Low cost home ownership: legal issues of the shared ownership lease

Analysis of the decision in Richardson v Midland Heart Ltd (formally Focus Homes Options) [2008] L&TR 31

The importance of the volatility risk premium for volatility forecasting

In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.

An empirical model comparison for valuing crack spread options

In this paper, we investigate the pricing of crack spread options. Particular emphasis is placed on the question of whether univariate modeling of the crack spread or explicit modeling of the two underlyings is preferable. Therefore, we contrast a bivariate GARCH volatility model for cointegrated underlyings with the alternative of modeling the crack spread directly. Conducting an empirical analysis of crude oil/heating oil and crude oil/gasoline crack spread options traded on the New York Mercantile Exchange, the more simplistic univariate approach is found to be superior with respect to option pricing performance.

Volatility modelling in the forex market: an empirical evaluation

We compare three frequently used volatility modelling techniques: GARCH, Markovian switching and cumulative daily volatility models. Our primary goal is to highlight a practical and systematic way to measure the relative effectiveness of these techniques. Evaluation comprises the analysis of the validity of the statistical requirements of the various models and their performance in simple options hedging strategies. The latter puts them to test in a "real life" application. Though there was not much difference between the three techniques, a tendency in favour of the cumulative daily volatility estimates, based on tick data, seems dear. As the improvement is not very big, the message for the practitioner - out of the restricted evidence of our experiment - is that he will probably not be losing much if working with the Markovian switching method. This highlights that, in terms of volatility estimation, no clear winner exists among the more sophisticated techniques.

Estimating the term structure of volatility and fixed income derivative pricing

Estimating the parameters of the instantaneous spot interest rate process is of crucial importance for pricing fixed income derivative securities. This paper presents an estimation for the parameters of the Gaussian interest rate model for pricing fixed income derivatives based on the term structure of volatility. We estimate the term structure of volatility for US treasury rates for the period 1983 - 1995, based on a history of yield curves. We estimate both conditional and first differences term structures of volatility and subsequently estimate the implied parameters of the Gaussian model with non-linear least squares estimation. Results for bond options illustrate the effects of differing parameters in pricing.

The effect of options on coordination

This paper studies how constraints on the timing of actions affect equilibrium in intertemporal coordination problems. The model exhibits a unique symmetric equilibrium in cut-o¤ strategies. The risk-dominant action of the underlying one-shot game is selected when the option to delay effort is commensurate with the option to wait longer for others' actions. The possibility of waiting longer for the actions of others enhances coordination, but the option of delaying one s actions can induce severe coordination failures: if agents are very patient, they might get arbitrarily low expected payoffs even in cases where coordination would yield arbitrarily large returns.

Modeling and predicting the CBOE market volatility index

This paper performs a thorough statistical examination of the time-series properties of the daily market volatility index (VIX) from the Chicago Board Options Exchange (CBOE). The motivation lies not only on the widespread consensus that the VIX is a barometer of the overall market sentiment as to what concerns investors' risk appetite, but also on the fact that there are many trading strategies that rely on the VIX index for hedging and speculative purposes. Preliminary analysis suggests that the VIX index displays long-range dependence. This is well in line with the strong empirical evidence in the literature supporting long memory in both options-implied and realized variances. We thus resort to both parametric and semiparametric heterogeneous autoregressive (HAR) processes for modeling and forecasting purposes. Our main ndings are as follows. First, we con rm the evidence in the literature that there is a negative relationship between the VIX index and the S&P 500 index return as well as a positive contemporaneous link with the volume of the S&P 500 index. Second, the term spread has a slightly negative long-run impact in the VIX index, when possible multicollinearity and endogeneity are controlled for. Finally, we cannot reject the linearity of the above relationships, neither in sample nor out of sample. As for the latter, we actually show that it is pretty hard to beat the pure HAR process because of the very persistent nature of the VIX index.

Do options contain information about excess bond returns ?

There is strong empirical evidence that risk premia in long-term interest rates are time-varying. These risk premia critically depend on interest rate volatility, yet existing research has not examined the im- pact of time-varying volatility on excess returns for long-term bonds. To address this issue, we incorporate interest rate option prices, which are very sensitive to interest rate volatility, into a dynamic model for the term structure of interest rates. We estimate three-factor affine term structure models using both swap rates and interest rate cap prices. When we incorporate option prices, the model better captures interest rate volatility and is better able to predict excess returns for long-term swaps over short-term swaps, both in- and out-of-sample. Our results indicate that interest rate options contain valuable infor- mation about risk premia and interest rate dynamics that cannot be extracted from interest rates alone.

Seeking growth under financial volatility

Includes bibliography

Distributive impact of public policy

Includes bibliography

Macroeconomic policies in times of crisis: options and perspectives

Includes bibliography

Crisis, volatility and fiscal policy in Latin America

Includes bibliography

Mortgage loans and access to housing for low-income households in Latin America

Includes bibliography

Polyculture of Freshwater Angelfish Pterophyllum scalare and Pacific white shrimp Litopenaeus vannamei in low-salinity water

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Low-Cost Ultra-Wide Genotyping Using Roche/454 Pyrosequencing for Surveillance of HIV Drug Resistance

Background: Great efforts have been made to increase accessibility of HIV antiretroviral therapy (ART) in low and middle-income countries. The threat of wide-scale emergence of drug resistance could severely hamper ART scale-up efforts. Population-based surveillance of transmitted HIV drug resistance ensures the use of appropriate first-line regimens to maximize efficacy of ART programs where drug options are limited. However, traditional HIV genotyping is extremely expensive, providing a cost barrier to wide-scale and frequent HIV drug resistance surveillance. Methods/Results: We have developed a low-cost laboratory-scale next-generation sequencing-based genotyping method to monitor drug resistance. We designed primers specifically to amplify protease and reverse transcriptase from Brazilian HIV subtypes and developed a multiplexing scheme using multiplex identifier tags to minimize cost while providing more robust data than traditional genotyping techniques. Using this approach, we characterized drug resistance from plasma in 81 HIV infected individuals collected in Sao Paulo, Brazil. We describe the complexities of analyzing next-generation sequencing data and present a simplified open-source workflow to analyze drug resistance data. From this data, we identified drug resistance mutations in 20% of treatment naive individuals in our cohort, which is similar to frequencies identified using traditional genotyping in Brazilian patient samples. Conclusion: The developed ultra-wide sequencing approach described here allows multiplexing of at least 48 patient samples per sequencing run, 4 times more than the current genotyping method. This method is also 4-fold more sensitive (5% minimal detection frequency vs. 20%) at a cost 3-5 x less than the traditional Sanger-based genotyping method. Lastly, by using a benchtop next-generation sequencer (Roche/454 GS Junior), this approach can be more easily implemented in low-resource settings. This data provides proof-of-concept that next-generation HIV drug resistance genotyping is a feasible and low-cost alternative to current genotyping methods and may be particularly beneficial for in-country surveillance of transmitted drug resistance.