• 충청수학회지
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• 제34권2호
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• pp.157-168
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• 2021

This study uses the benchmark interest rate of the Federal Open Market Committee (FOMC) to predict gold futures prices. For the predictions, we used the support vector machine (SVM) (a machine-learning model) and the long short-term memory (LSTM) deep-learning model. We found that the LSTM method is more accurate than the SVM method. Moreover, we applied the Boruta algorithm to demonstrate that the FOMC benchmark interest rates correlate with gold futures.

• KDI Journal of Economic Policy
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• 제31권2호
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• pp.15-45
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• 2009

본고에서는 3요인 무재정거래(3-factor no arbitrage) 조건하에서의 이자율 기간 구조를 추정하고 이를 이용하여 기간프리미엄의 추이 및 정책금리 변경의 유효성을 분석하였다. 기간프리미엄의 경우 3년물에서 높게 나타나고 있는데, 이는 장기적인 경제 상황보다 향후 3년 정도의 시계에서 경제의 불확실성이 높을 것이라는 투자자들의 인식을 반영한 것으로 해석된다. 한편, 최근 기준 지표금리의 변경에 따른 통화정책의 효과성을 살펴보기 위해 지표금리 변경시점을 전후로 하여 금융시장에서의 단기금리 변경이 채권시장의 수익률곡선의 형태에 미치는 효과를 분석해 보았다. 분석 결과, 금융시장에서의 대표적인 단기금리인 콜금리와 채권시장에서의 단기금리인 초단기이자율 간의 괴리가 지표금리 변경 이전과 비교하여 크게 확대된 점을 발견할 수 있었다. 이러한 괴리 확대가 새로운 기준금리에 대한 운용겸험 미숙에 연유한 것인지, 최근의 국제금융시장 불안에 따른 예외적인 경우인지는 현 단계에서는 명확히 결론짓기 어려우나 통화정책의 유효성을 제고하기 위해서는 이러한 괴리를 축소하는 통화정책 운용이 필요할 것이다.

• 유통과학연구
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• 제11권10호
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• pp.55-62
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• 2013

Purpose - The purpose of this study is to suggest a risk factor that significantly explains foreign currency risk premia. In recent years, some studies have found that the performance of the simultaneous consumption risk model improves considerably when tested on foreign currency portfolios, which are constructed based on the international interest rates differentials. However, this paper focuses on the long-run consumption risk factor. In our empirical research, we found that the real excess returns of high interest rate currency portfolios depreciate on average, when the future American long-run consumption growth rate appears low. This makes the high interest rate currency portfolios have relatively high risk premia. Meanwhile, the real excess returns of low interest rate currency portfolios appreciate on average, under the same conditions, which results in relatively low risk premia for these portfolios. Therefore, this long-run consumption risk factor might explain why low interest rate currencies do not appreciate as much as the interest rate differential, and why high interest rate currencies do not depreciate as much as the interest rate differential. Research design, data, methodology - In our explanation, we provide new evidence on the success of long-run consumption risks in currency risk premia by focusing on the long-run consumption risks borne by American representative investors. To uncover the hidden link between exchange rates and long-run consumption growth, we set the eight currency portfolios as our basic assets, which have been built based on the foreign interest rates of eighty countries. As these eight currency portfolios are rebalanced every year, the first group always contains the lowest interest rate currencies, and the last group contains the highest interest rate currencies. Against these basic eight currency portfolios, we estimate the long-run consumption risk model. We use recursive utility framework and the stochastic discount factor that depends on the present value of expected future consumption growth rates. We find that our model is optimized in the two-year period of constructing the durable consumption expectation factor. Our main results surprisingly surpass the performance of the existing benchmark simultaneous consumption model in terms of R², relatively risk aversion coefficient γ, and p-value of J-test. Results - The performance of our model is superior. R², relatively risk aversion coefficient γ, and p-value of J-test of our long-run durable consumption model are 90%, 93%, and 65.5%, respectively, while those of EZ-DCAPM are 87%, 113%, and 62.8%, respectively. Thus, we can speculate that the risk premia in foreign currency markets have been determined by the long-run consumption risk. Conclusions - The aggregate long-run consumption growth risk explains a large part of the average change in the real excess returns of foreign currency portfolios. The real excess returns of high interest rate currency portfolios depreciate on average when American long-run consumption growth rate is low, and the real excess returns of low interest rate currency portfolios appreciate under the same conditions. Thus, the low interest rate currency portfolios allow investors to hedge against aggregate long-run consumption growth risk.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• 토지주택연구
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• 제11권2호
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• pp.33-46
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• 2020

As the fastest growing office transaction volume in Korea, there's been a need for development of indicators to accurately diagnose the office capital market. The purpose of this paper is experimentally calculate to the office price index for effective benchmark indices in Seoul. The quantitative methodology used a Case-Shiller Repeat Sales Model (1991), based on actual multiple office transaction dataset with over minimum 1,653 ㎡ from Q3 1999 to 4Q 2019 in the case of 1,536 buildings within Seoul Metropolitan. In addition, the collected historical data and spatial statistical analysis tools were treated with the SAS 9.4 and ArcGIS 10.7 programs. The main empirical results of research are briefly summarized as follows; First, Seoul office price index was estimated to be 344.3 point (2001.1Q=100.0P) at the end of 2019, and has more than tripled over the past two decades. it means that the sales price of office per 3.3 ㎡ has consistently risen more than 12% every year since 2000, which is far above the indices for apartment housing index, announced by the MOLIT (2009). Second, between quarterly and annual office price index for the two-step estimation of the MIT Real Estate Research Center (MIT/CRE), T, L, AL variables have statistically significant coefficient (Beta) all of the mode l (p<0.01). Third, it was possible to produce a more stable office price index against the basic index by using the Moore-Penrose's pseoudo inverse technique at low transaction frequency. Fourth, as an lagging indicators, the office price index is closely related to key macroeconomic indicators, such as GDP(+), KOSPI(+), interest rates (5-year KTB, -). This facts indicate that long-term office investment tends to outperform other financial assets owing to high return and low risk pattern. In conclusion, these findings are practically meaningful to presenting an new office price index that increases accuracy and then attempting to preliminary applications for the case of Seoul. Moreover, it can provide sincerely useful benchmark about investing an office and predicting changes of the sales price among market participants (e.g. policy maker, investor, landlord, tenant, user) in the future.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권8호
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• pp.664-672
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• 2009

최근 영상 데이터의 효율적인 표현 및 처리를 위해 텐서를 사용하는 연구가 관심을 모으고 있다. 본 연구에서는 2차 텐서로 표현된 데이터를 효과적으로 분류하기 위한 시스템을 개발하는 것을 목적으로 한다. 이를 위해 먼저 일반적인 벡터 데이터에 대해 개발되어진 클래스 요인과 환경 요인으로 이루어진 데이터 생성 모델을 확장하여 2차 텐서로 표현된 영상에 적합한 데이터 생성 모델을 정의하고, 이에 적합한 유사도 함수를 제안하였다. 제안하는 유사도 함수는 행렬정규분포를 이용하여 환경 요인의 확률분포를 추정함으로써 얻을 수 있다. 여러 벤치마크 데이터들을 이용하여 실험한 결과 2차 텐서를 사용함으로써 벡터 형태의 표현방식을 사용하는 것에 비해 분류율이 향상되었음을 확인하였다. 또한 제안하는 유사도 함수가 다른 기존의 유사도 함수에 비해 영상 데이터에 적합함을 확인할 수 있었다.