatility spillover analysis proves a contagion effect occurred between different geographic markets, and even between markets of different natures and typologies, during the most turbulent moments of the COVID-19 crisis and the war in the Ukraine. Our results also reveal a weak positive correlation between most DeFi and ETF pairs and positive hedge ratios that approach unity during turbulent times. In addition, DeFi assets, except for the Bazaar (BZR) Protocol, can offer diversification gains when included in financial investment portfolios. These results are particularly relevant for portfolio managers and policy-makers when designing investment strategies, especially during periods of financial crisis.

Technological Shocks and Stock Market Volatility Over a Century

This paper provides a novel perspective on the innovation-stock market nexus by examining the predictive relationship between technological shocks and stock market volatility using data over a period of more than 140 years. Utilizing annual patent data for the U.S. and a large set of economies to create proxies for local and global technological shocks and a mixed-sampling data (MIDAS) framework, we present robust evidence that technological shocks capture significant predictive information regarding future realizations of stock market volatility, both in- and out-of-sample and at both the short and long forecast horizons. Further economic analysis shows that investment portfolios created by the volatility forecasts obtained from the forecasting models that incorporate technological shocks as predictors in volatility models experience significantly lower return volatility in the out-of-sample horizons, which in turn helps to improve the risk-return profile of those portfolios. Our findings present a novel take on the nexus between technological innovations and stock market dynamics and pave the way for several interesting avenues for future research regarding the role of technological innovations on asset pricing tests and portfolio models.

Reinforcement Learning-Based Multimodal Model for the Stock Investment Portfolio Management Task

Machine learning has been applied by more and more scholars in the field of quantitative investment, but traditional machine learning methods cannot provide high returns and strong stability at the same time. In this paper, a multimodal model based on reinforcement learning (RL) is constructed for the stock investment portfolio management task. Most of the previous methods based on RL have chosen the value-based RL methods. Policy gradient-based RL methods have been proven to be superior to value-based RL methods by a growing number of research. Commonly used policy gradient-based reinforcement learning methods are DDPG, TD3, SAC, and PPO. We conducted comparative experiments to select the most suitable method for the dataset in this paper. The final choice was DDPG. Furthermore, there will rarely be a way to refine the raw data before training the agent. The stock market has a large amount of data, and the data are complex. If the raw stock market data are fed directly to the agent, the agent cannot learn the information in the data efficiently and quickly. We use state representation learning (SRL) to process the raw stock data and then feed the processed data to the agent. It is not enough to train the agent using only stock data; we also added comment text data and image data. The comment text data comes from investors’ comments on stock bars. Image data are derived from pictures that can represent the overall direction of the market. We conducted experiments on three datasets and compared our proposed model with 11 other methods. We set up three evaluation indicators in the paper. Taken together, our proposed model works best.

Multi-asset portfolio model optimization based on mean multifractal detrended cross correlation analysis

ABSTRACT In order to make the constructed investment portfolio model better adapt to the actual securities market, this paper incorporates the multifractal correlations into the portfolio model of multi-risk assets optimization. On the basis of using variable detrended covariance to measure multifractal correlations, the variable detrended covariance is embedded into the reward-risk criterion, the mean multifractal detrended cross correlation analysis portfolio (M-D) model of multi-risk assets is constructed, and the analytical solution of the M-D model of multi-risk assets is given. The empirical analysis shows that the M-D model not only can improve investment performance but also meet the return-risk criterion much more, reaching the goal of optimizing the multi-risk asset portfolio model.

Connectedness and systemic risk between FinTech and traditional financial stocks: Implications for portfolio diversification

The rapid growth in FinTech is attracting significant investor attention. There are concerns that FinTech stocks may be a source of systemic risk and this has implications for the stability of the financial sector. This study uses a TVP-VAR model to estimate the dynamic connectedness between global FinTech stocks and the stocks of large US banks, regional US banks, US insurance, and global private equity. The findings reveal that FinTech and insurance stocks are net receivers of shocks while large US banks are a major source of shocks. Thus, FinTech stocks are not a source of systemic risk but can be affected by financial contagion and systemic risk originating from large US banks. The highest connectedness was observed at the onset of the COVID-19 lockdowns illustrating the dramatic impact that a health pandemic can have on systemic risk. Systemic risk also increased during the 2023 US bank panic. Connectedness has implications for constructing investment portfolios. The equally weighted, risk parity, and risk parity connectedness portfolios have similar portfolio summary statistics, but lower risk adjusted returns than the maximum Sharpe ratio portfolio which better captures the low correlation between FinTech stocks and traditional financial stocks. These results are robust across various portfolio rebalancing periods (daily, weekly, monthly).

The Causality Relationship between Credit Default Swaps (CDS) and Portfolio Investments: The Case of Türkiye

This study examines the causality relationship between portfolio investments and credit default swaps (CDS) in Türkiye. Analysing the dynamics between portfolio investments and CDS premiums, two important variables for financial markets is critical to understanding how risk perception and investment decisions are affected. While portfolio investments are generally considered an indicator of the confidence of foreign investors in the country's economy, CDS premiums are an important risk measure that reflects the country's debt risk and the risk perception of market participants. In this context, examining the relationships between the two variables contributes to the understanding of the effects of investor behavior and risk perception on macroeconomic indicators in financial markets. In the study, the Granger causality test was applied using data from the period 2014Q1-2024Q1. The results obtained show that CDS premiums have a significant and unidirectional causal effect on portfolio investments. Increases in CDS premiums increase investors' risk perception and lead to a decrease in portfolio investments. On the other hand, no causal effect of portfolio investments on CDS premiums was found. These findings emphasize the importance of risk management in terms of portfolio investments in Türkiye and reveal that CDS premiums play a role in investor decisions.

Cointegration Relationship between Portfolio Investments and Investment Instruments in Türkiye

As a result of globalization, the removal of barriers to international capital has created a source for countries in need of capital. These capital sources referred to as short-term capital movements or simply portfolio investments, provide significant benefits to the economy when they first enter the country. Investment instruments are instruments used by those who have excess capital in their hands in order to make a profit. The aim of this study is to reveal the cointegration relationships between portfolio investments and investment instruments in Türkiye. The motivation for this study is that there are few studies in the literature that examine cointegration relationships between all investment instruments and portfolio investments. The study comprises quarterly data covering the period from 2009Q1 to 2023Q2. The data has been obtained from the CBRT EVDS system. According to the results of ARDL cointegration analysis; there is a cointegration relationship between the variables both in the short and long run. According to these results, in Türkiye, investment instruments do not significantly affect portfolio investments, but portfolio investments significantly affect investment instruments.

RISKS OF INVESTMENT PORTFOLIO OF BANKS OF KAZAKHSTAN: PROBLEMS AND WAYS TO SOLUTION

The article examines the essence and classification of the definition of «market risk». It is noted that managing market risks in a bank is a complex and multifaceted process that requires constant analysis and monitoring of market conditions, and an important element of the market risk management system is the formation of an effective investment portfolio, which includes various assets with different levels of risk. This will allow you to control and minimize possible losses, and will also help the bank determine the optimal balance between risk and profitability, which will help increase its profits. Using modern data analysis methods, an analysis of the real average investment portfolio of second-tier domestic banks was carried out and an assessment of the generated conditional investment portfolio was given. Based on the study, problems were identified and directions for improving market risk management in the bank were given.

Measuring and analyzing the impact of portfolio investment on the trading volume index of the Iraq Stock Exchange for the period 2012-2022

The study aims to measure and analyze the role of portfolio investment in the trading volume index of the Iraqi securities market. The descriptive and analytical approach and the standard economics approach were used in building the model based on the EViews 13 program, as well as the use of the self-degradation model of distributed time gaps (ARDL). The study concluded that the statistically significant impact of portfolio investment on Iraq's short-term and long-term stock exchange volume index was demonstrated the study found that portfolio foreign investment is an important element of the economy. However, the Iraqi economy is an environment that is not attractive to investment because of the conditions of security and economic instability, which adversely affects foreign investors' willingness to invest and trade in the market. This is illustrated by the indicators during the course of the study, whether as regards the volume of non-Iraqis' trading or net portfolio investment and its impact on the volume index on the Iraq stock market. The study recommended the granting of many advantages and tax incentives to attract foreign investors to financial markets because of the great importance of portfolio investment in development and the development of the national economy as well as providing the right investment climate and working to diversify and develop new types of securities

CNN-BiLSTM-Attention Based Stock Price Prediction and Quantitative Investment Strategy

With the rapid development of technology and the increasing maturity of financial markets, stock price prediction has become a hot topic and an important trend in the financial field. However, the stock market has complexity and volatility, in order to reduce the investment risk and ensure the maximization of benefits, selecting the optimal stock to predict the stock price and formulating the quantitative trading strategy are extremely important issues for financial academics and investors. For the research of stock price prediction and quantitative trading, firstly, the quantitative stock selection model combining XGBoost and multi-factor stock selection model is constructed, and four stocks are screened out, and then the CNN-BiLSTM-Attention model is proposed to predict the stock price trend of the selected stocks, and it is found from the prediction results of the four stocks that the prediction accuracies all reach more than 95%, which is higher than that of the single model prediction. accuracy and passed the validity test of the fitted model. Secondly, based on the quantitative investment portfolio given in the above analysis and the quantitative stock trading strategy of MACD, the prediction results are verified, and the total return of most stocks based on the strategy is higher than 40% at the highest, and the loss is controlled within 10%, which indicates that the trading strategy in this paper is effective and feasible. The study concludes that greater returns can be obtained by calculating the total returns of stock portfolios based on different portfolio approaches.

Strategies for Mitigating and Managing Risks in Bank Investments

This paper suggests that while studies of banking risk management often emphasize analytics and stress testing to improve risk governance, there is too little emphasis on historical case studies to generate comprehensive risk management strategies. Using numerous case studies, the paper suggests four categories of risk - market risks, credit risks, regulatory risks, and operational risks - that impact overall investment outcomes. By extensively reviewing both historic failures and historic successes, the paper highlights the importance of understanding different types of risks and adopting strategic measures to manage them effectively. Emphasis is placed on the necessity of a diversified investment portfolio to mitigate market volatility and credit exposure. Additionally, the paper provides actionable strategies for navigating regulatory complexities and operational challenges, supported by real-world case studies and practical examples. This research aims to equip investors with valuable insights and tools to optimize investment opportunities while minimizing potential risks in the banking sector.

Pravni položaj berzi plemenitih metala u uporednom zakonodavstvu

In the years of economic and geopolitical crises and global inflation, there is a noticeable trend of increasing demand for precious metals, which play an increasingly prominent role as an instrument for diversifying the investment portfolio and as a security means. Therefore, the starting point of this research is the analysis of the legal regime for the organization and operation of precious metal exchanges in comparative legislation. Using a comparative and normative method, the author will critically review the principal legal characteristics of precious metal exchanges, the legal position and organization of the world’s most important precious metal exchanges, their business rules and the activities of the regulatory authority that supervises the precious metals trading. Therefore, the objective of this paper is to consider the importance of organizing and operating precious metals exchanges, taking into account that unconscionable, dishonest and non-transparent operations on the precious metals market can cause negative consequences for both market participants and the economy and society as a whole in the case of significant market disruptions.

The Retreat from BIST: Insights into Foreign Portfolio Investment Movements

The need for rapid growth and development in developing countries increases the demand for capital. As a result, foreign portfolio investments are of great importance, especially in emerging markets, as they help meet capital needs. However, their ability to move quickly also introduces high volatility to financial markets. This study examines changes in the share of foreign portfolio investors in Borsa Istanbul from 2004 to 2023, aiming to provide long-term insights to market participants. Initially, changes in the foreign portfolio investor ratio over time are graphically analyzed alongside the BIST 100 index and the average interest rate of deposits with a maturity of up to 3 months. These changes are evaluated in the context of both global and local developments. The study then investigates the causal relationship between the foreign portfolio investor ratio and the BIST 100 index using a cointegration test and a causality test based on the VECM model. The findings show a one-way causality from the BIST 100 index to the foreign portfolio investor ratio, indicating that foreign investors' market movements are largely influenced by the performance of the BIST 100, and local market dynamics significantly affect foreign capital inflows.

Capital Asset Pricing Model and Ordered Weighted Average Operator for Selecting Investment Portfolios

The main objective of this article is to present the formulation of a Capital Asset Pricing Model ordered weighted average CAPMOWAand its extensions, called CAPM-induced OWA (CAPMIOWA), CAPM Bonferroni OWA (CAPMBon-OWA), and CAPM Bonferroni-induced OWA CAPMBon-IOWA. A step-by-step process for applying this new proposal in a real case of formulating investment portfolios is generated. These methods show several scenarios, considering the attitude, preferences, and relationship of each argument, when underestimation or overestimation of the information by the decision maker may influence the decision-making process regarding portfolio investments. Finally, the complexity of the method and the incorporation of soft information into the modeling process lead to generating a greater number of scenarios and reflect the attitudes and preferences of decision makers.

Asymptotics for Finite-Time Ruin Probabilities of a Dependent Bidimensional Risk Model with Stochastic Return and Subexponential Claims

The paper considers a bidimensional continuous-time risk model with subexponential claims and Brownian perturbations, in which the price processes of the investment portfolio of the two lines of business are two geometric Lévy processes and the two lines of business share a common claim-number process, which is a renewal counting process. The paper mainly considers the claims of each line of business having a dependence structure. When the claims have subexponential distributions, the asymptotics of the finite-time ruin probabilities ψand(x1,x2;T) and ψsim(x1,x2;T) have been obtained. When the distributions of claims belong to the intersection of long-tailed and dominatedly varying-tailed distribution classes, the asymptotics of the finite-time ruin probability ψor(x1,x2;T) is given.

Effect of ESG performance on stock price crash risk: evidence from China

ABSTRACT This study investigates the impact of ESG performance on stock price crash risk using a dataset of Chinese-listed firms in the period 2015 – 2020. Empirical evidence reveals a negative association between ESG performance and stock price crash risk, particularly under high product market competition conditions. Mechanism analysis suggests that ESG performance reduces stock price crash risk by alleviating maturity mismatch and optimizing debt maturity in investment and financing, but only when market competition is intense. These findings align with the resource dependence theory, indicating that strong ESG performance enhances a firm’s ability to acquire resources and mitigate stock price crash risk in highly competitive environments. Consequently, ESG performance not only augments a firm’s competitive advantage but also serves as a risk reduction tool, enabling investors to construct more sustainable investment portfolios.