Bank of EnglandThis paper proposes a method for measuring investor risk appetite based on the variation in the ratio of risk-neutral to subjective probabilities used by investors in evaluating possible future returns to an asset. Unlike other indicators advanced in the literature, our measure of market sentiment distinguishes risk appetite from risk aversion, and is reported in levels rather than changes. Implementation of the approach yields results that respond to crises and other major economic events in a plausible manner.
A key issue raised by the rapid growth of computerised algorithmic trading is how it responds in extreme situations. Using data on foreign exchange orders and transactions that includes identification of algorithmic trading, we find that this type of trading contributed to the deterioration of market quality following the removal of the cap on the Swiss franc on 15 January 2015, which was an event that came as a complete surprise to market participants. In particular, we find that algorithmic traders withdrew liquidity and generated uninformative volatility in Swiss franc currency pairs, while human traders did the opposite. However, we find no evidence that algorithmic trading propagated these adverse effects on market quality to other currency pairs.
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