Dec

2

(1) When Do Stop-Loss Rules Stop Losses?
EFA 2007 Ljubljana Meetings Paper
51 Pages Posted: 5 Mar 2007
Kathryn Kaminski, Massachusetts Institute of Technology (MIT)
Andrew W. Lo, Massachusetts Institute of Technology (MIT) - Laboratory
for Financial Engineering
Date Written: January 3, 2007

In this paper, we develop a simple framework for measuring the impact of stop-loss rules on the expected return and volatility of an arbitrary portfolio strategy, and derive conditions under which stop-loss rules add or subtract value to that portfolio strategy. We show that under the Random Walk Hypothesis, simple 0/1 stop-loss rules always decrease a strategy's expected return, but in the presence of momentum, stop-loss rules can add value. To illustrate the practical relevance of our framework, we provide an empirical analysis of a stop-loss policy applied to a buy-and-hold strategy in U.S. equities, where the stop-loss asset is U.S. long-term government bonds. Using monthly returns data from January 1950 to December 2004, we find that certain stop-loss rules add 50 to 100 basis points per month to the buy-and-hold portfolio during stop-out periods. By computing performance measures for several price processes, including a new regime-switching model that implies periodic Flights-to-quality, we provide a possible explanation for our empirical results and connections to the behavioral finance literature.

(2) Stop-Loss Orders And Price Cascades In Currency Markets
C. L. Osler, New York Fed, June 2002

In this paper, I provide evidence that currency stop-loss orders contribute to rapid, self-reinforcing price movements, which I call "price cascades." Stop-loss orders…generate positive-feedback trading. Theoretical research on the 1987 stock market crash suggests that such trading can cause price discontinuities, which would manifest themselves as price cascades. My analysis of high-frequency exchange rates offers three main results that provide empirical support for the hypothesis that stop-loss orders contribute to price cascades: (1) Exchange rate trends are unusually rapid when rates reach exchange rate levels at which stop-loss orders have been documented to cluster. (2) The response to stop-loss orders is larger than the response to take-profit orders, which generate negative-feedback trading and are therefore unlikely to contribute to price cascades. (3) The response to stop-loss orders lasts longer than the response to take-profit orders. Most results are statistically significant for hours, although not for days. Together, these results indicate that stop-loss orders propagate trends and are sometimes triggered in waves, contributing to price cascades. Stop-loss propagated price cascades may help explain the well-known “fat tails” of the distribution of exchange-rate returns, or equivalently the high frequency of large exchange-rate moves. The paper also provides evidence that exchange rates respond to non-informative order flow.


Comments

Name

Email

Website

Speak your mind

Archives

Resources & Links

Search