Jonathan Wang’s Research:
Jouahn Nam, Jun Wang and
Ge Zhang, (2008) Managerial career concerns and
risk management. Journal of Risk and
Insurance, 75(3), 785-809.
We
present a dynamic model of corporate risk management and managerial career
concerns. We show that managers with low
(high) initial reputation have high (low) career concerns about keeping their
jobs and receiving all future income. These managers are more likely to
speculate (hedge) early in their careers. In the later stage of their careers
when managers have less career concerns, there is no speculative motive for
self interested managers. On the other hand, highly reputable managers have
minimal career concerns and they engage in neither hedging nor speculation
early in their careers, but they may choose to hedge after poor early
performance.
We consider a competitive and perfect financial market in which agents have
heterogeneous cash flow valuations. Instead of assuming that agents are endowed with rational expectations, we model their behavior
as the product of adaptive learning. Our results demonstrate that adaptive
learning affects security design profoundly, with securities mispriced even in
the long run and optimal designs trading off underpricing
against intrinsic value maximization. The evolutionary dominant security design
calls for issuing securities that engender large losses with a small but
positive probability, but that otherwise produce stable payoffs, almost the
exact opposite of the pure state claims that are optimal in the rational
expectations framework.
Jouahn Nam, Jun Wang and Ge Zhang (2008). Strategic trading against retail investors with loss aversion. International Review of
Economics and Finance, 17(1), 45-55.
In this paper, we study a model incorporating the retail trader's
reluctance to sell into losses. We show that in this setup the informed trader
always buys the asset when he receives a favorable signal. However, when the
informed trader receives an unfavorable signal, he may not always sell the
asset if the signal is moderately bad and the retail trader is reluctant to
realize losses. Hence the good news travels faster than the bad news and the
asset price exhibits steady climbs with sharp and sudden drops.
Thomas
Noe and Jun Wang (2004). Fooling all of the people some of the time: A theory of endogenous sequencing in confidential
negotiations,
Review of Economic Studies 71,
855-881.
This paper analyzes a bargaining game in which one party, called the
buyer, has the option of choosing the sequence of negotiations with other participants,
called sellers. When the sequencing of negotiations is confidential and the
sellers’ goods are highly complementary, efficient, non-dissipative equilibria exist in which the buyer randomizes over
negotiation sequences. In these equilibria, the buyer
can obtain higher payoffs than in pure strategy equilibria
or in public negotiations. The degree of sequencing uncertainty that maximizes
buyer payoffs is inversely related to the aggregate bargaining power of the
sellers.
Thomas Noe, Michael Rebello and Jun Wang
(2003). Corporate financing: An artificial agent-based
analysis. Journal of Finance 63,
943-973.
We examine corporate security choice by
simulating an economy populated by adaptive agents who learn about the structure
of security returns and prices through experience. Through a process of
evolutionary selection each agent gravitates toward strategies that generate
the highest payoffs. Despite the fact that markets are perfect and agents
maximize value, a financing hierarchy emerges in which straight debt dominates other financing
choices. Equity and convertible debt display significant underpricing.
In general, the smaller the probability of loss to outside investors, the more
likely the firm is to issue the security and the smaller the security's underpricing.
Thomas Noe and Jun Wang (2000). Strategic debt restructuring. Review of Financial Studies
13, 985-1016.
We analyze a distressed firm indebted to many creditors. The firm’s owners have the option of choosing the sequence of restructuring negotiations with the creditors. We show that sequencing flexibility is beneficial to firm owners, and that the optimal sequencing of restructuring negotiations involves exploiting the firm’s liabilities to some creditors so as to moderate the demands of others. Moderately distressed firms will eschew renegotiations with creditors in strong bargaining positions. Severely distressed firms will extract concessions from all creditors. In this case, owners can gain if they can credibly commit to conditional restructuring agreements that link the concessions of one creditor to concessions by others.
Jun Wang
(2000).
Trading and hedging in S&P 500 spot and futures markets using genetic
programming. Journal of Futures Markets
20, 911-942.
In this paper, genetic
programming, an optimization technique based on the principles of natural
evolution, is used to generate trading and hedging rules in S&P500 spot and
futures markets. We adopt a realistic trading process which includes reasonable
transaction costs, obtainable execution prices, and all the unique features of
futures trading. The results suggest that the spot market is quite efficient
with most genetically generated trading rules duplicating the buy-and-hold
strategy. Most of the trading activities of these trading programs are in the
futures market where transaction costs are substantially lower. The
out-of-sample performance of these trading rules vary
from year to year, indicating that genetic programming can
not consistently find outperforming technical trading rules. There is
some evidence of superior market timing abilities of these rules.
Mandeep Chahal and Jun
Wang (1998). Jump diffusion process and emerging bond and stock markets: An
investigation using daily data. Multinational
Finance Journal 1, 169-197.
The underlying stochastic processes that drive
returns in several emerging bond and stock markets are investigated using the
pure diffusion, the jump diffusion, the ARCH pure diffusion, and the ARCH jump
diffusion models. The results indicate that jump diffusion models fit the data
better than pure diffusion models. Possible sources and linkages of information
surprises in emerging stock and bond markets are also investigated. Bond and
stock returns of the same country exhibit simultaneous jumps, indicating a
possible linkage of the two markets.
Thomas Noe and Jun Wang (2002). The
self-evolving logic of financial claim prices, in Genetic Algorithms and
Genetic Programming in Computational Finance, eds. Shu-Heng
Chen, Kluwer Academic Publishers.
In this paper, we use Genetic Programming, an optimization technique based on the principles of natural selection, to price financial contingent claims. Compared to the traditional arbitrage-based approach, this technique is useful when the underlying asset dynamics are unknown or when the pricing equations are too complicated to solve analytically. Comparing to other established data-driven option pricing techniques such as neural networks, implied binomial trees, etc., genetic programming has the advantage of not restricting the structure of the pricing formulas. Formulas themselves evolve rather than simply the parameters of a single formula. In addition, because it is very easy to incorporate existing analytical pricing formulas into the evolutionary process, genetic programming can be applied in combination with existing pricing methods. In this paper, we show that genetic programming can recover Black-Scholes formula from a simulated data sample of fairly small size. The application to S&P 500 futures options shows promising results.
Yrjo Koskinen, Michael Rebello and Jun Wang (2008). Venture capital contracts: The role of market
conditions and the evolution of informational asymmetry.
We model a situation where the entrepreneur has an informational
advantage during the early stages of an investment project while the venture
capitalist has the informational advantage during the later stages. We examine
how this evolution of informational asymmetry affects venture investment and
the nature of financing contracts under two different scenarios with regard to
the distribution of bargaining power between the venture capitalist and
entrepreneur: when the venture capitalist has the bargaining advantage and when
the entrepreneur has the bargaining advantage. Our results demonstrate that the
distribution of bargaining power has a profound influence both on the terms of
contracts and on investments in venture-backed projects. Changes in bargaining
power can completely alter the payoff sensitivity of contracts offered to
entrepreneurs, and, as witnessed in the recent past, when entrepreneurs hold
the bargaining advantage, venture capitalists may acquiesce to excessive
investments in early stages of projects and subsequently terminate a larger
number of projects.
Thomas Noe, Michael Rebello and Jun Wang
(2008). Learning to bid: The design
of auctions under uncertainty and adaptation.
We examine auction design in a context where symmetrically informed
agents with common valuations learn to bid for a good. We show that bidder strategies, even in the
long run, do not converge to the Bertrand--Nash strategy of bidding the
expected value of the good. Although
individual agents learn Nash bidding in isolation, the learning of each agent,
by flattening the best reply correspondence of other agents, blocks common
learning. These negative externalities
are more severe in second-price auctions, auctions with many bidders, and
auctions where the good has an uncertain value ex post. For this reason, uncertainty, auction
structure, and the number of bidders matter, even absent private valuations,
asymmetric information, or risk aversion. These results suggest that
parametrically very parsimonious auction models, requiring only information
regarding the statistical properties of the auctioned good's payoffs, the
number of bidders, and the auction mechanism, can yield a rich set of
predictions regarding auction outcomes.
(Computer code: individual pool
learning, common pool learning)
Gautam Goswami, Thomas Noe
and Jun Wang (2005). Buying up the
block: An experimental investigation of capturing economic rents through
sequential negotiations.
This paper develops and
experimentally implements a simple multi-negotiation bargaining game, in which one
agent, called the ``developer,'' must reach agreements with a series of
other agents, called ``landowners,'' in order to implement a value-increasing
project. The game has a unique subgame perfect Nash equilibrium under which the surplus
from the project is split between the landowner and developer without any
dissipation of value. In the actual experiments, however, on average almost
half of the value of the project was dissipated. The costs of dissipation fell
disproportionately on the developer, who was able to capture less than 5% of
the value generated by the project. The
results of this experiment call into question the ability of private
negotiations between a large number of parties, even
in a world without explicit contracting costs, to induce Pareto-optimal
allocations of property rights.
Christopher Hessel
and Jun Wang (2004). Credit derivatives and volatility of credit spreads.
Jouahn Nam, Jun Wang and Ge Zhang
(2004). The impact of dividend tax
cuts and managerial stock holdings on corporate dividend policy.