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3 lut 2022 · This paper proposes a novel bond return (price or yield curve) prediction methodology, unifying the classical no arbitrage pricing framework, which is ubiquitou.
In this course project, we use a dataset describing the previous 10 trades of a large number of bonds among other relevant descriptive metrics to predict future bond prices. Each of 762,678 bonds in the dataset is described by a total of 61 attributes, including a ground truth trade price.
1 sty 2024 · In this paper, I identify a novel channel through which anticipated asset sales affect prices in a predictable manner. More specifically, I develop a theory that explains why bond prices gradually decline in a predictable manner prior to Treasury auctions.
26 wrz 2023 · This article presents a novel algorithm that accurately predicts market trends and identifies trading entry points for US 30-year Treasury bonds. The proposed method employs a hybrid approach, integrating a 1-dimensional convolutional neural network (1DCNN), long-short term memory (LSTM), and XGBoost algorithms.
19 sty 2020 · Investors aim to search for higher investment returns, to estimate longer-run returns, and to model risk premia. Policymakers attempt to predict future rates to help drive appropriate monetary and fiscal measures in order to maintain a healthy market and macroeconomy.
1 sty 2022 · Treasury Bond Price and Yield Curve Prediction via No Arbitrage Arguments and Machine Learning. January 2022. SSRN Electronic Journal. DOI: 10.2139/ssrn.4024209. Authors: Weiping Zhang....
Abstract. The literature on using yield curves to forecast recessions customarily uses 10-year{three-month Treasury yield spread without veri cation on the pair selection. This study investigates whether the predictive ability of spread can be improved by letting a machine learning algorithm identify the best maturity pair and coe cients.
