Pairs trading is a comparative-value form of statistical arbitrage designed to exploit temporary random departures from equilibrium pricing between two shares. However, the strategy is not riskless. Market events as well as poor statistical modeling and parameter estimation may all erode potential profits. Since conventional loss limiting trading strategies are costly, a preferable situation is to integrate loss limitation within the statistical modeling itself. This paper uses cointegration principles to develop a procedure that embeds a minimum profit condition within a pairs trading strategy. We derive the necessary conditions for such a procedure and then use them to define and implement a five-step procedure for identifying eligible trades. The statistical validity of the procedure is verified through simulation data. Practicality is tested through actual data. The results show that, at reasonable minimum profit levels, the protocol does not greatly reduce trade numbers or absolute profits relative to an unprotected trading strategy.

No abstract

This paper analyses the investment performance of Australian superannuation funds and their managers over the period from January 1973 to June 1981.The analysis indicated that both the funds and the managers performed poorly over the first two and a half years.It was found that the poor performance during these years outweighed the improved performance in sUbsequent years, resulting in an overall poor performance over the total period studied. Only one manager displayed a superior investment ability and this appears to be attributable to his ability to adjust the beta of his portfolio to suit market conditions.

Infrastructure service provision by government creates huge distributional issues about service availability and performance over time and the relative funding burdens borne by successive generations of consumers across time. But providing financial disclosure on these issues through inter‐generational accounting pre‐supposes that accounting measurement is both generationally neutral (temporal neutrality) and does not legitimate any particular pattern of distribution. At the very least, accounting measurements of service provision costs should possess the attribute of distributional fairness. They should not bias the inter‐generational allocation of cost or funding burdens. We argue that the forced application of inappropriate commercial accounting concepts of asset valuation, depreciation and capital maintenance does produce significant generational bias. More flexibility is required to produce the necessary accounting measurement attributes for financial disclosure on whether government has discharged its continuing accountability for inter‐generational equity in burden sharing. We discuss three conceptual issues and illustrate the need for flexibility by proposing an alternative ‘flow of obligations’ approach which does not require reference to valuations of community service resources or arbitrary cost allocations under depreciation.

Accounting-based valuation studies of US firms tend to support Ohlson's proposition that residual income and book value numbers have information content in explaining observed market values. But European evidence also suggests that the conservative/liberal orientation of accounting tradition can produce significant national differences in associations between accounting performance measures and stock prices - in earnings behaviour, coefficient values and parameter sensitivity. We address these issues from an equity valuation perspective using Swedish data to assess the additional information content of Ohlson's information dynamics and analysts' forecasts in relation to market valuations in a more conservative accounting environment than the US. The study compares the explanatory and predictive power of Ohlson's (1995) residual income model (RIV) with a linear information dynamics version (LIM) that specifies both residual income and non-accounting information as autoregressive processes. Both versions are applied with, and without, future performance expectations from non-accounting sources (analysts' forecasts). As with US evidence, we find that the inclusion of analysts' forecasts improves both (i) cross-sectional correlations with current prices for both RIV and LIM models and (ii) the predictive power of RIV models in relation to future annual cross-sectional stock returns. The contribution of linear information dynamics is significant but varies across approaches. We also find significant differences between Swedish and US firms in earnings behaviour and associations between accounting numbers and market equity prices.