Center of Asset and Wealth Management Blog

Better sleep at night: Feedback trading is more promising during the day

The knowledge about the existence of feedback trading is beneficial for traders in any given market.

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The behavior of different types of investors is a popular field of research in financial studies, especially studies on trading strategies. Several hypotheses and models try to explain the theoretical foundation of feedback strategies, where the distribution of returns depends on current and past performance. Unanticipated changes provide new information for market participants and corresponding stock price changes help to inform traders by adopting their strategy during both up and down price movements. Noise in the market (distortion of overall market trend by sudden price movements) induces more liquidity and simultaneously more risk, expressed through higher volatility. Noise trading leads to large price deviations from fundamental values. Thereby, informed traders cannot fully offset the impact of noise traders in a high-risk environment because risk rises especially during short time horizons.


Feedback trading is a form of noise trading.  
A destabilizing effect occurs when noise trading strategies correlate with one another. This is the case when market participants conclude relevant information from analyzing the same indicators, thus ending up with highly correlated trades and hence influencing price fluctuations. One of the most common destabilizing forms of noise trading is feedback trading. Positive feedback traders actively buy (sell) stocks in a rising (falling) market while negative feedback traders adhere to a “buy low and sell high” investment strategy. In their paper “Feedback trading: Strategies during day and night with global interconnectedness”, Alex Kusen and Markus Rudolf offer an informative framework for exploring feedback trading from two new angles.

  1. They decompose the overall return premium into day and night returns. Prices are more efficient, and more information is revealed during the day. Market closures, on the other hand, affect the mean and standard deviation of returns due to risk compensations when trading overnight.
  2. The authors assume interconnectedness between multiple countries and introduce a global feedback trading model. Dynamic effects with spillovers shed light on investors’ strategies and provide justifications for price fluctuations.


Empirical results illustrate two important findings.
First, feedback trading strategies differ across markets when distinguishing between day and night returns. A decline in trading volume overnight causes positive feedback trading to occur more often for day than night returns because investors need to be compensated for bearing higher risk. Feedback traders in Germany and the UK behave different during a full trading day in contrast to traders in Japan as well as Hong Kong. No feedback trading is found to exist in Germany during trading hours. An inverse relationship is found in the UK. During the day, investors follow a positive feedback trading strategy, whereas feedback trading is found to be absent during night hours.

Second, feedback trading patterns change when considering an interaction of specific markets. Day returns from Germany induce a decline of trend chasing investors in the UK, whereas investors’ behavior in Germany is not influenced by any other country. When considering night returns, one-sided spillovers are present from Germany to the UK. 

All in all, feedback trading strategies differ between the day and night with spillover effects arising from market interactions.


Please refer to the original paper for further details:

Kusen, A. and M. Rudolf (2019). Feedback trading: Strategies during day and night with global interconnectedness. Research in International Business and Finance 48, 438-463.