Imputation Methods for Incomplete Dependent Variables in Finance

Missing observations in dependent variables is a common feature of many financial applications. Standard ad hoc missing value imputation methods invariably fail to deliver efficient and unbiased parameter estimates. A number of recently developed classical and Bayesian iterative methods are evaluated for the treatment of missing dependent variables when the independent variables are completely observed. These methods are compared by simulation to commonly applied alternative missing data methodologies in the finance literature. The methods are then applied to a system of simultaneous equations modelling the maturity, secured status, and pricing of U.S. bank revolving loan contracts. Two of the four dependent variables in this application are characterised by severe missingness. The system of equations approach allows us to also exploit the additional information contained in the interdependencies among these features. The results indicate that proper treatment of missingness can be important for many financial applications.

Structurally Sound Dynamic Index Futures Hedging

Portfolio managers use index futures for a variety of reasons. Regardless of their motivation, they will keep a close eye on the relation between the futures and their stock portfolio returns. Whenever this relation is perceived to have changed, the manager will decide whether it is worthwhile to rebalance the portfolio mix. Exact measures as to when and how much rebalancing should occur, have not yet been established. This paper proposes a heuristic algorithm to dynamically update hedged portfolios. This dynamic hedging algorithm is based on a Reverse Order Cusumsquare (ROC) testing procedure, proposed by Pesaran and Timmermann (2002), to optimally determine forecast estimation windows. In a comparison with standard alternatives (expanding window, EWLS window and rolling window), we find significant improvements in hedging performance, both in- and out-of-sampreverse order cusum-square test; index futures hedging

Market Structure and Stock Splits

Enhanced liquidity is one possible motivation for stock splits but empirical research frequently documents declines in liquidity following stock splits. Despite almost thirty years of inquiry, little is known about all the changes in a stock's trading activity following a stock split. We examine how liquidity measures change around more than 2,500 stock splits and find a pervasive decline in most measures. Large stock splits exhibit a more severe liquidity decline than small stock splits, especially on Nasdaq. We also examine a longer time period around stock splits and find that the differences between small and large stocks may be short-lived. Following the 1997 changes in order handling rules and reduction in tick size, liquidity declines following stock splits continue, however, the declines are not as severe on Nasdaq, suggesting the change in order handling rules may have been effective.

Bayesian Target Zones

Several authors have postulated econometric models for exchange rates restricted to lie within known target zones. However, it is not uncommon to observe exchange rate data with known limits that are not fully 'credible'; that is, where some of the observations fall outside the stated range. An empirical model for exchange rates in a soft target zone where there is a controlled probability of the observed rates exceeding the stated limits is developed in this paper. A Bayesian approach is used to analyse the model, which is then demonstrated on Deutschemark-French franc and ECU-French franc exchange rate data.

Stock margins and the condition probability of price reversals

Does the cost of trading affect stock prices? Yes, according to the evidence in this article. The authors find that high costs seem to reduce the frequency of price reversals.Stocks ; Stock - Prices

Tracking Error and Active Portfolio Management

Persistent bear market conditions have led to a shift of focus in the tracking error literature. Until recently the portfolio allocation literature focused on tracking error minimization as a consequence of passive benckmark management under portfolio weights, transaction costs and short selling constraints. Abysmal benchmark performance shifted the literature's focus towards active portfolio strategies that aim at beating the benchmark while keeping tracking error within acceptable bounds. We investigate an active (dynamic) portfolio allocation strategy that exploits the predictability in the conditional variance-covariance matrix of asset returns. To illustrate our procedure we use Jorion's (2002) tracking error frontier methodology. We apply our model to a representative portfolio of Australian stocks over the period January 1999 through November 2002.

Limits to Linear Price Behaviour: Target Zones for Futures Prices Regulated By Limits

This paper analyzes the random walk behaviour of futures prices when the exchange regulated by price limits. Using a model analogous to exchange rate target zone models, the study tests for the existence of a nonlinear S-shape relation between observed and theoretical futures prices. This phenomenon reflects the adjustment in traders' expectations even when limits are not actually hit. The approach is illustrated for five agricultural futures contracts traded at the Chicago Board of Trade. There is some evidence of nonlinearity in quiet periods. In cases of fundamental realignments, that is volatile periods, this non-liearity disappears.price limits; target zones; gravitation; mean reversion

Migration of Price Discovery With Constrained Futures Markets

This paper investigates the information content of futures option prices when the futures price is regulated while the futures option price itself is not. The New York Board of Trade provides the empirical setting for this type of dichotomy in regulation. Most commodity derivatives markets regulate prices of all derivatives on a particular commodity simultaneously. NYBOT has taken an almost unique position by imposing daily price limits on their futures contracts while leaving the options prices on these futures contracts unconstrained. The study takes a particular interest in the volatility and futures prices of the options-implied risk neutral density when the underlying futures contract is locked limit.option implied density; price limits

Diversification Meltdown or the Impact of Fat tails on Conditional Correlation?

A perceived increase in correlation during turbulent market conditions implies a reduction in the benefits arising from portfolio diversification. Unfortunately, it is exactly then that these benefits are most needed. To determine whether diversification truly breaks down, we investigate the robustness of a popular conditional correlation estimator against alternative distributional assumptions. Analytical results show that the apparent meltdown in the benefits from diversification could be a consequence of assuming normally distributed returns. A more realistic assumption - the bivariate Student-t distribution - suggests that constant correlation may be sustained over the full support of the multivariate return distributionConditional correlation, Truncated correlation, Bivariate Student-t correlation.