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thesis.Rmd
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thesis.Rmd
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---
output:
bookdown::pdf_document2:
template: ../template/thesis_template.tex
fig_caption: yes
keep_tex: no
number_sections: yes
toc: true
toc_depth: 2
latex_engine: xelatex
title: "Generative Adversarial Network (GAN) model in Asset Pricing"
author: "Wang Lingjie"
keywords:
"
Generative Adversarial Network, Asset Pricing,
Stochastic Discount Factor, Machine Learning,
Deep Learning, Stock Returns
"
bibliography: ../ref.bib
csl: ../template/apa.csl
nocite: ""
abstract:
"
An important topic in asset pricing is explaining
the variation in expected returns of financial assets.
No-arbitrage pricing theory suggests the idea of a
pricing kernel that governs asset prices.
However, it remains a challenge to estimate the
asset-pricing kernel. The difficulties include (1)
choosing the right factors, (2) estimating the pricing
kernel’s functional form, and (3) selecting the right
portfolio to estimate the kernel.
Recently, @chen_deep_2021 proposed a Generative
Adversarial Network (GAN) model that attempts to solve
all three challenges in a single setup and claim to
achieve the best performance compared to all existing
models.
This paper seeks to empirically validate @chen_deep_2021's
research based on the United States stock data
with the United Kingdom (UK) London Stock Exchange
1998 - 2017 data.
This paper found that the GAN model outperformed
the benchmark four-factor model in terms of Sharpe ratio.
"
# acknowledgement: "acknowledgement.tex"
---
```{r echo=F, warning=F, message=F}
# libraries
library(tidyverse)
library(kableExtra)
```
<!-- introduction -->
# Introduction
\thispagestyle{plain}
```{r, child=("introduction.Rmd")}
```
<!-- literature review -->
# Literature Review
\thispagestyle{plain}
```{r, child=("lit_review.Rmd")}
```
<!-- model -->
# Methodology
\thispagestyle{plain}
```{r, child=("model.Rmd")}
```
<!-- model training -->
# Model Training {#model_training}
\thispagestyle{plain}
```{r, child=("training.Rmd")}
```
<!-- model evaluation -->
# Evaluation metrics
\thispagestyle{plain}
```{r, child=("metrics.Rmd")}
```
<!-- data -->
# Data {#data}
\thispagestyle{plain}
```{r, child=("results/data.Rmd")}
```
<!-- empirical results -->
# Empirical findings
\thispagestyle{plain}
```{r, child=("results.Rmd")}
```
\newpage
# Discussion
\thispagestyle{plain}
```{r, child=("discussion.Rmd")}
```
<!-- conclusion -->
# Conclusion
\thispagestyle{plain}
```{r, child=("conclusion.Rmd")}
```
<!-- references -->
\newpage
# Bibliography
\thispagestyle{plain}