Il risk management tecnico nel trading di portafoglio

Il problema che si cerca di risolvere attraverso la gestione quantitativa del portafoglio è la riduzione del rischio tramite strategie che non dipendano dalla diversificazione dei titoli che compongono il portafoglio. Nel momento in cui si decide di applicare un trading system su un determinato gruppo di asset, il capitale non viene allocato automaticamente su tutti i titoli e si deve affrontare invece un continuo investimento tramite l’apertura dinamica di posizioni sul mercato.Questo significa che la diversificazione non è più una misura adeguata del rischio sostenuto poiché i rendimenti attesi dell’investimento non dipendono più dalle proprietà stesse degli strumenti scelti, ma dalla profittabilità dei segnali generati dalla logica del trading system su questi. Bisogna testare in questo caso le performance del sistema a livello statistico e prevedere anche, per esempio, che l’algoritmo possa generare dei segnali errati che portano a delle posizioni in perdita. Il portafoglio a livello quantitativo deve essere gestito tramite dei trading system che abbiano la possibilità di valutare aspetti globali, come il profitto totale di tutte le posizioni attualmente aperte, o l’intero rischio sostenuto dal capitale gestito. Le decisioni non vengono prese dall’analisi delle prestazioni individuali che la strategia ottiene operando sui singoli titoli. Per affrontare una possibile soluzione a questa problematica si sono quindi selezionati due trading system le cui prestazioni fossero robuste su un intero portafoglio e non solo su determinati titoli. In un successivo momento vengono analizzate le prestazioni del portafoglio aggiungendo ai test due ulteriori strategie di uscita: lo stoploss di portafoglio e il target di portafoglio. Nonostante esse ricalchino idee ampiamente utilizzate per la gestione delle singole posizioni su un titolo, per i test si è deciso di modificarle implementando la gestione globale del capitale all’interno del trading system di portafoglio.

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.

Decision support system for risk management:a case study

This study demonstrates a quantitative approach to construction risk management through analytic hierarchy process and decision tree analysis. All the risk factors are identified, their effects are quantified by determining probability and severity, and various alternative responses are generated with cost implication for mitigating the quantified risks. The expected monetary values are then derived for each alternative in a decision tree framework and subsequent probability analysis aids the decision process in managing risks. The entire methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Analysis of risk management disclosures by Australian publicly listed companies

In the aftermath of the global financial crisis, effective risk management (RM) and its communication to stakeholders are now considered essential components in corporate governance. However, despite the importance of RM communication, it is still unclear how and to what extent disclosures in financial reports can achieve effective communication of RM activities. The situation is hampered by the paucity of international RM Research that captures institution differences in corporate governance standards. The Australian setting provides an ideal environment in which to examine RM communication because the Australian Securities Exchange (ASX) has since 2007 recommended RM disclosures under its principle-based governance rules. The recommendations are contained in Principle 7 of the Corporate Governance Principles and recommendations (ASX CGPR). Accordingly, to assess the effectiveness of the AXS's RM governance principle, this study examines the nature and extent of RM disclosures reported by major ASX-listed firms. Using a mixed method approach (thematic content analysis and a series of regression analysis) we find widespread divergence in disclosure practices and low conformance with the Principle 7 recommendations. Certain corporate governance mechanisms appear to influence some categories of RM dislcosure but equity risk has surprisingly little explanatory power. These results suggest that the RM disclosures practices observed in the Australian setting may not be meeting the objectives of regulators and the needs of stakeholders.

Risk management plan and pharmacovigilance system - biopharmaceuticals: biosimilars.

Editor literario del libro, Giancarlo Nota - All chapters are Open Access articles distributed under the Creative Commons Non Commercial-Share Alike-Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited.

Comparative analysis of corporate risk management practices in Croatian and Slovenian companies

The paper explores differences as well as commonalities in corporate risk management practices and risk exposures in the large non-financial Slovenian and Croatian companies. Comparative analysis of survey results have revealed that the majority of analysed companies in both Croatia and Slovenia are using some form of risk management to manage interest-rate, foreign exchange, or commodity price risk. Regarding the intensity of influence of financial risks on the performance of the analysed companies, the results have shown that the price risk has the highest influence among the Slovenian as well as the Croatian companies. Croatian companies are more affected by currency risk than the Slovenian companies, while the interest-rate risk has been ranged as less important in comparison with commodity price and currency risks. The survey’s results have clearly indicated that Croatian and Slovenian non-financial companies manage financial risks primarily with simple risk management instruments such as natural hedging. In the case of derivatives use, forwards and swaps are by far the most important instruments in both countries, but futures as representatives of standardised derivatives and structured derivatives are more important in the Slovenian than in the Croatian companies.

Risk management and the potential of cattle insurance in Tigray, Northern Ethiopia

This study explores the role of livestock insurance to complement existing risk management strategies adopted by smallholder farmers. Using survey data, first, it provides insights into farmers’ risk perception of livestock farming, in terms of likelihood and severity of risk, attitude to risk and their determinants. Second, it examines farmers’ risk management strategies and their determinants. Third, it investigates farmers’ potential engagement with a hypothetical cattle insurance decision and their intensity of participation. Factor analysis is used to analyse risk sources and risk management, multiple regressions are used to identify the determinants; a Heckman model was used to investigate cattle insurance participation and intensity of participation. The findings show different groups of farmers display different risk attitude in their decision-making related to livestock farming. Production risk (especially livestock diseases) was perceived as the most likely and severe source of risk. Disease control was perceived as the best strategy to manage risk overall. Disease control and feed management were important strategies to mitigate the production risks. Disease control and participation on safety net program were found to be important to counter households’ financial risks. With regard to the hypothetical cattle insurance scheme, 94.38% of households were interested to participate in cattle insurance. Of those households that accepted cattle insurance, 77.38% of the households were willing to pay the benchmark annual premium of 4% of the animal value while for the remaining households this was not affordable. The average number of cattle that farmers were willing to insure was 2.71 at this benchmark. Results revealed that income (log income) and education levels influenced positively and significantly farmers’ participation in cattle insurance and the number of cattle to insure. The findings prompt policy makers to consider livestock insurance as a complement to existing risk management strategies to reduce poverty in the long-run.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

Quantitative analysis for business decisions,

Mode of access: Internet.

Construction risk management:a quantitative approach

Conventional project management techniques are not always sufficient for ensuring time, cost and quality achievement of large-scale construction projects due to complexity in planning and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in Government policies and regulations, unforeseen inflation) under-estimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk numagement throughout project life cycle. However, the effectiveness of risk management depends on the technique in which the effects of risk factors are analysed and! or quantified. This study proposes Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique as a tool for risk analysis because it can handle subjective as well as objective factors in decision model that are conflicting in nature. This provides a decision support system (DSS) to project managenumt for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and competitive business environment. The whole methodology is explained through a case study of a cross-country petroleum pipeline project in India and its effectiveness in project1nana.gement is demonstrated.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Can risk management boost the supply of affordable housing development and management?

Purpose: The purpose of this paper is to analyse the risk management process conducted by some private and not-for-profit affordable housing providers in South East Queensland, and draw conclusions about the relationship between risk assessments/responses and past experiences.----- Design/methodology/approach: In-depth interviews of selected non-government housing providers have been conducted to facilitate an understanding of their approach to risk assessment in developing and in managing affordable housing projects. Qualitative data are analysed using thematic analysis to find emerging themes suggested by interview participants.----- Findings: The paper finds that informal risk management process is used as part of normal business process in accordance with industry standards. Many interviewees agree that the recognition of financial risk and the fear of community rejection of such housing projects have restrained them from committing to such investment projects. The levels of acceptance of risk are not always consistent across housing providers which create opportunities to conduct multi-stakeholder partnership to reduce overall risk.----- Research limitations/implications: The paper has implications for developers or investors who seek to include affordable housing as part of their portfolio. However, data collected in the study are a cross-section of interviews that will not include the impact on recent tax incentives offers by the Australian Commonwealth Government.----- Practical implications: The study suggests that implementing improvements to the risk mitigation and management framework may assist in promoting the supply of affordable housing by non-government providers.----- Originality/value: The focus of the study is the interaction between partnerships and risk management in development and management of affordable rental housing.

Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Public policy, disaster risk management and climate change adaptation

Public policymakers are caught in a dilemma : there is a growing list of urgent issues to address, at the same time that public expenditure is being cut. Adding to this dilemma is a system of government designed in the 19th century and competing theories of policymaking dating back to the 1950s. The interlinked problems of disaster risk management and climate change adaptation are cases in point. As the climate changes, there will be more frequent, intense and/or prolonged disasters such as floods and bushfires. Clearly a well integrated whole of government response is needed, but how might this be achieved? Further, how could academic research contribute to resolving this dilemma in a way that would produce something of theoretical interest as well as practical outcomes for policymakers? These are the questions addressed by our research via a comparative analysis of the 2009 Victorian bushfires, the 2011 Perth Hills bushfires, and the 2011 Brisbane floods. Our findings suggest that there is a need to: improve community engagement and communication; refocus attention on resilience; improve interagency communication and collaboration; and, develop institutional arrangements that support continual improvement and policy learning. These findings have implications for all areas of public policy theory and practice.

Risk management for mycotoxin contamination of Australian maize

Recent incidents of mycotoxin contamination (particularly aflatoxins and fumonisins) have demonstrated a need for an industry-wide management system to ensure Australian maize meets the requirements of all domestic users and export markets. Results of recent surveys are presented, demonstrating overall good conformity with nationally accepted industry marketing standards but with occasional samples exceeding these levels. This paper describes mycotoxin-related hazards inherent in the Australian maize production system and a methodology combining good agricultural practices and the hazard analysis critical control point framework to manage risk.