Communications for Statistical Applications and Methods
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v.29
no.1
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pp.85-101
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2022
Derivative-linked securities (DLS) is a type of derivatives that offer an agreed return when the underlying asset price moves within a specified range by the maturity date. The underlying assets of DLS are diverse such as interest rates, exchange rates, crude oil, or gold. A German 10-year bond rate-linked DLS and a USD-GBP CMS rate-linked DLS have recently become a social issue in Korea due to a huge loss to investors. In this regard, this paper accounts for the payoff structure of these products and evaluates their prices and fair coupon rates as well as risk measures such as Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). We would like to examine how risky these products were and whether or not their coupon rates were appropriate. We use Hull-White Model as the stochastic model for the underlying assets and Monte Carlo (MC) methods to obtain numerical results. The no-arbitrage prices of the German 10-year bond rate-linked DLS and the USD-GBP CMS rate-linked DLS at the center of the social issue turned out to be 0.9662% and 0.9355% of the original investment, respectively. Considering that Korea government bond rate for 2018 is about 2%, these values are quite low. The fair coupon rates that make the prices of DLS equal to the original investment are computed as 4.76% for the German 10-year bond rate-linked DLS and 7% for the USD-GBP CMS rate-linked DLS. Their actual coupon rates were 1.4% and 3.5%. The 95% VaR and TVaR of the loss for German 10-year bond rate-linked DLS are 37.30% and 64.45%, and those of the loss for USD-GBP CMS rate-linked DLS are 73.98% and 87.43% of the initial investment. Summing up the numerical results obtained, we could see that the DLS products of our interest were indeed quite unfavorable to individual investors.
The real estate market is an important part of a country's economy and plays a major role in economic growth through the growth of many related industries. Changes in interest rates affect asset prices and have a significant impact on housing prices. This study analyzed housing prices by dividing them into nationwide, local, and Seoul housing prices in order to analyze whether the effect of changes in interest rates on housing prices shows regional differences. The analysis was conducted from the first quarter of 2011 to the fourth quarter of 2021, and was analyzed using the DOLS model. The main analysis results are as follows. First, interest rates were found to have a significant negative effect on national housing prices, and a drop in interest rates significantly increased national housing prices and an increase in interest rates significantly lowered national housing prices. The consumer price index and loan growth rate also had a positive effect on housing prices nationwide, but statistical significance was not high. Second, interest rates had a negative effect on local housing prices, unlike national housing prices, but were not statistically significant. On the other hand, it was found that the consumer price index and loan growth rate had a larger and significant positive effect on local housing prices compared to national housing prices. Finally, it was found that the interest rate had the only significant negative effect on housing prices in Seoul. And this effect was greater and more significant than the effect on national and local housing prices. In the end, it was found that the effect of interest rates on Korean housing prices differs locally. Interest rates have a significant negative effect on national housing prices, and local housing prices, but they are not statistically significant. In addition, the interest rate was found to have the largest and most significant negative effect on housing prices in Seoul. In addition, it was found that there was a difference in the effect of macroeconomic variables on housing prices. This means that there are differences between regions with different factors influencing local and Seoul housing prices, and this point should be considered when drafting and implementing real estate policies.
The notion of customer orientation is now importantly considered in the context of banking industries. Despite customer-oriented organizational cultures, there are few studies addressing the relationship between customer orientation and its outcomes. In particular, this study aims at testing the effect of customer orientation as a key marketing effort designed by a bank. This is because interest rate sensitivity is critical for evaluating banking services after raising the base rate. In so doing, first, this study investigates the relationships among customer orientation, interest rate sensitivity, and customer loyalty. Second, this paper examines how the moderating effects of both deposit interest and loan interest rates influence the linkages of customer orientation-interest rate sensitivity and customer orientation-customer loyalty. To test the proposed model, research data are collected from 304 subjects who use banking services(e.g., Shin-Han, Kookmin, the First Bank, Hana, and Woori banks). Each construct was measured by published items and the psychometric properties of the three constructs, excluding two constructs of the moderators, were evaluated by employing the method of confirmatory factor analysis via the use of AMOS. The model fit was also evaluated using the CFI, TLI, and RMSEA fit indices that are recommended based on their relative stability and insensitivity to sample size. The findings show that the relationship between customer orientation and customer loyalty is significant, whereas the relationships between customer orientation and interest rate sensitivity and between interest rate sensitivity and customer loyalty are not supported. Although customer orientation is highly evaluated, customers' interest rate sensitivity that results in the comparison of interest rates plays an important role in reducing the effect of customer orientation. As a consequence, interest rate sensitivity does not influence customer loyalty. First of all, one of interesting results in this study is that the moderating effect of loan interest rate is quite different from deposit interest rate. In the case of deposit interest rate, the linkages both customer orientation-interest rate sensitivity and customer orientation-customer loyalty are insignificant. In the case of loan interest rate, however, the two proposed linkages are supported. As our proposed relationships are still in its infancy in the context of banking industry, our study contributes to enhance scholars' knowledge of bank services and provides insights for practitioners when their marketing strategies, particularly both deposit and interest rates, have to be established. Finally, this research also illuminates the need for further research that considers the influence of customer orientation on consumer's decision-making and bank profits. More specifically, the results are encouraging and will lead us to further investigate this key outcome of the banking deposit/interest rates.
This paper analyzes the effects of the cut in the legal maximum interest rate (from 27.4% to 24%) that occurred in February of 2018 on loan interest rates, the default rates, and the loan approval rate of borrowers in the non-banking sector. We use the difference-in-difference identification strategy to estimate the effect of the cut in the legal maximum interest rate using micro-level data from a major credit-rating company. The legal maximum rate cut significantly lowers the loan interest rate and default rate of low-credit borrowers (i.e., high-credit-risk borrowers) in the non-banking sector. However, this effect is limited to borrowers who have not been excluded from the market despite the legal maximum interest rate cut. The loan approval rate of low-credit borrowers decreased significantly after the legal maximum interest rate cut. Meanwhile, the loan approval rate of high-credit and medium-credit (i.e., low credit risk and medium credit risk) borrowers increased. This implies that financial institutions in the non-banking sector should reduce the loan supply to low-credit borrowers who are no longer profitable while increasing the loan supply to high- and medium-credit borrowers.
This paper investigates the effects of inflation on real estate prices, particularly the discrepancy between the sales and chonsei prices of housing, in an economy in which real interest rates are secularly declining due to the fall in capital productivity. When real interest rates fall, real estate prices rise relative to chonsei prices, and thus the well-known adverse effect of inflation, or the discrepancy between the value of financial assets (or chonsei principal) and the value of real assets (or real estate), is aggravated although the monetary authority maintains the same rate of inflation. This theoretical prediction can help explain the trend of the ratio of apartment sales prices to chonsei prices. That is, the stabilization of inflation relative to real interest rates appears to have contributed to the secular stabilization of this ratio in the 1990s, while the fall in real interest rates appears to have led to the rise of this ratio since 2001.
Purpose - This study aims in analyzing the dynamic relationship between household loans and housing prices according to the characteristics of depository institutions after the financial crisis, identifying the recent trends between them, and making policy suggestions for stabilizing house prices. Design/methodology/approach - The monthly data used in this study are household loans, household loan interest rates, and housing prices ranging from January 2012 to May 2020, and came from ECOS of the Bank of Korea and Liiv-on of Kookmin Bank. This study used vector auto-regression, generalized impulse response function, and forecast error variance decomposition with the data so as to yield analysis results. Findings - The analysis of this study no more shows that the household loan interest rates in both deposit banks and non-bank deposit institutions had statistically significant effects on housing prices. Also, unlike the previous studies, there was statistically significant bi-directional causality between housing prices and household loans in neither deposit banks nor non-bank deposit institutions. Rather, it was found that there is a unidirectional causality from housing prices to household loans in deposit banks, which is considered that housing prices have one-sided effects on household loans due to the overheated housing market after the financial crisis. Research implications or Originality - As a result, Korea's housing market is closely related to deposit banks, and housing prices are acting as more dominant information variables than interest rates or loans under the long-term low interest rate trend. Therefore, in order to stabilize housing prices, the housing supply must be continuously made so that everyone can enjoy housing services equally. In addition, the expansion and reinforcement of the social security net should be realized systematically so as to stop households from being troubled with the housing price decline.
Journal of Korean Institute of Industrial Engineers
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v.36
no.3
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pp.203-211
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2010
This study examines a cointegrated vector autoregressive (VAR) model where parameters are subject to switch across the regimes in the term structure of interest rates. To employ the regime switching framework, the Markov-switching vector error correction model (MS-VECM) is allowed to the regime shifts in the vector of intercept terms, the variance-covariance terms, the error correction terms, and the autoregressive coefficient parts. The corresponding approaches are illustrated using the term structure of interest rates in the US Treasury bonds over the period of 1958 to 2009. Throughout the modeling procedure, we find that the MS-VECM can form a statistically adequate representation of the term structure of interest rate in the US Treasury bonds. Moreover, the regime switching effects are analyzed in connection with the historical government monetary policy and with the recent global financial crisis. Finally, the results from the comparisons both in information criteria and in forecasting exercises with and without the regime switching lead us to conclude that the models in the presence of regime dependence are superior to the linear VECM model.
PURWONO, Rudi;NUGROHO, Ris Yuwono Yudo;MUBIN, M. Khoerul
The Journal of Asian Finance, Economics and Business
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v.6
no.2
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pp.33-44
/
2019
The Indonesian government launched a new people's business credit program as part of a package of economic policy and deregulation. The interest rate is set lower than the average of the current loan interest rates, especially when compared with rural bank interest rates. To capture the social spatial aspects, quota sampling is applied to ten areas that divided based on the social culture. Further, the method utilized in this research is logit models, which designed to analyse the determinants of asymmetric information particularly on the rural bank and small micro enterprises. The study was conducted in East Java as the province with the largest number of rural banks in Indonesia. Based on the estimation of asymmetric information model to the respondent of rural banks and small businesses, the result shows that adverse selection can be avoided by strengthening the information about prospective borrowers. Regarding moral hazard, rural banks and small businessmen argued that the imposition of the collateral to the debtor has an important role to avoid moral hazard. Rural bank respondents stated that the KUR program with low-interest rates has affected their business development. The results implied the need of broadening the collaboration schemes between this people's business credit program and rural banks.
This paper estimates the term structure of interest rates with the setup of 3-factor no arbitrage model and investigates the trend of term premia and the effectiveness of changes in policy interest rates. The term premia are found to be high in a three-year medium term objective, which can be interpreted as reflecting the recognition of investors who expect a higher uncertainty in real activities for the coming three years than for a longer term. Then, in order to look into the effect of policy interest rates after the recent change of benchmark interest rate, this paper analyzes the effects of the changes in short-term interest rates of the financial market on the yield curve of the bond market at time of change. Empirical results show that the discrepancy between call rate, short-term rate in money market, and instantaneous short rate, short-term rate in the bond market, is found to be significantly widened, comparing to the periods before the change in benchmark interest rate. It is not easy to conclude clearly for now whether such a widening gap is caused by the lack of experiences with managing new benchmark interest rate or is just an exceptional case due to the recent turmoil in the global financial market. However, monetary policy needs to be operated in a manner that could reduce the gap to enhance its effectiveness.
Proceedings of the Korea Inteligent Information System Society Conference
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2000.04a
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pp.235-241
/
2000
This article suggests integrated neural network models for the interest rate forecasting using change point detection. The basic concept of proposed model is to obtain intervals divided by change point, to identify them as change-point groups, and to involve them in interest rate forecasting. the proposed models consist of three stages. The first stage is to detect successive change points in interest rate dataset. The second stage is to forecast change-point group with data mining classifiers. The final stage is to forecast the desired output with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. This article is then to examine the predictability of integrated neural network models for interest rate forecasting using change-point detection.
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