An investigation to establish whether property maintenance can diminish the number of empty commercial buildings in Sheffield and Leeds

Property maintenance has long been considered an undesirable and overlooked area amongst the construction and property industries; however, a large proportion of construction output comes from such maintenance works. Empty commercial property is an emotive and challenging area, which has been made more topical due to the implementation of the Rating (Empty Property) Act 2007 placing further financial liability on owners with the aim of „incentivising‟ them either to develop, re-let or sell their vacant buildings. As such, the level of property maintenance is important to allow the building to be at a lettable or saleable standard, which in turn should allow the number of unused commercial buildings in the United Kingdom (UK) to reduce. A mixture of primary and secondary sources were utilised to fulfil this research to determine whether incentives exist or can exist to increase the level of property maintenance to diminish the number of vacant commercial buildings in Leeds and Sheffield. The primary data was based on six case studies, four example cases in point and two interviews. Ratings were assigned according to factors and incentives to analyse the data to assist in the findings of this research. This change in Government policy is causing outrage amongst UK businesses and professional bodies of the property industry, in extreme cases leading to the demolition of the building to avoid liability and other detrimental consequences, such as staff reductions to make up for the liability. It has come also alongside the worst recession of recent times

Critical Market Crashes

This review is a partial synthesis of the book ``Why stock market crash'' (Princeton University Press, January 2003), which presents a general theory of financial crashes and of stock market instabilities that his co-workers and the author have developed over the past seven years. The study of the frequency distribution of drawdowns, or runs of successive losses shows that large financial crashes are ``outliers'': they form a class of their own as can be seen from their statistical signatures. If large financial crashes are ``outliers'', they are special and thus require a special explanation, a specific model, a theory of their own. In addition, their special properties may perhaps be used for their prediction. The main mechanisms leading to positive feedbacks, i.e., self-reinforcement, such as imitative behavior and herding between investors are reviewed with many references provided to the relevant literature outside the confine of Physics. Positive feedbacks provide the fuel for the development of speculative bubbles, preparing the instability for a major crash. We demonstrate several detailed mathematical models of speculative bubbles and crashes. The most important message is the discovery of robust and universal signatures of the approach to crashes. These precursory patterns have been documented for essentially all crashes on developed as well as emergent stock markets, on currency markets, on company stocks, and so on. The concept of an ``anti-bubble'' is also summarized, with two forward predictions on the Japanese stock market starting in 1999 and on the USA stock market still running. We conclude by presenting our view of the organization of financial markets.Comment: Latex 89 pages and 38 figures, in press in Physics Report

Regrets, learning and wisdom

This contribution discusses in what respect Econophysics may be able to contribute to the rebuilding of economics theory. It focuses on aggregation, individual vs collective learning and functional wisdom of the crowds.Comment: 9 pages, 1 figure. Opinion paper submitted to European Physical Journal - Special Topics "Can economics be a physical science?

Market dynamics associated with credit ratings: a literature review.

Credit ratings produced by the major credit rating agencies (CRAs) aim to measure the creditworthiness, or more specifically the relative creditworthiness of companies, i.e. their ability to meet their debt servicing obligations. In principle, the rating process focuses on the fundamental long-term credit strength of a company. It is typically based on both public and private information, except for unsolicited ratings, which focus only on public information. The basic rationale for using ratings is to achieve information economies of scale and solve principal-agent problems. Partly for the same reasons, the role of credit ratings has expanded significantly over time. Regulators, banks and bondholders, pension fund trustees and other fiduciary agents have increasingly used ratings-based criteria to constrain behaviour. As a result, the influence of the opinions of CRAs on markets appears to have grown considerably in recent years. One aspect of this development is its potential impact on market dynamics (i.e. the timing and path of asset price adjustments, credit spreads, etc.), either directly, as a consequence of the information content of ratings themselves, or indirectly, as a consequence of the “hardwiring” of ratings into regulatory rules, fund management mandates, bond covenants, etc. When considering the impact of ratings and rating changes, two conclusions are worth highlighting. – First, ratings correlate moderately well with observed credit spreads, and rating changes with changes in spreads. However, other factors, such as liquidity, taxation and historical volatility clearly also enter into the determination of spreads. Recent research suggests that reactions to rating changes may also extend beyond the immediately-affected company to its peers, and from bond to equity prices. Furthermore, this price reaction to rating changes seems to be asymmetrical, i.e. more pronounced for downgrades than for upgrades, and may be more significant for equity prices than for bond prices. – Second, the hardwiring of regulatory and market rules, bond covenants, investment guidelines, etc., to ratings may influence market dynamics, and potentially lead to or magnify threshold effects. The more that different market participants adopt identical ratings-linked rules, or are subject to similar ratings-linked regulations, the more “spiky” the reaction to a credit event is likely to be. This reaction may include, in some cases, the emergence of severe liquidity pressures. Efforts have recently been made, notably with support from the rating agencies themselves, to encourage a more systematic disclosure of rating triggers and to renegotiate and smooth the possibly more destabilising forms of rating triggers. However, the lack of a clear disclosure regime makes it difficult to assess how far this process has evolved. Questions also remain as to the extent to which ratings-based criteria introduce a fundamentally new element into market behaviour, or, conversely, the extent to which they are simply a va riant of more traditional contractual covenants. Rating agencies strive to provide credit assessments that remain broadly stable through the course of the business cycle (rating “through the cycle”). Agencies and other analysts frequently contrast the fundamental credit analysis on which ratings are based with market sentiment — measured for example by bond spreads — which is arguably subject to more short-term influences. Agencies are adamant that they do not directly incorporate market sentiment into ratings (although they may use market prices as a diagnostic tool). On the contrary, they make every effort to exclude transient market sentiment. However, as reliance on ratings grows, CRAs are being increasingly expected to satisfy a widening range of constituencies, with different, and even sometimes conflicting, interests: issuers and “traditional” asset managers will look for more than a simple statement of near-term probability of loss, and will stress the need for ratings to exhibit some degree of stability over time. On the other hand, mark-to-market traders, active investors and risk managers may seek more frequent indications of credit changes. Hence, in the wake of major bankruptcies with heightened credit stress, rating agencies have been under considerable pressure to provide higher-frequency readings of credit status, without loss of quality. So far, they have responded to this challenge largely by adding more products to their traditional range, but also through modifications in the rating process. The rating process and the range of products offered by rating agencies have thus evolved over time, with, for instance, an increasing emphasis on the analysis of liquidity risks, a new focus on the hidden liabilities of companies and an increased use of market-based tools. It is too early, however, to judge whether these changes should simply be regarded as a refinement of the agencies’ traditional methodology or whether they suggest a more fundamental shift in the approach to credit risk measurement. For the same reason, it is not possible to draw any firm conclusions about changes in the effects of credit ratings on market dynamics.

Defending Against Speculative Attacks

While virtually all currency crisismodels recognise that the fate of a currency peg depends on how tenaciously policy makers defend it, they seldom model how this is done. We incorporate themechanics of speculation and the interest rate defence against it in the model ofMorris and Shin (American Economic Review 88, 1998). Our model captures that the interest rate defence reduces speculators’ profits and thus postpones the crisis. It predicts that well before the fall of a currency interest rates are increased to offset the buildup of exchange market pressure, and this then unravels in a sharp depreciation. This pattern is at odds with predictions of standard models, but we show that it fits well with reality.Exchange Market Pressure, Currency Crisis, Interest Rate Defence, Global Game

A Dynamical Thermostat Approach To Financial Asset Price Dynamics

A dynamical price formation model for financial assets is presented. It aims to capture the essence of speculative trading where mispricings of assets are used to make profits. It is shown that together with the incorporation of the concept of risk aversion of agents the model is able to reproduce several key characteristics of financial price series. The approach is contrasted to the conventional view of price formation in financial economics.Comment: contribution to the 6th Granada Seminar 2000: Modeling Complex Systems, 10 pages, eps figure

Practical Deep Reinforcement Learning Approach for Stock Trading

Stock trading strategy plays a crucial role in investment companies. However, it is challenging to obtain optimal strategy in the complex and dynamic stock market. We explore the potential of deep reinforcement learning to optimize stock trading strategy and thus maximize investment return. 30 stocks are selected as our trading stocks and their daily prices are used as the training and trading market environment. We train a deep reinforcement learning agent and obtain an adaptive trading strategy. The agent's performance is evaluated and compared with Dow Jones Industrial Average and the traditional min-variance portfolio allocation strategy. The proposed deep reinforcement learning approach is shown to outperform the two baselines in terms of both the Sharpe ratio and cumulative returns

Is it Social Influence on Beliefs Under Ambiguity? A Possible Explanation for Volatility Clustering

Influencing and being influenced by others is the very essence of human behaviour. We put forward an exploratory asset-pricing model allowing for social influence on investor judgments under ambiguity. The time series of returns generated by our model displays volatility clustering, a puzzling stylised fact observed in financial markets. This suggests that social influence on investor judgments may be playing a role in generating volatility clustering.Social Influence, Knightian Uncertainty, Ambiguity, Volatility Clustering

Reasons and opportunism control in public grants policies for development and innovations of businesses

In this paper we would to analyze the mechanism of public grants on economic growth. In particular this topic has been the subject of scientific interest by economists and, recently, also by business economics scholars. The studies of the economists focused on the motivations of the intervention itself; the business economic studies, on the other hand, have analyzed the impact both on the behavior of entrepreneurs and on the firms themselves by public grants. The studies examined so far highlight two basic conceptual dimensions, different, but also complementary to each other: on the one hand the economic-oriented to investigate the motivations and effectiveness of the public intervention; the second, business-oriented, focused on the firm’s behavior following public grant. Based on these arguments, our research question arises: could the effectiveness of public intervention for funding development and business innovation be influenced by the differences in the various socio-political and institutional contexts in which they are applied? The aim of paper is analyze the motivations of public grants policies and their influence on the behavior of firms. In this way we want to identify asolutions scheme able to recover efficiency and effectiveness of public actions to support development. It is therefore possible to identify some corrective mechanisms on public intervention policies. In particular with reference to the behaviors induced by the grants policies, the idea is to re-design the grants policies in consideration of the different forms of pre and post contractual opportunism. With reference, instead, to the motivations underlying the public grants policies, it is necessary to examine the relationship between the State (Principal) and the beneficiary firms (Agent) in relation to the respective dimensions of the contractual force