Essays In Machine Learning In Finance
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Essays On Machine Learning And Finance
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Author : Matthias Schnaubelt
language : en
Publisher:
Release Date : 2020
Essays On Machine Learning And Finance written by Matthias Schnaubelt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Essays In Machine Learning In Finance
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Author : Ye Ye
language : en
Publisher:
Release Date : 2022
Essays In Machine Learning In Finance written by Ye Ye and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
The bond market is one of the largest financial markets, with $52.9 trillion of debt outstanding for the US market as of 2021. The implied interest rate for borrowing at different horizons is the fundamental object for this market. However, a complete set of interest is not observed and must be estimated from the noisy market data. In two papers, we develop machine learning methods to precisely estimate the term structure of interest rates and to understand and manage interest-rate related risks. In the first paper, we introduce a robust, flexible and easy-to-implement method for estimating the yield curve from Treasury securities. This method is non-parametric and optimally learns basis functions in reproducing Hilbert spaces with an economically motivated smoothness reward. We provide a closed-form solution of our machine learning estimator as a simple kernel ridge regression, which is straightforward and fast to implement. We show in an extensive empirical study on U.S. Treasury securities, that our method strongly dominates all parametric and non-parametric benchmarks, which positions our method as the new standard for yield curve estimation. In the second paper, we develop a sparse factor model for bond returns, that unifies non- parametric term structure estimation with cross-sectional factor modeling. Building on the modeling framework of the first paper, we estimate an optimal set of sparse basis functions, which maps into a cross-sectional conditional factor model. Our estimated factors are investable portfolios of traded assets, that replicate the full term structure and are sufficient to hedge against interest rate changes. In an extensive empirical study on U.S. Treasury securities, we show that the term structure of excess returns is well explained by four factors. We introduce a new measure for the time-varying complexity of bond markets based on the exposure to higher-order factors.
Three Essays On Machine Learning In Empirical Finance
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Author : Jinhua Wang
language : en
Publisher:
Release Date : 2022
Three Essays On Machine Learning In Empirical Finance written by Jinhua Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Essays In Machine Learning And Natural Language Processing In Finance
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Author : Lars Moritz Scherrmann
language : en
Publisher:
Release Date : 2024
Essays In Machine Learning And Natural Language Processing In Finance written by Lars Moritz Scherrmann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
Essays On Machine Learning And Price Impact In Institutional Finance
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Author : Zihan Lin (Researcher in machine learning)
language : en
Publisher:
Release Date : 2022
Essays On Machine Learning And Price Impact In Institutional Finance written by Zihan Lin (Researcher in machine learning) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Institutional investors play crucial roles in financial markets. First, they delegate investment for individual investors. We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance, and the returns of predictive long-short portfolios are higher following a period of high sentiment. Second, institutional investors provide liquidity to investor demand. We hypothesize and provide evidence that prices are more inelastic when demand is less diversifiable. We decompose order-flow imbalances into components with varying degrees of diversifiability and estimate their price impacts. Our findings are consistent with weaker liquidity provision at less diversifiable levels.
Essays On Machine Learning In Empirical Finance And Accounting Research
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Author : Daniel Marcel Metko
language : en
Publisher:
Release Date : 2022
Essays On Machine Learning In Empirical Finance And Accounting Research written by Daniel Marcel Metko and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Essays On Conditional Asset Pricing And Machine Learning In Finance
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Author : Stephen Owen
language : en
Publisher:
Release Date : 2021
Essays On Conditional Asset Pricing And Machine Learning In Finance written by Stephen Owen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
In recent years there has been wide-scale access to improved statistical estimation techniques and the implementation of such techniques in financial economics. In this dissertation, I provide two brief overviews of the evolution of linear factor models in asset pricing and machine learning in finance. I then provide four research essays that implement machine learning in financial economic research settings. The first essay revisits tests of the conditional Capital Asset Pricing Model in an international context using multivariate generalized autoregressive conditional heteroskedasticity techniques. The second essay studies the use of hierarchical clustering in mean-variance optimal portfolio management. The third essay proposes a novel paragraph embedding technique that leverages the question-and-answer structure of earnings announcement calls to model the similarity between documents. The fourth and final essay studies the impact that dodgy managers have on idiosyncratic security performance.
Essays On Information Transmission Machine Learning In Finance
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Author : Sasan Mansouri
language : en
Publisher:
Release Date : 2021
Essays On Information Transmission Machine Learning In Finance written by Sasan Mansouri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Essay On Big Data And Machine Learning In Finance
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Author : Gunsu Son
language : en
Publisher:
Release Date : 2023
Essay On Big Data And Machine Learning In Finance written by Gunsu Son and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Despite structural differences between the options and stock markets, few studies have discussed the behavior and impact of high-frequency traders (HFTs) in the options market. Options exchanges identify high-frequency/algorithmic traders as Professional Customers (PCs). In this study, we use granular data that identifies trades by customers, PCs, and Market Makers (MMs). We find that PCs mainly trade as a counterparty to customers, similar to MMs. However, the liquidity provision by PCs leads to order flow toxicity: PCs use a "cream skimming" strategy that imposes adverse selection costs on MMs. PCs mainly trade with uninformed customers, most likely leveraging their speed and algorithmic advantage. PCs provide less liquidity when the market and stock volatility are high. Customer call option trades made with PCs have one-tenth of price impact and no return or volatility predictability, while there is significant price impact in addition to return and volatility predictability when executed against MMs during the next 30 minutes. Our finding on HFTs' non-arbitrage channel of order flow toxicity is new and suggests that the role of HFTs should be better understood in the context of the options market structure.
Essays On The Suitability Of Machine Learning Algorithms For Financial Forecasts
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Author : Marko Kureljusic
language : en
Publisher:
Release Date : 2022
Essays On The Suitability Of Machine Learning Algorithms For Financial Forecasts written by Marko Kureljusic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.