This paper shows that arbitrage is limited if rational agents face uncertainty about completing their arbitrage portfolios. This “execution risk” arises in our model because there are slippages in asset prices as arbitrageurs compete for the limited supply of assets needed for a profitable arbitrage portfolio. This is distinct from the existing limits of arbitrage such as noise trader risk, fun...

The outbreak of COVID-19 in 2019 has brought huge conflicts to the development world economy. As one countries affected by epidemic, China suffered economic losses. At same time, follow-up impact this epidemic is continuous, not disappeared short term and a large scope. Based on existing research results, paper analyzes Noise Trader Risk (NTR) factors that are positively related it, attempts pr...

In this paper I hypothesize that the well documented positive mean excess stock return earned by parent firms when they announce they are carving out stock in a subsidiary is due to noise traders who optimistically misinterpret a carve-out’s true value-irrelevance, rather than to the impounding of new value-enhancing information by sophisticated investors. I offer three pieces of evidence that ...

We are interested in model risk control problems. We study a strategy for the trader which, in a sense, guarantees good performances whatever is the unknown model for the assets of his/her portfolio. The trader chooses trading strategies to decrease the risk and therefore acts as a minimizer; the market systematically acts against the interest of the trader, so that we consider it acts as a max...

We provide a natural learning process in which a financial trader without a risk receives a gain in case when Stock Market is inefficient. In this process, the trader rationally choose his gambles using a prediction made by a randomized calibrated algorithm. Our strategy is based on Dawid’s notion of calibration with more general changing checking rules and on some modification of Kakade and Fo...

Value at Risk (VaR) has emerged in recent years as a standard tool to measure and control the risk of trading portfolios. Yet, existing theoretical analyses of the optimal behavior of a trader subject to VaR limits have produced a negative view of VaR as a risk-control tool. In particular, VaR limits have been found to induce increased risk exposure in some states and an increased probability o...

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering) of financial markets have a possible explanation in the interactions among agents. However, the complexity, originating from the presence of non-linearity and interactions, often limits the analytical approach to the dynamics of these models. In this paper we show that even a ve...

We study endogenous liquidity trading in a market with long-lived asymmetric information. We distinguish between public information, tractable information that can be acquired and intractable information that cannot be acquired. Besides information asymmetry and noise, the adverse-selection spread depends on the diffusion of intractable information and on the interest rate. With endogenous liqu...

In this paper, we study predictability of exchange rates and explore determinants of its dynamics over time. We model the admissible amount of predictability in two ways, each corresponding in a stylized manner to a broad class of rational currency pricing models, namely those under which the marginal currency trader can diversify away currency risk and alternative specifications under which th...

Abstract This paper investigates whether noise traders can survive in the long run and how they influence financial markets by proposing an agent-based artificial stock market, as one simulation model of computational economics. market contains traders, informed uninformed traders. Informed learn from information using Genetic Programming, while cannot. The system is first calibrated to real re...