Asset Management: Identifying and Evaluating our Roadway System

Historically SCDOT ranks in the top 10 each year for highway conditions and cost-effectiveness as rated by the Reason Foundation. With billions of dollars invested and billions to be invested it makes sense to invest the public's tax dollars as wisely as possible. Therefore, assessing what we have or better yet what condition what we have is in can be vital to public safety and setting priorities. The focus of this project is on the maintenance responsibility of Roadway Inspection as outlined in SCDOT Engineering Directive Memorandum #8. This memorandum is a portion of the way SCDOT provides for the safety of the traveling public and keeps South Carolina's most expensive asset in working order.

Latent Variable Models for Stochastic Discount Factors.

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

Crescimento do consumo e a estrutura a termo de taxa de juros: um estudo voltado para o caso brasileiro

Tendo por base o trabalho realizado por Hyde e Sherif (2010) com dados do mercado inglês, foi desenvolvido estudo com o objetivo de avaliar a capacidade do spread de curto e longo prazo da taxa de juros de funcionar como indicador do crescimento futuro do consumo no Brasil. Tanto Hyde e Sherif (2010) como outros estudos realizados em países desenvolvidos indicaram relação positiva entre o spread de juros de curto e longo prazo e o crescimento do consumo. Entretanto, as análises empíricas realizadas neste estudo para o caso brasileiro, apresentaram resultados divergentes do esperado pela teoria, indicando relação negativa entre o spread de juros e o crescimento do consumo. Em algumas análises, os estudos não indicaram relação entre as variáveis. Foram discutidas possíveis razões para estes resultados contraintuitivos, tais como tamanho reduzido da amostra, nível da taxa de juros no Brasil e liquidez do mercado futuro de juros. Adicionalmente foram analisados os modelos teóricos C-CAPM (Consumption-based asset pricing model) e o modelo de consumo habitual desenvolvido por Campbell e Cochrane (1999) com a adaptação proposta por Wachter (2006). Os resultados encontrados no modelo C-CAPM divergiram do esperado, já que a estimativa do coeficiente relativo de aversão ao risco apresentou sinal negativo. Por outro lado, os resultados obtidos no modelo de Wachter (2006) ficaram em linha com o esperado na teoria, tanto em relação à significância dos parâmetros como aos respectivos sinais e magnitudes.

Factores económicos do risco sistemático nas carteiras de investimento: o caso português

Dissertação de mest. em Ciências Económicas e Empresariais, Unidade de Ciências Económicas e Empresariais, Univ. do Algarve, 1996

Size anomalies in EU bank stock returns

Mestrado em Finanças

Bank audit fees and asset securitization risks

Using the lens of audit pricing, we provide insights into auditors’ behaviors in relation to the risk of asset securitizations to bank holding companies in a period encompassing the Global Financial Crisis (GFC) and the introduction of the accounting standards FAS 166 and FAS 167. Using US bank holding company data from 2003 to 2011, we find significant and positive associations between asset securitization risks and audit fees. We find that auditors appear to focus on different aspects of asset securitization risks after the onset of the GFC, and increase their attention to the systemic risks facing bank holding companies in general. After the implementation of FAS 166 and FAS 167, which removed the discretion to treat asset securitizations as sales and required the consolidation of the accounts of special purpose entities, asset securitization risks no longer have a significant effect on audit fees.

Electricity pricing in New Zealand and the Australian State of Queensland: Accounting for the impact of sector restructuring

The electricity industries of New Zealand (NZ) and the Australian state of Queensland have undergone substantial structural and regulatory reform with the common intent to improve economic efficiency. Deregulation and privatisation have been key elements of the reform but have been approached differently by each jurisdiction. This study traces the link between structural and regulatory regimes and asset valuation, profits and, ultimately, pricing. The study finds that key drivers in recent price increases are the government-owned generation and retail sector in NZ and the government-owned distribution sector in Queensland. It is concluded that, contrary to the rationale for the imposition of regulatory controls in a nonmarket environment, the regulatory regimes appear to have contributed to higher rather than lower pricing structures.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Essays on energy derivatives pricing and financial risk management

This thesis consists of an introductory chapter (essay I) and five more empirical essays on electricity markets and CO2 spot price behaviour, derivatives pricing analysis and hedging. Essay I presents the structure of the thesis and electricity markets functioning and characteristics, as well as the type of products traded, to be analyzed on the following essays. In the second essay we conduct an empirical study on co-movements in electricity markets resorting to wavelet analysis, discussing long-term dynamics and markets integration. Essay three is about hedging performance and multiscale relationships in the German electricity spot and futures markets, also using wavelet analysis. We concentrate the investigation on the relationship between coherence evolution and hedge ratio analysis, on a time-frequency-scale approach, between spot and futures which conditions the effectiveness of the hedging strategy. Essays four, five and six are interrelated between them and with the other two previous essays given the nature of the commodity analyzed, CO2 emission allowances, traded in electricity markets. Relationships between electricity prices, primary energy fuel prices and carbon dioxide permits are analyzed on essay four. The efficiency of the European market for allowances is examined taking into account markets heterogeneity. Essay five analyzes stylized statistical properties of the recent traded asset CO2 emission allowances, for spot and futures returns, examining also the relation linking convenience yield and risk premium, for the German European Energy Exchange (EEX) between October 2005 and October 2009. The study was conducted through empirical estimations of CO2 allowances risk premium, convenience yield, and their relation. Future prices from an ex-post perspective are examined to show evidence for significant negative risk premium, or else a positive forward premium. Finally, essay six analyzes emission allowances futures hedging effectiveness, providing evidence for utility gains increases with investor’s preference over risk. Deregulation of electricity markets has led to higher uncertainty in electricity prices and by presenting these essays we try to shed new lights about structuring, pricing and hedging in this type of markets.

Risk Aversion, Intertemporal Substitution, and Option Pricing

This paper develops a general stochastic framework and an equilibrium asset pricing model that make clear how attitudes towards intertemporal substitution and risk matter for option pricing. In particular, we show under which statistical conditions option pricing formulas are not preference-free, in other words, when preferences are not hidden in the stock and bond prices as they are in the standard Black and Scholes (BS) or Hull and White (HW) pricing formulas. The dependence of option prices on preference parameters comes from several instantaneous causality effects such as the so-called leverage effect. We also emphasize that the most standard asset pricing models (CAPM for the stock and BS or HW preference-free option pricing) are valid under the same stochastic setting (typically the absence of leverage effect), regardless of preference parameter values. Even though we propose a general non-preference-free option pricing formula, we always keep in mind that the BS formula is dominant both as a theoretical reference model and as a tool for practitioners. Another contribution of the paper is to characterize why the BS formula is such a benchmark. We show that, as soon as we are ready to accept a basic property of option prices, namely their homogeneity of degree one with respect to the pair formed by the underlying stock price and the strike price, the necessary statistical hypotheses for homogeneity provide BS-shaped option prices in equilibrium. This BS-shaped option-pricing formula allows us to derive interesting characterizations of the volatility smile, that is, the pattern of BS implicit volatilities as a function of the option moneyness. First, the asymmetry of the smile is shown to be equivalent to a particular form of asymmetry of the equivalent martingale measure. Second, this asymmetry appears precisely when there is either a premium on an instantaneous interest rate risk or on a generalized leverage effect or both, in other words, whenever the option pricing formula is not preference-free. Therefore, the main conclusion of our analysis for practitioners should be that an asymmetric smile is indicative of the relevance of preference parameters to price options.

A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks

We propose a nonparametric method for estimating derivative financial asset pricing formulae using learning networks. To demonstrate feasibility, we first simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis functions, multilayer perceptrons, and projection pursuit. To illustrate practical relevance, we also apply our approach to S&P 500 futures options data from 1987 to 1991.

Stock return comovements and integration within the Latin American integrated market

Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.

Analytic approximations for multi-asset option pricing

We derive general analytic approximations for pricing European basket and rainbow options on N assets. The key idea is to express the option’s price as a sum of prices of various compound exchange options, each with different pairs of subordinate multi- or single-asset options. The underlying asset prices are assumed to follow lognormal processes, although our results can be extended to certain other price processes for the underlying. For some multi-asset options a strong condition holds, whereby each compound exchange option is equivalent to a standard single-asset option under a modified measure, and in such cases an almost exact analytic price exists. More generally, approximate analytic prices for multi-asset options are derived using a weak lognormality condition, where the approximation stems from making constant volatility assumptions on the price processes that drive the prices of the subordinate basket options. The analytic formulae for multi-asset option prices, and their Greeks, are defined in a recursive framework. For instance, the option delta is defined in terms of the delta relative to subordinate multi-asset options, and the deltas of these subordinate options with respect to the underlying assets. Simulations test the accuracy of our approximations, given some assumed values for the asset volatilities and correlations. Finally, a calibration algorithm is proposed and illustrated.

Equity pricing in the mining sector: evidence from NYSE and LSE

The study examines the Capital Asset Pricing Model (CAPM) for the mining sector using weekly stock returns from 27 companies traded on the New York Stock Exchange (NYSE) or on the London Stock Exchange (LSE) for the period of December 2008 to December 2010. The results support the use of the CAPM for the allocation of risk to companies. Most companies involved in precious metals (particularly gold), which have a beta value less than unity (Table 1), have been actuated as shelter values during the financial crisis. Values of R2 do not shown very explanatory power of fitted models (R2 < 70 %). Estimated coefficients beta are not sufficient to determine the expected returns on securities but the results of the tests conducted on sample data for the period analysed do not appear to clearly reject the CAPM