Positive feedback investors buy stocks when prices rise and sell when prices fall. Many forms of behaviour common in financial markets can be described as positive feedback trading. It can result from extrapolative expectations about prices (Frankel and Froot, 1988), or trend chasing (De Long et al., 1990). It can also be a consequence of stop loss orders, which in effect prompt selling in response to price declines. Similarly, positive feedback trading can result from the liquidation of the positions of investors incapable to meet margin calls. Positive feedback trading is also displayed by buyers of portfolio insurance, who might use this practice because their willingness to bear risk rises sharply with wealth (Black, 1988).
2.14.1 Destabilizing feature of positive feedback trading
With positive feedback traders, rational speculation can be destabilizing. When rational speculators receive good news and eventually trade, they recognize that the initial price increase will stimulate buying by positive feedback traders tomorrow. In expectation of these purchases, informed rational speculators buy more today, driving prices up today higher than their fundamental values. Tomorrow, positive feedback traders react by buying due to today’s price increase and so keep prices above fundamentals even as rational speculators are selling out and stabilizing prices. The critical issue is that, although part of the price rise is rational, part of it is an outcome from rational speculators’ anticipatory trades and from positive feedback traders’ reaction to such trades. Trades from rational speculators destabilize prices because they prompt positive feedback trading by other investors (DeLong et al., 1990). Furthermore, it might pay a large speculator to destabilize prices (Hart, 1977).
48 In addition, the interaction of informed rational speculators and positive feedback traders leads to price destabilization which has several plausible empirical implications. DeLong et al. (1990) model generates a positive correlation of stock returns at short horizons, as positive feedback traders responds to past price increases by entering into the market, and negative correlations of stock returns at long horizons as prices eventually return to fundamentals. Such an attribute of realized returns has found also empirical support in Poterba and Summers (1988).
Managed futures trading are also purported to be guided by similar, positive feedback systems (Brorsen and Irwin, 1987). This may cause unwarranted futures price movements as managed funds and pools attempt to simultaneously buy after a price increase or sell after a price decrease30. Captivatingly, the concentration of commodity pool trading in financial futures markets is high, as these are the largest and most liquid markets. Commodity pool trading is not intense in smaller futures markets, such as livestock futures. This substantiates the observation that CPOs31 and CTAs are aware of the possible market impacts of their trading and seek to curtail the impacts by limiting the size of their trading in smaller markets (Irwin and Yoshimaru, 1999).
2.14.2 Horizons of positive feedbacks
Importantly, positive feedback trading can occur at many horizons. Investment pools buy stock and then sell the stock slowly as positive feedback demand picks up rely on extrapolative expectations over a horizon of a few days. Frankel and Froot’s (1988) forecast have a horizon of several months, which is also relevant for bubbles like those
30 Positive feedback trading systems also are known as technical trading systems. These systems are based
on historical price patterns, and include moving average, price channel, and momentum systems. Previous research indicates technical systems tend to generate similar futures trading signals (Lukac, Brorsen, and Irwin, 1988).
49 that may have occurred in 1929 and 1987. Provided people anticipate a price rise over specific horizons on which they focus to continue, they structure extrapolative expectations that may support positive feedback trading patterns. Furthermore, De Long et al. (1990) suggest that that application to longer horizons is the most appropriate, since in that case learning is less likely to prevent positive feedback traders from repeating their mistakes.
2.14.3 Under-reaction hypothesis of positive feedbacks
Jegadeesh and Titman (1993) and others have documented the seeming profitability of such strategies. Over short periods of 3-12 months, there is a considerable degree of stock return persistence32. Also, observations that (1) positive feedbacks seem profitable, (2) that the volume of profits is linked to the “slow” adjustment of prices to earnings surprises as well as to (3) the “slow” revision of analyst earnings forecasts- all point to the conclusion that the market under reacts to information, especially news about company income (Chan, Jegadeesh, and Lakonishok, 1996). In a similar fashion, (Schiereck et al., 1999) using Frankurt Stock Exchange (FSE) find that positive feedback strategies appear to beat a passive approach33 that invests in the market index.
2.14.4 Performance of positive feedback trading
Sirri and Tufano (1998) find that mutual fund managers tend to pursue such strategies. Brennan and Cao (1997) present evidence supporting the analysis that foreign investors should pursue such strategies and achieve inferior performance because they are less informed than domestic investors. Choe et al. (1999) find that foreign investors tend to be feedback traders, the latter paper focusing on short past-return horizons. Cutler et al. (1990) find evidence of positive correlation of returns at horizons of a few weeks or
32 Positive feedbacks in 12-month returns are also reported in De Bondt and Thaler (1985). The findings
were not emphasized, however, since long-horizon price reversals were the focus of the paper.
33 The passive approach would be similar to a buy-and-hold (excess) return, which combines the return for
each stock multiplicatively, [(1+Rj,1)(1+Rj,2)…(1+Rj,n)], and subtracts the compounded market return,
50 months. Grinblatt and Keloharju (2000) analyzing the Finnish market, also demonstrate that positive feedback behaviour is correlated with investor performance, and that both the behaviour and performance appear to be associated with the level of sophistication of the investor, i.e, foreign investors (professionally managed funds or investment banking houses), pursue positive feedback strategies and achieve superior performance. More importantly, after removing feedback investing’s contribution to performance, Grinblatt and Keloharju (2000) find that the feedback-adjusted performance of foreigners is highly significant34. Lakonishok et al. (1994) show how the positive feedback strategy of uninformed traders is directly associated with trend following and higher volatility. Finally, Jegadeesh and Titman (1993) show that following a positive feedback strategy over the previous six months will generate returns of approximately 1% per month over the six subsequent months in US markets.
2.14.5 Do positive feedbacks persist in long run?
Following market under reaction and over reaction hypotheses, one could argue feedback trading to be successful over short-time periods (six to twelve months). That’s because market participants who share a positive sentiment about an asset will continue to buy even when negative information starts to build up. However, this negative information will eventually result in an over enthusiastic price revision, which does not take into account factors such as the probability that firms with bad results will turn themselves around, and that very few actually go out of business (Hilton, 2001). Despite these arguments, however, positive feedbacks might persist in the long run.
Firstly, every episode might look different to positive feedback traders, and so their learning from past mistakes might be limited. Learning might be particularly restricted if each episode of divergence of price from fundamentals takes several years, as might have been the case with conglomerates and real estate investment trusts (Soros,
34 The feedback-adjusted return for a stock over say (t to t+x) is the stock’s actual return from t to t+120
less the average of the x days (that begin on day t) of the alternative stock(s) in the feedback class portfolio to which the stock belongs on day t (Grinblatt and Keloharju, 2000).
51 1987). Alternatively stated, by the time the new bubble emerges, many investors have forgotten the old one or have been replaced by younger investors who have never experienced the old one at all. Secondly, even if noise traders exit the market with losses now, they may save and return to the market later, especially if several years pass between bubbles. Finally, if traders’ mistakes cause them to take positions that carry more market risk than rational investors’ positions, they can earn higher returns in the market even if they make judgment errors. As such, positive feedback trading may well persevere in the long run (De Long et al., 1990). However, Frankel and Froot (1988) find market participants expect recent price changes (short run) to trigger others in the same direction, while they also expect prices to return to their fundamental values in the long run. Similarly, De Bondt and Thaler (1987), and De Long et al. (1990) find that extreme actions in prices of individual assets eventually revert, as long as part of these movements is accounted for by positive feedback trading.
2.14.6 Robustness in positive feedbacks
First, positive correlations of returns on a stock market index at short horizons can come in part from non-synchronous trading (De Long et al., 1990). In this case, the positive serial correlation is a fabrication of the construction of the market index and not a fact about the prices at which trades in individual securities can be carried out. However, Cutler et al. (1990) find significant positive serial correlations at short horizons in bond, gold, and foreign exchange market, where non-trading problems are not likely to be serious.
2.14.7 Feedback trading and herding
Extant evidence suggests that individual investors’ herding is related to lag returns, i.e, individual investors feedback trade. Patel, Zeckhauser, and Hendricks (1991) demonstrate that flows into mutual funds are an increasing function of recent market performance. Similarly, Sirri and Tufano (1998) present evidence that individual investors invest disproportionately in funds with strong prior performance. Alternatively,
52 consistent with the disposition effect, Odean (1998) support that individual investors are more likely to sell past winners than losers. As for institutional investors, studies like Wermers (1999) and Lakonishok et al. (1992) present strong evidence that these investors engage in some positive feedback trading and also document a strong relation between mutual fund herding and quarterly returns, i.e., they herd and exhibit positive feedback trading.