Littérature scientifique sur le sujet « Intra-horizon risk »

We propose a consistent and computationally efficient 2-step methodology for the estimation of multidimensional non-Gaussian asset models built using Lévy processes. The proposed framework allows for dependence between assets and different tail behaviors and jump structures for each asset. Our procedure can be applied to portfolios with a large number of assets because it is immune to estimation dimensionality problems. Simulations show good finite sample properties and significant efficiency gains. This method is especially relevant for risk management purposes such as, for example, the computation of portfolio Value at Risk and intra-horizon Value at Risk, as we show in detail in an empirical illustration.

Purpose This article aims to analyze the performance and risk of landmark building in the housing sector and to evaluate their usefulness for a diversification strategy. Design/methodology/approach After comparing summary statistics on the performance of landmark building with respect to other types of housing investments, the article evaluates their usefulness for a diversification strategy. The role of landmark buildings is studied using the modern portfolio theory and evaluating the role of this type of asset in the optimal asset allocation. The analysis is performed considering both the risk/return trade-off in a one-year and a multiple-year time horizon. Findings The results show that a landmark building can be a good investment opportunity, especially for high-risk/return investors. A not perfect correlation of the returns of this asset class with other types of housing investments implies the existence of a minimum investment in this asset class for almost all portfolios on the efficient frontier. Results are robust with respect to the length of the investment time horizon. Originality/value The article presents a unique analysis of intra-housing market diversification opportunities focusing on the role of landmark building in the portfolio construction. Empirical evidence supports the hypothesis that real estate investors can take advantage of investing in landmark buildings in the residential sector as well because there are no reasons to limit such investments to trophy buildings in the office and commercial sectors.

Mackerel, the third largest oil field in the Gippsland Basin, is a mature field with over 80 per cent of reserves produced from 18 original development wells.The initial Mackerel development was based on a fairly simplistic reservoir model incorporating the results of the four exploration wells. The net to gross was anticipated at 90 per cent throughout the reservoir and no significant permeability barriers were expected. After 10 years of production a review of field performance indicated the reservoir was not as homogenous as first anticipated.Redevelopment of the Mackerel Field began in 1990 following the acquisition of the first of two high resolution 3D surveys and culminated in the drilling of 18 additional wells from the Mackerel platform during 1993 and 1994. It was these 3D surveys which changed the entire reservoir model of Mackerel to one of a far more compartmentalised nature.Seismic attribute analysis, when calibrated to 2D forward modelling was used to predict intra-reser- voir seals and the distribution of poorer quality reservoir; both not previously recognised over the field. The truncation points of the intra-reservoir seals against the main field-wide trapping unconformity were accurately mapped using seismic attributes and image enhancement techniques such as ER Mapper. Previously undetectable fault extensions, with throw around 10 m, can act as partial flow barriers and were recognised for the first time via 'sun-angle illumination' of azimuth maps. This allowed optimum well placement and helped explain historical field performance. Horizon slicing techniques and the calibration of volume attributes were used to establish depositional environments and seal capacity of the predicted intra-reservoir seals.The drilling results have shown that over the production life of the Mackerel Field the reservoir consists of a number of drainage compartments, each separated by seismically resolvable intra-res- ervoir seals.The redevelopment of the Mackerel field increased production rate by 18 thousand barrels per day (kBD) in 1993, and proved additional capture reserves of which approximately 40 percent can be directly attributed to the 3D seismic data and the applied interpretation techniques.

This study examines the dynamic nature of return spillover across Bitcoins indices and foreign exchange pairs denominated in 6 major trading currencies. The findings of spillover index, Spillover Asymmetry Measure (SAM) and frequency connectedness methodologies indicate that return spillover across Bitcoin markets and foreign exchange pairs dominated in six major trading currencies is very low. The intra-market return spillover for the Bitcoin markets and foreign exchange pairs is found to be significant. Presence of asymmetry in the return spillover is also found. Evidence indicates that return spillover are dominated in short horizon, with significant spillover occurring within 4 days of an event. The low integration of Bitcoin markets with the foreign exchange markets provide significant implication for portfolio diversification and risk minimization.

An epidemiological model, which describes the transmission dynamics of SARS-CoV-2 under specific consideration of the incubation period including the population with subclinical infections and being infective is presented. The COVID-19 epidemic in Greece was explored through a Monte Carlo uncertainty analysis framework, and the optimal values for the parameters that determined the transmission dynamics could be obtained before, during, and after the interventions to control the epidemic. The dynamic change of the fraction of asymptomatic individuals was shown. The analysis of the modelling results at the intra-annual climatic scale allowed for in depth investigation of the transmission dynamics of SARS-CoV-2 and the significance and relative importance of the model parameters. Moreover, the analysis at this scale incorporated the exploration of the forecast horizon and its variability. Three discrete peaks were found in the transmission rates throughout the investigated period (15 February–15 December 2020). Two of them corresponded to the timing of the spring and autumn epidemic waves while the third one occurred in mid-summer, implying that relaxation of social distancing and increased mobility may have a strong effect on rekindling the epidemic dynamics offsetting positive effects from factors such as decreased household crowding and increased environmental ultraviolet radiation. In addition, the epidemiological state was found to constitute a significant indicator of the forecast reliability horizon, spanning from as low as few days to more than four weeks. Embedding the model in an ensemble framework may extend the predictability horizon. Therefore, it may contribute to the accuracy of health risk assessment and inform public health decision making of more efficient control measures.

Recent studies undertaken by Hydro-Québec evaluate three aspects of the integration of wind generation on their system reliability/security. In an operations setting, the impacts on intra-hourly operating reserves and on extra-hourly balancing reserves are examined. On an operations planning horizon, the wind power capacity credit is evaluated for winter peak loading conditions, when very cold temperatures risk disabling part of the wind generation. Depending on the study, various mathematical tools were used to generate the statistical characteristics of the load and anticipated wind generation: time-series analysis, wind simulation at new/future wind plant sites, power system simulation and a posteriori determination of forecast errors. However, in each case the measure used to quantify the impact of wind generation has been related to the change in the variance of the total system uncertainty as a result of the addition of wind power generation.

BackgroundHydroxychloroquine (HCQ) is a key treatment for patients with lupus, but the major long-term toxicity is HCQ retinopathy. A large cross-sectional study found a prevalence of HCQ retinopathy of 7.5% overall and 5 times higher odds associated with HCQ dose >5 mg/kg/day, which led to ophthalmology guidelines recommending the avoidance of HCQ dosing >5 mg/kg.1 However, whether this dosing recommendation is applicable to the future risk of HCQ retinopathy is unknown, as is the incidence of severe bullseye retinopathy vs. the mild, pre-symptomatic stage. Furthermore, recent studies have indicated that the use of lower doses of HCQ may increase the risk of lupus flares and hospitalizations.2ObjectivesTo determine the incidence of HCQ retinopathy associated with long-term HCQ use and compare them according to HCQ dose.MethodsWe emulated a hypothetical target trial using observational data3 from the US integrated health network Kaiser Permanente Northern California to compare two HCQ weight-based dosing strategies, >5 vs ≤5 mg/kg/day, based on dispensed tablets per year. A secondary analysis evaluated >80% of prescription days covered by dispensed tablets per year with HCQ dose >5 vs ≤5 mg/kg. We included 4,677 patients who initiated and continued HCQ for at least 5 years between 1997-2020. We emulated randomization of treatment strategy by cloning each subject and assigning a replicate to each treatment group.3 We censored replicates if and when they deviated from the assigned treatment group, assessed as the average dose in the first 5 years and annually thereafter. We used inverse probability weighting to account for censoring. The primary outcome was HCQ retinopathy, assessed by expert adjudication of spectral domain-optical coherence tomography (SD-OCT) and graded by severity. All SD-OCTs were prospectively reviewed by an expert ophthalmologist (RM), and a second expert ophthalmologist (MM) reviewed all abnormal scans and a random subset of normal scans. We assessed intra-rater reliability of SD-OCT findings. We used pooled logistic regression to estimate the cumulative incidence of HCQ retinopathy for each HCQ dose strategy from initiation. The odds ratios approximated hazard ratios (HRs) because the outcome at each one-year time block is <5%.ResultsAmong 4,677 patients, the mean age at HCQ initiation was 52 years; 83% were female. The racial/ethnic composition included 51% non-Hispanic White, 19% Hispanic, 14% Asian, and 11% Black patients. 756 (16.2%) and 3,921 (83.8%) patients initiated HCQ with the primary definition of the treatment strategies >5 and ≤5 mg/kg/day, respectively. The weighted kappa was 0.80 for SD-OCT reliability. 164 patients developed HCQ retinopathy (100 mild, 38 moderate, and 26 severe cases). The cumulative incidence of retinopathy over 18 years was 37.6% for >5 and 5.7% for ≤5mg/kg of HCQ in our primary analysis. The corresponding risk was 26.5% for >5 and 3.2% for ≤5 mg/kg in our secondary analysis using >80% of prescription days. Compared with ≤5 mg/kg of HCQ, the HRs of retinopathy were 9.65 (95% CI 5.73-16.65) and 10.79 (95% CI 6.40-20.07) for >5 mg/kg using the primary and secondary definitions of HCQ dose categories, respectively (Figure 1).ConclusionThe risk of HCQ retinopathy associated with long-term adherence to >5 mg/kg dosing was high, approximately 10 times that of ≤5 mg/kg dosing. However, most cases identified during the study were mild and pre-symptomatic, supporting the value of regular screening. These data should be incorporated into individualized decisions about long-term use of HCQ.References[1]Melles RB, Marmor MF. The risk of toxic retinopathy in patients on long-term hydroxychloroquine therapy. JAMA Ophthalmol 2014;132(12):1453-60[2]Almeida-Brasil CC et al. Flares after hydroxychloroquine reduction or discontinuation: results from the SLICC inception cohort. Ann Rheum Dis 2021 Dec 15, epub ahead of print[3]Hernán MA, Robins JM. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available. Am J Epidemiol 2016;183(8):758-64Disclosure of InterestsApril Jorge: None declared, Ronald Melles: None declared, Michael Marmor: None declared, Carol Conell: None declared, Baijun Zhou: None declared, Jingbo Niu: None declared, Yuqing Zhang: None declared, Hyon Choi Consultant of: Ironwood, Selecta, Horizon, Takeda, Kowa, and Vaxart., Grant/research support from: Ironwood and Horizon

As one of the members of the Organisation of Islamic Corporation (OIC), Indonesia has excellent trade prospects. Therefore, this study has a purpose to examine the impact of macroeconomics factors on trade between Indonesia and intra-OIC countries. The variables of macroeconomics in this study consist of country risks, inflation, exchange rate, oil price, and economic growth. Quantitative is the right method for this study, applying Ordinary Least Square (OLS) regression with the help of EViews. The data used for the analysis is a time horizon with annual frequency from 1986 to 2016. Furthermore, finding shows that almost all variables of macroeconomics play an insignificant role in determining the trade between Indonesia and Islamic countries. However, the oil price is the only variable to show its contribution towards trade between Indonesia and intra-OIC countries. The results indicate that macroeconomic variables do not contribute to the key decisions for conducting trade internationally. Political factors and bilateral treaties become better variables to explain Indonesia's trade with other Islamic countries.

Multidimensional asset models based on Lévy processes have been introduced to meet the necessity of capturing market shocks using more refined distribution assumptions compared to the standard Gaussian framework. In particular, along with accurately modeling marginal distributions of asset returns, capturing the dependence structure among them is of paramount importance, for example, to correctly price derivatives written on more than one underlying asset. Most of the literature on multivariate Lévy models focuses in fact on pricing multi-asset products, which is also the case of the model introduced in Ballotta and Bonfiglioli (2014). Believing that risk and portfolio management applications may benefit from a better description of the joint distribution of the returns as well, we choose to adopt Ballotta and Bonfiglioli (2014) model for asset allocation purposes and we empirically test its performances. We choose this model since, besides its flexibility and the ability to properly capture the dependence among assets, it is simple, relatively parsimonious and it has an immediate and intuitive interpretation, retaining a high degree of mathematical tractability. In particular we test two specifications of the general model, assuming respectively a pure jump process, more precisely the normal inverse Gaussian process, or a jump-diffusion process, precisely Merton’s jump-diffusion process, for all the components involved in the model construction. To estimate the model we propose a simple and easy-to-implement three-step procedure, which we assess via simulations, comparing the results with those obtained through a more computationally intensive one-step maximum likelihood estimation. We empirically test portfolio construction based on multivariate Lévy models assuming a standard utility maximization framework; for the exponential utility function we get a closed form expression for the expected utility, while for other utility functions (we choose to test the power one) we resort to numerical approximations. Among the benchmark strategies, we consider in our study what we call a ‘non-parametric optimization approach’, based on Gaussian kernel estimation of the portfolio return distribution, which to our knowledge has never been used. A different approach to allocation decisions aims at minimizing portfolio riskiness requiring a minimum expected return. Following Rockafellar and Uryasev (2000), we describe how to solve this optimization problem in our multivariate Lévy framework, when risk is measured by CVaR. Moreover we present formulas and methods to compute, as efficiently as possible, some downside risk measures for portfolios made of assets following the multivariate Lévy model by Ballotta and Bonfiglioli (2014). More precisely, we consider traditional risk measures (VaR and CVaR), the corresponding marginal measures, which evaluate their sensibility to portfolio weights alterations, and intra-horizon risk measures, which take into account the magnitude of losses that can incur before the end of the investment horizon. Formulas for CVaR in monetary terms and marginal measures, together with our approach to evaluate intra-horizon risk, are among the original contributions of this work.

博士
國立政治大學
財務管理研究所
99
Traditional risk measures, such as Value-at-Risk and Expected Shortfall, generally estimated only the possible losses at the end of the holding period, but ignored the risks before the end of the time horizon. However, from the experiences of recent financial crises, we have learned that such risk measures failed to reflect all the risks that investors actually faced during the holding period. In view of this, this dissertation contains three essays to discuss the measurement of intra-horizon risks and their applications in risk management. In the first essay, we reviewed the existing literature regarding “intra-horizon risks” and examined the contributions of the three intra-horizon risk measures: Intra-Horizon Value-at-Risk (IHVaR), Intra-Horizon Expected Shortfall (IHES), and Intra-Horizon Probability of Breaching (IHPB). From the numerical examples we found that among the three intra-horizon risk measures, the probability of breaching a certain threshold during the time horizon (IHPB), would be the most promising one to bring additional contributions to the existing risk measurement models. Next, in the second essay we applied the intra-horizon risk into credit risk modeling to take into account the risks of obligors’ early defaults or liquidations. Given the probabilities of default (PD) and losses given default (LGD), we estimated the worst-case probabilities of default (WCPD) for corporate exposures with different credit ratings, and compared our results with the IRB formula set forth in the Basel II. The comparisons showed that when considering the intra-horizon risks, the exposures with better credit ratings would suffer from larger negative impacts, and the evolving path of the systematic risk factor would play critical role. Specifically, when assuming a linear decreasing path for the systematic risk factor, the intra-horizon risk model would have roughly equivalent results to the IRB formula. But, when assuing a worst-at-any-time path, the capital charges would be definitely higher than the IRB formula; especially for the investment grade exposures, the required capital might increase by more than 9.5%. Finally, in the last essay we tried to implement the intra-horizon risk to the trading strategies that would be almost riskless when invesors could hold the positions to maturity, such as arbitrage or spot/futures hedging strategies. There have been many papers or financial crisis events confirming that these strategies should be risky and might cause serious problems to the financial systems. Therefore, we derived an IHVaR generalized approximation formula based on the generalized Brownian bridge stochastic process, to facilitate measure the maximum losses that investors might suffer during the time horizon under a certain confidence level. Then, using the S&P 500 index arbitrage strategy with a holding period of 3 months to empirically test the results, we found that our IHVaR generalized approximation has performed better than the historical simulation approach since 1990.