forecasting crude oil price volatility and value at risk evidence from historical and recent data abstract this paper adopts the markov switching multifractal msm model and a battery of generalized autoregressive conditional heteroscedasticity garch type models to model and forecast oil price volatility extending previous work by wei et al 2010 and wang et al 2016 we evaluate the forecasting performance of all these models via a superior predictive ability spa test we go beyond previous research by i considering oil price volatility in the nineteenth century along with recent data ii applying different types of msm models and iii considering value at risk predictions besides our forecasting of volatility confirming its successful performance in other studies the new msm model comes out as the model that most often across forecasting horizons and subsamples cannot be outperformed by other models this superiority also applies to forecasting of value at risk

the drivers of international migration to the uk a panel based bayesian model averaging approach a heterogeneous panel based bayesian model averaging approach is used to identify the robust economic and policy drivers of international migration to the uk from 14 different source regions over 1980 2007 around three quarters of the increase in net immigration over the last decade which is particularly pronounced for selected source regions is associated with structural change which may be attributed to uk and foreign immigration policy the remainder of the rise is largely explained by friends and family effects there are considerable uncertainties associated both with the effects of particular economic drivers of immigration and with forecasts of immigration

developing a stress testing framework based on market risk models the basel 2 accord requires regulatory capital to cover stress tests yet no coherent and objective framework for stress testing portfolios exists we propose a new methodology for stress testing in the context of market risk models that can incorporate both volatility clustering and heavy tails empirical results compare the performance of eight risk models with four possible conditional and unconditional return distributions over different rolling estimation periods when applied to major currency pairs using daily data spanning more than 20 years we find that stress test results should have little impact on current levels of foreign exchange regulatory capital

answering the skeptics yes standard volatility models do provide accurate forecasts a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using arch and stochastic volatility models while most of these studies have documented highly significant in sample parameter estimates and pronounced intertemporal volatility persistence traditional ex post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts contrary to this contention we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications new methods for improved ex post interdaily volatility measurements based on high frequency intradaily data are also discussed

network structure and regional innovation a study of university industry ties the emergence of the network paradigm has led to growing interest in understanding network structures relating to knowledge flows and patterns of regional innovation this paper explores the structure of knowledge networks stemming from ties between universities and other actors principally firms based upon a network analysis of empirical data for regions across the uk it is found that the most innovative and economically developed regions are more likely to be the location for actors holding highly central and influential positions within knowledge network architectures it is concluded that network structures and resulting stocks of structural network capital influence patterns of regional innovation and development

can fat tail create the momentum and reversal we suggest that fat tail variations can cause both short term momentum and long term reversal simultaneously in both the time series and cross sectional returns of securities the fat tail of the

incentives contracts and markets a general equilibrium theory of firms1 this paper takes steps toward integrating firm theory in the spirit of alchian and demsetz 1972 and grossman and hart 1986 contract theory in the spirit of holmstrom 1979 and general equilibrium theory in the spirit of arrow and debreu 1954 and mckenzie 1959 in the model presented here the set of firms that form and the contractual arrangements that appear the assignments of agents to firms the prices faced by firms for inputs and outputs and the incentives to agents are all determined endogenously at equilibrium agents choose consumption but they also choose which firms to join which roles to occupy in those firms and which actions to take in those roles agents interact anonymously with the large market but strategically within the small firms they join the model accommodates moral hazard adverse selection signaling and insurance equilibria may be pareto ranked

value at risk estimation with the optimal dynamic biofuel portfolio abstract in the past petroleum companies only paid attention to hedging the variation in the crude oil price and volatility however they have now expanded their analysis to encompass renewable sources such as corn and soybeans under the current low carbon biofuel obligations this paper employs garch 1 1 and arji models to estimate the one day ahead value at risk var of the optimal dynamic biofuel portfolio which consists of crude oil corn and soybeans the optimal blended standard is subject to the dual limitations of minimum production costs and the lowest biofuel using requirements our empirical findings confirm that the arji model is more suitable than the garch 1 1 model and further captures the discontinuous jump behavior from the in the sample data the results of out of sample forecasts also are represented that our models play important roles in var estimation and risk management for biofuel portfolio we therefore suggest that the petroleum companies should simultaneously pay attention to jump risk in hedging material costs in the prices of energy related crops

delegated portfolio management abstract a problem of screening agents with privately known forecasting abilities and reservation utilities and then eliciting truthful information from these agents once they are employed is considered for the case of risk averse agents and large principals an approximately optimal solution is constructively characterized under the assumption that payoffs are normally distributed a significant extension of the definnetti savage probability elicitation result is developed under this extension knowledge of agent preferences is not required when the underlying conditional distributions are symmetric and this fact is exploited to solve the screening problem in a mean variance formulation

asset prices and institutional investors empirical evidence indicates that trades by institutional investors have sizable effects on asset prices generating phenomena such as index effects asset class effects and others it is difficult to explain such phenomena within standard representative agent asset pricing models in this paper we consider an economy populated by institutional investors alongside standard retail investors institutions care about their performance relative to a certain index our framework is tractable admitting exact closed form expressions and produces the following analytical results we find that institutions optimally tilt their portfolios towards stocks that comprise their benchmark index the resulting price pressure boosts index stocks while leaving nonindex stocks unaffected by demanding a higher fraction of risky stocks than retail investors institutions amplify the index stock volatilities and aggregate stock market volatility and give rise to countercyclical sharpe ratios trades by institutions induce excess correlations among stocks that belong to their benchmark index generating an asset class effect institutions finance their additional purchases of index stocks by taking on leverage a policy prescription that calls for a reduction in leverage while reducing the riskiness of institutional portfolios would also reduce the ability of institutions to tilt their portfolios towards index stocks depressing the index level

forecasting portfolio value at risk with nonparametric lower tail dependence estimates abstract we propose to forecast the value at risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence we compare our proposed method to a conventional copula garch model where the parameter of a clayton copula is estimated via canonical maximum likelihood the superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine dimensional financial portfolio a comparison of the out of sample forecasting accuracy of both models confirms that our model yields economically significantly better value at risk forecasts than the competing parametric calibration strategy

are interest rate options important for the assessment of interest rate risk abstract fixed income options contain substantial information on the price of interest rate volatility risk in this paper we ask if those options will also provide information related to other moments of the objective distribution of interest rates based on dynamic term structure models within the class of affine models we find that interest rate options are useful for the identification of interest rate quantiles two three factor models are adopted and their adequacy to estimate value at risk of zero coupon bonds is tested we find significant difference on the quantitative assessment of risk when options are or not included in the estimation process of each of these dynamic models statistical backtests indicate that bond estimated risk is clearly more adequate when options are adopted although not yet completely satisfactory

evaluating interval forecasts a complete theory for evaluating interval forecasts has not been worked out to date most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage consequently i set out to build a consistent framework for conditional interval forecast evaluation which is crucial when higher order moment dynamics are present the new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management

moral hazard and the portfolio management problem this paper investigates the significance of nonlinear contracts on the incentive for portfolio managers to collect information in addition the manager must be motivated to disclose this information truthfully we analyze three contracting regimes 1 first best where effort is observable 2 linear with unobservable effort and 3 the optimal contract within the bhattacharya pfleiderer quadratic class we find that the linear contract leads to a serious lack of effort expenditure by the manager this underinvestment problem can be successfully overcome through the use of quadratic contracts these contracts are shown to be asymptotically optimal for very risk tolerant principals

real time density forecasts from bayesian vector autoregressions with stochastic volatility central banks and other forecasters are increasingly interested in various aspects of density forecasts however recent sharp changes in macroeconomic volatility including the great moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession pose significant challenges to density forecasting accordingly this paper examines with real time data density forecasts of u s gdp growth unemployment inflation and the federal funds rate from bayesian vector autoregression bvar models with stochastic volatility the results indicate that adding stochastic volatility to bvars materially improves the real time accuracy of density forecasts this article has supplementary material online

estimating value at risk of crude oil price and its spillover effect using the ged garch approach estimation has been carried out using garch type models based on the generalized error distribution ged for both the extreme downside and upside value at risks var of returns in the wti and brent crude oil spot markets furthermore according to a new concept of granger causality in risk a kernel based test is proposed to detect extreme risk spillover effect between the two oil markets results of an empirical study indicate that the ged garch based var approach appears more effective than the well recognized hsaf i e historical simulation with arma forecasts moreover this approach is also more realistic and comprehensive than the standard normal distribution based var model that is commonly used results reveal that there is significant two way risk spillover effect between wti and brent markets supplementary study indicates that at the 99 confidence level when negative market news arises that brings about a slump in oil price return historical information on risk in the wti market helps to forecast the brent market conversely it is not the case when positive news occurs and returns rise historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other these results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets

rolling sampled parameters of arch and levy stable models in this paper an asymmetric autoregressive conditional heteroskedasticity arch model and a levy stable distribution are applied to some well known financial indices dax30 ftse20 ftse100 and sp500 using a rolling sample of constant size in order to investigate whether the values of the estimated parameters of the models change over time although there are changes in the estimated parameters reflecting that structural properties and trading behaviour alter over time the arch model adequately forecasts the one day ahead volatility a simulation study is run to investigate whether the time variant attitude holds in the case of a generated arch data process revealing that even in that case the rolling sampled parameters are time varying

comparison of historically simulated var evidence from oil prices abstract cabedo and moya cabedo j d moya i 2003 estimating oil price value at risk using the historical simulation approach energy economics 25 239 253 find that arma with historical simulation delivers var forecasts that are superior to those from garch we compare the arma with historical simulation to the semi parametric garch model proposed by barone adesi et al barone adesi g giannopoulos k vosper l 1999 var without correlations for portfolios of derivative securities journal of futures markets 19 5 583 602 the results suggest that the semi parametric garch model generates var forecasts that are superior to the var forecasts from the arma with historical simulation this is due to the fact that garch captures volatility clustering our findings suggest that cabedo and moya s conclusion is mainly driven by the normal distributional assumption imposed on the future risk structure in the garch model

liquidity adjusted intraday value at risk modeling and risk management an application to data from deutsche borse abstract this paper develops a high frequency risk measure the liquidity adjusted intraday value at risk livar our objective is to explicitly consider the endogenous liquidity dimension associated with order size by reconstructing the open limit order book of deutsche borse changes in the tick by tick ex ante frictionless return and actual return are modeled jointly the risk related to the ex ante liquidity premium is then quantified our model can be used to identify the impact of ex ante liquidity risk on total risk and to provide an estimation of the var for the actual return at a point in time in our sample liquidity risk can account for up to 32 of total risk depending on order size

dynamics of credit spread moments of european corporate bond indexes abstract traditional quantitative credit risk models assume that changes in credit spreads are normally distributed but empirical evidence shows that they are likely to be skewed fat tailed and change behaviour over time not taking into account such characteristics can compromise calculation of loss probabilities pricing of credit derivatives and profitability of trading strategies therefore the aim of this study is to investigate the dynamics of higher moments of changes in credit spreads of european corporate bond indexes using extensions of garch type models that allow for time varying volatility skewness and kurtosis of changes in credit spreads as well as a regime switching garch model which allows for regime shifts in the volatility of changes in credit spreads performance evaluation methods are used to assess which model captures the dynamics of observed distribution of the changes in credit spreads produces superior volatility forecasts and value at risk estimates and yields profitable trading strategies the results presented can have significant implications for risk management trading activities and pricing of credit derivatives

do banks overstate their value at risk abstract this paper is the first empirical study of banks risk management systems based on non anonymous daily value at risk var and profit and loss data using actual data from the six largest canadian commercial banks we uncover evidence that banks exhibit a systematic excess of conservatism in their var estimates the data used in this paper have been extracted from the banks annual reports using an innovative matlab based data extraction method out of the 7354 trading days analyzed in this study there are only two exceptions i e days when the actual loss exceeds the disclosed var whereas the expected number of exceptions with a 99 var is 74 for each sample bank we extract from historical vars a risk overstatement coefficient ranging between 19 and 79 we attribute var overstatement to several factors including extreme cautiousness and underestimation of diversification effects when aggregating vars across business lines and or risk categories we also discuss the economic and social cost of reporting inflated vars

forecasting quantiles of day ahead electricity load accurate load forecasting plays a crucial role in the decision making process of many market participants but probably is most important for the dispatch planning of an electricity market operator despite the competitive forecast accuracy achieved by existing point forecast models point forecasts can only provide limited information relating to the expected level of future load to account for the uncertainty of future load and provide a more complete picture of the future load conditions for dispatch planning purposes quantile forecasts can be useful this paper proposes a computationally efficient approach to forecasting the quantiles of electricity load which is then applied to forecasting in the national electricity market of australia the proposed model performs competitively in comparison with one industry standard and two recently proposed quantile forecasting methods one of the main advantages of the proposed approach is the ease with the number of covariates can be expanded this is a particularly important feature in the context of load forecasting where large numbers of important drivers are usually necessary to provide accurate load forecasts

towards a knowledge based theory of the geographical cluster co located firms within related industries enhance the ability to create knowledge by variation and a deepened division of labour the interdependent development between economic activities and local institutions make the cluster attractive to some industries and hostile to others the very reasons why cognitive distance might be small within the cluster tend to make cognitive distance great between clusters and make interfirm co operation across bodies of knowledge more costly the additional value created when clustering may justify the additional cost copyright 2001 by oxford university press

a new pearson type qmle for conditionally heteroscedastic models this article proposes a novel pearson type quasi maximum likelihood estimator qmle of garch p q models unlike the existing gaussian qmle laplacian qmle generalized non gaussian qmle or lad estimator our pearsonian qmle pqmle captures not just the heavy tailed but also the skewed innovations under strict stationarity and some weak moment conditions the strong consistency and asymptotic normality of the pqmle are obtained with no further efforts the pqmle can be applied to other conditionally heteroscedastic models a simulation study is carried out to assess the performance of the pqmle two applications to four major stock indexes and two exchange rates further highlight the importance of our new method heavy tailed and skewed innovations are often observed together in practice and the pqmle now gives us a systematic way to capture these two coexisting features

roughing it up including jump components in the measurement modeling and forecasting of return volatility a rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high frequency returns coupled with simple modeling procedures building on recent theoretical results in barndorff nielsen and shephard 2004a 2005 for related bi power variation measures the present paper provides a practical and robust framework for non parametrically measuring the jump component in asset return volatility in an application to the dm exchange rate the s p500 market index and the 30 year u s treasury bond yield we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process moreover many jumps appear directly associated with specific macroeconomic news announcements separating jump from non jump movements in a simple but sophisticated volatility forecasting model we find that almost all of the predictability in daily weekly and monthly return volatilities comes from the non jump component our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling forecasting and pricing the continuous and jump components of the total return variation process

time series copulas for heteroskedastic data we propose parametric copulas that capture serial dependence in stationary heteroskedastic time series we suggest copulas for first order markov series and then extend them to higher orders and multivariate series we derive the copula of a volatility proxy based on which we propose new measures of volatility dependence including co movement and spillover in multivariate series in general these depend upon the marginal distributions of the series using exchange rate returns we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models and produce more accurate value at risk forecasts

following or breaking regional development paths on the role and capability of the innovative entrepreneur structural change economic diversification and new path development feature prominently in scientific and policy debates against the backdrop of increasing specialization in the economy this paper reinterprets schumpeterian innovative entrepreneurship as a fundamental process that creates new connections between distinct fields of specialization thereby induces path breaking innovations and structural change it is argued that the transformation capability of innovative entrepreneurs rests essentially on their position s and networks within evolving innovation systems by focusing on micro level processes and transformation capability the paper complements the large body of work on structural barriers unintended consequences supporting institutional arrangements and policy implications are discussed

modeling and forecasting extreme commodity prices a markov switching based extreme value model abstract we propose a markov switching multifractal peaks over threshold msm pot model to capture the dynamic behavior of the random occurrences of extreme events exceeding a high threshold in time series of returns this approach allows introducing changes of regimes in the conditional mean function of the inter exceedance times i e the time between two consecutive extreme events in order to admit the presence of short and long term memory patterns further through its multifractal structure the msm pot approach is able to capture the typical stylized facts of extreme events observed in financial time series such as temporal clustering of the size of exceedances and temporal behavior of tail thickness we compare the performance of the msm pot model with competing self exciting models and a garch evt approach in an in and out of sample var forecasting exercise based on the extreme returns of six daily commodity futures prices i e brent and wti crude oil cocoa cotton copper and gold empirical results suggest that the var estimates generated by the msm pot model for the returns analyzed produce the most accurate forecasts

multivariate density forecast evaluation and calibration in financial risk management high frequency returns on foreign exchange we provide a framework for evaluating and improving multivariate density forecasts among other things the multivariate framework lets us evaluate the adequacy of density forecasts involving cross variable interactions such as time varying conditional correlations we also provide conditions under which a technique of density forecast calibration can be used to improve deficient density forecasts and we show how the calibration method can be used to generate good density forecasts from econometric models even when the conditional density is unknown finally motivated by recent advances in financial risk management we provide a detailed application to multivariate high frequency exchange rate density forecasts

dynamic return volatility dependence and risk measure of covar in the oil market a time varying mixed copula model abstract this study investigates the risk level in the oil market measured by value at risk var and conditional var covar as well as the dynamic and asymmetric dependence between wti returns and crude oil volatility index ovx by constructing six time varying mixed copula models results show that mixed copula between t copula and the 270 degree rotated clayton copula is the optimal fitting copula to measure dynamic dependence the estimated time varying kendall coefficients indicate that wti returns and ovx present negative dependence most of the time there exists a structural change point of dependence between wti returns and ovx changes on april 17 2009 while the dependence characteristics within the subsamples are similar to that in the whole sample indicating the rationality of our time varying mixed copula models finally the tests show significant risk spillover from ovx to wti returns and also asymmetric effects for covars in response to different upside and downside extreme ovx movements

innovation networks and vertical integration abstract a central debate in industrial policy today is that between proponents of large vertically integrated firms on the one hand and those of networks of small specialized producers on the other this paper argues that neither institutional structure is the panacea its supporters claim the menu of institutional alternatives is in fact quite large and both firms and networks of which there are several kinds can be successful growth promoting adaptations to the competitive environment industrial structures vary in their ability to coordinate information flows necessary for innovation and to overcome power relationships adverse to innovation the relative desirability of the various structures then depends on the nature and scope of technological change in the industry and on the effects of various product life cycle patterns the principal policy conclusion of this analysis is that the government s role ought to be facilitating rather than narrow and prescriptive allowing scope for firms to develop organizational forms that are best adapted to their particular environments

pricing discretely monitored asian options under levy processes we present methodologies to price discretely monitored asian options when the underlying evolves according to a generic levy process for geometric asian options we provide closed form solutions in terms of the fourier transform and we study in particular these formulas in the levy stable case for arithmetic asian options we solve the valuation problem by recursive integration and derive a recursive theoretical formula for the moments to check the accuracy of the results we compare the implementation of our method to monte carlo simulation implemented with control variates and using different parametric levy processes we also discuss model risk issues

continuous cascade models for asset returns abstract in this paper we make a short overview of continuous cascade models recently introduced to model asset return fluctuations we show that these models account in a very parcimonious manner for most of stylized facts of financial time series we review in more details the simplest continuous cascade namely the log normal multifractal random walk mrw it can simply be considered as a stochastic volatility model where the log volatility memory has a peculiar logarithmic shape this model possesses some appealing stability properties with respect to time aggregation we describe how one can estimate it using a gmm method and we present some applications to volatility and var value at risk forecasting

forecasting daily supermarket sales using exponentially weighted quantile regression inventory control systems typically require the frequent updating of forecasts for many different products in addition to point predictions interval forecasts are needed to set appropriate levels of safety stock the series considered in this paper are characterised by high volatility and skewness which are both time varying these features motivate the consideration of forecasting methods that are robust with regard to distributional assumptions the widespread use of exponential smoothing for point forecasting in inventory control motivates the development of the approach for interval forecasting in this paper we construct interval forecasts from quantile predictions generated using exponentially weighted quantile regression the approach amounts to exponential smoothing of the cumulative distribution function and can be viewed as an extension of generalised exponential smoothing to quantile forecasting empirical results are encouraging with improvements over traditional methods being particularly apparent when the approach is used as the basis for robust point forecasting

forecasting the joint distribution of australian electricity prices using dynamic vine copulae abstract we consider the problem of modelling and forecasting the distribution of a vector of prices from interconnected electricity markets using a flexible class of drawable vine copula models where we allow the dependence parameters of the constituting bivariate copulae to be time varying we undertake in sample and out of sample tests using daily electricity prices and evidence that our model provides accurate forecasts of the underlying distribution and outperforms a set of competing models in their abilities to forecast one day ahead conditional quantiles of a portfolio of electricity prices our study is conducted in the australian national electricity market nem which is the most efficient power auction in the world electricity prices exhibit highly stylised features such as extreme price spikes price dependency between regional markets correlation asymmetry and non linear dependency the developed approach can be used as a risk management tool in the electricity retail industry which plays an integral role in the apparatus of modern energy markets electricity retailers are responsible for the efficient distribution of electricity while being exposed to market risk with extreme magnitudes

value at risk estimations of energy commodities via long memory asymmetry and fat tailed garch models abstract in this paper we evaluate the value at risk var and the expected shortfalls for some major crude oil and gas commodities for both short and long trading positions classical var estimations as well as riskmetrics and other extensions to cases considering for long range memory asymmetry and fat tail in energy markets volatility were conducted we computed the var for three arch garch type models including figarch fiaparch and hygarch these models were estimated in the presence of three alternative innovation s distributions normal student and skewed student our results show that considering for long range memory fat tails and asymmetry performs better in predicting a one day ahead var for both short and long trading positions moreover the fiaparch model outperforms the other models in the var s prediction these results present several potential implications for energy markets risk quantifications and hedging strategies

time series analysis for financial market meltdowns abstract there appears to be a consensus that the recent instability in global financial markets may be attributable in part to the failure of financial modeling more specifically it is alleged that current risk models have failed to properly assess the risks associated with large adverse stock price behavior in this paper we first discuss the limitations of classical time series models for forecasting financial market meltdowns then we set forth a framework capable of forecasting both extreme events and highly volatile markets based on the empirical evidence presented in this paper our framework offers an improvement over prevailing models for evaluating stock market risk exposure during distressed market periods

continuous time models realized volatilities and testable distributional implications for daily stock returns we provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous time jump diffusion models traditionally used in asset pricing finance our approach builds directly on recently developed realized variation measures and non parametric jump detection statistics constructed from high frequency intra day data a sequence of simple to implement moment based tests involving various transformations of the daily returns speak directly to the importance of different distributional features and may serve as useful diagnostic tools in the specification of empirically more realistic continuous time asset pricing models on applying the tests to the 30 individual stocks in the dow jones industrial average index we find that it is important to allow for both time varying diffusive volatility jumps and leverage effects to satisfactorily describe the daily stock price dynamics copyright 2009 john wiley sons ltd

the dynamics of portfolio management contracts we consider the multiperiod relationship between a client and a portfolio manager and the resulting problem of motivating a manager of unknown ability to acquire valuable information we explore the contractual forms and the optimal retention policy of the client and find that the optimal initial set of contracts features a smaller performance based fee component paid to the manager than in a first best contract and the contract choice elicits only partial information about the manager as a result ex post performance measurement is critical to future recontracting in general managers are retained only if the returns on their portfolio exceed the benchmark by an appropriate amount article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

modelling interregional links in electricity price spikes abnormally high price spikes in spot electricity markets represent a significant risk to market participants as such a literature has developed that focuses on forecasting the probability of such spike events moving beyond simply forecasting the level of price many univariate time series models have been proposed to dealwith spikes within an individual market region this paper is the first to develop a multivariate self exciting point process model for dealing with price spikes across connected regions in the australian national electricity market the importance of the physical infrastructure connecting the regions on the transmission of spikes is examined it is found that spikes are transmitted between the regions and the size of spikes is influenced by the available transmission capacity it is also found that improved risk estimates are obtained when inter regional linkages are taken into account

the spatial evolution of the british automobile industry does location matter this article aims to describe and explain the spatial evolution of the automobile sector in great britain from an evolutionary perspective this analysis is based on a unique database of all entries and exits in this sector during the period 1895 1968 collected by the authors cox regressions show that spinoff dynamics agglomeration economies and time of entry have had a significant effect on the survival rate of automobile firms during the period 1895 1968

do urban social enterprises benefit from agglomeration evidence from four uk cities pinch s and sunley p do urban social enterprises benefit from agglomeration evidence from four uk cities regional studies this paper examines the relevance of clustering theory for an understanding of the location of social enterprises ses this is accomplished through an analysis of the extent to which managers of ses in four major uk cities perceive themselves to benefit from agglomeration effects the paper concentrates on two broad sets of agglomeration processes the first is marshallian externalities and porter s cluster processes and the second set includes urbanization economies and local institutional relationships the study suggests the key benefits of agglomeration to ses are that it enables access to demand for se goods and services together with institutional support funding and commercial contracts as well as access to both formal and informal networks that can provide a wide range of knowledge and mutual support it was however difficult to find direct evidence to support the i

the fine structure of asset returns an empirical investigation we investigate the importance of diffusion and jumps in a new model for asset returns in contrast to standard models we allow for jump components displaying finite or infinite activity and variation empirical investigations of time series indicate that index dynamics are devoid of a diffusion component which may be present in the dynamics of individual stocks this leads to the conjecture confirmed on options data that the risk neutral process should be free of a diffusion component we conclude that the statistical and risk neutral processes for equity prices are pure jump processes of infinite activity and finite variation

capturing deep tail risk via sequential learning of quantile dynamics abstract this paper develops a conditional quantile model that can learn long term and short term memories of sequential data it builds on sequential neural networks and yet outputs interpretable dynamics we apply the model to asset return time series across eleven asset classes using historical data from the 1960s to 2018 our results reveal that it extracts not only the serial dependence structure in conditional volatility but also the memories buried deep in the tails of historical prices we further evaluate its value at risk forecasts against a wide range of prevailing models our model outperforms the garch family as well as models using filtered historical simulation conditional extreme value theory and dynamic quantile regression these studies indicate that conditional quantiles of asset return have persistent sources of risk that are not coming from those responsible for volatility clustering these findings could have important implications for risk management in general and tail risk forecasts in particular

optimal risk sharing with effort and project choice we consider first best risk sharing problems in which the agent can control both the drift effort choice and the volatility of the underlying process project selection in a model of delegated portfolio management it is optimal to compensate the manager with an option type payoff where the functional form of the option is obtained as a solution to an ordinary differential equation in the general case the optimal contract is a fixed point of a functional that connects the agent s and the principal s maximization problems we apply martingale duality methods familiar from optimal consumption investment problems

equilibrium prices in the presence of delegated portfolio management abstract this paper analyzes the asset pricing implications of commonly used portfolio management contracts linking the compensation of fund managers to the excess return of the managed portfolio over a benchmark portfolio the contract parameters the extent of delegation and equilibrium prices are all determined endogenously within the model we consider symmetric fulcrum performance fees distort the allocation of managed portfolios in a way that induces a significant and unambiguous positive effect on the prices of the assets included in the benchmark and a negative effect on the sharpe ratios asymmetric performance fees have more complex effects on equilibrium prices and sharpe ratios with the signs of these effects fluctuating stochastically over time in response to variations in the funds excess performance

dynamic capabilities what are they this paper focuses on dynamic capabilities and more generally the resource based view of the firm we argue that dynamic capabilities are a set of specific and identifiable processes such as product development strategic decision making and alliancing they are neither vague nor tautological although dynamic capabilities are idiosyncratic in their details and path dependent in their emergence they have significant commonalities across firms popularly termed best practice this suggests that they are more homogeneous fungible equifinal and substitutable than is usually assumed in moderately dynamic markets dynamic capabilities resemble the traditional conception of routines they are detailed analytic stable processes with predictable outcomes in contrast in high velocity markets they are simple highly experiential and fragile processes with unpredictable outcomes finally well known learning mechanisms guide the evolution of dynamic capabilities in moderately dynamic markets the evolutionary emphasis is on variation in high velocity markets it is on selection at the level of rbv we conclude that traditional rbv misidentifies the locus of long term competitive advantage in dynamic markets overemphasizes the strategic logic of leverage and reaches a boundary condition in high velocity markets copyright 2000 john wiley sons ltd

is there evidence of pessimism and doubt in subjective distributions implications for the equity premium puzzle abel 2002 shows that pessimism and doubt in the subjective distribution of the growth rate of consumption reduce the equity premium puzzle we quantify the amount of pessimism and doubt in survey data on us consumption and income individual forecasters are in fact pessimistic but show marked overconfidence rather than doubt however the implications for abel s model depend on how the empirically heterogeneous beliefs are mapped into beliefs of a representative agent we use an arrow debreu economy to show that disagreement increases the equity premium when incorporating this in our estimation we find little empirical evidence of either overconfidence or doubt

forecasting the var of crude oil market do alternative distributions help abstract accurate modeling of the empirical distribution of crude oil market returns is extremely important in estimating risk measures in addition to several commonly used distributions alternative distributions are explored in this study some of which account for the asymmetry and heavy tails simultaneously found in distributions and contain more tail parameters to separately depict the right and left tails when forecasting the value at risk var of crude oil markets during highly volatile periods seven backtests are also conducted to compare the var forecasting accuracy among different distributions the empirical results indicate that a highly volatile environment challenges the commonly used distributions and the four risk models based on commonly used distributions are rejected about 27 to 38 of the time the alternative distributions i e skewed general error distributions sged generalized hyperbolic skewed student t distributions ghst and generalized asymmetric student t gast distributions generally produce more accurate var measurement and gast gives the best measurement accuracy the empirical results imply that risk managers or policymakers should further consider more flexible distributions such as sged ghst or gast in particular when quantifying or managing the risk in turbulent market times

early warning signals using avars of infinitely divisible garch models evidence from stock index markets classical time series models have failed to properly assess the risks that are associated with large adverse stock price behaviour this article contributes to autoregressive moving average model garch arma garch models with standard infinitely divisible innovations and assesses the performance of these models by comparing them with other time series models that have normal innovation we discuss the limitations of value at risk var and aim to develop early warning signal models using average value at risk avars based on the arma garch model with standard infinitely divisible innovations empirical results for the daily dow jones industrial average index the england financial times stock exchange 100 index and the japan nikkei 225 index reveal that estimating avars for the arma garch model with standard infinitely divisible innovations offers an improvement over prevailing models for evaluating stock market risk exposure during periods of distress in financial markets and provides a suitable early

revisiting marshall s agglomeration economies technological relatedness and the evolution of the sheffield metals cluster potter a and watts h d revisiting marshall s agglomeration economies technological relatedness and the evolution of the sheffield metals cluster regional studies according to alfred marshall firms receive increasing returns from a trinity of agglomeration economies a local pool of skilled labour local supplier linkages and local knowledge spillovers this article re examines the mechanisms underlying marshall s agglomeration economies in the sheffield metals cluster wherein marshall discovered them despite the cluster s decline empirical evidence is found that the mechanisms underlying marshallian agglomeration economies continue to occur within the surviving metals industry however upon closer examination marshallian agglomeration economies have evolved to become more prevalent amongst plants that use related metals technology the results highlight the importance of technological relatedness to cluster survival

backtesting trading risk of commercial banks using expected shortfall this paper uses saddlepoint technique to backtest the trading risk of commercial banks using expected shortfall it is found that four out of six us commercial banks have excessive trading risks monte carlo simulation studies show that the proposed backtest is very accurate and powerful even for small test samples more importantly risk managers can carry out the proposed backtest based on any number of exceptions so that incorrect risk models can be promptly detected before any further huge losses are realized

co evolution of firms industries and networks in space ter wal a l j and boschma r co evolution of firms industries and networks in space regional studies the cluster literature suffers from a number of shortcomings 1 it often neglects that cluster firms are heterogeneous in terms of capabilities 2 it tends to overemphasize the importance of geographical proximity and underestimates the role of networks and 3 it hardly addresses the origins and evolution of clusters the authors propose a theoretical framework that brings together the literature on clusters industrial dynamics the evolutionary theory of the firm and network theory it is described how clusters co evolve with 1 the industry with to they adhere 2 the capabilities of the firms they contain and 3 the industry wide knowledge network of which they are part ter wal a l j et boschma r la coevolution geographique des entreprises des industries et des reseaux regional studies la documentation sur les clusters souffre d un nombre de points faibles 1 elle ne tient c

the duality of collaboration inducements and opportunities in the formation of interfirm linkages i argue that the linkage formation propensity of firms is explained by simultaneously examining both inducement and opportunity factors drawing upon resource based and social network theory literatures i identify three forms of accumulated capital technical commercial and social that can affect a firm s inducements and opportunities to form linkages firms possessing these capital stocks enjoy advantages in linkages formation however firms lacking these accumulated resources can still form linkages if they generate a radical technological breakthrough thus i identify paths to linkage formation for leading as well as peripheral firms i test these arguments with longitudinal data on technical collaborative linkages in the global chemicals industry copyright 2000 john wiley sons ltd

knowledge and competitive advantage the coevolution of firms technology and national institutions this issue of jibs offers reviews of two books that analyse the dynamic interaction between the business environments and business strategies in very different ways the institutional underpinnings for business strategies are a major research topic for comparative management aiming to explain why in different contexts firms pursue different strategies and with different implications for performance j peter murman in knowledge and competitive advantage takes a historical perspective focusing on the co evolutionary processes between national innovation systems business strategies and performance this books thus adds to the industry level longitudinal research reviewed in jibs no 4 2003 tom murtha et al s managing new industry creation and david mckendrick et al s from silicon valley to singapore

optimal contracts in a continuous time delegated portfolio management problem this article studies the contracting problem between an individual investor and a professional portfolio manager in a continuous time principal agent framework optimal contracts are obtained in closed form these contracts are of a symmetric form and suggest that a portfolio manager should receive a fixed fee a fraction of the total assets under management plus a bonus or a penalty depending upon the portfolio s excess return relative to a benchmark portfolio the appropriate benchmark portfolio is an active index that contains risky assets where the number of shares invested in each asset can vary over time rather than a passive index in which the number of shares invested in each asset remains constant over time fund managers compensation schemes in a delegated portfolio management setting have been of special interest to both academics and practitioners academic interest stems in part from the rapid growth of managed funds over the last two decades gompers and metrick 1998 report that by december 1996 mutual funds pension funds and other financial intermediaries held discretional control over more than half of the u s equity market it is thus of importance to study the impact of institutional trading on asset prices and to integrate into one model both asset pricing and delegated portfolio management compensation as advocated by brennan 1993 allen and santomero 1997 and allen 2001 it is also important to understand the relationship between a manager s trading strategies and his implicit incentives or career concerns see e g brown harlow and starks 1996 brown goetzmann and park 1997 chevalier and ellison 1999 and chen and pennacchi 2000 these concerns include internal promotion from a small to a large fund higher outside offers and the flow of money through the fund under management 1 the importance of fund manager compensation is also underscored by congressional passage in 1970 of the amendment to

beyond sharpe ratio optimal asset allocation using different performance ratios abstract as the assumption of normality in return distributions is relaxed classic sharpe ratio and its descendants become questionable tools for constructing optimal portfolios in order to overcome the problem asymmetrical parameter dependent performance ratios have been recently proposed in the literature the aim of this note is to develop an integrated decision aid system for asset allocation based on a toolkit of eleven performance ratios a multi period portfolio optimization up covering a fixed horizon is set up at first bootstrapping of asset return distributions is assessed to recover all ratios calculations at second optimal rebalanced weights are achieved at third optimal final wealth is simulated for each ratios eventually we make a robustness test on the best performance ratios empirical simulations confirm the weakness in forecasting of sharpe ratio whereas asymmetrical parameter dependent ratios such as the generalized rachev sortino satchell and farinelli tibiletti ratios show satisfactorily robustness

improving the value at risk forecasts theory and evidence from the financial crisis abstract the recent financial crisis has raised numerous questions about the accuracy of value at risk var as a tool to quantify extreme losses in this paper we develop data driven var approaches that are based on the principle of optimal combination and that provide robust and precise var forecasts for periods when they are needed most such as the recent financial crisis within a comprehensive comparative study we provide the latest piece of empirical evidence on the performance of a wide range of standard var approaches and highlight the overall outperformance of the newly developed methods

competition in portfolio management theory and experiment we explore theoretically and experimentally the general equilibrium price and allocation implications of delegated portfolio management when the investor manager relationship is nonexclusive our theory predicts that competition forces managers to promise portfolios that mimic arrow debreu ad securities which investors then combine to fit their preferences a weak version of the capital asset pricing model capm obtains where state prices relative to state probabilities implicit in prices of traded securities will be inversely ranked to aggregate wealth across states our experiment broadly corroborates the price and choice predictions of the theory however price quality deteriorates when only a few managers attract most of the available wealth wealth concentration increases because funds flow toward managers who offer portfolios closer to replicating ad securities as in the theory but also because funds flow to managers who had better performance in the immediate past an observation unrelated to the theory this paper was accepted by jerome detemple finance

survival of businesses using collaborative relationships to commercialize complex goods authors with many theoretical and managerial perspectives argue that businesses commercializing technologically complex goods benefit when they collaborate closely with other businesses collaboration is viewed as a means for businesses to overcome competency limitations and to achieve the close configuration of components required for complex goods we predict that collaborative relationships often assist businesses to produce complex goods but that the relationships might also cause problems for the collaborating businesses we find that firms using development oriented and marketing oriented collaborative relationships in the hospital software systems industry are less likely to shut down than businesses that follow independent approaches when the environment changes gradually but businesses using collaborative relationships are sometimes susceptible to being acquired by other firms following a sudden environmental shock businesses with collaborative relationships for activities central to the shock became more likely to shut down while businesses with collaborative relationships for activities outside the focus of the shock became more likely to survive the study critically evaluates and tests the widely stated but little tested argument that interfirm collaboration is usually beneficial the results address the issue of whether organizational choices affect comparative business performance

portfolio performance and agency the evaluation and compensation of portfolio managers is an important problem for practitioners optimal compensation will induce managers to expend eort to generate information and to use it appropriately in an informed portfolio choice our general model points the way towards analysis of optimal performance evaluation and contracting in a rich model optimal contracting in the model includes an important role for portfolio restrictions that are more complex than the sharing rule the agent s compensation gives the agent approximately to a benchmark return plus an incentive fee equal to a portfolio measure that is approximately the excess of return above the benchmark this measure is often used by practitioners but is simpler than the jensen measure and other measures commonly recommended in the academic literature in addition to the excess return above the xed benchmark the manager is given some additional incentive to take a position that deviates from the benchmark to remove an incentive to tend towards being a closet indexer ecient contracting involves restrictions on what portfolio strategies can be pursued and prior communication of the information gathered

point process models for extreme returns harnessing implied volatility forecasting the risk of extreme losses is an important issue in the management of financial risk there has been a great deal of research examining how option implied volatilities iv can be used to forecast asset return volatility however the role of iv in the context of predicting extreme risk has received relatively little attention the potential benefit of iv in forecasting extreme risk is considered within a range of models beginning with the traditional garch based approach along with a number of novel point process models univariate models where iv is included as an exogenous variable are considered along with a novel bivariate approach where extreme movements in iv are treated as another point process it is found that in the context of forecasting value at risk the bivariate models produce the most accurate forecasts across a wide range of scenarios

how relevant is volatility forecasting for financial risk management it depends if volatility fluctuates in a forecastable way volatility forecasts are useful for risk management hence the interest in volatility forecastability in the risk management literature volatility forecastability however varies with horizon and different horizons are relevant in different applications moreover existing assessments of volatility forecastability are plagued by the fact that they are joint assessments of volatility forecastability and an assumed model and the results can vary not only with the horizon but also with the assumed model to address this problem we develop a model free procedure for assessing volatility forecastability across horizons perhaps surprisingly we find that volatility forecastability decays quickly with horizon volatility forecastability although clearly of relevance for risk management at the short horizons relevant for say trading desk management may be much less important at longer horizons

bridging the gap between the distribution of realized ecu volatility and arch modelling of the euro the garch nig model summary this paper bridges the gap between traditional arch modelling and recent advances on realized volatilities based on a ten year sample of five minute returns for the ecu basket currencies versus the us dollar we find that the realized volatilities constructed from the summation of the high frequency intraday squared returns conditional on the lagged squared daily returns are approximately inverse gaussian ig distributed while the distribution of the daily returns standardized by their realized volatilities is approximately normal moreover the implied daily garch model with normal inverse gaussian nig errors estimated for the ecu returns results in very accurate out of sample predictions for the three years of actual daily euro us dollar exchange rates copyright 2002 john wiley sons ltd

multinomial var backtests a simple implicit approach to backtesting expected shortfall under the fundamental review of the trading book frtb capital charges for the trading book are based on the coherent expected shortfall es risk measure which show greater sensitivity to tail risk in this paper it is argued that backtesting of expected shortfall or the trading book model from which it is calculated can be based on a simultaneous multinomial test of value at risk var exceptions at different levels an idea supported by an approximation of es in terms of multiple quantiles of a distribution proposed in emmer et al 2015 by comparing pearson nass and likelihood ratio tests lrts for different numbers of var levels n it is shown in a series of simulation experiments that multinomial tests with n 4 are much more powerful at detecting misspecifications of trading book loss models than standard bi nomial exception tests corresponding to the case n 1 each test has its merits pearson offers simplicity nass is robust in its size properties to the choice of n the lrt is very powerful though slightly over sized in small samples and more computationally burdensome a traffic light system for trading book models based on the multinomial test is proposed and the recommended procedure is applied to a real data example spanning the 2008 financial crisis