• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Korean Management Science Review
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• v.30 no.1
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• pp.167-181
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• 2013

We investigate the dynamic asset allocation problem under inflation risk when the wealth of an investor is constrained with minimum requirements. To capture the investor's risk preference, the CRRA utility function is considered and he maximizes his expected utility at predetermined date of the refund by participation in the financial market. The financial market is supposed to consist of three kinds of financial instruments which are a risk free asset, a risky asset, and an index bond. The role of an index bond is managing inflation risk represented by price process. The optimal wealth and the optimal asset allocation are derived explicitly by using the method to get the European call option pricing formula. From the numerical results, it is confirmed that the investments on index bond is high when the investor's wealth level is low. However, as his wealth increases, the investments on index bond decreases and he invests on risky asset more. Furthermore, the minimum wealth constraint induces lower investment on risky asset but the effect of the constraints is reduced as the wealth level increases.

• KDI Journal of Economic Policy
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• v.28 no.2
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• pp.239-262
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• 2006

The paper suggests that there has been a shift in the allocation of bank credit from large firms to small firms before and after the economic crisis. The paper also suggests that the improved lending practices of financial institutions, at least partially, contributed to this shift of corporate loans from large firms to small firms. Comparing the periods before and after the economic crisis also suggests that some important changes occurred to the corporate bond market. The effect of firm size on the corporate bond market differs before and after the economic crisis. Before the crisis, the larger the firms, the more they could borrow in the corporate bond market. However, after the crisis, it is not the case. The following interpretation could be put forward. Before the crisis, investors in the corporate bond market expected that the government would rescue large firms if they face the risk of bankruptcies. However, the collapse of Daewoo Group in 1999 shattered the TBTF (Too Big To Fail) myth of the public. The liquidity crisis of Hyundai Group in 2000-2001 reinforced the disintegration of the TBTF myth.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.30-38
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• 2017

Contingent convertible (Coco) bonds have been issued in 2009 after financial crisis for improvement of capital structure in international banks. With more focuses on coco bonds in financial market, academic fields have paid attention to the instrument for optimal structure for issuers and rational pricing methodologies. However, there is a crucial discrepancy in prevailing pricing model and their target subjects. Though most of the coco bonds have been issued based on accounting triggers, many of existing models are based on market prices and therefore exhibit limitations in practical use. In this paper, a more practical pricing method for accounting triggered coco bonds is proposed using stochastic equity ratio process. Empirical results tested on coco bond issued by JB financial group supported the proposed approach with favorable performance in tracking actual market prices.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.181-193
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• 2022

This paper seeks to investigate major macroeconomic factors and bond yield interactions in Thai bond markets, with the goal of forecasting future bond yields. This study examines the best predictive yields for future bond yields at different maturities of 1-, 3-, 5-, 7-, and 10-years using time series data of economic indicators covering the period from 1998 to 2020. The empirical findings support the hypothesis that macroeconomic factors influence bond yield fluctuations. In terms of forecasting future bond yields, static predictions reveal that in most cases, the BVAR model offers the best predictivity of bond rates at various maturities. Furthermore, the BVAR model has the best performance in dynamic rolling-window, forecasting bond yields with various maturities for 2-, 4-, and 8-quarters. The findings of this study imply that the BVAR model forecasts future yields more accurately and consistently than other competitive models. Our research could help policymakers and investors predict bond yield changes, which could be important in macroeconomic policy development.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.113-124
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• 2021

The study investigates how financial markets respond to a shock to tone and semantic similarity of the Bank of Thailand press releases. The techniques in natural language processing are employed to quantify the tone and the semantic similarity of 69 press releases from 2010 to 2018. The corpus of the press releases is accessible to the general public. Stock market returns and bond yields are measured by logged return on SET50 and short-term and long-term government bonds, respectively. Data are daily from January 4, 2010, to August 8, 2019. The study uses the Structural Vector Auto Regressive model (SVAR) to analyze the effects of unanticipated and temporary shocks to the tone and the semantic similarity on bond yields and stock market returns. Impulse response functions are also constructed for the analysis. The results show that 1-month, 3-month, 6-month and 1-year bond yields significantly increase in response to a positive shock to the tone of press releases and 1-month, 3-month, 6-month, 1-year and 25-year bond yields significantly increase in response to a positive shock to the semantic similarity. Interestingly, stock market returns obtained from the SET50 index insignificantly respond to the shocks from the tone and the semantic similarity of the press releases.

• Management & Information Systems Review
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• v.30 no.2
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• pp.257-275
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• 2011

The price relationship between the futures market and the underlying spot market has attracted the attention of academics, practitioners, and regulators due to their roles during periods of turbulence in financial markets. The purpose of this paper is to investigate the dynamic of price relationship(or lead-lag relationship) between Korean Treasury Bond futures market and spot market. To examine the nature of the price relationship, descriptive statistics, serial correlation, and cross-correlation are used as a preliminary statistics in the Korean Treasury Bond spot and futures market. Next, following Stoll-Whaley(1990) and Chan(1992), the multiple regression method is used to examine the lead-lag patterns between the two markets. The empirical results are summarized as follows. The mean returns of spot markets and future markets are positive(+) and negative(-) respectively and the standard deviation of both stock and futures returns increase through the sub-periods. For the most periods, there is negative skewness in the both markets. The zero excess kurtosis due to the heavy tails of the distribution are relatively large. The autocorrelations in the spot returns for the sample periods are positive in time lag 1, but the autocorrelations in the future returns shows no significant evidence. The results of the daily cross-correlations between the KTB spot and futures returns indicate that a lead-lag relationship don't exist for price changes of futures and spot markets as a preliminary analysis. Finally, empirical results of regression analysis for both market indicate that there is no evidence that the KTB futures lead the KTB spot market, or the KTB spot market lead the KTB futures market. These results are robust for all sub-periods.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.139-150
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• 2017

Open economy tightly works with foreign economy. This paper investigates the effect of the shock of foreign bond yield on the credit spreads of domestic corporate bonds in Korea. Foreign bond is referred to as US treasury bond. Credit spreads are defined with the difference between log yields of domestic corporate bonds and log yield of Korea treasury bond. With the data of monthly three-year AA- and BBB- corporate bond yields- ratings, monthly three-year Korean treasury bond yields, monthly US dollar foreign exchange rates, and monthly three-year US Treasury bond yields during the period from October 2000 to September 2014 including global financial crisis period, the paper documents the results as follow. First of all, the yield of Korean treasury and the credit spreads are very sensitive to the increase in the level and the volatility of the yield of the US treasury bond. Changes in the level and the volatility little affect the change of the exchange rate. Second, the change in the level and the volatility negatively affect the level of Korean treasury bond yields but lead to the increase in the level of Korean treasury bond yields at the same time. Third, there exist time lags of the increases of credit spreads by the increase in the level and the volatility. These imply that credit spreads and bond yields are very sensitive to the change in the yields of foreign bonds such as US treasury bond.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.123-144
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• 2015

Through the event study methodology and the case study on the Company T and its subsidiaries, this study analyzes the effect of credit rating downgrade in the Korean stock market. Our empirical results cast some doubts on whether credit rating agencies made adequate credit rating adjustments on the Chaebol companies, and suggest that little information was provided to the bond market investors. This study provides some policy implications by recommending that regulators encourage credit rating agencies to provide more accurate and appropriate information to market participants.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.255-269
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• 2020

Purpose - This paper analyzes the market efficiency focusing on the long memory properties of the domestic futures market. By decomposing futures prices into yield and volatility and looking at the long memory properties of the time series, this study aims to understand the futures market pricing and change behavior and risks, specifically and in detail. Design/methodology/approach - This study analyzes KOSPI 200 futures, KOSDAQ 150 futures, 3 and 10-year government bond futures, US dollar futures, yen futures, and euro futures, which are among the most actively traded on the Korea Exchange. To analyze the long memory and market efficiency, we used the Variance Ratio, Rescaled-Range(R/S), Geweke and Porter-Hudak(GPH) tests as semi- parametric methods, and ARFIMA-FIGARCH model as the parametric method. Findings - It was found that all seven futures supported the efficiency market hypothesis because the property of long memory turned out not to exist in their yield curves. On the other hand, in futures volatility, all 7 futures showed long memory properties in the analysis, which means that if new information is generated in the domestic futures market and the market volatility once expanded due to the impact, it does not decrease or shrink for a long period of time, but continues to affect the volatility. Research implications or Originality - The results of this paper suggest that it can be useful information for predicting changes and risks of volatility in the domestic futures market. In particular, it was found that the long memory properties would be further strengthened in the currency futures and bond rate futures markets after the global financial crisis if the regime changes of the domestic financial market are taken into account in the analysis.