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Full-Text Articles in Finance and Financial Management

Intraday Algorithmic Trading Using Momentum And Long Short-Term Memory Network Strategies, Andrew R. Whitinger Ii May 2022

Intraday Algorithmic Trading Using Momentum And Long Short-Term Memory Network Strategies, Andrew R. Whitinger Ii

Undergraduate Honors Theses

Intraday stock trading is an infamously difficult and risky strategy. Momentum and reversal strategies and long short-term memory (LSTM) neural networks have been shown to be effective for selecting stocks to buy and sell over time periods of multiple days. To explore whether these strategies can be effective for intraday trading, their implementations were simulated using intraday price data for stocks in the S&P 500 index, collected at 1-second intervals between February 11, 2021 and March 9, 2021 inclusive. The study tested 160 variations of momentum and reversal strategies for profitability in long, short, and market-neutral portfolios, totaling 480 portfolios. …


Esg Investing: From Fad To Force, Erin Cullen Apr 2022

Esg Investing: From Fad To Force, Erin Cullen

Senior Theses

ESG Investing is the application of environmental, social, and governance factors to identify material investment risks and growth opportunities. Though traditionally viewed as non-financial factors, this paper asserts that ESG factors are indeed financially material. This work first surveys the current state of ESG Investing, its shortcomings, and its success despite these inherent issues. Section II adds a new perspective to ESG research by examining the applications of ESG scores in portfolio management. The study conducts t-tests to answer whether the typical holdings of an ESG mutual fund are more sustainable than those of traditional funds. The paper then focuses …


The Adoption Of Cryptocurrency Technology Into The Us Banking Infrastructure, Trevor Melito Apr 2020

The Adoption Of Cryptocurrency Technology Into The Us Banking Infrastructure, Trevor Melito

Senior Theses

This thesis examines the possibility of using Blockchain technology to permanently change the payment structure of the US banking system. First, I examine the current technology that dominates the banking sector. I introduce the most frequently used payments methods including Automatic Clearing House transfers and wire transfers, both domestically and internationally. In addition, I highlight the major players controlling these transactions. Under the current system, frictions between senders and receivers cause billions of dollars in losses each year.

Next, I examine Blockchain’s roots along with some similar cryptocurrency technology, namely Distributed Ledger Technology and Smart Contracts. The transparency, security, and …


Predicting Schedule Duration For Defense Acquisition Programs: Program Initiation To Initial Operational Capability, Christopher A. Jimenez Mar 2016

Predicting Schedule Duration For Defense Acquisition Programs: Program Initiation To Initial Operational Capability, Christopher A. Jimenez

Theses and Dissertations

Accurately predicting the most realistic schedule for a defense acquisitions program is an extremely difficult task considering the inherent risk and uncertainties present in the early stages of a program. We use a multiple regression analysis to predict schedule duration in a defense acquisition program. The prediction scope of our research is limited to predicting schedule duration from program initiation to initial operation capability (IOC).We use the data from 56 programs across all services, which was acquired from a SAR database created by RAND. We were able to achieve an R2 of 0.429 and an Adjusted R2 of 0.384 in …


Diversification And Market Neutral Portfolios In S&P500, Alan S. Agnew Jan 2016

Diversification And Market Neutral Portfolios In S&P500, Alan S. Agnew

Williams Honors College, Honors Research Projects

Our goal is to investigate strategies to deal with the risks associated with holding asset in the stock market. We first deal with risk of holding a specific stock, by the use of diversification. Later, we’ll attempt to deal with the market risk, which is the risk of entire market going up and down. Data used in this project comes from daily adjusted closing price of stocks listed in the S&P500 index ranging from January 3rd, 2000 to December 31st, 2015 and the data is processed using statistical software R.

Sections 2 through 4 of this …


A Stochastic Volatility Model With Leverage Effect And Regime Switching, Hong Jiang Jan 2014

A Stochastic Volatility Model With Leverage Effect And Regime Switching, Hong Jiang

Legacy Theses & Dissertations (2009 - 2024)

Modeling the volatility of asset returns is a very important study in financial economics. Among the time-varying volatility models, the Stochastic Volatility (SV) models are argued to have advantages over the autoregressive conditional heteroskedasticity (ARCH) models. The purpose of this article is to put forward a generalized and flexible Stochastic Volatility model, the Stochastic Volatility Model with Leverage Effect and Regime Switching (SVLR model), which could capture the complex features of financial time series to the most extent.


Socially Responsible Investment In A Changing World, Desheng Wu Dec 2011

Socially Responsible Investment In A Changing World, Desheng Wu

Electronic Thesis and Dissertation Repository

Socially responsible investment funds make up a growing segment of the investment world. This work considers the impact of including SRI in an investor portfolio both normally and during crisis times. Regimes are identified using Markov switching models. This study is based on return data of four indices, namely, the MSCI World Index, S&P 500, Eurostoxx 50, and the socially responsible index - Advanced Sustainable Performance Index (ASPI). The approaches used are portfolio optimization, GARCH and Markov switching models. Our work shows that a socially responsible index is a good asset to keep in a portfolio. Our simulation results suggest …


Modeling And Simulation Of Value -At -Risk In The Financial Market Area, Xiangyin Zheng Apr 2006

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 …