# A melhor ferramenta para a sua pesquisa, trabalho e TCC!

## Constructing good deals in discrete time arbitrage-free dynamic pricing models

## The Behavior of Savings and Asset Prices When Preferences and Beliefs are Heterogeneous

## Liquidity Clienteles : Transaction Costs and Investment Decisions of Individual Investors

## Building proxies that capture time-variation in expected returns using a VAR approach

## Essays in Financial Economics and Econometrics

## Intertemporal Substitutability, Risk Aversion and Asset Prices

## Mean-Variance Hedging for Pricing European Options Under Assumption of Non-continuous Trading

## A New Approach to Model Free Option Pricing

## Theory of Information Pricing

## Pricing Step Options under the CEV and other Solvable Diffusion Models

## Adapted Downhill Simplex Method for Pricing Convertible Bonds

## Minimax Option Pricing Meets Black-Scholes in the Limit

## Multi-Moments Method for Portfolio Management: Generalized Capital Asset Pricing Model in Homogeneous and Heterogeneous markets

## Pricing with coherent risk

## G-Doob-Meyer Decomposition and its Application in Bid-Ask Pricing for American Contingent Claim Under Knightian Uncertainty

## Application of simplest random walk algorithms for pricing barrier options

## Fast Numerical Method for Pricing of Variable Annuities with Guaranteed Minimum Withdrawal Benefit under Optimal Withdrawal Strategy

## Efficient Pricing of CPPI using Markov Operators

## Option Pricing in Multivariate Stochastic Volatility Models of OU Type

## High-Frequency Financial Volatility and the Pricing of Volatility Risk

The idea that integrates parts of this dissertation is that high-frequency data allow for more precise and robust methods for forecasting financial volatility and elucidating the role of volatility in forming asset prices. Thus, the first two chapters compare the performance of model-free forecasts specifically designed to employ high-frequency data with the performance of "classical" forecasts developed for daily data. The final chapter of the dissertation incorporates high-frequency data to verify the predictions of asset pricing models about the risk-return relationships at the very shortest horizons. The results are arranged in the following order.

Chapter 1 presents the analytical comparison of feasible reduced-form forecasts designed to employ high-frequency data and model-based forecasts updated to use high-frequency data. The prediction errors of both forecast groups are calculated using the ESV-representation of Meddahi (2003), which allows one to generalize the statements from this analysis to a wider class of volatility processes. The results show that reduced-form forecasts outperform model-based forecasts at longer horizons and perform just as well for day-ahead forecasts.

Chapter 2 expands the conclusions from Chapter 1 to economic measures of forecast performance. These performance measures are constructed within a microeconomic framework that mimics the decision making process of a variance trader who uses volatility forecasts to predict the future profitability of a trade. The results support the theoretical predictions of Chapter 1.

Chapter 3 is co-authored with Professor Tim Bollerslev and Professor George Tauchen. It extends the "long-run risk" model of Bansal and Yaron(2004) to consistently price volatility risks and to be applicable to high-frequency data. The hypothesis at the outset is that while financial volatility is a long-memory process (it exhibits long-range dependence)...