• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.573-588
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• 2023

Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.1-10
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• 2021

This paper compares the performance of Fama-French three-factor and five-factor models using a dataset of 20 Pakistani commercial banks for the period 2011 to 2020. We focus on an emerging economy as the findings from earlier studies on developed countries cannot be generalized in emerging markets. For empirical analysis, twelve portfolios were developed based on size, market capitalization, investment strategy, and growth. Subsequently, we constructed five Fama-French factors namely, R_M, SMB, HML, RMW, and CMA. The OLS regression technique with robust standard errors was applied to compare the predictive power of both the Fama-French models. Further, we also compared the mean-variance efficiency of the Fama-French models through the GRS test. Our empirical analysis provides three unique and interesting findings. First, both asset pricing models have similar predictive power to explain the expected portfolio returns in most cases. Second, our results from the GRS test suggest that there is no noticeable difference in the mean-variance efficiency of one asset pricing model over the other. Third, we find that all factors of both Fama-French models are statistically significant and are important for explaining the volatility of expected commercial bank returns in the context of Pakistan.

• Management Science and Financial Engineering
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• v.2 no.1
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• pp.73-101
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• 1996

We show assets can be classified into diversifiable risks and non-diversifiable risks based on aggregate endowment and spanning so that in equilibrium agents eliminate diversifiable risks which must have zero values. Consequently, the benchmark portfolio that represents a pricing operator should have only a non-diversifiable risk, aggregate endowment should earn a positive risk premium over a riskless asset, and, even in incomplete markets, there should be a pricing operator represented by a function of aggregate endowment if any asset mean-independent of aggregate endowment is diversifiable. These results apply to both the CAPM and a representative agent model.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.123-138
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• 2022

Purpose - This study compares the performances of dynamic asset allocation strategies using Korean stocks and U.S. dollar, which have been negatively correlated for a long time, to examine the diversification effects in the portfolios of them. Design/methodology/approach - In the current study, we use KOSPI200 index, as a proxy of the aggregated portfolio of Korean stocks, and USDKRW foreign exchange rate to implement various portfolio management strategies. We consider the equally-weighted, risk-parity, minimum variance, most diversified, and growth optimal portfolios for comparison. Findings - We first find the enhancement of risk adjusted returns due to risk reduction rather than return increasement for all the portfolios of consideration. Second, the enhancement is more pronounced for the trading strategies using correlations as well as volatilities compared to those using volatilities only. Third, the diversification effect has become stronger after the global financial crisis in 2008. Lastly, we find that the performance of the growth optimal portfolio can be improved by utilizing the well-known momentum phenomenon in stock markets to select the length of the sample period to estimate the expected return. Research implications or Originality - This study shows the potential benefits of adding the U.S. dollar to the portfolios of Korean stocks. The current study is the first to investigate the portfolio of Korean stocks and U.S. dollar from investment perspective.

• Journal of Families and Better Life
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• v.14 no.3
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• pp.109-120
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• 1996

While theories of portfolio selection have been developed very little is known about how individuals actually go about constructing their asset potfolios. This study investigates empirically the characteristics of household's assets and which factor associated with risky and safe asset amount. Data used in this study consisted of 2,164 households and the statistics employed to analyze the data are univariate procedure Logit analysis and OLS. The results of this study were as follows: Among 2,164 households 505 housholds(23.3%) had risky assets. Average risky asset amount is 8,351,500 won and average safe asset amount is 7,086,900 won. Region education and occupation of household head home ownership transfer and other income and total expenditure had significant effects on either and other income and total expenditure had significant effects on either household having risky asset or safe asset. Financial income transfer and other income and total expenditure had significantly p sitive relation with the risky asset amount. Whereas age and the occupation of household head the sense of economic wellbeing earned financial tranfer and other income and total expenditure had significantly positive relation with safe asset amount.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.3
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• pp.245-262
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• 2007

This paper aims at analyzing the characteristics of performance and asset management system of listed property trusts(LPT) in Australia, and elucidating the implications for Korean real estate indirect investment market. The main results of this paper are as follows. Firstly, LPT have a leading position among the real estate indirect investment systems in Australia, through the rapid growth of market capitalization. Secondly, LPT achieved superior risk adjustment performance than other financial products, and had valid portfolio diversification effect. Thirdly, many LPT have used stapled securities structure as a asset management system, and stapled LPT revealed superior risk adjustment performance than unit LPT. Finally, implications and policy measures such as using the stapled structure and activating the development activities were examined for the development of Korean real estate indirect investment market.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.419-430
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• 2023

Currently, NFTs have no dominant application except for the proof of ownership for digital content, and it also have small liquidity problem, which makes their price difficult to predict. Real estate usually has very high barriers to investment due to its high pricing. Real estate can be converted into NFTs and also divided into small value fungible tokens (FTs), and it can increase the the volume of the investor community due to more liquidity and better accessibility. In this document, we implement and design a system that allows ordinary users can invest on high priced real estate utilizing Black Litterman (BL) model-based Portfolio investment interface. To this end, we target a set of real estates pegged as collateral and issue NFT for the collateral using blockchain. We use oracle to get the current real estate information and to monitor varying real estate prices. After tokenizing real estate into NFTs, we divide the NFTs into easily accessible price FTs, thereby, we can lower prices and provide large liquidity with price volatility limited. In addition, we also implemented BL based asset portfolio interface for effective portfolio composition for investing in multiple of real estates with small investments. Using BL model, investors can fix the asset portfolio. We implemented the whole system using Solidity smart contracts on Flask web framework with public data portals as oracle interfaces.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.1113-1122
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• 2020

The purpose of this study is to examine how the Indian banks have adjusted their risk-based capital ratios during 2009-2018 to meet the regulatory requirements. Banks can, in principle, increase their risk-based regulatory capital ratio, either by increasing their levels of regulatory capital or by shrinking their risk-weighted assets by adjusting asset growth or risk in the portfolio. We investigate banks' capital behavior by decomposing the change in the capital ratio into the contribution of its components and analyzing their variance across regulatory regimes and banks' ownerships. We further investigate how each component of the capital ratio is adjusted by the banks by breaking down them into balance sheet items. We find that the banks' capital behavior significantly differed between public and private sector banks and between the two regulatory regimes. During Basel II, banks, in general, followed a strategy of aggressive asset growth with increased risk-taking. The decline in the CRAR because of such an expansionary strategy was adjusted by augmenting additional capital. However, during Basel III, due to higher capital requirements, both in terms of quantity and quality, banks followed a strategy of cutting back their asset growth and reducing the risk in their portfolio to maintain their CRAR.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.537-557
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• 2005

The estimate on volatility of stock price is related with optimum of portfolio and Important for allocation of capital asset. If the volatility of stock price is varied according to macroeconomic variables on monetary policy and industrial production, it will assist capital asset to allocate. This paper is related with stock market volatilities on macroeconomic variables in U.S. and Europe, Korea. And, it Is pertain to vary in time of this variables. Thus, this paper is related with volatilities of monetary and physical macroeconomic variables on basis of statistics. And, it is ranged front capital investment to portfolio allocation. Also, this paper takes out of sample forecast and study more after this. In case Germany, France, Italy and the Netherlands, the relative importance of monetary policy and Industrial production Is different from these countries. In case Italy and the Netherlands, monetary policy is primary factor at stabilizing for volatility of stock price. In case Korea, increasing monetary policy and industrial production is positively affected stock market. It is that the positive effect of stock price is caused by mollifying monetary policy and economic growth. Specially, this conclusion is similar to US. In Korea, gradual increase in monetary and industrial production is necessary to stability of stock market. It is different to previous results on basis of increasing stock price of money in long period.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.605-618
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• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.