No-arbitrage one-factor term structure models in zero- or negative-lower-bound environments

  • 847 Views
  • 118 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

One-factor no-arbitrage term structure models where the instantaneous interest rate follows either the process proposed by Vasicek (1977) or by Cox, Ingersoll, and Ross (1985), commonly known as CIR, are parsimonious and analytically tractable. Models based on the original CIR process have the important characteristic of allowing for a time-varying conditional interest rate volatility but are undefined in negative interest rate environments. A Shifted-CIR no-arbitrage term structure model, where the instantaneous interest rate is given by the sum of a constant lower bound and a non-negative CIR-like process, allows for negative yields and benefits from similar tractability of the original CIR model. Based on the U.S. and German yield curve data, the Vasicek and Shifted-CIR specifications, both considering constant and time-varying risk premia, are compared in terms of information criteria and forecasting ability. Information criteria prefer the Shifted-CIR specification to models based on the Vasicek process. It also provides similar or better in-sample and out-of-sample forecasting ability of future yield curve movements. Introducing a time variation of the interest rate risk premium in no-arbitrage one-factor term structure models is instead not recommended, as it provides worse information criteria and forecasting performance.

view full abstract hide full abstract
    • Figure 1. In-sample and out-of-sample 6-month-ahead yield variation forecasting ability in comparison to the random walk hypothesis
    • Figure 2: In-sample and out-of-sample short-term rate volatility forecasting
    • Figure 3. Out-of-sample parameter estimates for the Vasicek models
    • Figure 4. Out-of-sample parameter estimates for the S-CIR models with non-positive lower bound
    • Figure 5. Out-of-sample parameter estimates for the S-CIR models with an unconstrained lower bound
    • Figure 6. Out-of-sample 6-month-ahead yield variation forecasting ability in comparison to the random walk hypothesis (sub-samples pre-2008 and post-2008)
    • Table 1. In-sample parameter estimates
    • Table 2. Data and model-implied averages and volatilities of bond yields
    • Conceptualization
      Andrea Tarelli
    • Data curation
      Andrea Tarelli
    • Formal Analysis
      Andrea Tarelli
    • Investigation
      Andrea Tarelli
    • Methodology
      Andrea Tarelli
    • Project administration
      Andrea Tarelli
    • Software
      Andrea Tarelli
    • Supervision
      Andrea Tarelli
    • Validation
      Andrea Tarelli
    • Visualization
      Andrea Tarelli
    • Writing – original draft
      Andrea Tarelli
    • Writing – review & editing
      Andrea Tarelli
Related Articles

  • The place and perspectives of Ukraine in international integration space

    Vitalina BabenkoORCID Researcher ID, Maryna PasmorORCID , Juliia Pankova , Mykhailo Sidorov doi: http://dx.doi.org/10.21511/ppm.15(1).2017.08
    Problems and Perspectives in Management Volume 15, 2017         Issue #1         pp. 80-92 Views: 1545 Downloads: 247 TO CITE АНОТАЦІЯ

    The resulting indexes for integration processes state development analysis were formed. The integral indexes illustrating integration state were calculated on the basis of member countries of BRICS and Ukraine. It provided the possibility to evaluate socioeconomic state of the countries from the point of view of international integration and create integration processes development scenarios. The strategic directions of integration processes development for Ukraine and member countries of BRICS were formed.

  • Forecasting the level of financial security of the country (on the example of Ukraine)

    Józef Antoni HaberORCID , Alina BukhtiarovaORCID Researcher ID, Svitlana ChornaORCID , Olesia Iastremska , Tetiana Bolgar doi: http://dx.doi.org/10.21511/imfi.15(3).2018.25
    Investment Management and Financial Innovations Volume 15, 2018         Issue #3         pp. 304-317 Views: 1328 Downloads: 316 TO CITE АНОТАЦІЯ

    In the conditions of functioning of economic relations, which arise between subjects of the financial system of Ukraine, the question of creating safe conditions for their activity is increasingly being raised. Attention is paid to the investigation of the state of financial security of the country as a component of economic security, in terms of its key elements, which allows attention to the most important indicators and to develop measures to prevent existing threats.
    The purpose of the paper is to forecast the level of financial security of the country based on regression analysis of impacts factors. The object of the study is the financial system as a mechanism, which is aimed at the activities of financial security subjects of the country to ensure its proper level. As a result of the regression analysis, it was found that changing in the country’s banking security by 1% will decrease the overall financial security index by 0.04 points, while the non-banking market will grow by 0.07 and the monetary component will decrease by 0.51.
    Based on the calculation of the arithmetic mean of absolute deviations of independent variables, the estimated value of Ukraine’s financial security level is calculated, which is 40.09% in 2018.
    Proposals for improving the “Methodological Recommendations for Calculating the Level of Economic Security of Ukraine” will help to solve the problem of mathematical substantiation of the choice of indicators for assessing financial security, minimize risks, eliminate subjectivity and improve the efficiency and the quality of the country’s financial security assessment methodology.
    The article deals with the issues of the financial component of economic security as the main element of ensuring sustainable financial development of the country.

  • Assessment of public welfare in Ukraine in the context of the COVID-19 pandemic and economy digitalization

    Serhii KozlovskyiORCID Researcher ID, Iaroslav PetrunenkoORCID Researcher ID, Viktoriia BaidalaORCID Researcher ID, Viktoriia MyronchukORCID Researcher ID, Tetiana KulinichORCID Researcher ID doi: http://dx.doi.org/10.21511/ppm.19(1).2021.35
    Problems and Perspectives in Management Volume 19, 2021         Issue #1         pp. 416-431 Views: 1230 Downloads: 802 TO CITE АНОТАЦІЯ

    With the emergence of the global COVID-19 pandemic in 2019, a process of transformation of the modern economic system took place, which requires new approaches to assessing economic processes. One of such processes is the assessment of public welfare. The purpose of this study is to develop an approach to assessing the level of public welfare of the population of Ukraine in the context of the COVID-19 pandemic and economy digitalization. To solve this problem, the methods of artificial intelligence, in particular the method of fuzzy sets theory, which allows using the incomplete information and making high-quality forecast calculations, are used. The factors influencing the level of public welfare during the COVID-19 pandemic have been identified. These are the following factors: gross domestic product, poverty rate, welfare index, human development index, subsistence level, and indicators that characterize the COVID-19 pandemic (i.e. the total number of COVID-19 cases, the total number of deaths from COVID-19, and the total number of vaccinations from COVID-19 in Ukraine). Using fuzzy sets theory, an economic-mathematical model for assessing the level of public welfare in the context of the COVID-19 pandemic in Ukraine was built. Two-dimensional dependences of the level of public welfare of Ukraine in the context of the COVID-19 pandemic on indicators such as gross domestic product, subsistence level, and the total number of cases of COVID-19 in Ukraine were obtained. The results of the study established that the level of public welfare in the context of the COVID-19 pandemic on the 0-100 scale is predicted to be as follows points: 2021 – 17, 2022 – 23, 2023 – 27, 2024 – 19, 2025 – 35 and will not meet international standards.

Download Preview
Close
Investment Management and Financial Innovations
Investment Management and Financial Innovations