Endogenously-Timed Herding And The Synchronization Of Investment Cycles

This paper combines the recent garne theoretic approach of endogenous timing of entry to herding models with a rnacroeconornic model of investrnent cycles. The integrated description embodies the qualitative resuits of the rnyopic herding model in a medium run investment objective of smooth ing the capital stock adjustment process. lt features a completely disaggregated structure and bears the potential to synchronize individual cyclic investing be haviors. This synchronization via nonlinear feedback from the aggregate ac tivity can serve as an explanation of the inexistent cancelling of heterogeneous sectoral quasi-cycles. The model others an explanatory base for the constitu tion of the observed strong cyclicality of the aggregate investment series by a multitude of different periodicities and phases on the individual level. Finally, based on recent ndings of the herding literature, the stabilization potential of third parties' information revelation is conjectured

Characterizing Strategic Cascades on Networks

Transmission of disease, spread of information and rumors, adoption of new products, and many other network phenomena can be fruitfully modeled as cascading processes, where actions chosen by nodes influence the subsequent behavior of neighbors in the network graph. Current literature on cascades tends to assume nodes choose myopically based on the state of choices already taken by other nodes. We examine the possibility of strategic choice, where agents representing nodes anticipate the choices of others who have not yet decided, and take into account their own influence on such choices. Our study employs the framework of Chierichetti et al. [2012], who (under assumption of myopic node behavior) investigate the scheduling of node decisions to promote cascades of product adoptions preferred by the scheduler. We show that when nodes behave strategically, outcomes can be extremely different. We exhibit cases where in the strategic setting 100% of agents adopt, but in the myopic setting only an arbitrarily small epsilon % do. Conversely, we present cases where in the strategic setting 0% of agents adopt, but in the myopic setting (100-epsilon)% do, for any constant epsilon > 0. Additionally, we prove some properties of cascade processes with strategic agents, both in general and for particular classes of graphs.Comment: To appear in EC 201

Endogenously-Timed Herding And The Synchronization Of Investment Cycles

This paper combines the recent garne theoretic approach of endogenous timing of entry to herding models with a rnacroeconornic model of investrnent cycles. The integrated description embodies the qualitative resuits of the rnyopic herding model in a medium run investment objective of smooth ing the capital stock adjustment process. lt features a completely disaggregated structure and bears the potential to synchronize individual cyclic investing be haviors. This synchronization via nonlinear feedback from the aggregate ac tivity can serve as an explanation of the inexistent cancelling of heterogeneous sectoral quasi-cycles. The model others an explanatory base for the constitu tion of the observed strong cyclicality of the aggregate investment series by a multitude of different periodicities and phases on the individual level. Finally, based on recent ndings of the herding literature, the stabilization potential of third parties' information revelation is conjectured.herding ; investment cycles ; nonlinear entrainment

Informational Herding and Optimal Experimentation

We show that far from capturing a formally new phenomenon, informational herding is really a special case of single-person experimentation -- and 'bad herds' the typical failure of complete learning. We then analyze the analogous team equilibrium, where individuals maximize the present discounted welfare of posterity. To do so, we generalize Gittins indices to our non-bandit learning problem, and thereby characterize when contrarian behaviour arises: (i) While herds are still constrained efficient, they arise for a strictly smaller belief set. (ii) A log-concave log-likelihood ratio density robustly ensures that individuals should lean more against their myopic preference for an action the more popular it becomes.Bayesian learning, value function, herding, experimentation, log concavity, Gittins index, team equilibrium

Informational Herding and Optimal Experimentation

We show that far from capturing a formally new phenomenon, informational herding is really a special case of single-person experimentation - and `bad herds' the typical failure of complete learning. We then analyze the analogous team equilibrium, where individuals maximize the present discounted welfare of posterity. To do so, we generalize Gittins indices to our non-bandit learning problem, and thereby characterize when contrarian behaviour arises: (i) While herds are still constrained efficient, they arise for a strictly smaller belief set. (ii) A log-concave log-likelihood ratio density robustly ensures that individuals should lean more against their myopic preference for an action the more popular it becomes.herding; optimal learning; experimentation; contrarianism

Parimutuel Betting under Asymmetric Information

This paper examines a game-theoretical model of parimutuel betting markets with asymmetric information. Generically, all Bayesian-Nash equilibria of the simultaneous game are characterized depending on the number of bettors and the quality of their private information. An equilibrium where all bettors use their private information always exists and becomes unique as the number of bettors increases. On the contrary, in a sequential framework, a perfectly revealing equilibrium does not always exist and disappears as the number of bettors increases. Bettors arbitrate between following their private signal, following the choices of previous bettors, and betting against the trend. On average,information is well aggregated by the market, but extreme effects based on herd and contrarian behavior occur in identifiable states of the world,leading to significant mispricing.Parimutuel betting; Asymmetric information; Information.

Informational Herding and Optimal Experimentation

We show that far from capturing a formally new phenomenon, informational herding is really a special case of single-person experimentation — and ‘bad herds’ the typical failure of complete learning. We then analyze the analogous team equilibrium, where individuals maximize the present discounted welfare of posterity. To do so, we generalize Gittins indices to our non-bandit learning problem, and thereby characterize when contrarian behaviour arises: (i) While herds are still constrained efficient, they arise for a strictly smaller belief set. (ii) A log-concave log-likelihood ratio density robustly ensures that individuals should lean more against their myopic preference for an action the more popular it becomes

Informational Herding and Optimal Experimentation

We show that far from capturing a formally new phenomenon, informational herding is really a special case of single-person experimentation — and ‘bad herds’ the typical failure of complete learning. We then analyze the analogous team equilibrium, where individuals maximize the present discounted welfare of posterity. To do so, we generalize Gittins indices to our non-bandit learning problem, and thereby characterize when contrarian behaviour arises: (i) While herds are still constrained efficient, they arise for a strictly smaller belief set. (ii) A log-concave log-likelihood ratio density robustly ensures that individuals should lean more against their myopic preference for an action the more popular it becomes

Investor behaviour, financial markets and the international economy

This dissertation focuses on analysing investor behaviour and price processes in asset markets. It consists of four self-contained essays in the areas of market microstructure, risk attitude of boundedly rational investors, and international finance. Chapter 2 provides a review of the existing literature on the informational aspects of price processes. A common feature of these models is that prices reflect information that is dispersed among many traders. Dynamic models can explain crashes and illustrate a rationale for technical/chart analysis. The second emphasis of this survey is on herding models. In Chapter 3, I have developed a multi-period trading-game that analyses the impact of information leakage. I find that a trader who receives a signal about a future public announcement can exploit this information twice. First, when he receives his signal, and second, at the time of the public announcement. Furthermore, I show that the investor trades very aggressively on the rumour in order to manipulate the price. This enhances his informational advantage after the correct information is made public. He also trades for speculative reasons, i.e. he buys stocks that he plans to sell after the public announcement. Chapter 4 provides a theoretical rationale for experimental results such as loss aversion and diminishing sensitivity. A decision maker is considered to be boundedly rational if he can not find his new optimal consumption bundle with certainty when he is faced with a new income level. This makes him more risk averse at his current reference income level. It also makes him less risk averse for a range of incomes below his reference income level. Chapter 5 considers a two country economy similar to that in Obstfeld and Rogoff (1995). We find that conclusions about whether monetary shocks lead to exchange rate overshooting and spillovers on foreign production and consumption depend crucially on the form of price stickiness.' Sticky retail prices not only allow for a profitable ‘Beggar Thy Neighbour Policy’ but also lead to exchange rate overshooting. This is not the case under sticky wholesale prices and sticky wages

Resilience of Locally Routed Network Flows: More Capacity is Not Always Better

In this paper, we are concerned with the resilience of locally routed network flows with finite link capacities. In this setting, an external inflow is injected to the so-called origin nodes. The total inflow arriving at each node is routed locally such that none of the outgoing links are overloaded unless the node receives an inflow greater than its total outgoing capacity. A link irreversibly fails if it is overloaded or if there is no operational link in its immediate downstream to carry its flow. For such systems, resilience is defined as the minimum amount of reduction in the link capacities that would result in the failure of all the outgoing links of an origin node. We show that such networks do not necessarily become more resilient as additional capacity is built in the network. Moreover, when the external inflow does not exceed the network capacity, selective reductions of capacity at certain links can actually help averting the cascading failures, without requiring any change in the local routing policies. This is an attractive feature as it is often easier in practice to reduce the available capacity of some critical links than to add physical capacity or to alter routing policies, e.g., when such policies are determined by social behavior, as in the case of road traffic networks. The results can thus be used for real-time monitoring of distance-to-failure in such networks and devising a feasible course of actions to avert systemic failures.Comment: Accepted to the IEEE Conference on Decision and Control (CDC), 201