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Finance and Financial Management Commons™
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- Delta sequences (1)
- Finance (1)
- Financial market (1)
- High-frequency estimation (1)
- Kernel estimator (1)
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- Kernel regression (1)
- Machine learning (1)
- Microstructure noise (1)
- Multifactor models (1)
- Pure sciences (1)
- Q-learning (1)
- Regression trees (1)
- Reinforcement learning (1)
- Risk factors (1)
- Risk management (1)
- Securities markets (1)
- Simulation (1)
- Spot volatility (1)
- Statistics (1)
- Time series analysis (1)
- Value-at-risk (1)
Articles 1 - 3 of 3
Full-Text Articles in Finance and Financial Management
Regression Tree Construction For Reinforcement Learning Problems With A General Action Space, Anthony S. Bush Jr
Regression Tree Construction For Reinforcement Learning Problems With A General Action Space, Anthony S. Bush Jr
Electronic Theses and Dissertations
Part of the implementation of Reinforcement Learning is constructing a regression of values against states and actions and using that regression model to optimize over actions for a given state. One such common regression technique is that of a decision tree; or in the case of continuous input, a regression tree. In such a case, we fix the states and optimize over actions; however, standard regression trees do not easily optimize over a subset of the input variables\cite{Card1993}. The technique we propose in this thesis is a hybrid of regression trees and kernel regression. First, a regression tree splits over …
Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, Weixuan Gao
Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, Weixuan Gao
Arts & Sciences Electronic Theses and Dissertations
This thesis studies a unifying class of nonparametric spot volatility estimators proposed by Mancini et. al.(2013). This method is based on delta sequences and is conceived to include many of the existing estimators in the field as special cases. The thesis first surveys the asymptotic theory of the proposed estimators under an infill asymptotic scheme and fixed time horizon, when the state variable follows a Brownian semimartingale. Then, some extensions to include jumps and financial microstructure noise in the observed price process are also presented. The main goal of the thesis is to assess the suitability of the proposed methods …
Modeling And Simulation Of Value -At -Risk In The Financial Market Area, Xiangyin Zheng
Modeling And Simulation Of Value -At -Risk In The Financial Market Area, Xiangyin Zheng
Doctoral Dissertations
Value-at-Risk (VaR) is a statistical approach to measure market risk. It is widely used by banks, securities firms, commodity and energy merchants, and other trading organizations. The main focus of this research is measuring and analyzing market risk by modeling and simulation of Value-at-Risk for portfolios in the financial market area. The objectives are (1) predicting possible future loss for a financial portfolio from VaR measurement, and (2) identifying how the distributions of the risk factors affect the distribution of the portfolio. Results from (1) and (2) provide valuable information for portfolio optimization and risk management.
The model systems chosen …