Joint value at risk: a new conditional risk measure

In this PhD thesis a new firm level conditional risk measure is developed. It is named Joint Value at Risk (JVaR) and is defined as a quantile of a conditional distribution of interest, where the conditioning event is a latent upper tail event. It addresses the problem of how risk changes under extreme volatility scenarios. The properties of JVaR are studied based on a stochastic volatility representation of the underlying process. We prove that JVaR is leverage consistent, i.e. it is an increasing function of the dependence parameter in the stochastic representation. A feasible class of nonparametric M-estimators is introduced by exploiting the elicitability of quantiles and the stochastic ordering theory. Consistency and asymptotic normality of the two stage M-estimator are derived, and a simulation study is reported to illustrate its finite-sample properties. Parametric estimation methods are also discussed. The relation with the VaR is exploited to introduce a volatility contribution measure, and a tail risk measure is also proposed. The analysis of the dynamic JVaR is presented based on asymmetric stochastic volatility models. Empirical results with S&P500 data show that accounting for extreme volatility levels is relevant to better characterize the evolution of risk. The work is complemented by a review of the literature, where we provide an overview on quantile risk measures, elicitable functionals and several stochastic orderings.

Flexibility and firm value: the role of inventories

In the present thesis I study the contribution to firm value of inventories management from a risk management perspective. I find a significant contribution of inventories to the value of risk management especially through the operating flexibility channel. In contrast, I do not find evidence supporting the view of inventories a reserve of liquidity. Inventories substitute, albeit not perfectly, derivatives or cash holdings. The substitution between hedging with derivatives and inventory is moderated by the correlation between cash flow and the underlying asset in the derivative contract. Hedge ratios increase with the effectiveness of derivatives. The decision to hedge with cash holdings or inventories is strongly influenced by the degree of complementarity between production factors and by cash flow volatility. In addition, I provide a risk management based explanation of the secular substitution between inventories and cash holdings documented, among others, in Bates et al. (2009), Journal of Finance. In a sample of U.S. firms between 1980 and 2006, I empirically confirm the negative relation between inventories and cash and provide evidence on the poor performance of investment cash flow sensitivities as a measure of financial constraints also in the case of inventories investment. This result can be explained by firms' scarce reliance on inventories as a reserve of liquidity. Finally, as an extension of my study, I contrast with empirical data the theoretical predictions of a model on the integrated management of inventories, trade credit and cash holdings.

Essays in Financial Econometrics

The first paper sheds light on the informational content of high frequency data and daily data. I assess the economic value of the two family models comparing their performance in forecasting asset volatility through the Value at Risk metric. In running the comparison this paper introduces two key assumptions: jumps in prices and leverage effect in volatility dynamics. Findings suggest that high frequency data models do not exhibit a superior performance over daily data models. In the second paper, building on Majewski et al. (2015), I propose an affine-discrete time model, labeled VARG-J, which is characterized by a multifactor volatility specification. In the VARG-J model volatility experiences periods of extreme movements through a jump factor modeled as an Autoregressive Gamma Zero process. The estimation under historical measure is done by quasi-maximum likelihood and the Extended Kalman Filter. This strategy allows to filter out both volatility factors introducing a measurement equation that relates the Realized Volatility to latent volatility. The risk premia parameters are calibrated using call options written on S&P500 Index. The results clearly illustrate the important contribution of the jump factor in the pricing performance of options and the economic significance of the volatility jump risk premia. In the third paper, I analyze whether there is empirical evidence of contagion at the bank level, measuring the direction and the size of contagion transmission between European markets. In order to understand and quantify the contagion transmission on banking market, I estimate the econometric model by Aït-Sahalia et al. (2015) in which contagion is defined as the within and between countries transmission of shocks and asset returns are directly modeled as a Hawkes jump diffusion process. The empirical analysis indicates that there is a clear evidence of contagion from Greece to European countries as well as self-contagion in all countries.

Emerging contaminants in agricultural ecosystems: impact of selected pharmaceutical on water and soil ecology and pratical implications

Pharmaceuticals are useful tools to prevent and treat human and animal diseases. Following administration, a significant fraction of pharmaceuticals is excreted unaltered into faeces and urine and may enter the aquatic ecosystem and agricultural soil through irrigation with recycled water, constituting a significant source of emerging contaminants into the environment. Understanding major factors influencing their environmental fate is consequently needed to value the risk, reduce contamination, and set up bioremediation technologies. The antiviral drug Tamiflu (oseltamivir carboxylate, OC) has received recent attention due to the potential use as a first line defence against H5N1 and H1N1 influenza viruses. Research has shown that OC is not removed during conventional wastewater treatments, thus having the potential to enter surface water bodies. A series of laboratory experiments investigated the fate and the removal of OC in surface water systems in Italy and Japan and in a municipal wastewater treatment plant. A preliminary laboratory study investigated the persistence of the active antiviral drug in water samples from an irrigation canal in northern Italy (Canale Emiliano Romagnolo). After an initial rapid decrease, OC concentration slowly decreased during the remaining incubation period. Approximately 65% of the initial OC amount remained in water at the end of the 36-day incubation period. A negligible amount of OC was lost both from sterilized water and from sterilized water/sediment samples, suggesting a significant role of microbial degradation. Stimulating microbial processes by the addition of sediments resulted in reduced OC persistence. Presence of OC (1.5 μg mL-1) did not significantly affect the metabolic potential of the water microbial population, that was estimated by glyphosate and metolachlor mineralization. In contrast, OC caused an initial transient decrease in the size of the indigenous microbial population of water samples. A second laboratory study focused on basic processes governing the environmental fate of OC in surface water from two contrasting aquatic ecosystems of northern Italy, the River Po and the Venice Lagoon. Results of this study confirmed the potential of OC to persist in surface water. However, the addition of 5% of sediments resulted in rapid OC degradation. The estimated half-life of OC in water/sediment of the River Po was 15 days. After three weeks of incubation at 20 °C, more than 8% of 14C-OC evolved as 14CO2 from water/sediment samples of the River Po and Venice Lagoon. OC was moderately retained onto coarse sediments from the two sites. In water/sediment samples of the River Po and Venice Lagoon treated with 14C-OC, more than 30% of the 14C-residues remained water-extractable after three weeks of incubation. The low affinity of OC to sediments suggests that the presence of sediments would not reduce its bioavailability to microbial degradation. Another series of laboratory experiments investigated the fate and the removal of OC in two surface water ecosystems of Japan and in the municipal wastewater treatment plant of the city of Bologna, in Northern Italy. The persistence of OC in surface water ranged from non-detectable degradation to a half-life of 53 days. After 40 days, less than 3% of radiolabeled OC evolved as 14CO2. The presence of sediments (5%) led to a significant increase of OC degradation and of mineralization rates. A more intense mineralization was observed in samples of the wastewater treatment plant when applying a long incubation period (40 days). More precisely, 76% and 37% of the initial radioactivity applied as 14C-OC was recovered as 14CO2 from samples of the biological tank and effluent water, respectively. Two bacterial strains growing on OC as sole carbon source were isolated and used for its removal from synthetic medium and environmental samples, including surface water and wastewater. Inoculation of water and wastewater samples with the two OC-degrading strains showed that mineralization of OC was significantly higher in both inoculated water and wastewater, than in uninoculated controls. Denaturing gradient gel electrophoresis and quantitative PCR analysis showed that OC would not affect the microbial population of surface water and wastewater. The capacity of the ligninolytic fungus Phanerochaete chrysosporium to degrade a wide variety of environmentally persistent xenobiotics has been largely reported in literature. In a series of laboratory experiments, the efficiency of a formulation using P. chrysosporium was evaluated for the removal of selected pharmaceuticals from wastewater samples. Addition of the fungus to samples of the wastewater treatment plant of Bologna significantly increased (P < 0.05) the removal of OC and three antibiotics, erythromycin, sulfamethoxazole, and ciprofloxacin. Similar effects were also observed in effluent water. OC was the most persistent of the four pharmaceuticals. After 30 days of incubation, approximately two times more OC was removed in bioremediated samples than in controls. The highest removal efficiency of the formulation was observed with the antibiotic ciprofloxacin. The studies included environmental aspects of soil contamination with two emerging veterinary contaminants, such as doramectin and oxibendazole, wich are common parasitic treatments in cattle farms.

Outcome a lungo termine dei pazienti pediatrici con rene singolo. Valutazione di marker laboratoristici e strumentali di danno renale

Obiettivi: valutare in pazienti con rene singolo congenito la correlazione tra il filtrato glomerulare misurato con il DTPA (DTPA-VFG) e 1) marker laboratoristici di danno renale (creatinina, cistatinaC, proteinuria) 2) formule per stimare il filtrato glomerulare 3) parametri di valutazione della crescita renale ecografica. Materiali e metodi: Sono stati arruolati 118 pazienti con rene singolo congenito tra 0 e 18 anni. Sono stati valutati a ogni visita altezza, creatinina, cistatinaC, proteinuria e lunghezza ecografica renale. E’ stato calcolato il filtrato stimato con formule basate sulla creatinina (Schwartz), sulla cistatina C (Zappitelli, Filler, Grubb e Bokenkamp) e su entrambe (equazione di Zappitelli). La crescita renale è stata valutata come rapporto lunghezza ecografica/altezza corporea (USL/H), differenza percentuale tra lunghezza renale misurata e attesa per età (delta%) e presenza o meno d’ipertrofia compensatoria. In 74 bambini è stata misurata la DTPA-VFG. Risultati: Il follow-up è di 2.1 ± 0.9 anni. Il 65% sono maschi. Nessun paziente ha sviluppato danno renale cronico. La media del DTPA-VFG era di 135±44ml/min/1.73m², il valore medio della creatinina 0.47±0.17mg/dl e di cistatinaC di 1±0.4mg/L. La lunghezza ecografica renale media era di 100±17 mm, il rapporto USL/H medio di 0.8±0,1 e il delta% di 1,13±11,4, il 66% presentava ipertrofia renale. Le uniche correlazioni significative con DTPA-VFG sono inversa con la creatinina (p=<.001) e lineare con USL/H (p=<.001). Discussione: Lo studio ha mostrato che come per altre nefrouropatie, la creatina e l’ecografia renale siano due strumenti validi per il follow-up dei pazienti con rene singolo congenito. Il limite principale è dovuto al fatto che nessuno dei pazienti ha sviluppato danno renale cronico e pertanto non è stato possibile stabilire dei cutt-off di rischio per parametri quali USL/H.

Dynamics of coastal aquifers: data-driven forecasting and risk analysis

This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

The impact of R&D in firm value across Europe

In this thesis the impact of R&D expenditures on firm market value and stock returns is examined. This is performed in a sample of European listed firms for the period 2000-2009. I apply different linear and GMM econometric estimations for testing the impact of R&D on market prices and construct country portfolios based on firms’ R&D expenditure to market capitalization ratio for studying the effect of R&D on stock returns. The results confirm that more innovative firms have a better market valuation,investors consider R&D as an asset that produces long-term benefits for corporations. The impact of R&D on firm value differs across countries. It is significantly modulated by the financial and legal environment where firms operate. Other firm and industry characteristics seem to play a determinant role when investors value R&D. First, only larger firms with lower financial leverage that operate in highly innovative sectors decide to disclose their R&D investment. Second, the markets assign a premium to small firms, which operate in hi-tech sectors compared to larger enterprises for low-tech industries. On the other hand, I provide empirical evidence indicating that generally highly R&D-intensive firms may enhance mispricing problems related to firm valuation. As R&D contributes to the estimation of future stock returns, portfolios that comprise high R&D-intensive stocks may earn significant excess returns compared to the less innovative after controlling for size and book-to-market risk. Further, the most innovative firms are generally more risky in terms of stock volatility but not systematically more risky than low-tech firms. Firms that operate in Continental Europe suffer more mispricing compared to Anglo-Saxon peers but the former are less volatile, other things being equal. The sectors where firms operate are determinant even for the impact of R&D on stock returns; this effect is much stronger in hi-tech industries.

Scenari finanziari e portafogli ottimi: modelli di previsione e strategie per l'asset allocation tattica

Le scelte di asset allocation costituiscono un problema ricorrente per ogni investitore. Quest’ultimo è continuamente impegnato a combinare diverse asset class per giungere ad un investimento coerente con le proprie preferenze. L’esigenza di supportare gli asset manager nello svolgimento delle proprie mansioni ha alimentato nel tempo una vasta letteratura che ha proposto numerose strategie e modelli di portfolio construction. Questa tesi tenta di fornire una rassegna di alcuni modelli innovativi di previsione e di alcune strategie nell’ambito dell’asset allocation tattica, per poi valutarne i risvolti pratici. In primis verificheremo la sussistenza di eventuali relazioni tra la dinamica di alcune variabili macroeconomiche ed i mercati finanziari. Lo scopo è quello di individuare un modello econometrico capace di orientare le strategie dei gestori nella costruzione dei propri portafogli di investimento. L’analisi prende in considerazione il mercato americano, durante un periodo caratterizzato da rapide trasformazioni economiche e da un’elevata volatilità dei prezzi azionari. In secondo luogo verrà esaminata la validità delle strategie di trading momentum e contrarian nei mercati futures, in particolare quelli dell’Eurozona, che ben si prestano all’implementazione delle stesse, grazie all’assenza di vincoli sulle operazioni di shorting ed ai ridotti costi di transazione. Dall’indagine emerge che entrambe le anomalie si presentano con carattere di stabilità. I rendimenti anomali permangono anche qualora vengano utilizzati i tradizionali modelli di asset pricing, quali il CAPM, il modello di Fama e French e quello di Carhart. Infine, utilizzando l’approccio EGARCH-M, verranno formulate previsioni sulla volatilità dei rendimenti dei titoli appartenenti al Dow Jones. Quest’ultime saranno poi utilizzate come input per determinare le views da inserire nel modello di Black e Litterman. I risultati ottenuti, evidenziano, per diversi valori dello scalare tau, extra rendimenti medi del new combined vector superiori al vettore degli extra rendimenti di equilibrio di mercato, seppur con livelli più elevati di rischio.

The cardio-renal axis. Non ST-segment elevation myocardial infarction risk stratification according to renal dysfunction

Background: Chronic kidney disease (CKD) is one of the strongest risk factor for myocardial infarction (MI) and mortality. The aim of this study was to assess the association between renal dysfunction severity, short-term outcomes and the use of in-hospital evidence-based therapies among patients with non–ST-segment elevation myocardial infarction (NSTEMI). Methods: We examined data on 320 patients presenting with NSTEMI to Maggiore’s Emergency Department from 1st Jan 2010 to 31st December 2011. The study patients were classified into two groups according to their baseline glomerular filtration rate (GFR): renal dysfunction (RD) (GFR<60) and non-RD (GFR≥60 ml/min). Patients were then classified into four groups according to their CKD stage (GFR≥60, GFR 59-30, GFR 29-15, GFR <15). Results: Of the 320 patients, 155 (48,4%) had a GFR<60 ml/min at baseline. Compared with patients with a GFR≥60 ml/min, this group was, more likely to be female, to have hypertension, a previous myocardial infarction, stroke or TIA, had higher levels of uric acid and C-reactive protein. They were less likely to receive immediate (first 24 hours) evidence-based therapies. The GFR of RD patients treated appropriately increases on average by 5.5 ml/min/1.73 m2. The length of stay (mean, SD) increased with increasing CKD stage, respectively 5,3 (4,1), 7.0 (6.1), 7.8 (7.0), 9.2 (5.8) (global p <.0001). Females had on average a longer hospitalization than males, regardless of RD. In hospital mortality was higher in RD group (3,25%). Conclusions: The in-hospital mortality not was statically difference among the patients with a GFR value ≥60 ml/min, and patients with a GFR value <60 ml/min. The length of stay increased with increasing CKD stages. Despite patients with RD have more comorbidities then without RD less frequently receive guideline –recommended therapy. The GFR of RD patients treated appropriately improves during hospitalization, but not a level as we expected.

Coastal modelling studies for forecasting and remediation solutions

The coastal area along the Emilia-Romagna (ER), in the Italian side of the northern Adriatic Sea, is considered to implement an unstructured numerical ocean model with the aim to develop innovative tools for the coastal management and a forecasting system for the storm surge risk reduction. The Adriatic Sea has been the focus of several studies because of its peculiar dynamics driven by many forcings acting at basin and local scales. The ER coast is particularly exposed to storm surge events. In particular conditions, winds, tides and seicehs may combine and contribute to the flooding of the coastal area. The global sea level rise expected in the next decades will increase even more the hazard along the ER and Adriatic coast. Reliable Adriatic and Mediterranean scale numerical ocean models are now available to allow the dynamical downscaling of very high-resolution models in limited coastal areas. In this work the numerical ocean model SHYFEM is implemented in the Goro lagoon (named GOLFEM) and along the ER coast (ShyfER) to test innovative solutions against sea related coastal hazards. GOLFEM was succesfully applied to analyze the Goro lagoon dynamics and to assess the dynamical effects of human interventions through the analysis of what-if scenarios. The assessment of storm surge hazard in the Goro lagoon was carried out through the development of an ensemble storm surge forecasting system with GOLFEM using forcing from different operational meteorological and ocean models showing the fundamental importance of the boundary conditions. The ShyfER domain is used to investigate innovative solutions against storm surge related hazard along the ER coast. The seagrass is assessed as a nature-based solution (NBS) for coastal protection under present and future climate conditions. The results show negligible effects on sea level but sensible effects in reducing bottom current velocity.