Showing 1 - 2 of 2 Items

Extreme Value Theory and Backtest Overfitting in Finance

Date: 2015-05-01

Creator: Daniel C Byrnes

Access: Open access

In order to identify potentially profitable investment strategies, hedge funds and asset managers can use historical market data to simulate a strategy's performance, a process known as backtesting. While the abundance of historical stock price data and powerful computing technologies has made it feasible to run millions of simulations in a short period of time, this process may produce statistically insignificant results in the form of false positives. As the number of configurations of a strategy increases, it becomes more likely that some of the configurations will perform well by chance alone. The phenomenon of backtest overfitting occurs when a model interprets market idiosyncrasies as signal rather than noise, and is often not taken into account in the strategy selection process. As a result, the finance industry and academic literature are rife with skill-less strategies that have no capability of beating the market. This paper explores the development of a minimum criterion that managers and investors can use during the backtesting process in order to increase confidence that a strategy's performance is not the result of pure chance. To do this we will use extreme value theory to determine the probability of observing a specific result, or something more extreme than this result, given that multiple configurations of a strategy were tested.


Modeling the Development & Expression of Political Opinion: A Zallerian Approach

Date: 2024-01-01

Creator: Avery C Ellis

Access: Open access

Research focused on John Zaller's famous RAS model of political opinion formation and change from "The Nature and Origins of Mass Opinion" (1992). Analyzed the mathematical and psychological underpinnings of the model, the first paper to do so in over fifteen years and the first to do so through an analysis of motivated reasoning and Bayesian reasoning. Synthesized existing critiques of Zaller's model and other literature to suggest ways to build on Zaller, utilizing fundamental reunderstandings of opinions and messages from political and mathematical perspectives. Found verification for Zaller's model, confirming its value, but also found support for the proposed RAIS model, which suggests foundational changes in the way citizens interact with information in the current political environment. Confirmed the utility of a Zallerian framework for analyzing shifts in mass opinion over time and suggested ways to improve the creation of surveys and polls for understanding elections and reported opinions on issues.