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Open AccessArticle

Autoencoder-Based Three-Factor Model for the Yield Curve of Japanese Government Bonds and a Trading Strategy

1
Department of Systems Innovations, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan
2
Financial and Economic Research Center, Nomura Securities Co. Ltd., Tokyo 100-8130, Japan
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2020, 13(4), 82; https://doi.org/10.3390/jrfm13040082
Received: 2 March 2020 / Revised: 20 April 2020 / Accepted: 21 April 2020 / Published: 23 April 2020
(This article belongs to the Special Issue AI and Financial Markets)
Interest rates are representative indicators that reflect the degree of economic activity. The yield curve, which combines government bond interest rates by maturity, fluctuates to reflect various macroeconomic factors. Central bank monetary policy is one of the significant factors influencing interest rate markets. Generally, when the economy slows down, the central bank tries to stimulate the economy by lowering the policy rate to establish an environment in which companies and individuals can easily raise funds. In Japan, the shape of the yield curve has changed significantly in recent years following major changes in monetary policy. Therefore, an increasing need exists for a model that can flexibly respond to the various shapes of yield curves. In this research, we construct a three-factor model to represent the Japanese yield curve using the machine learning approach of an autoencoder. In addition, we focus on the model parameters of the intermediate layer of the neural network that constitute the autoencoder and confirm that the three automatically generated factors represent the “Level,” “Curvature,” and “Slope” of the yield curve. Furthermore, we develop a long–short strategy for Japanese government bonds by setting their valuation with the autoencoder, and we confirm good performance compared with the trend-follow investment strategy. View Full-Text
Keywords: yield curve; term structure of interest rates; machine learning; autoencoder; interpretability yield curve; term structure of interest rates; machine learning; autoencoder; interpretability
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Suimon, Y.; Sakaji, H.; Izumi, K.; Matsushima, H. Autoencoder-Based Three-Factor Model for the Yield Curve of Japanese Government Bonds and a Trading Strategy. J. Risk Financial Manag. 2020, 13, 82.

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