Abstract
This paper models the behaviour of financial ratios using the techniques of continuous time stochastic calculus. Previous work in the area has been restricted to models based on first order stochastic differential equations. However, in the present paper we model a ratio's displacement from its long term mean in terms of a second order stochastic differential equation. In this way we show that higher order equations may be used to provide more flexible modelling procedures than those previously studied. The paper begins by describing a ratio's evolution in terms of a particular form of second order stochastic differential equation. A solution is then obtained for this equation. We then show how the parameters of the model may be estimated from a given set of empirical data. The model is then applied to a data set of four ratios for 118 UK companies covering a period of 37 years. For three of the four ratios, clear evidence of a period emerges. Previous work suggests that these ratios are well described by mean reversion processes. Our empirical analysis, however, suggests there is a significant tendency for adjustments to 'overshoot' the targeted long term mean. Taken together with prior work in the area, the paper begins to provide a broad picture of the way in which financial ratios evolve over time.
Original language | English |
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Pages (from-to) | 419-427 |
Number of pages | 9 |
Journal | Omega |
Volume | 23 |
Issue number | 4 |
DOIs | |
Publication status | Published - Aug 1995 |
Keywords
- Markov
- distribution
- ratio
- steady state