a multi objective multi period stochastic programming model for public debt management while raising debt on behalf of the government public debt managers need to consider several possibly conflicting objectives and have to find an appropriate combination for government debt taking into account the uncertainty with regard to the future state of the economy in this paper we explicitly consider the underlying uncertainties with a complex multi period stochastic programming model that captures the trade offs between the objectives the model is designed to aid the decision makers in formulating the debt issuance strategy we apply an interactive procedure that guides the issuer to identify good strategies and demonstrate this approach for the public debt management problem of turkey

bond pricing and the term structure of interest rates a new methodology for contingent claims valuation this paper presents a unifying theory for valuing contingent claims under a stochastic term structure of interest rates the methodology based on the equivalent martingale measure technique takes as given an initial forward rate curve and a family of potential stochastic processee for its subsequent movements a no arbitrage condition restricts this family of processes yielding valuation formulae for interest rate sensitive contingent claims which do not explicitly depend on the market prices of risk examples are provided to illustrate the key results in relation to the term structure of interest rates arbitrage pricing theory has two purposes the first is to price all zero coupon default free bonds of varying maturities from a finite number of economic fundamentals called state variables the second is to price all interest rate sensitive contingent claims taking as given the prices of the zero coupon bonds this paper presents a general theory and a unifying framework for understanding arbitrage pricing theory in this context of which all existing arbitrage pricing models are special cases in particular vasicek 1977 brennan and schwartz 1979 langetieg 1980 ball and torous 1983 ho and lee 1986 schaefer and schwartz 1987 and artzner and delbaen 1988 the primary contribution of this paper however is a new methodology for solving the second problem i e the pricing of interest rate sensitive contingent claims given the prices of all zero coupon bonds the methodology is new because i it imposes its stochastic structure directly on the evolution of the forward rate curve ii it does not require an inversion of the term structure to eliminate the market prices of risk from contingent claim values and iii it has a stochastic spot rate process with multiple stochastic factors influencing the term structure the model can be used to consistently price and hedge all contingent claims american or european on the term structure and it is derived from necessary and more importantly sufficient conditions for the absence of arbitrage the arbitrage pricing models of vasicek 1977 brennan and schwartz 1979 langetieg 1980 and artzner and delbaen 1988 all require an iformerly titled bond pricing and the term structure of interest rates a new methodology

lag length selection and tests of granger causality between money and income one of the most widely accepred relationships in macroeconomics is the positive relationship between the rate of growth of the money supply and the rate of growth of income a diversity of opinion arises however with the attempt to identify a causal relationship between these variables while friedman and schwartz 1963 initiated the empirical investigation of money income causality sims 1972 made the most significant contribution to this literature with a practical application of the criterion developed by granger 1969 for identifying a causal relationship since the appearance of sims s approach and an alternative one advanced by sargent 1976 many researchers have applied these techniques to the investigation of the causal relationship between money and income l with two exceptions hsiao 1981 and mcmillin and fackler 1984 these researchers have arbitrarily chosen the lengths of their distributed lags the purpose of this paper is to test for granger causality between money and income this paper differs from previous work in that considerably more attention is focused on the effect of the lag specification on the test results in particular we investigate the extent to which rules of thumb arbitrary lag specifications and

changes in the u s wage structure 1963 1987 application of quantile regression the 1980 s witnessed rapid changes in the structure of wages in the united states in this study recently developed techniques for quantile regression are applied to every march current population survey since 1964 and changes in the return to schooling and experience at different points of the wage distribution are examined the quantile regression technique parsimoniously describes the entire conditional wage distribution this conditional distribution is used to examine changes in within group wage inequality as measured by the difference between conditional quantiles two linear models are considered a simple one group model and a 16 group model the results suggest that the returns to schooling and experience differ across quantiles of the wage distribution but their patterns of change are similar significant differences in wage inequality are also found across the various skill groups the paper also presents a new imputation method for cps data

measuring over education previous work on over education has assumed homogeneity of workers and jobs relaxing these assumptions we find that over educated workers have lower education credentials than matched graduates among the over educated graduates we distinguish between the apparently over educated workers who have similar unobserved skills as matched graduates and the genuinely over educated workers who have a much lower skill endowment over education is associated with a pay penalty of 5 11 for apparently over educated workers compared with matched graduates and of 22 26 for the genuinely over educated over education originates from the lack of skills of graduates this should be taken into consideration in the current debate on the future of higher education in the uk

dynamic models for fixed income portfolio management under uncertainty abstract we develop multi period dynamic models for fixed income portfolio management under uncertainty using multi stage stochastic programming with recourse the models integrate the prescriptive stochastic programs with descriptive monte carlo simulation models of the term structure of interest rates extensive validation experiments are carried out to establish the effectiveness of the models in hedging against uncertainty and to assess their performance vis a vis single period models an application to tracking the salomon brothers mortgage index is reported with very encouraging results results that establish the efficacy of the models in hedging against out of sample scenarios are also reported for an application from money management the multi period models outperform classical models based on portfolio immunization and single period models

rational prepayment and the valuation of mortgage backed securities this article presents a new model of mortgage prepayments based on rational decisions by mortgage holders these mortgage bolders face beterogeneous transaction costs which are explicitly modeled the model is estimated using a version of hansen s 1982 generalized method of moments and is sbown to capture many of the empirical features of mortgage prepayment estimation results indicate that mortgage holders act as tbougb tbey face transaction costs tbat far exceed tbe explicit costs usually incurred on refinancing they also wait an average of more than a year before refinancing even when it is optimal to do so the model fits observed prepayment behavior as well as thee recent empirical model of schwartz and torous 1989 implications for pricing mortgage backed securities are discussed

money velocity causality detection evidence from some developing countries abstract this paper is an attempt to test friedman s hypothesis that the variability of money growth causes velocity to change the granger causality method is applied to test this hypothesis using quarterly data from 1974 i to 1985 iv for seven developing countries indonesia nigeria qatar kuwait saudi arabia the united arab emirates and venezuela these countries are characterized by relatively narrow but expanding money markets

a generalized valuation model for fixed rate residential mortgages this paper uses option pricing techniques to rationally price mortgage instruments subject to both default and prepayment risk attention is given to terminations due to purely financial consideration of the mortgage contract itself as well as to personally induced terminations explicit inclusion of default in the mortgage valuation procedure also permits the valuation of insurance against such default qualitatively it is found that default differs significantly in the behavior from either prepayment or nonfinancial termination quantitatively however there is significant substitution between prepayment and default so that the addition of a default feature to the contract has only a modest impact on mortgage values unless there is substantial price volatility in the housing market or a high loan to value ratio copyright 1992 by ohio state university press

monetary variability united states and japan note many economists have criticized the federal reserve because of the high variability of monetary growth in the united states since the change in operating procedures on october 6 1979 chairman paul volcker has responded to this criticism in congressional testimony november 19 1980 and in a letter to senator garn february 18 1982 by asserting that international comparisons all appear to demonstrate the same point u s monetary aggregates rank at or near the top of the league in terms of low variability and this is true even allowing for the technical difficulties involved in making such international comparisons

robust min max portfolio strategies for rival forecast and risk scenarios we consider an extension of the markowitz mean variance optimization framework to multiple return and risk scenarios it is well known that asset return forecasts and risk estimates are inherently inaccurate the method proposed provides a means for considering rival representations of the future the optimal portfolio is computed simultaneously with the worst case to take account of all rival scenarios this is a min max strategy which is essentially equivalent to a robust pooling of the scenarios robustness is ensured by the noninferiority of min max for example a basic worst case optimal return is guaranteed in view of multiple return scenarios if robustness happens to have too high a cost guided by the min max pooling it is also possible to explore other pooling alternatives a min max algorithm is used to solve the problem and illustrate the robust character of min max with return and risk scenarios we study the properties of the min max risk return frontier and compare with the potentially suboptimal worst case where the investment strategy and the worst case are computed separately 2000 elsevier science b v all rights reserved jel classixcation c44 c61 c63 g11

autoregressive modelling and money income causality detection abstract a step wise procedure based on granger s concept of causality and abaike s final prediction error criterion is suggested as a practical means to identify the order of lags of each variable in a multivariate autoregressive process the model seems useful because it can serve as a reduced form formulation to avoid imposing often spurious or false restrictions of the model it also provides a reasonably powerful test of causality the idea is applied to u s postwar money and income data it is found that between m1 and gnp a bivariate feedback model fits the data best between m2 and gnp a one way causal model from money to income performs better diagnostic checks applied to our model seem to indicate the adequacy of our approach

a model for designing callable bonds and its solution using tabu search abstract we formulate the problem of designing callable bonds as a non linear global optimization problem the data of the model are obtained from simulations of holding period returns of a given bond design which are used to compute a certainty equivalent return viz some target assets the design specifications of the callable bond are then adjusted so that the certainty equivalent return is maximized the resulting problem is multi modal and a tabu search procedure implemented on a distributed network of workstations is used to optimize the bond design the model is compared with the classical portfolio immunization model and the tabu search solution technique is compared with simulated annealing for solving the global optimization program it is shown that the global optimization model yields higher returns than portfolio immunization it is also shown that tabu search is computationally more efficient than simulated annealing in solving the model and it produces better solutions

complete prepayment models for mortgage backed securities the estimation of prepayment rates for pools of mortgages is a critical component in determining the value of mortgage backed securities mbs for short and derivative products this paper discusses the development of prepayment models for pools of fixed rate mortgages the models are complete calibrated functional forms are given for all of the factors that determine prepayment rates hence the models can be used as benchmarks against the simple models of the public securities association the federal housing administration experience or the variety of projected prepayment rates generated by proprietary industry models the key factors that determine prepayment rates are 1 refinancing incentive 2 seasonal variations 3 seasoning of the mortgage pool and 4 burnout effect each factor is modeled separately and is calibrated using historical data a multiplicative relationship determines the prepayment rate of the mortgage pool a novel feature of our model is the use of basis functions that cap

optimal mismatch and promotions i introduction a substantial proportion of workers are employed in jobs for which they appear to be either overqualified or underqualified for instance using data from the panel study of income dynamics sicherman 1991 finds that 40 percent of his sample are overeducated and another 16 percent are undereducated rumberger 1987 reports similar values using data from the quality of employment surveys other studies which find substantial education mismatch include duncan and hoffman 1981 verdugo and verdugo 1989 and hersch 1991 and evidence that a single firm hires both under and overqualified workers is presented here this paper provides an explanation for why firms hire both overqualified and underqualified workers firms hire overqualified workers because these workers require less training for their initial positions such workers also form a pool from which promotions are made which lowers hiring costs for higher level positions within the firm workers accept positions for which they are overqualified to enhance their probability of promotion and because of search and mobility costs but if they fail to be promoted to a position that better matches their qualifications they are more likely to quit firms hire underqualified workers despite their longer training requirement since such workers are less likely to quit and provide continuity of the labor force over time thus contrary to job matching arguments that would explain these hires as a result of imperfect information hiring of seemingly mismatched workers is optimal and these matches are made with perfect information the model developed in this paper yields three testable hypotheses 1 training time for entry level jobs is inversely related to overqualification at the time of hire 2 workers who are overqualified on their current job are those who have failed to be promoted to a job which better matches their qualifications and such workers are more likely to quit and 3 workers overqualified at time of hire are more likely to be promoted to test these hypotheses i use new data collected for this purpose previous empirical research such as that cited above was restricted by data availability to examining only the match between education and the worker s current job thus the quality of the match with the worker s initial job and the match between worker qualifications other than education has gone unexplored however various worker characteristics in addition to education are often substituted for each other in determining a worker s qualification for a job thus i examine additional qualifications including the match between the worker s experience level of previous job and use of skills information on the match between the worker s qualifications and those required for the initial job with the employer is particularly important since entry level qualifications determine training time for the initial job as well as the likelihood of promotion further individual specific training time for the initial job is necessary but typically not available since data sets providing information on training such as the panel study of income dynamics and quality of employment surveys request information on training time for the average worker and not for the individual worker the data set reveals several interesting statistics qualification mismatch at hire is fairly common for this firm 29 percent of the sample report themselves overqualified for their first job with the firm while 13 percent report themselves as underqualified lateral intra firm mobility is common and occurs far more frequently than promotions workers in the sample average 1 3 promotions but four different jobs with the employer this suggests that the job matching process occurs not only by turnover but through intrafirm mobility consistent with the assumptions and implications of the model the empirical results indicate that workers who are overqualified at hire receive less training and more promotions and that workers overqualified for their current job are more likely to quit

a two factor stochastic programming model of danish mortgage backed securities abstract danish mortgage loans have several features that make them interesting short term revolving adjustable rate mortgages are available as well as fixed rate 10 20 or 30 year annuities that contain embedded options call and delivery options the decisions faced by a mortgagor are therefore non trivial both in terms of deciding on an initial mortgage and in terms of managing rebalancing it optimally we propose a two factor arbitrage free interest rate model calibrated to observable security prices and implement on top of it a multi stage stochastic optimization program with the purpose of optimally composing and managing a typical mortgage loan we model accurately both fixed and proportional transaction costs as well as tax effects risk attitudes are addressed through utility functions and through worst case min max optimization the model is solved in up to 9 stages having 19 683 scenarios numerical results which were obtained using standard soft and hardware indicate that the primary determinant in choosing between adjustable rate and fixed rate loans is the short long interest rate differential i e term structure steepness but volatility also matters refinancing activity is influenced by volatility and of course transaction costs

integrated simulation and optimization models for tracking indices of fixed income securities increasing performance pressures on fixed income managers have led to a search for new and creative ways to add to portfolio returns the largest pension plan sponsors insurance companies foundations and money management firms are using indexed portfolios as their fixed income assets management strategies since the late 1970s tracking a fixed income index is a difficult task due to transaction costs portfolio size and diversification restrictions liquidity requirements bid ask spreads etc this paper develops an integrated simulation and optimization approach for tracking fixed income indices the model was implemented at metropolitan life insurance company we introduce a simulation model for generating scenarios of holding period returns of the securities in the index then we develop optimization models to select a portfolio that tracks the index the models penalize downside deviations of the portfolio return from the index the developed framework is used to track the salomon brothers mortgag

a stochastic programming model for money management abstract portfolio managers in the new fixed income securities have to cope with various forms of uncertainty in addition to the usual interest rate changes uncertainy in the timing and amount of cashflows changes in the default and other risk premia and so on complicate the portfolio manager s problem we develop here a multi period dynamic portfolio optimization model to address this problem the model specifies a sequence of investment decisions over time that maximize the expected utility of return at the end of the planning horizon the model is a two stage stochastic program with recourse the dynamics of interest rates cashflow uncertainty and liquidity default and other risk premia are explicitly modeled through postulated scenarios simulation procedures are developed to generate these scenarios the optimization models are then integrated with the simulation procedures extensive validation experiments are carried out to establish the effectiveness of the model in dealing with uncertainty in particular the model is compared against the popular portfolio immunization strategy and against a portfolio based on mean absolute deviation optimization

educational mismatch and the earnings distribution thanks to the participants of the 2015 new directions in human capital theory workshop at the university of birmingham uk the 2016 midwestern economic society annual meetings the 2017 scottish economic society annual conference seminar participants at the university of aberdeen and to the editor and the two referees for helpful comments on the paper the usual disclaimer applies

a mixed integer linear programming model for optimal sovereign debt issuance abstract governments borrow funds to finance the excess of cash payments or interest payments over receipts usually by issuing fixed income debt and index linked debt the goal of this work is to propose a stochastic optimization based approach to determine the composition of the portfolio issued over a series of government auctions for the fixed income debt to minimize the cost of servicing debt while controlling risk and maintaining market liquidity we show that this debt issuance problem can be modeled as a mixed integer linear programming problem with a receding horizon the stochastic model for the interest rates is calibrated using a kalman filter and the future interest rates are represented using a recombining trinomial lattice for the purpose of scenario based optimization the use of a latent factor interest rate model and a recombining lattice provides us with a realistic yet very tractable scenario generator and allows us to do a multi stage stochastic optimization involving integer variables on an ordinary desktop in a matter of seconds this in turn facilitates frequent re calibration of the interest rate model and re optimization of the issuance throughout the budgetary year allows us to respond to the changes in the interest rate environment we successfully demonstrate the utility of our approach by out of sample back testing on the uk debt issuance data

a comparison of alternative models for pricing gnma mortgage backed securities since the issuance of the first government national mortgage association gnma mortgage backed pass through security in february 1970 the total amount of gnmas issued has grown to over 105 billion in terms of their trading volume gnma securities are the most actively traded class of long term fixedrate instruments however this gross volume statistic masks the fact that gnmas are not homogeneous securities they differ by coupon interest rate and remaining term to maturity there is also a widely held belief 12 and some evidence 7 that gnmas differ according to their expected prepayment rates the bulk of the trading volume in gnmas is comprised of newly issued securities new securities are generally issued at the federal housing administration fha maximum interest rate and have terms to maturity of 30 years while most gnma trading is comprised of new issues the bulk of the outstanding securities is comprised of old securities whose coupon rates may differ from the current fha ceiling and whose remaining terms to maturity are less than 30 years this raises a pricing problem for gnma security dealers portfolio managers financial institutions that hold large portfolios of gnma securities and other potential gnma investors up to date market price quotes are available for new issues but quotes for old ones are not so readily available thus potential traders confront the problem of pricing these infrequently traded securities the problem of pricing gnma securities was initially addressed by curley and guttentag 5 they presented a model for the pricing of gnmas that was an imaginative and important extension of the then widely used average life procedure the particular innovation of their model was to incorporate estimates of the prepayment probabilities to determine expected future cash flows through simulation and sensitivity analysis curley and guttentag hereafter c g compared prices generated by their model with those generated by the traditional average life procedure in his discussion of the c g paper brealey 1 encouraged the authors to extend their model to incorporate uncertainty and to value explicitly the call options attached to the underlying mortgage loans in a previous paper 6 we

capturing the correlations of fixed income instruments this paper develops a framework for managing portfolios of fixed income instruments based on traditional principles from the equities market i e based on diversification it shows through an analysis of the high yield bond market over the period 1987 to 1991 that fixed income prices could be highly correlated these correlations can be quantified and integrated in a systematic way in an asset liability management framework for vanishing fixed income securities however we cannot resort to statistical analysis of historical data in order to quantify correlations the paper develops a forward looking simulation procedure for capturing correlations applications are illustrated for examples from high yield bonds and mortgage backed securities the superiority of the proposed approach over the traditional portfolio immunization techniques is demonstrated in the context of funding an insurance liability stream with mortgage instruments

mortgage loan portfolio optimization using multi stage stochastic programming we consider the dynamics of the danish mortgage loan system and propose several models to reflect the choices of a mortgagor as well as his attitude towards risk the models are formulated as multi stage stochastic integer programs which are difficult to solve for more than 10 stages scenario reduction and lp relaxation are used to obtain near optimal solutions for large problem instances our results show that the standard danish mortgagor should hold a more diversified portfolio of mortgage loans and that he should rebalance the portfolio more frequently than current practice