This study examines the returns, relative to the S&P 500, on cash indices and futures tracking smaller stocks around the turn of the year. While we control for volatility clustering, return autocorrelation in small stock indices, and other calendar effects, our main focus is the evolution of the turn of the year effect through time: in particular, whether the effect is smaller or takes place earlier subsequent to the introduction of the S&P Midcap and Russell 2000 futures in 1993. We find that evidence of a traditional turn of the year effect, in both cash and futures, is confined to the pre-1993 period. Post-1993, there are no abnormal returns during the turn of the year window as a whole. Interestingly, returns in this period remain high on the last trading day of December, but they are negativeWe thank an anonymous referee and the editor for valuable comments and suggestions on earlier versions of the paper. Any remaining errors are our own responsibility. across the first five trading days of January. In addition, post-1993, we often observe significant abnormal returns prior to the traditional turn of the year, i.e., in the pre-Christmas and post-Christmas windows. Taken together, our results suggest that market participants may be eliminating the turn of the year effect with the aid of two new futures contracts that are well suited to this purpose.

Purpose – The purpose of this study is to explore the early stage of development of a cluster. The literature on early stage of cluster development shows that there are often random effects such as an entrepreneur and spin-off companies, and in this study, a coordinated approach for cluster development is described. Design/methodology/approach – A single exploratory case study approach is followed. The aerospace cluster in the Spokane region, State of Washington, is described. Data from a variety of sources are triangulated to enhance the credibility of the case study findings. Findings – It was found that although there are many types of collaborations occurring in the region, which involve policy and government organizations, the main driver of the early-stage cluster development is manufacturers-led coordinating mechanism. Individual manufacturers are too small to be successful in the aerospace industry, and they are collaborating to present a united “front” to out-of-the-region customers. Once customers place an order, then within this coordinating mechanism, the work is divided among different manufacturers. Research limitations/implications – The research has two main limitations. First, it is a single case study, and therefore, the results may not be generalizable. Second, the cluster is in an early stage of development, so it is not (yet) clear whether this manufacturers-led coordinated approach will have long-term success. Practical implications – The studies offer potential for cluster development that go beyond relying on a single entrepreneur or on mostly government- or policy-driven initiatives. Instead, this is an approach that can be used by industry to lift the overall competitiveness of their region. Social implications – This cluster development approach offers potential for economic development of smaller regions which mainly consist of small- and medium-sized companies without endowment benefits or a large local customer base. Originality/value – This study adds to the existing knowledge on clusters and cluster types. The identified cluster approach does not fit with the main types of clusters that have been identified in the literature. The companies involved are mainly small- to medium-sized companies, but by coordinating their capabilities, they are able to present core capabilities in a much more attractive manner to customers. This cluster development approach is not driven by or achieved through advantages in innovation, vertical or horizontal supply chain competition and advantages, creation of spin-off firms, or a regional demand base as customers are located outside the region. It deviates in terms of the types of companies involved and, mostly, in a sense that it acts as one unit to customers who are located outside the region.

Financial crises have regularly afflicted economies throughout history and the United States has been no exception.  This paper examines the Panic of 1907, the Crash of 1929 and the Great Depression and the Great Recession of 2007-08 and discusses the responses of the government and regulators.  The short version of the story is that the while the government response has varied in terms of monetary and fiscal policy, the regulatory response has remained essentially the same.  The typical reactive regulation sounds good and gives the appearance of accomplishing something but, in fact, only serves to sow the seeds of future crises. The ineffective implementation of existing regulation has had a similar result. Indeed, several authors note that most financial innovation in recent years has its origins in circumventing new regulations. Likewise, government monetary and fiscal responses may or may not help the economy and often give the appearance of great arbitrariness.  Our conclusion is that there will be unforeseen financial crises in the future, sweeping regulation and promises of recent politicians notwithstanding.  Serious study of the unanticipated consequences of this regulation and the development of more robust risk management systems will help us mitigate the effects of future crises but will be of little assistance when it comes to avoiding them. Developing the analyses and risk management systems requires a detailed study of financial history keep both successes and failures fresh in our collective memory.

Buy and hold strategies make staying disciplined difficult for investors, especially given the variability of returns for different asset classes/strategies during divergent market conditions. Market timing strategies, on the other hand, present significant theoretical benefits, but in reality these benefits are difficult to obtain. Tactical asset allocation, where limited deviations from the strategic allocation are allowed permits the portfolio manager to take advantage of market conditions fits between these two extremes. The authors correlate daily returns for each of eighteen separate asset classes typically used in diversified institutional portfolios and daily closing values of the VIX (the ticker symbol for the Chicago Board Options Exchange Volatility Index). This information is used to select those classes whose returns are most responsive to the level of the VIX. Portfolio allocations for eight selected asset classes are revised depending on the level of the VIX at the daily close of the market. The portfolio is rebalanced on the business day following the day the VIX hits the trigger value. The VIX tactical allocation overlay yields an increase in return over the buy and hold portfolio of approximately 38 basis points. The authors conclude that the tactical asset allocation strategy based on the level of VIX provides a higher return than the neutral buy and hold allocation with a higher Sharpe ratio and lower volatility.

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="color: #0d0d0d; font-size: 10pt; mso-themecolor: text1; mso-themetint: 242;"><span style="font-family: Times New Roman;">The required rate of return should equal the average expected return in the market for the same level of risk.<span style="mso-spacerun: yes;">&nbsp; </span>However, firms should only accept such projects with expected returns that <span style="text-decoration: underline;">exceed</span> this required rate of return.<span style="mso-spacerun: yes;">&nbsp; </span>This contradicts our first statement that the required rate of return <span style="text-decoration: underline;">equals</span> this average expected return for the market.<span style="mso-spacerun: yes;">&nbsp; </span>We study this possible paradox in the context of a stochastic general-equilibrium model with endogenous prices.<span style="mso-spacerun: yes;">&nbsp; </span>We find that the capitalization of the real options involved in this model explains away this contradiction or paradox.</span></span></p>