DETERMINING FACTORS FOR 10-YEAR LOCAL CURRENCY SOVEREIGN BONDS YIELD WITH DYNAMIC REGRESSION MODEL

INDONESIA CASE

  • Dea Avega Editya Kementerian Keuangan
Keywords: sovereign bonds, machine learning, forecasting, dynamic linear regression, ARIMA

Abstract

Sovereign bonds, particularly Local Currency Bonds (LCB) of 10-year tenure, had a strategic role in economy, thus understanding factors affecting its yield’s movement would help government to maintain economic stability.

This paper empirically study Indonesia’s 10-year LCB and its relationship with several factors; US Treasury (UST) yield, credit default swap (CDS), foreign ownership, central bank's policy rate (policy rate), exchange rate, volatility index (VIX) and primary dealers' trading behavior. The relationship was modelled using Dynamic Regression Model (DRM), with ARIMA errors to absorb the dynamics. Evaluation on the model's performance was conducted by making prediction on the real LCB yield’s movement during 2021.

The best model containing 10y-UST yield and its lag-1, 5y-CDS and its lag-1, exchange rate, policy rate and ARIMA errors of AR(1) and AR(2) could perform well in predicting the real yield. This study confirmed that 10y-UST and its lag-1 are the main drivers for the LCB yield’s movement, along with compelling influence of the exchange rate.

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Published
2022-09-26
How to Cite
Editya, D. (2022). DETERMINING FACTORS FOR 10-YEAR LOCAL CURRENCY SOVEREIGN BONDS YIELD WITH DYNAMIC REGRESSION MODEL. Jurnal BPPK : Badan Pendidikan Dan Pelatihan Keuangan, 15(1), 35-48. https://doi.org/https://doi.org/10.48108/jurnalbppk.v15i1.715
Section
Articles