Successful applicants will be issued a casual registration identity card, which must be shown to ManchesterMarkets every time you attend the market to apply for daily casual trading, and when requested. The card confirms that you are registered with ManchesterMarkets and eligible to trade at the LocalMarkets on a daily casual basis, subject to the terms and conditions of registration and the ManchesterMarkets Service Standards. The casual registration identity card will provide details of the goods and services you will be allowed to sell at the Localmarkets, and will show when your public liability insurance expires, and when you are required to provide further proof of UK working should the documents you have provided have time-limit restrictions. Your casual registration identity card will expire at the time your public liability expires and at the deadline for providing further documentary evidence of UK working, and will only be renewed when you provide proof of your renewed insurance policy and any other additional documents.
1.6. Thesis Road Map 10 spread trading in commodity markets. First, we describe cointegration and its applica- tion in pairs trading, a one factor mean-reverting Vasicek process to model the spread process, presented by Elliott et al. (2005), and the two factor model proposed by Demp- ster et al. (2008) to model the spot spread process. Second, we apply these three models to our empirical sample data and compare the results. Later, in Chapter 4, we analyze the recent behavioral change in the location spread between WTI crude oil and Brent oil. Since important news can generate a shock in a spread process, we propose to im- plement a jump, which is compound Poisson process, in the one-factor and two-factor spread models. In these models, jump sizes follow the double exponential distribution introduced by Kou (2002). A new one-factor mean-reverting process is introduced to explain not only the mean-reverting property of the spread process, but also the skewness and the kurtosis characteristics of a spread process. The transition density of this nonlin- ear mean-reverting stochastic process is unknown so the new local linearization method is deployed to estimate the model’s parameters. Since the spread between WTI crude oil and Brent oil has recently experienced a structural break for fundamental reasons, we deploy Regime-Switching Models (RSM) in this generalized one-factor mean-reverting dynamics to capture this phenomena in the spread process in Chapter 4. In Chapter 5, we will develop a novel mean-reverting random walk, obtain its continuous time dynam- ics, and use it to model the spread dynamics. The new mean-reverting process will be compared to Elliott et al. (2005)’s one factor model and its advantages and disadvantages are investigated. We will deploy both models: the new one factor mean-reverting model and the Vasicek process, to price the spread between WTI and WTS crude oils. Using both observed and estimated results, we will discuss which process can better describe the reality of the spread process.
Thus, there is no centralized exchange providing immediacy of trade and pre-trade price transparency. To initiate a transaction, a prospective seller must contact multiple potential buyers. Comparing two similar aircraft for sale is costly since aircraft sales involve the material inspection of the aircraft, which could be located in two different countries. In addition, a sale involves legal costs, which increase substantially if there are legal disputes over the title or if the local aviation authority has deregistered the aircraft. In some cases, there could also be outstanding bills for maintenance, fuel, and parking that have to be paid before the aircraft is released by the local authority, and sold. Thus, aircraft are seldom sold at auctions. Pulvino (1998) reports that in one of the first auctions, organized in 1994 to enhance the liquidity of the market, only nine of the 35 aircraft offered for sale were sold. Some subsequent auctions ended without even a single sale. Hence, aircraft markets share many features with other over- the-counter markets for financial assets (mortgage-backed securities, corporate bonds, bank loans, derivatives, etc.) and for real assets (real estate), in which trading involves material and opportunity costs (Duffie, Gˆarleanu and Pedersen, 2005 and 2007). As a result, most
Background: The traditional markets in southern Ecuador and within the Andean region are especially important for plant resource trading among local people, even since before Spanish colonization; therefore, ethnobotanical studies are currently necessary and important. These strategic spaces persist for the traditional medicine cultural value reflected in the higher consumption of medicinal plants, which span all socioeconomic levels of rural and urban people. The purpose of this study includes the following: 1) to create a novel list of medicinal plants sold at 33 traditional markets; 2) to establish medicinal plant use agreement amongst vendors with the Factor of Informant Consensus (FIC); and 3) to determine the most sold medicinal plant species using the Fidelity Level (FL).
Commodity Derivatives markets are amongst the worlds largest financial markets. Initially conceived as a hedging platform for producers and consumers in the localmarkets, Commodity Derivatives trading today has evolved to provide sophisticated Investment & Risk managed opportunities to various organizations around the world. Investments in commodities were traditionally
Intuitively, a link between i and j represents that they are potential counterparties in a trade. There is a single risky asset in zero net supply. The …nal value of the asset is uncertain and interdependent across dealers with an arbitrary correlation coe¢ cient controlling the relative importance of the common and private components. Each dealer observes a private signal about her value, and all dealers have the same quality of information. Since values are interde- pendent, inferring each others’signals is valuable. Values and signals are drawn from a known multivariate normal distribution. Each dealer simultaneously chooses her trading strategy, un- derstanding her price e¤ect given other dealers’strategies. For any private signal, each dealer’s trading strategy is a generalized demand function which speci…es the quantity of the asset she is willing to trade with each of her counterparties depending on the vector of prices in the transactions she engages in. Each dealer, in addition to trading with other dealers, also trades with price sensitive costumers. In equilibrium prices and quantities have to be consistent with the set of generalized demand functions and the market clearing conditions for each link. We refer to this structure as the OTC game. The OTC game is, essentially, a generalization of the Vives (2011) variant of Kyle (1989) to networks. Most of our results apply to any network.
Second, the EMH claims that even if some investors are not fully rational, markets could still be efficient as long as they trade randomly and hence their trades would cancel each other. This implies that the correlation in the strategies of the irrational investors is limited. In contrast, Kahneman and Tversky (1973) reveal that investor sentiment typically determines the common judgment errors made by a substantial number of investors. Shiller (1984) argues that the mistakes would become more severe when the noise traders behave socially and follow each others. Empirical studies also confirm that the aggregate trading of noise traders could be systematically correlated. Barber, Odean, and Zhu (2006a) demonstrate that the trading of individual investors is surprisingly systematic using trading records in U.S. stock markets. Barber, Odean, and Zhu (2006b) argue that noise traders indeed move the markets because they find that noise trader can affect stock prices using eighteen years of tick-by-tick transactional data for U.S. stocks. Finally, Shleifer (2000) presents that professional managers of pension and mutual funds are subject to the same biases as individual investors.
142 . See, e.g., In re Kreisler, 546 F.3d 863 (7th Cir. 2008) (using “assignment,” “purchase,” and “sale” interchangeably). See also Richard L. Ferrell, Court Says ‘No Harm, No Foul’ in Claims Trading Case Standards for Distressed Debt Claims Trading Continue to Evolve, J. C ORP . R ENEWAL , Mar. 10, 2009, https://www.turnaround.org/Publications/Articles.aspx?objectID =10736; Ken Coleman & Hugh McDonald, District Court Enron Opinion: A Pyrrhic Victory for Traders, A SSET S ALES C OMMITTEE N EWSLETTER (A M . B ANKR . I NST ., Alexandria, Va.), Oct. 2007, http://www.abiworld.org/committees/newsletters/assetsales/vol4num3/Southern.html (noting that “a great deal of debt is traded using documents somewhat indiscriminately labeled ‘purchase and sale’ and ‘assignment and acceptance’ or ‘assignment and assumption,’ or is simply not documented by more than a trade confirmation. This potential problem is compounded by the fact that most loan and credit agreements contain appendices, often labeled as ‘assignment,’ which lenders are required to use in order to transfer their debt to a downstream purchaser/assignee.”); Bingham, Ruling in Enron Claims Trading Case Cheers Distressed Debt Traders, Sept. 11, 2007, http://www.bingham.com/Media.aspx?MediaID=5678 (“Typically in commercial law a sale is a form of assignment. . . .”); U.C.C. § 2-106(1) (2003) (defining “sale” as “the passing of title from the seller to the buyer for a price”).
On the basis of the three benchmarks used in this article to measure trading volume, we observe a clear increase in the level of trading activity of the sampled FTSE100 stocks in the post-SETS period. However, this result may be unrelated to any influence that increased transparency standards had on trading volume following the change of trading system and the introduction of a central order book for FTSE100 stocks. Thus, a procedure had to be devised to measure the influence of the introduction of SETS on trading volume during the examined period in isolation from that of other factors – factors that do not relate to this change. For this reason, we used two different methods that permitted us to isolate the trend in trading volume, which is common in both the pre- SETS and the post-SETS periods. In using the first method, we removed the deterministic trading volume trend that is shared by both periods. We named the modified measures: de-trended measures of trading volume. The use of the de-trended measures led us to the conclusion that the introduction of SETS did not have an appreciable impact on trading volume for the sampled FTSE100 stocks. In using the second method, we utilized a stochastic structural time series analysis technique, which allowed us to reach a similar conclusion: the introduction of SETS did not lead to any appreciable increase in trading volume for the stocks under study.
would not recommend that the Commission institute enforcement action against the Singapore International Monetary Exchange Limited (SIMEX) or its members solely based upon SIMEX’s failure to obtain contract market designation pursuant to Sections 5 and 5a of the Commodity Exchange Act (Act) if: (i) SIMEX members trade for their proprietary accounts through SIMEX’s electronic trading and order matching system (SIMEX ETS) terminals in the United States; (ii) SIMEX members who are registered with the Commission as futures commission merchants (FCM) or who are exempt from such registration pursuant to Rule 30.10 (Rule 30.10 firms) submit orders from U.S. customers for transmission to SIMEX ETS; and/or (iii) SIMEX members who are registered with the Commission as FCMs or who are Rule 30.10 firms accept orders through automated order routing systems (AORS) from U.S. customers for submission to SIMEX ETS.
We show through examples that bubble injections can generate large increases in the volume of trade. First, we analyze the complete markets example studied in Alvarez and Jermann (2001) and Kehoe and Levine (2001), in which agents are not allowed to trade after default. We substitute the one-period Arrow securities used by them with infinitely lived assets that dynamically complete the markets. We focus on two types of dividend structures and on deterministic and stochastic bubbles, and show that a bubble injection in one of the assets can induce a volume of trade increase in all assets, thus causing a large market-wide increase in trade volume. The increase is persistent, even when the bubble lasts arbitrarily long. When the bubble crashes, the volume of trade collapses when compared to the volume levels in the absence of a bubble, and then reverts back to normal. Second, we consider an incomplete markets economy having a Pareto optimal equilibrium. As in Judd, Kubler, and Schmedders (2003), there is no trade after an initial portfolio rebalancing by the agents. A bubble injection generates persistent market-wide increases in the volume of trade.
Today, electronic trading in the Treasury securities market takes place using a variety of trading protocols across a diverse set of trading venues, most of which allow for some degree of automation by market makers but only a subset of which are amenable to the deployment of fully automated trading strategies. Electronic trading in the Treasury markets has arguably improved overall liquidity through enhanced order flow and competition, thus reducing trading costs and allowing market participants to more effectively manage risk. Some have also reasoned that automated trading has improved market efficiency by reducing valuation discrepancies across related markets. However, the increased adoption of automated trading has also led market participants and regulators to articulate concerns about the potential for greater operational risk, disruptive market practices and trading strategies, and the risk of sharp, short-term disruptions to the Treasury securities market of the kind experienced in the equities and futures markets, which have a significant automated trading presence. Given the growth of automated trading in the Treasury securities market and the increasing role that automated trading firms play as providers of liquidity in the inter-dealer market, the Treasury Market Practices Group (TPMG) is releasing an updated set of best practices recommendations designed to promote and support the continued efficiency and integrity of the markets.
conclusion, that an increase in market overconfidence is associated with the increase in average price and trading activity. The reduction of the aggregated average market price and trade volume over the experiment’s periods is observed. Thus hypothesis that overconfidence also reduces to the end of the game was tested. For that, based on the data from the first and last seven periods, two bias scores for each market were constructed. Overconfidence measure of the first part of the experiment is, in most markets, lower than that of the second part and this difference is significant. This finding could serve as an explanation why bubbles burst close to the end (or in some cases middle) of the experiment. Menkhoff, Schmidt, and Brozynski (2006) find similar results of decrease in overconfidence with experience; however Kirchler and Maciejovsky (2002) report that overconfidence increases with the experience. Analysis of the five bubble measures (NPD, NAD, Amplitude, Hassel-R2, and Velocity) revealed that in the markets formed of overconfident subjects bubbles are more likely to occur and that they are significantly larger in magnitude than in rational markets. Large and significant correlation between bubble measures and measures of overconfidence provide additional evidence that overconfidence has significant effect on price and trading behavior in experimental asset markets. Comparison of the selected bubble measures, averaged over five rational and overconfident markets, to the measures obtained in other experiments in which bubble-crash pattern was observed (e.g. Smith, Suchanek, and Williams, 1988) and the experiment of Noussair and Tucker (2006) in which bubbles were practically eliminated, suggests that there is evidence of the smaller deviations from the fundamental value in the rational market treatment than those observed in previous studies of markets of this type. To conclude, the analysis of the bubble measures demonstrates that although bubbles in the rational markets are not completely eliminated, they are less severe in comparison to the bubbles in overconfident markets. Moreover bubble measures increase with the increase in market overconfidence.
Dynamic development has always been the exception rather than the rule in capital markets. Large-scale technological, economic and political transformations have provided the driving force for episodes of growth and transformation, often followed by collapse, reform, consolidation and long periods of quiescence. The financing of the Dutch and English trading companies during the 17th century, the worldwide railway booms of the mid 19th century and colonial expansion around the millenium are all examples of such episodes. Many of today’s stock markets were shaped by them. Periods of expansion were often ended by financial market collapses and interspersed with more ephemeral investment surges having more the character of ’bubbles’, using the modern definition of the term (for a full discussion see Dwyer and Hafer
As LETS are a relatively new form of social organisation, it is not surprising that little empirical data about their activities exists. In particular there is very little qualitative information drawn from intensive case study research, and there are even fewer examples of published critical academic analysis (but see Aldridge et al. 2002; Lee 1996; Seyfang 2001; Williams et al. 2001). Consequently discussion is only slowly moving beyond the perpetuation of the idealised representations of LETS development, originating in the promotional literature, that focus upon the assumed ‘potential’ of these organisations (e.g. see Figure 1). Within this literature, LETS have been described as offering a new method of self-provisioning, and as a means for people to re-negotiate their working lives, for example by mixing traditional paid work with LETS work; developing new skills and abilities; and even perhaps providing the opportunity to initiate and incubate a small business – paying for the initial set-up costs in local currency prior to formal self- employment. It is on the basis of this unexamined ‘potential’ that LETS are being promoted by a number of state and voluntary agencies as a tool for community development and economic regeneration (see DETR 1988; DfEE 1999; Social Exclusion Unit 1998; 2000). For example, a recent government working paper (DETR 1998) includes LETS as one of a number of new bottom- up approaches to local economic development; and over 100 LETS have received some form of support from local authorities (LETSLink UK 1997). This assistance has included direct funding, such as the employment of LETS development workers (e.g. Hounslow and Greenwich); and various forms of support in-kind, such as a range of promotional activities and the free use of facilities (e.g. Dursley). However, it is important to examine how LETS perform as tools of local economic development in practice, in different localities, both in order to evaluate their chances of success, and to allow the identification of developmental constraints prior to their widespread promotion 3 .
Efficient market hypothesis fails from time to time. There are many reasons why it happens. We will try to concentrate on one of them – force-majeure events – situations when something important happens unexpectedly. In this case market simply can’t absorb information in one moment. So for some period of time it becomes inefficient and stays inefficient until new information will not be included by the market. Such situations give us possibility to predict the market’s behavior. This is our intuitive assumption. To confirm or refuse it we will analyze the reaction of financial markets to the biggest force-majeure events during last 20 years. Also we will try to develop a trading strategy based on financial market’s reaction to force- majeure events.
The energy transition will not be done by large companies. It requires from the consumer to become a prosumer and to become energy aware. The prosumer in the energy world is nowadays mainly described as the one investigating in energy generation through for instance solar panels or for large consumers by biomass or by wind energy. However, this kind of prosumers are not achieving the required renewable energy speed. Local communities are a huge driver (Walker, 2008) for energy initiatives. Van Der Schoor et al (2017) performed an extensive research of passive consumers or simple prosumers moving towards active creators of new energy systems. Most of these initiatives are grassroot innovations which means they are community-led solutions for sustainability (Hargreaves et al, 2013). These bottom-up initiatives take control over the production and distribution of energy. Table 4 shows these grassroot innovations at the level of prosumer and communities besides the top- down possibilities. The grow of local and regional initiatives is supported by a research from TNO (2015) who performed research towards a future-proof energy system. They recall a trend towards an energetic society with wealthy, cooperating and autonomous citizens and innovative companies. Local communities can contribute to the three ambitions and challenges as shown in figure 17 since the energy they generate is sustainable, they create a more reliable grid by having a local grid and thus reduce transfer of energy over the large grid thus also reducing the price since less transportation is required.
Another way that investors can interact with a liquidity provider is through a NAV + transaction, also known as a creation or redemption. The majority of these transactions take place between clients and liquidity providers who are set up as APs in the specific funds they are looking to trade. In this scenario, an investor arranges to create or redeem shares with an AP. The end price the client pays or receives for the shares is based on the closing NAV as well as any implicit costs which the AP incurs in the process of creating or redeeming the shares. As previously discussed, these costs include many of the trading costs outlined in Section II. Given the nature of a NAV + trade, market risk is accepted by the client until an order’s NAV is determined. Since any market risk is taken on by the client, this tends to be the more cost-efficient way of transacting in a fund. It is extremely important to note, however, that any market risk assumed by a client in a NAV+ trade, although difficult to quantify, can translate into significant unintended market movement costs. For example, certain ETFs are unable to confirm NAV until one day after an order has been accepted. This tends to happen with ETFs tracking global benchmarks that might have securities in the underlying basket that are closed for trading at the time an order is received. As such, the market can potentially move significantly (either positively or negatively) between the time a client places an order in their ETF of choice and the NAV is confirmed the next day. For clients with a shorter term, more tactical view on their ETF choices, this market risk tends to be less than ideal given the nature of their investment goals.
The objective of this section is to introduce the overview of basics of power trading (Restructuring). Trading electricity using a common power system is the only way for a large group of consumers to buy electricity from a large group of producers. The objective of the electricity trading system is that all the consumers pay for the amount of electricity they have consumed and at the same time all the producers get paid for their generation. In a nutshell, in a typical cost plus reasonable profit regulation regime, the incentives to cut cost are non-existent. Under competition, most of the risks are borne at least initially by owners – they would be responsible for bad decisions as also for profits from sound decision and managements practices. Rules, regulations and procedures have been developed over the years for facilitating short term trading in electricity, with the clear objective of: