The QLBS Q-Learner goes NuQLear: fitted Q iteration,inverse RL,and option portfolios

The QLBS model is a discrete-time option hedging and pricing model that is based on Dynamic Programming (DP) and Reinforcement Learning (RL). It combines the famous Q-Learning method for RL with the Black–Scholes (–Merton) (BSM) model's idea of reducing the problem of option pricing and hedging to the problem of optimal rebalancing of a dynamic replicating portfolio for the option, which is made of a stock and cash. Here we expand on several NuQLear (Numerical Q-Learning) topics with the QLBS model. First, we investigate the performance of Fitted Q Iteration for an RL (data-driven) solution to the model, and benchmark it versus a DP (model-based) solution, as well as versus the BSM model. Second, we develop an Inverse Reinforcement Learning (IRL) setting for the model, where we only observe prices and actions (re-hedges) taken by a trader, but not rewards. Third, we outline how the QLBS model can be used for pricing portfolios of options, rather than a single option in isolation, thus providing its own, data-driven and model-independent solution to the (in)famous volatility smile problem of the Black–Scholes model.     

Gaming the future of an urban network

Scenario and gaming techniques have a number of complementary characteristics. In this article, the design and evaluation of a gaming-scenario experiment for the exploration of development planning in an urban network in the Netherlands is presented. Two gaming sessions were held using two long-term scenarios (2030) as varying contexts. The combined gaming-scenario approach made it possible to evaluate the impact of external future developments and trends on the administrative and spatial development. Evaluation results of the gaming experiment indicate that the gaming-scenario approach generated new and critical insights on development planning and the future of the urban network. Through the game, the principal, the game leaders but most of all the stakeholder-participants experienced and realized that the management of development planning in urban networks is a very difficult task and is full of pitfalls.     

Size and diversity in VC syndicates and their impact on IPO performance

This paper investigates the impact of venture capital (VC) syndicate size and composition on the IPO and post-IPO performances of investee companies in an attempt to shed some light on the extent to which larger and more diverse syndicates are more likely to suffer from internal agency problems which might hinder the decision-making process and lead to less value added for their portfolio companies. The question is of great relevance because, while the vast majority of the empirical literature compares VC backed IPOs with non-VC backed ones, most VC funding is provided by syndicates of two or more financiers. We construct alternative measures of size as well as diversity based on several VC characteristics such as age, geographic location, type and affiliation of VC firms and find that larger and more diverse syndicates are associated with higher underpricing and lower valuation at the IPO date. Furthermore, we provide evidence that that diversity and size are negatively correlated to the long-term performance of the IPO firms and this finding is robust to several alternative measures of long-term performance.     

The effects of venture capital syndicate diversity on earnings management and performance of IPOs in the US and UK: An institutional perspective

This study examines the extent to which principal–principal agency conflicts within venture capital (VC) syndicates lead to additional principal–agent conflicts in IPO firms in two institutional contexts. Using a matched sample of 274 VC-backed IPOs in the US and the UK, it shows that the diversity of a VC syndicate increases pre-IPO discretionary current accruals, used as a proxy for earnings management, but the impact of such diversity is higher in the US. There is also evidence of higher underpricing and lower aftermarket performance in firms with higher earnings management and VC diversity, and these negative performance effects are also higher in the US. Our findings indicate that local and informal institutions have a significant effect on multiple agency conflicts in IPO firms and performance outcomes.     

What Drives Security Issuance Decisions: Market Timing,Pecking Order,or Both?

We study market timing and pecking order in a sample of debt and equity issues and share repurchases of Canadian firms from 1998 to 2007. We find that only when firms are not financially constrained is there evidence that firms issue (repurchase) equity when their shares are overvalued (undervalued) and evidence that overvalued issuers earn lower postannouncement long‐run returns. Similarly, we find that only when firms are not overvalued do they prefer debt to equity financing. These findings highlight an interaction between market timing and pecking order effects.     

Fair value and audit fees

This paper investigates the effect of fair value reporting and its attributes on audit fees. We use as our primary sample the European real estate industry around mandatory IFRS adoption (under which reporting of property fair values becomes compulsory), due to its unique operating and reporting characteristics. We document lower audit fees for firms reporting property assets at fair value relative to those employing depreciated cost—a difference that appears driven, in part, by impairment tests that occur only under depreciated cost. We further find that audit fees are decreasing in firms’ exposure to fair value and increasing both in the complexity of the fair value estimation and for recognition (versus only disclosure) of fair values. We corroborate our findings in two alternative settings: contrasting UK and US real estate firms and using UK investment trusts. Overall, the results suggest that fair values can lead to lower monitoring costs; however, any reductions in audit fees will vary with salient characteristics of the fair value reporting, including the difficulty to measure and the treatment within the financial statements.     

Network positioning and R&D activity: a study of Italian groups

Traditionally, R&D studies focus on organisational characteristics and internal context factor effects on a firm's R&D activities. This paper extends previous research by analysing firm–level R&D expenditures in the wider context of inter–organisational networks. Using sample of 2002 manufacturing firms in Italy, it provides evidence that R&D intensity is linked to a firm's positioning within an industrial group's hierarchy. Further tests on the antecedents of R&D expenditures are carried out in relation to the effects of firm characteristics and industry factors. Important findings include a significant and positive association between R&D intensity and the firm's size, performance, intangible assets and industry concentration. These findings suggest that, in addition to firm–level factors and its market environment, network resources and organisation may play an important role in driving the intensity of the firm's R&D expenditures.     

Asymmetric trading by insiders – comparing abnormal returns and earnings prediction in Spain and Australia

This paper examines whether the ‘external governance’ imposed by comparative financial accounting standards reduces the trading advantage of insiders. We do this by directly comparing insider trading returns and insider’s ability to predict future earnings from accruals in Spain and Australia. Results show higher excess returns and greater prediction of future earnings from conditioned insider trading in Australia that is then utilized by financial analysts to lower forecast errors – particularly in contrarian‐based accruals trading. Possible explanations include: (i) a high asymmetric quality for market‐based accruals, (ii) information transfer from informed insiders to uninformed insiders and financial analysts and (iii) a more timely dissemination of financial information in Spain through different ownership and governance structures.