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    The lack of sufficient people resources and the volume of regulatory change are top concerns among nearly 800 financial institutions who responded to an authoritative Thomson Reuters survey on the impact of global changes in Know Your Customer (KYC) regulation, while a parallel survey of their corporate customers found that 89 percent had not had a good KYC experience, and 13 percent had changed their financial institution relationship as a result.read more...

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    Press release about Agustín Carstens being reappointed as Chair of the BIS Global Economy Meeting and the BIS Economic Consultative Committee (9 May 2016)

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    The Board of the International Organization of Securities Commissions today published The Impact of Storage and Delivery Infrastructure on Commodity Derivatives Market Pricing. The report sets out the findings and conclusions of the review of the impact of storage infrastructures on the integrity of the price formation process of physically-delivered commodity derivatives contracts traded on regulated exchanges. The price formation process for commodity derivatives is complex and is affected by many factors, not just the traditional elements of supply and demand. Rail cars, grain silos, oil tankers and metal warehouses are all fundamental components of a delivery system that ensures derivatives contracts can be fulfilled and commodities are delivered. Physical delivery and storage infrastructure can therefore have a profound impact on the economics of the futures markets, such as the cost of carrying the derivatives contract, convergence between the derivative and the physical market prices, and the premiums for each of the contract's delivery points.

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    The Board of the International Organization of Securities Commissions today published The Impact of Storage and Delivery Infrastructure on Commodity Derivatives Market Pricing. The report sets out the findings and conclusions of the review of the impact of storage infrastructures on the integrity of the price formation process of physically-delivered commodity derivatives contracts traded on regulated exchanges.read more...

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    The Financial Conduct Authority (FCA), today opened its regulatory sandbox to firms. The sandbox is a ‘safe space’ in which businesses can test innovative products, services, business models and delivery mechanisms while ensuring that consumers are appropriately protected. The regulatory sandbox is part of Project Innovate, an initiative kicked off in October 2014, to help us encourage innovation in the interests of consumers and promote competition through disruptive innovation.read more...

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    Bursa Malaysia Securities Berhad (635998-W) (Bursa Malaysia Securities) has publicly reprimanded KAF-Seagroatt & Campbell Berhad (KAF) in respect of the company’s fourth quarterly report for the financial year ended 31 May 2015 (“QR 4/2015”) announced on 31 July 2015 which was in contravention of paragraph 9.16(1)(a) of the Bursa Malaysia Securities Main Market Listing Requirements (Main LR).  read more...

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    Securities read more...

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    The Depository Trust & Clearing Corporation (DTCC), the premier post-trade market infrastructure for the global financial services industry, and the Korea Exchange (KRX), the sole securities and derivatives exchange operator in South Korea, today announced the signing of a Memorandum of Understanding (MOU) to cooperate with each other on a Trade Repository (TR) solution in Korea.read more...

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    In a case brought by the Financial Conduct Authority (FCA) and following a three-month trial at Southwark Crown Court, two defendants – a senior investment banker and a Chartered Accountant – have been convicted of conspiring to insider deal between November 2006 and March 2010.read more...

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    OSE has set the position limits on Securities Options, which will be applied from May 13, 2016.read more...

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    Bats Global Markets, Inc. (Bats: BATS), a leading global operator of exchanges and services for financial markets, today reported April data and highlights, including record U.S. Options market share of 11.6% vs. 9.9% a year ago.read more...

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    In the month of April price improved contracts on BOX Options Exchange (“BOX”) averaged 297,158 per day. Price improvement versus the prevailing NBBO for contracts submitted via BOX’s price improvement auction, PIP, averaged $467,418 per day, while total savings to investors in April was $9.8M. With this, BOX has saved investors over $761M since its inception in 2004. Overall average daily trading volume on BOX in the month of April was 407,208 contracts.read more...

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    The U.S. Commodity Futures Trading Commission (CFTC) today issued an Order filing and simultaneously settling charges against Cunningham Commodities, LLC (Cunningham), a registered Futures Commission Merchant (FCM) based in Chicago, Illinois. The Order finds that Cunningham violated CFTC’s Regulations that 1) require an FCM to immediately report to the CFTC any deficiency in its customer segregated account or the targeted residual interest in its customer segregated account and 2) require an FCM to submit daily reports to the CFTC for positions held by certain large traders (Large Trader Reports) whose accounts are carried by the FCM.read more...

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    Announcing Expansion of LSN Law & Society: Private Law Sponsored eJournalread more...

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    In this paper we propose a novel application of Gaussian processes (GPs) to financial asset allocation. Our approach is deeply rooted in Stochastic Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert Fernholz that aims at flexibly analysing the performance of certain investment strategies in stock markets relative to benchmark indices. In particular, SPT has exhibited some investment strategies based on company sizes that, under realistic assumptions, outperform benchmark indices with probability 1 over certain time horizons. Galvanised by this result, we consider the inverse problem that consists of learning (from historical data) an optimal investment strategy based on any given set of trading characteristics, and using a user-specified optimality criterion that may go beyond outperforming a benchmark index. Although this inverse problem is of the utmost interest to investment management practitioners, it can hardly be tackled using the SPT framework. We show that our machine learning approach learns investment strategies that considerably outperform existing SPT strategies in the US stock market.

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    We pursue the robust approach to pricing and hedging of financial derivatives. We investigate when the pricing--hedging duality for a regular agent, who only observes the stock prices, extends to agents with some additional information. We introduce a general framework to express the superhedging and market model prices for an informed agent. Our key insight is that an informed agent can be seen as a regular agent who can restrict her attention to a certain subset of possible paths. We use results of Hou \& Ob\l\'oj \cite{ho_beliefs} on robust approach with beliefs to establish the pricing--hedging duality for an informed agent. Our results cover number of scenarios, including information arriving before trading starts, arriving after static position in European options is formed but before dynamic trading starts or arriving at some point before the maturity. For the latter we show that the superhedging value satisfies a suitable dynamic programming principle, which is of independent interest.

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    The article presents a general discrete time dividend valuation model when the dividend growth rate is a general continuous variable. The main assumption is that the dividend growth rate follows a discrete time semi-Markov chain with measurable space. The paper furnishes sufficient conditions that assure finiteness of fundamental prices and risks and new equations that describe the first and second order price-dividend ratios. Approximation methods to solve equations are provided and some new results for semi-Markov reward processes with Borel state space are established. The paper generalizes previous contributions dealing with pricing firms on the basis of fundamentals.

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    In an efficient stock market, the log-returns and their time-dependent variances are often jointly modelled by stochastic volatility models (SVMs). Many SVMs assume that errors in log-return and latent volatility process are uncorrelated, which is unrealistic. It turns out that if a non-zero correlation is included in the SVM (e.g., Shephard (2005)), then the expected log-return at time t conditional on the past returns is non-zero, which is not a desirable feature of an efficient stock market. In this paper, we propose a mean-correction for such an SVM for discrete-time returns with non-zero correlation. We also find closed form analytical expressions for higher moments of log-return and its lead-lag correlations with the volatility process. We compare the performance of the proposed and classical SVMs on S&P 500 index returns obtained from NYSE.

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    Financial markets have been extensively studied as highly complex evolving systems. In this paper, we quantify financial price fluctuations through a coupled dynamical system composed of phase oscillators. We find a Financial Coherence and Incoherence (FCI) coexistence collective behavior emerges as the system evolves into the stable state, in which the stocks split into two groups: one is represented by coherent, phase-locked oscillators, the other is composed of incoherent, drifting oscillators. It is demonstrated that the size of the coherent stock groups fluctuates during the economic periods according to real-world financial instabilities or shocks. Further, we introduce the coherent characteristic matrix to characterize the involvement dynamics of stocks in the coherent groups. Clustering results on the matrix provides a novel manifestation of the correlations among stocks in the economic periods. Our analysis for components of the groups is consistent with the Global Industry Classification Standard (GICS) classification and can also figure out features for newly developed industries. These results can provide potentially implications on characterizing inner dynamical structure of financial markets and making optimal investment tragedies.

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