US QE and the Indian Bond Market

Paul, Moumita; Reddy, Kalluru Siva

doi:10.1007/s40953-021-00257-9

Cited by 2 publications

(3 citation statements)

References 51 publications

(25 reference statements)

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“…However, Indian bond markets have spillover effects, with negative consequences. The RBI's monetary policy autonomy has partially disappeared due to asset mispricing in bond markets [8]. Based on the above literature review, we conclude that the bond market during the post epidemic period is unique, however there are few studies analyze on this aspect of the market.…”

Section: Introductionmentioning

confidence: 90%

China's Bond Market: The Current Situation, Problems, and Countermeasures

Zhou

2023

AEMPS

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It is undeniable that the bond market plays a key role in the social economy as a whole. Economic development and the state of the bond market often reflect the state of the country's financial markets. Bond markets in China have developed rapidly and have a large financing capacity. In recent years, however, the volatility of the bonds in China has gradually increased due to epidemics, policies and funds, etc. The bond market has undergone a drastic adjustment. This paper describes the current bond market situation in China, analyzes the problems, and proposes solutions for the market. The main problems are the credit risks in bond rating and the impact of political risks on bond market. This paper provides advice on credit risk from the perspective of creating a credit environment, improving data quality, and strengthening regulation. This study has a positive impact on China's bond market's development.

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Section: Introductionmentioning

confidence: 90%

China's Bond Market: The Current Situation, Problems, and Countermeasures

Zhou

2023

AEMPS

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“…Bond markets are the third basic component of financial systems, according to Thumrongvit, Kim, and Pyun (2013) and are becoming more and more important for the growth of the financial sector. Paul and Reddy (2022) elucidated how the financial sector grew enormously as it developed, satisfying the demands of the public and private domains. A portion of this rise coul d come from the bond market.…”

Section: Financial Marketmentioning

confidence: 99%

“…To ascertain the significance, the study also applies robustness checks that consider the date, frequency, and dissemination of the news. Paul and Reddy (2022) use an autoregressive distributed lag (ARDL) bounds-testing co-integration method to look at short-and long-term effects of US quantitative easing (QE) on the benchmark 10-year Indian government bond rate. The analysis indicates that in the absence of QE, yields would have been less volatile.…”

Section: Traditional Statistical Techniquesmentioning

confidence: 99%

Neural network and machine learning use cases: Indian bond market predictions

Antony,

Natarajan

2024

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This study examines machine learning techniques to investigate how artificial intelligence (AI) affects predicting future trends in the bond market. The bond market offers a global perspective on capital costs for a business by establishing the fair value of the bond issue, which is based on multiple factors. The asset price market, which has employed machine learning (ML) and deep learning (DL) techniques to address the primary forecasting difficulty, surprisingly plays a significant role in predicting future bond market returns. As an outcome, if this gap can be forecast, it can act as the bond market's data-driven long-term direction and yield additional profits. Daily security-specific data for the 10-to-3-year Indian Treasury Bond (ITB) was gathered from 2013 to 2022 and is available in the global government bonds database. The researchers looked at how well the auto-regressive integrated moving average (ARIMA), linear regression, and deep recurrent neural network-long short-term memory (DLSTM) models could predict bond yields and returns in future bond markets. The empirical results demonstrate that the DLSTM models most fairly predict the price of government bonds over both the short and longer horizons when compared to ARIMA and linear regression.

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US QE and the Indian Bond Market

Cited by 2 publications

References 51 publications

China's Bond Market: The Current Situation, Problems, and Countermeasures

China's Bond Market: The Current Situation, Problems, and Countermeasures

Neural network and machine learning use cases: Indian bond market predictions

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