Market or limit orders?

In this paper we investigate the problem of optimal order placement of an asset listed on an exchange using both market and limit orders in a simple model of market dynamics. We seek to understand under which settings it is optimal to place limit or market orders. Limit orders typically lower transaction costs but increase the risk of incomplete order execution, whereas market orders typically have higher transaction costs but are guaranteed to be executed. Rather than considering order book dynamics to determine if a limit order is executed we rely on price dynamics for this. We look at implementation shortfall in this setup with market impact of trading and propose a dynamic program to find the optimal placement of both market and limit orders for risk-neutral and risk-averse traders. With this we find a bound on the expected cost of trading and show that a trader who behaves optimally should always expect to pay less to trade less. We then solve the dynamic program numerically and examine optimal order placement strategies. We find that the decision between market and limit orders is sensitive to price volatility, risk aversion, and trading costs.     

Corporate governance and family firm performance during the Global Financial Crisis

We investigate the impact of corporate governance on accounting and market performance relationships of family firms during the Global Financial Crisis (GFC). We expect the monitoring aspects of corporate governance to complement the long-term orientation of family firms, improving the value relevance of accounting and market performance during times of exogenous financial shocks such as the GFC. We find that the family-firm value is more sensitive to book value than earnings changes. We also find better corporate governance, irrespective of whether it is a family firm or non-family firm, is associated with better accounting and market performance during the GFC.     

Effect of concentration in airline market on Spanish airport technical efficiency

This paper tries to measure the effect of airline market concentration on airport technical efficiency. With this aim, a Stochastic Frontier Analysis (SFA) is applied, estimating with a one-step procedure technical efficiency and the effect of airlines' market power on that efficiency. Results suggest that when airports are lowly concentrated increasing concentration reduces such inefficiencies. However, this effect practically disappears when airports are highly concentrated. Additionally, the government's policies to improve airports' performance seems to have a positive effect in the short run.     

Limit order books,uninformed traders and commodity derivatives: Insights from the European carbon futures

This paper provides a suitable model for studying the strategic behavior of uninformed investors that trade commodity derivatives via limit order books. Two main testable implications are obtained after solving for the model equilibrium. The adverse selection costs of uninformed traders depend on the inflow of market orders and their risk aversion. Next, the adverse selection costs of uninformed buyers and sellers and the difference of their asset valuations determine the size of their bid-ask spread.An analysis of European carbon futures data confirms the relevance of these implications. Moreover, we detect a diagonal effect that results in a positive correlation of market orders, which is driven by adverse selection, then by order splitting strategies and by imitative strategies of uninformed traders to a lesser extent.     

Risk allocation under liquidity constraints

Risk allocation games are cooperative games that are used to attribute the risk of a financial entity to its divisions. In this paper, we extend the literature on risk allocation games by incorporating liquidity considerations. A liquidity policy specifies state-dependent liquidity requirements that a portfolio should obey. To comply with the liquidity policy, a financial entity may have to liquidate part of its assets, which is costly.The definition of a risk allocation game under liquidity constraints is not straightforward, since the presence of a liquidity policy leads to externalities. We argue that the standard worst case approach should not be used here and present an alternative definition. We show that the resulting class of transferable utility games coincides with the class of totally balanced games. It follows from our results that also when taking liquidity considerations into account there is always a stable way to allocate risk.     

To Ban or not to ban rate parity,that is the question… or not?

Considering the heated debate in the hotel industry about the rate parity clause and the appropriateness of its ban to give rise to rate disparity, this article analyzes the hotel performance that has resulted from the rate parity prohibition established in some European countries, by looking into the market value of the hotels involved. The empirical analysis conducted on a sample of hotel companies trading on the stock exchange in Germany and France shows that the approval of the rate parity ban generates positive abnormal returns. However, an increase in risk is detected. It seems that, while the prospects of greater autonomy to set prices in the hotel industry and stronger competition in the online distribution industry are looked at positively, the hotels will have to deal with a customer’s potential higher perception of price unfairness, less control over its own brand and a greater likelihood of price wars.     

基于交易者预期的房地产价格变化模型

本文基于交易者预期和正反馈,建立了一个房地产价格变动模型.根据该模型,分类讨论了交易者对房地产政策预期的不同,对房地产价格演变方向的影响.研究结果表明,房地产调控政策能否有效,除取决于政策出台时间、政策力度外,还取决于其能否有效改变交易者对市场未来走势的预期.     

Deep hedging

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We discuss how standard reinforcement learning methods can be applied to non-linear reward structures, i.e. in our case convex risk measures. As a general contribution to the use of deep learning for stochastic processes, we also show in Section 4 that the set of constrained trading strategies used by our algorithm is large enough to ε-approximate any optimal solution. Our algorithm can be implemented efficiently even in high-dimensional situations using modern machine learning tools. Its structure does not depend on specific market dynamics, and generalizes across hedging instruments including the use of liquid derivatives. Its computational performance is largely invariant in the size of the portfolio as it depends mainly on the number of hedging instruments available. We illustrate our approach by an experiment on the S&P500 index and by showing the effect on hedging under transaction costs in a synthetic market driven by the Heston model, where we outperform the standard ‘complete-market’ solution.     

众包能力对新产品开发模糊前端绩效的影响

在开放式创新情境下，企业对模糊前端众包任务、创意和流程的有效管理是推动产品创意进入新产品开发后端，提升模糊前端绩效的关键，但众包能力影响模糊前端绩效的过程机理仍不明确。基于信息处理理论，构建众包能力、市场不确定性、技术不确定性与模糊前端绩效作用关系的理论模型，利用287份企业问卷调研数据对研究假设及影响路径进行实证检验。研究结果表明：众包能力对降低市场不确定性、技术不确定性和提高模糊前端绩效均有显著正向影响；降低市场不确定性及技术不确定性在众包能力与模糊前端绩效间起部分中介作用。     

地理距离、契约设计与企业内部资本市场借贷风险防控——来自中国企业集团内部借贷交易的证据

地理因素对保持距离型市场交易的影响已被大量文献证实,但系统考察地理因素是否以及如何影响企业内部经济活动的研究仍十分匮乏。基于手工搜集整理的企业集团内部委托贷款这一独特数据,我们实证考察了地理距离对企业集团内部借贷契约设计的影响及相关的风险防控问题。实证结果显示,借贷距离越远,针对借款者的契约设计越严苛,不仅贷款者更可能要求借款者提供抵押担保,而且对资金用途施加限制的概率也大幅增加。进一步研究发现,与地理距离阻碍了信息搜集和监督的经济直觉一致,距离对企业内部借贷契约严苛性的推高作用会因为借贷双方之间的信息摩擦问题差异而改变。而且,基于借贷违约信息的检验结果表明,作为应对信息不对称的机制,动态调整契约严苛性这一精巧契约设计有效降低了企业内部贷款违约风险。本文不仅增进了对地理因素影响企业内部资本配置的认识,而且加深了对企业内部借贷契约设计的理解,从而对如何有效防控企业内部资本市场运作风险具有启示意义。