Short-Term Price Overreaction: Identification, Testing, Exploitation

This paper examines short-term price reactions after one-day abnormal price changes and whether they create exploitable profit opportunities in various financial markets. A t-test confirms the presence of overreactions and also suggests that there is an "inertia anomaly", i.e. after an overreaction day prices tend to move in the same direction for some time. A trading robot approach is then used to test two trading strategies aimed at exploiting the detected anomalies to make abnormal profits. The results suggest that a strategy based on counter-movements after overreactions does not generate profits in the FOREX and the commodity markets, but it is profitable in the case of the US stock market. By contrast, a strategy exploiting the "inertia anomaly" produces profits in the case of the FOREX and the commodity markets, but not in the case of the US stock market

Detecting informed trading activities in the options markets: Appendix on subprime financial crisis

This appendix extends the empirical results in Chesney, Crameri, and Mancini (2011). Informed trading activities on put and call options are analyzed for 19 companies in the banking and insurance sectors from January 1996 to September 2009. Our empirical findings suggest that certain events such as the takeovers of AIG and Fannie Mae/Freddie Mac, the collapse of Bear Stearns Corporation and public announcements of large losses/writedowns are preceded by informed trading activities in put and call options. The realized gains amount to several hundreds of millions of dollars. Several cases are discussed in detail

Foreign exchange, fractional cointegration and the implied-realized volatility relation

Almost all relevant literature has characterized implied volatility as a biased predictor of realized volatility. This paper provides new time series techniques to assess the validity of this finding within a foreign exchange market context. We begin with the empirical observation that the fractional order of volatility is often found to have confidence intervals that span the stationary/non-stationary boundary. However, no existing fractional cointegration test has been shown to be robust to both regions. Therefore, a new test for fractional cointegration is developed and shown to be robust to the relevant orders of integration. Secondly, employing a dataset that includes the relatively new Euro markets, it is shown that implied and realized volatility are fractionally cointegrated with a slope coefficient of unity. Moreover, the non-standard asymptotic distribution of estimators when using fractionally integrated data is overcome by employing a bootstrap procedure in the frequency domain. Strikingly, tests then show that implied volatility is an unbiased predictor of realized volatility

Network architecture of energy landscapes in mesoscopic quantum systems

Mesoscopic quantum systems exhibit complex many-body quantum phenomena, where interactions between spins and charges give rise to collective modes and topological states. Even simple, non-interacting theories display a rich landscape of energy states-distinct many-particle configurations connected by spin- and energy-dependent transition rates. The ways in which these energy states interact is difficult to characterize or predict, especially in regimes of frustration where many-body effects create a multiply degenerate landscape. Here, we use network science to characterize the complex interconnection patterns of these energy-state transitions. Using an experimentally verified computational model of electronic transport through quantum antidots, we construct networks where nodes represent accessible energy states and edges represent allowed transitions. We find that these networks exhibit Rentian scaling, which is characteristic of efficient transportation systems in computer circuitry, neural circuitry, and human mobility, and can be used to measure the interconnection complexity of a network. We find that the topological complexity of the state transition networks-as measured by Rent's exponent-correlates with the amount of current flowing through the antidot system. Furthermore, networks corresponding to points of frustration (due, for example, to spin-blockade effects) exhibit an enhanced topological complexity relative to non-frustrated networks. Our results demonstrate that network characterizations of the abstract topological structure of energy landscapes capture salient properties of quantum transport. More broadly, our approach motivates future efforts to use network science to understand the dynamics and control of complex quantum systems

A behavioural approach to the pricing of European options

Empirical studies on quoted options highlight deviations from the theoretical model of Black and Scholes; this is due to different causes, such as assumptions regarding the price dynamics, markets frictions and investors’ attitude toward risk. In this contribution, we focus on this latter issue and study how to value options within the continuous cumulative prospect theory. According to prospect theory, individuals do not always take their decisions consistently with the maximization of expected utility. Decision makers have biased probability estimates; they tend to underweight high probabilities and overweight low probabilities. Risk attitude, loss aversion and subjective probabilities are described by two functions: a value function and a weighting function, respectively. As in Versluis et al. [15], we evaluate European options; we consider the pricing problem both from the writer’s and holder’s perspective, and extend the model to the put option. We also use alternative probability weighting functions