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Languages : en
Pages :
Book Description
Three Essays on Improving Financial Risk Estimation, Forecasting and Backtesting
Author: Three Essays on Improving Financial Risk Estimation, Forecasting and Backtesting
Author: Sebastian BayerThree Essays on Estimation, Forecasting and Evaluation of Financial Risk
Author: Timo DimitriadisThree Essays on Using High Frequency Data in Estimating Financial Risks
Author: Lidan GrossmassThree Essays on High Frequency Financial Data and Their Use for Risk Management
Author: Maria PacurarPublisher:
ISBN:
Category : Monte Carlo method
Languages : en
Pages : 0
Book Description
Three Essays on Financial Risk
Author: Kai YaoThree Essays on Financial Risks Using High Frequency Data
Author: Serge Luther Nyawa WomoPublisher:
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Category :
Languages : en
Pages : 0
Book Description
This thesis is about financial risks and high frequency data, with a particular focus on financial systemic risk, the risk of high dimensional portfolios and market microstructure noise. It is organized on three chapters. The first chapter provides a continuous time reduced-form model for the propagation of negative idiosyncratic shocks within a financial system. Using common factors and mutually exciting jumps both in price and volatility, we distinguish between sources of systemic failure such as macro risk drivers, connectedness and contagion. The estimation procedure relies on the GMM approach and takes advantage of high frequency data. We use models' parameters to define weighted, directed networks for shock transmission, and we provide new measures for the financial system fragility. We construct paths for the propagation of shocks, firstly within a number of key US banks and insurance companies, and secondly within the nine largest S&P sectors during the period 2000-2014. We find that beyond common factors, systemic dependency has two related but distinct channels: price and volatility jumps. In the second chapter, we develop a new factor-based estimator of the realized covolatility matrix, applicable in situations when the number of assets is large and the high-frequency data are contaminated with microstructure noises. Our estimator relies on the assumption of a factor structure for the noise component, separate from the latent systematic risk factors that characterize the cross-sectional variation in the frictionless returns. The new estimator provides theoretically more efficient and finite-sample more accurate estimates of large-scale integrated covolatility, correlation, and inverse covolatility matrices than other recently developed realized estimation procedures. These theoretical and simulation-based findings are further corroborated by an empirical application related to portfolio allocation and risk minimization involving several hundred individual stocks. The last chapter presents a factor-based methodology to estimate microstructure noise characteristics and frictionless prices under a high dimensional setup. We rely on factor assumptions both in latent returns and microstructure noise. The methodology is able to estimate rotations of common factors, loading coefficients and volatilities in microstructure noise for a huge number of stocks. Using stocks included in the S&P500 during the period spanning January 2007 to December 2011, we estimate microstructure noise common factors and compare them to some market-wide liquidity measures computed from real financial variables. We obtain that: the first factor is correlated to the average spread and the average number of shares outstanding; the second and third factors are related to the spread; the fourth and fifth factors are significantly linked to the closing log-price. In addition, volatilities of microstructure noise factors are widely explained by the average spread, the average volume, the average number of trades and the average trade size.
Three Essays on Estimation and Dynamic Modelling of Multivariate Market Risks Using High Frequency Financial Data
Author: Valeri VoevThree Essays on Estimating, Filtering, and Predicting Financial Volatility
Author: Christian MücherThree Essays on the Risk and Distribution of a Portfolio's Future Losses
Author: Wei HePublisher:
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Category :
Languages : en
Pages :
Book Description
This Ph.D. dissertation contains three individual and internally related essays. The first essay applies the least-squares Monte-Carlo (LSM) methodology to derive the distribution of the exotic option values at a future time. LSM presents a powerful statistical procedure that efficiently yields derivative distributions for exotic options that do not possess analytic solutions. By means of several examples, using options with closed-from solutions, this essay demonstrates the ability of LSM to produce excellent estimates of derivative distribution at a reasonable computational cost. The second and third essays compare two of the major credit risk portfolio models used by two prominent financial companies: J. P. Morgan's CreditMetrics and Credit Swiss First Boston's CreditRisk+. The second essay compares the two models from a methodological and an empirical point of view. Factor Analysis is utilized to link the different input data employed by these two models. The third essay creates a hypothetical world in which the true transition matrices are known so that a benchmark distribution of portfolio loss is derived to evaluate the model's performance. The results suggest that despite the fact that the recommendations made by each approach to a financial institution trying to determine how much economic capital to hold is different, these two models perform equally well when credit-rating-change risk is eliminated from the CreditMetrics approach.