on the frequency of large stock returns putting booms and busts into perspective textabstractnumerous articles have investigated the distribution of share prices and find that the returns are fat tailed nevertheless there is still controversy about the amount of probability mass in the tails and hence about the most appropriate distribution to use in modeling returns this controversy has proven hard to resolve as the alternatives are non nested we employ extreme value theory focusing exclusively on the larger observations in order to assess the tail shape within a unified framework we find that at least the first two moments exist this enables one to generate robust probabilities on large returns which put the recent stock market swings into historical perspective

optimal currency composition for china s foreign reserves a copula approach this paper investigates the optimal currency composition for a country s foreign reserves in the context of china we examine the asymmetric fat tail and complex dependence structure in distributions of currency returns a skewed fat tailed and pair copula construction is then built to capture features of higher moments in a d vine copula approach we show that under the disappointment aversion effect the central bank in our model can achieve sizeable gains in expected economic value from switching from the mean variance to copula modelling we find that this approach will lead to an optimal currency composition that allows china to have more space for international currency diversification while maintaining the leading position of the us dollar in the currency shares of china s reserves

revisiting the home bias puzzle downside equity risk deviations from normality in financial return series have led to the development of alternative portfolio selection models one such model is the downside risk model whereby the investor maximizes his return given a downside risk constraint in this paper we empirically observe the international equity allocation for the downside risk investor using nine international markets returns over the last 34 years the results hold for both daily and monthly data and also from an international perspective due to greater downside risk investors may think globally but instead act locally the model s results therefore provide an alternative view of the home bias puzzle

the optimal value at risk hedging strategy under bivariate regime switching arch framework unlike the majority of other hedging literatures in which variance is taken as the risk indicator this article uses the value at risk var as the risk management tool of the hedged portfolio this article adopts a bivariate markov regime switching autoregressive conditional heteroscedastic swarch model to formulate the optimal var hedging strategy and then compares it with the other dynamic futures hedging strategies mentioned in the literature in hedging performance using taiwan stock exchange capitalization weighted stock index taiex futures data the in sample and out of sample results shows that when var is used as the criterion to measure the futures hedging effectiveness the performance of the dynamic hedging strategy is superior to that of the static hedging strategy and the performance of the optimal var hedging strategy is better than that of the minimum variance and mean variance hedging strategies besides from the standpoint that the volatility of hedge ratio and hedged portfolio var

the statistical distribution of exchange rates empirical evidence and economic implications the abundant evidence that changes in exchange rates have distributions with fatter tails than the normal distribution has led researchers to consider non normal distributions including the student the stable paretian and mixtures of distributions this paper compares the empirical fits of three non normal candidates and the normal distribution for daily changes in the logarithms of exchange rates using maximum likelihood estimation of the parameters and chi square goodness of fit tests the student and mixture of two normals provide the best fits but there is evidence that the distribution parameters may vary over time

tail estimation and mean var portfolio selection in markets subject to financial instability abstract risk managers are increasingly required by international regulatory institutions to adopt accurate techniques for the measurement and control of portfolios financial risks the task requires first the identification of the different risk sources affecting the portfolio and the measurement of their impact then after the adoption of appropriate portfolio strategies aimed at neutralising these risks the comprehensive concept of value at risk var as a maximum tolerable loss with a given confidence interval has become in this regard the industry standard in risk management in the paper we focus on the implications of different risk measurement techniques and portfolio optimisation strategies in presence of markets subject to periods of severe instability resulting in significant deviations of financial returns from the normality assumption typically adopted in mainstream finance comparative results on 1 day var 99 estimation are presented over a range of bond and equity markets with different risk profiles the reference period of our analysis includes several market shocks and in particular the argentinean eurobond crisis of july 2001 the solution of an optimal portfolio problem over the crisis period is discussed within a mean variance var99 portfolio space emphasising the difficulty of the portfolio s relative return maximisation problem faced by fund managers

optimal portfolio selection in a value at risk framework abstract in this paper we develop a portfolio selection model which allocates financial assets by maximising expected return subject to the constraint that the expected maximum loss should meet the value at risk limits set by the risk manager similar to the mean variance approach a performance index like the sharpe index is constructed furthermore when expected returns are assumed to be normally distributed we show that the model provides almost identical results to the mean variance approach we provide an empirical analysis using two risky assets us stocks and bonds the results highlight the influence of both non normal characteristics of the expected return distribution and the length of investment time horizon on the optimal portfolio selection

bank regulation and international financial stability a case against the 2006 basel framework for controlling tail risk in trading books abstract in attempting to promote international financial stability the basel committee on banking supervision 2006 provided a framework that sought to control the amount of tail risk that large banks around the world would take in their trading books relative to their corresponding minimum capital requirements however many of these banks suffered significant trading losses during the recent financial crisis our paper examines whether the basel framework allowed banks to take substantive tail risk in their trading books without a capital requirement penalty we find that it allowed banks to do so and that its minimum capital requirements can be notably procyclical hence focusing on the way the basel framework sought to control the amount of tail risk in trading books relative to their corresponding minimum capital requirements our paper supports the view that it was not properly designed to promote financial stability we also discuss alternative regulatory frameworks that would potentially be more effective than the basel framework in preventing banks from taking substantive tail risk in their trading books without a capital requirement penalty

analysing inflation by the fractionally integrated arfima garch model this paper considers the application of long memory processes to describing inflation for ten countries we implement a new procedure to obtain approximate maximum likelihood estimates of an arfima garch process which is fractionally integrated i d with a superimposed stationary arma component in its conditional mean additionally this long memory process is allowed to have garch type conditional heteroscedasticity on analysing monthly post world war ii cpi inflation for ten different countries we find strong evidence of long memory with mean reverting behaviour for all countries except japan which appears stationary for three high inflation economies there is evidence that the mean and volatility of inflation interact in a way that is consistent with the friedman hypothesis

a dynamic autoregressive expectile for time invariant portfolio protection strategies constant proportion portfolio insurance cppi is nowadays one of the most popular techniques for portfolio insurance strategies it simply consists of reallocating the risky part of a portfolio with respect to market conditions via a leverage parameter called the multiple guaranteeing a predetermined floor we propose to introduce a conditional time varying multiple as an alternative to the standard unconditional cppi method directly linked to actual risk management problematics this ex ante approach for the conditional multiple aims to diversify the risk model associated for example with the expected shortfall es or extreme risk measure estimations first we recall the portfolio insurance principles and main properties of the cppi strategy including the time invariant portfolio protection tipp strategy as introduced by estep and kritzman 1988 we emphasize the existence of an upper bound on the multiple for example to hedge against sudden drops in the market then we provide the main properties of the conditional multiples for well known financial models including the discrete time portfolio rebalancing case and levy processes to describe the risky asset dynamics for this purpose we precisely define and evaluate different gap risks in both conditional and unconditional frameworks as a by product the introduction of discrete or random time portfolio rebalancing allows us to determine and or estimate the density of durations between rebalancements finally from a more practical and statistical point of view due to trading restrictions we present the class of dynamic autoregressive expectile dare models for estimating the conditional multiple this latter approach provides useful complementary information about the risk and performance associated with probabilistic approaches to the conditional multiple

non linear dependence modelling with bivariate copulas statistical arbitrage pairs trading on the s p 100 abstractwe develop a copula based pairs trading framework and apply it to the sp the top 5 momentum pairs yield 7 22 per year standard deviations are low leading to annualized sharpe ratios of 1 52 top 5 mean reversion and 1 33 top 5 momentum respectively

downside risk and portfolio diversification in the euro zone equity markets with special consideration of the crisis period abstract this study examines the value at risk for ten euro zone equity markets individually and also divided into two groups piigs portugal italy ireland greece and spain and the core austria finland france germany and the netherlands employing four var estimation and evaluation methods considered over the full period and the pre and post global crisis subperiods 1 and 2 the backtesting results are also evaluated according to the basel capital requirements the results demonstrate that the cevt methods meet all the statistical criteria the best for most individual equity indices over the full period but these results over the two subperiods for those two methods are mixed compared to those the dpot methods moreover the two optimal group portfolios of the piigs and the core as well as the grand portfolio that combines the ten indices do not show much diversification benefits the piigs portfolio selects spain s ibex only while that of the core opts for austria s atx only in the full period and subperiod 1 however germany s dax overwhelmingly dominates both the core and the grand portfolios in subperiod 2

options and structured products in behavioral portfolios abstract options and structured products have no roles in mean variance portfolios but they have roles in behavioral portfolios behavioral portfolios are composed of mental account sub portfolios each associated with a goal such as retirement income or bequest investors optimize each mental account by finding the assets and asset allocation that maximizes the expected return of each mental account sub portfolio subject to the condition that the probability of failing to reach a preset threshold aspiration level not exceed a preset probability put options are useful in downside protection mental accounts whose goal is avoiding poverty whereas call options are useful in upside potential mental accounts whose goal is a shot at riches we also explore the roles in behavioral portfolios of option collars capital guaranteed notes and barrier range notes

multivariate dependence and portfolio optimization algorithms under illiquid market scenarios we propose a model for optimizing structured portfolios with liquidity adjusted value at risk lvar constraints whereby linear correlations between assets are replaced by the multivariate nonlinear dependence structure based on dynamic conditional correlation t copula modeling our portfolio optimization algorithm minimizes the lvar function under adverse market circumstances and multiple operational and financial constraints when we consider a diversified portfolio of international stock and commodity market indices under multiple realistic portfolio optimization scenarios the obtained results consistently show the superiority of our approach relative to other competing portfolio strategies including the minimum variance risk parity and equally weighted portfolio allocations

optimal mean variance portfolio selection using cauchy schwarz maximization fund managers highly prioritize selecting portfolios with a high sharpe ratio traditionally this task can be achieved by revising the objective function of the markowitz mean variance portfolio model and then resolving quadratic programming problems to obtain the maximum sharpe ratio portfolio this study presents a closed form solution for the optimal sharpe ratio portfolio by applying cauchy schwarz maximization and the concept of kuhn tucker conditions an empirical example is used to demonstrate the efficiency and effectiveness of the proposed algorithms moreover the proposed algorithms can also be used to obtain the optimal portfolio containing large numbers of securities which is not possible or at least is complicated via traditional quadratic programming approaches

self fulfilling risk panics abstract recent crises have seen large spikes in asset price risk we propose an explanation for such panics based on self fulfilling shifts in beliefs about risk a negative link between the curre

evaluating the dynamic performance of energy portfolios empirical evidence from the dea directional distance function abstract in recent years the complex global energy commodity market has led to increased uncertainty for energy investment returns and tremendous challenges for investors to design appropriate energy portfolios therefore we employ four popular portfolio methods to determine energy portfolios based on daily fossil fuel futures prices during 2006 2015 moreover we use the dea window analysis method and dea directional distance function to comprehensively evaluate the dynamic performance of these energy portfolios based on the efficiency perspective the empirical results indicate that first to increase investment returns the mean variance method that exclusively emphasizes the maximization of returns shows the best performance however in order to decrease the volatility and risk of investment returns the mean variance method that aims to resist risk more than make profits and the bootstrap historical simulation value at risk var method have the best performance second when the global financial crisis broke out in the second half of 2008 and energy markets experienced a sharp downturn in the second half of 2014 the dea efficiency of energy portfolios appeared relatively lower than those of their neighboring periods regardless of which portfolio method is employed finally the average dea efficiencies of energy portfolios are all higher than those of single energy investment throughout the sample period except when the equally weighted method and the information entropy comprehensive index method are used meanwhile the mean variance method that prefers profit making to risk resisting possesses the highest average dea efficiency among various methods concerned

portfolio frontiers with restrictions to tracking error volatility and value at risk abstract asset managers are often given the task of restricting their activity by keeping both the value at risk var and the tracking error volatility tev under control however these constraints may be impossible to satisfy simultaneously because var is independent of the benchmark portfolio the management of these restrictions is likely to affect portfolio performance and produces a wide variety of scenarios in the risk return space the aim of this paper is to analyse various interactions between portfolio frontiers when risk managers impose joint restrictions upon tev and var specifically we provide analytical solutions for all the intersections and we propose simple numerical methods when such solutions are not available finally we introduce a new portfolio frontier

a multivariate latent factor decomposition of international bond yield spreads a factor analysis of long term bond spreads is performed by decomposing international interest rate spreads into national and global factors the factors are latent and are assumed to have garch type specifications as well as exhibiting serial dependence an indirect estimator is used to compute estimates of the unknown parameters the sampling performance of this estimator is investigated and compared with an alternative direct estimator based on the kalman predictor the factor model is applied to weekly data on long bond spreads between five countries australia japan germany canada and the uk and the usa over the period 1991 to 1999 the resulting factor decomposition is used to examine the international investor s optimal portfolio decision in a mean variance framework copyright 2000 john wiley sons ltd

production planning for a deteriorating item with stochastic demand and consumer choice abstract this paper concerns inventory control of a deteriorating product with non negligible procurement lead time that perishes after a known number of periods demand for fresh products during each period is represented as a random variable with known probability distribution but only a fraction of this demand is satisfied during any given period due to item deterioration we derive the expected profit function for a two period problem with one production opportunity before the selling season begins and a single product type with two period shelf life for the case in which demand during both periods is uniform independent and identically distributed we identify sufficient conditions for the existence of an optimal solution and present a straightforward procedure for obtaining the solution

a stochastic variance factor model for large datasets and an application to s p data the aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets we suggest use of the principal component methodology of stock and watson 2002 for the stochastic volatility factor model discussed by harvey ruiz and shephard 1994 the method is simple and computationally tractable for very large datasets we provide theoretical results on this method and apply it to s p data

macroeconomic forecasting using diffusion indexes this article studies forecasting a macroeconomic time series variable using a large number of predictors the predictors are summarized using a small number of indexes constructed by principal component analysis an approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts the method is used to construct 6 12 and 24 monthahead forecasts for eight monthly u s macroeconomic time series using 215 predictors in simulated real time from 1970 through 1998 during this sample period these new forecasts outperformed univariate autoregressions small vector autoregressions and leading indicator models

grading the performance of market indicators with utility benchmarks selected from footsie a 2000 case study the suitable choice of a benchmark portfolio is a critical problem prior to using the information ratio as the performance ranking of funds depends on this choice in this paper a method to optimize benchmark selection taking account of the investor s preferences is proposed and applied to a case study of performance for 29 market indicators on stock exchanges throughout the world the method that relies on recent results in optimization theory requires defining the opportunity set to select the benchmarks this set being footsie in the case study the computational process and numerical results are presented through tables and figures the accuracy of the method being also numerically tested