Financial Technology Focus

Vendor News: September 30, 2015 - More than half of large insurers to increase use of cloud and co-sourcing services over next five years finds SS&amp;C survey

Posted on: 30 September 2015 | 9:27 am

Vendor News: Fidessa launches Sentinel Trading Compliance

Posted on: 28 September 2015 | 3:08 am

Vendor News: Infosys Positioned as a Leader and Star Performer in 2015 Banking Application Outsourcing PEAK Matrix&acirc;&cent; by Everest

Infosys, (NYSE: INFY), a global leader in consulting, technology, outsourcing and next-generation services, has been positioned as a Leader and Star Performer in the 2015 PEAK Matrixâ¢ for banking application outsourcing (AO) by Everest Group. The consulting and research firm also positioned Infosys as a Leader in capital markets for the second consecutive year.

Posted on: 22 September 2015 | 5:06 am

Vendor News: Portfolio Probe available for R version 3.2

Portfolio Probe available for R version 3.2 body,.backgroundTable{ background- } #contentTable{ border:0px none #000000; margin-top:10px; } .headerTop{ background- border-top:0px none #000000; border-bottom:0px none #FFFFFF; text-align:center; padding:0px; } .adminText{ font-size:10px; line-height:200%; font-family:Verdana; text-decoration:none; } .headerBar{ background- border-top:0px none #333333; border-bottom:1px solid #eeeeee; padding:0px; } .headerBarText{ font-size:30px; font-family:Verdana; font-weight:normal; text-align:left; } .title{ font-size:24px; font-weight:bold; font-family:Trebuchet MS; line-height:110%; } .subTitle{ font-size:14px; font-weight:bold; font-style:normal; font-family:Trebuchet MS; } .defaultText{ font-size:12px; line-height:150%; font-family:Verdana; width:400px; background- padding:20px; } .sideColumn{ background- border-left:1px solid #CCCCCC; text-align:left; width:200px; padding:20px; margin:0px; } .sideColumnText{ font-size:11px; font-weight:normal; font-family:Arial; line-height:150%; } .sideColumnTitle{ font-size:15px; font-weight:bold; font-family:Arial; line-height:150%; } .footerRow{ background- border-top:0px none #FFFFFF; padding:20px; } .footerText{ font-size:10px; line-height:100%; font-family:Verdana; } a,a:link,a:visited{ text-decoration:underline; font-weight:normal; } .headerTop a{ text-decoration:underline; font-weight:normal; } .footerRow a{ text-decoration:underline; font-weight:normal; } Email not displaying correctly? View it in your browser. Investment technology for the 21st century. R version 3.2 Portfolio Probe is available for R version 3.2. But there is a catch. For some reason Portfolio Probe does not install in the normal way with install.packages. The workaround is to go to the 3.2 subdirectory of the Portfolio Probe repository: http://www.portfolioprobe.com/R/bin/windows/contrib/3.2/ Save the Portfolio Probe zip file to some place on your machine and then install it from there. This process is described in the Frequently Asked Support Questions page: http://www.portfolioprobe.com/user-area/frequently-asked-support-questions/read more...

Posted on: 17 May 2015 | 4:55 am

Mark Joshi drops first release of Kooderive, an open source library for pricing derivatives using GPUs

Mark Joshi writes:read more...

Posted on: 17 September 2013 | 12:25 am

Link Library: Video - One Half Second of High Frequency Trading in a Single Stock

1/2 second of trading activity in Johnson & Johnson (symbol JNJ) on May 2, 2013 This video was featured at Wired Business Conference (watch it now: http://fora.tv/2013/05/07/Nanex_CEO_E...) Follow us on twitter @nanexllc for Wall Street Breaking coverage. Set to lowest resolution for an "artistic rendering", or highest resolution for science. The animation tool that created this video was written in "C" using Windows GDI - simple lines, polygons and ellipses. We wrote it to explain to the SEC and CFTC (the regulators) how our markets work. We got the idea after realizing, in face to face meetings with them, they didn't understand market structure or the importance of latency and the consolidated feed. That was several years ago. We still aren't sure if they get it, or are just playing dumb. The bottom box (SIP) shows the National Best Bid and Offer. Watch how much it changes in the blink of an eye. Watch High Frequency Traders (HFT) at the millisecond level jam thousands of quotes in the stock of Johnson and Johnson (JNJ) through our financial networks on May 2, 2013. Video shows 1/2 second of time. If any of the connections are not running perfectly, High Frequency Traders can profit from the price discrepancies that result. There is no economic justification for this abusive behavior. Each box represents one exchange. The SIP (CQS in this case) is the box at 6 o'clock. It shows the National Best Bid/Offer. Watch how much it changes in a fraction of a second. The shapes represent quote changes which are the result of a change to the top of the book at each exchange. The time at the bottom of the screen is Eastern Time HH:MM:SS:mmm (mmm = millisecond). We slow time down so you can see what goes on at the millisecond level. A millisecond (ms) is 1/1000th of a second. Note how every exchange must process every quote from the others -- for proper trade through price protection. This complex web of technology must run flawlessly every millisecond of the trading day, or arbitrage (HFT profit) opportunities will appear. It is easy for HFTs to cause delays in one or more of the connections between each exchange. http://www.nanex.net/Research/IsNBBOI...

Posted on: 14 May 2013 | 8:07 am

Video: Larry Tabb on The Future Of Data Management in a post-Crisis World

Larry Tabb of TABB Group recently discussed with Wall Street & Technology senior editor Melanie Rodier how firms are adapting their data management processes to the post-financial-crisis environment.read more...

Posted on: 30 January 2013 | 5:39 am

SEC-mandated XBRL data at risk of being irrelevant to investors and analysts

In 2009, the Securities and Exchange Commission mandated that public companies submit portions of annual (10-K) and quarterly (10-Q) reports—in a digitized format known as eXtensible Business Reporting Language (XBRL). The goal of this type of data was to provide more relevant, timely, and reliable "interactive" data to investors and analysts. The XBRL-formatted data is meant to allow users to manipulate and organize the financial information according to their own purposes faster, cheaper, and more easily than current alternatives.read more...

Posted on: 23 January 2013 | 8:42 am

Video - Trading's evolving next generation? Control systems, feedback loops, adaptive knowledge capture

Research Library: Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices

Siddhivinayak KulkarniUniversity of Ballarat Imad HaidarUniversity of Ballarat Abstract This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the crude oil dynamic which help investors and individuals for risk managements.

Posted on: 30 November 2012 | 2:59 am

Video - Ciamac Moallemi: High-Frequency Trading and Market Microstructure

Ciamac Moallemi is the Barbara and Meyer Feldberg Associate Professor of Business in the Decision, Risk, & Operations Division of the Graduate School of Business at Columbia University. read more...

Posted on: 28 November 2012 | 9:20 am

Vendor News: NAG announces support for IBM BlueGene/Q supercomputers

Vendor News: Prescient Ridge Management signs Connamara Systems for New Trading Infrastructure and Support Services

New trading infrastructure provides entry into new markets and upgrades automated execution capabilitiesChicago, October 31, 2012 – Connamara Systems, LLC (Connamara), provider of services to exchanges, swap execution facilities, CTAs and Hedge Funds, today announced signing Prescient Ridge Management, LLC (PRM) a managed futures fund which specializes in short-term, automated trading strategies, for Connamara’s Made-to-Measure Trading Solutions to design and implement an updated trading infrastructure for PRM. This engagement is a result of PRM’s Investment Committee decision to trade new markets which opens new growth opportunities and new trading strategies for the firm going forward.Prescient Ridge Management’s President, Alan Swimmer, states: “Connamara Systems proved the right fit for PRM. Their Made-to-Measure customizable approach allows us to focus on the Fund’s new trading ideas by improving efficiency and increasing scalability. Our philosophy to trading has always been combining the best professional expertise with the best technology the market can offer.”Connamara’s approach to trading infrastructure design and implementation uses Connamara proprietary components to shorten implementation time and will provide a robust, scalable and flexible platform that allows PRM access to more markets and more asset classes. Connamara also provides all source code which lessens relationship dependency as vendor and in-house teams work collaboratively. In addition to source code for the platform, Connamara will provide all the automated regression tests, and the necessary testing and continuous integration frameworks to allow Prescient Ridge Management to extend and maintain the platform.Connamara will also integrate Prescient Ridge Management’s trading strategy software with the new trading infrastructure for order routing and management, market data, position and risk management as well as post-trade analysis and reporting to ensure a complete and seamless transaction life-cycle process. Going forward, post-delivery, Connamara will be providing on-going support and development services to Prescient Ridge Management. The Connamara Systems integration team consists of three software engineers, one senior software engineer, one Business analyst, one project manager.“Connamara Systems has been developing and delivering custom application development for almost 15 years. Having this experience and business approach allows us to move quickly as changes in the industry occur and provide a solid, proven technology base that enables us to reduce the time to market and lower the cost to our clients,” says Jim Downs, Founder and CEO of Connamara Systems.About Prescient Ridge Management LLCFounded in 2006, Prescient Ridge Management, LLC is the managing member of the Prescient Ridge Fund, LLC, a managed futures fund which specializes in short-duration, systematic trading strategies. The fund uses proprietary trading strategies to capture price movements in over 30 global exchange listed futures. Prescient Ridge Management is headquartered in Highland Park, IL just north of Chicago.For more information, please visit: http://www.prmllc.comAbout Connamara Systems:Founded in 1998 by Jim Downs, a long time index options market-maker at the Chicago Board Options Exchange, Connamara Systems offers solutions to exchanges, swap execution facilities, CTAs and Hedge Funds. Connamara delivers next generation, end-to-end trading and risk management solutions, including matching engines, order and execution management, algorithmic trading, and market data integration. Incorporating the client’s specific needs with the most advanced, tested technology, Connamara takes a made-to-measure approach to its software. Connamara is headquartered in Chicago. For more information, please visit: http://www.connamara.comread more...

Posted on: 31 October 2012 | 8:47 am

Intel and OnX Announce Social Media Hub for the Finteligent Trading Technology Community

TORONTO, Ontario and New York, NY, October 23, 2012 – read more...

Posted on: 24 October 2012 | 6:32 am

Research Library: The Diversity of High Frequency Traders

Björn HagstromerStockholm University - School of Business Lars L. NordenStockholm University - School of Business Abstract The regulatory debate concerning high frequency trading (HFT) emphasizes the importance of distinguishing different HFT strategies and their influence on market quality. Using unique data from NASDAQ OMX Stockholm, we are the first to empirically provide such a distinction for equity markets. Comparing the behavior of market making HFTs to opportunistic HFTs (arbitrage and momentum HFT strategies), we find that market makers constitute the lion share of HFT trading volume (63-72%) and limit order traffic (81-86%). Furthermore, market makers have higher order-to-trade ratios, lower latency, lower inventory, and supply liquidity more often than opportunistic HFTs. In a natural experiment based on tick size changes, we find that both market making and opportunistic HFT strategies mitigate intraday price volatility. The findings indicate that, e.g., the financial transaction tax proposed by the European Commission, which would render most HFT strategies unprofitable, would primarily hit market makers and increase market volatility. Number of Pages in PDF File: 57

Posted on: 8 October 2012 | 10:52 am

Vendor News: Buy-side forced to adopt more sophisticated risk management as interconnectivity between buy-side stakeholders grows, says Algorithmics, an IBM Company

White paper analyses impact, requirements and opportunities of buy-side interconnectivityread more...

Posted on: 19 September 2012 | 9:33 am

Link Library: Black Rhino - A Financial Network Multi Agent Simulator

Black Rhino - A Financial Network Multi Agent Simulator black_rhino is an open source easy-to-use-and-adapt financial network multi agent simulation (MAS) that serves two purposes. First, it can be used as a practical tool to simulate and analyse a model banking system. This is particularly handy for central banks and policy makers, as black_rhino fills a gap in the policy-toolbox. Second, and perhaps more importantly, it is a python module that can be easily adapted, changed, and modified for research purposes. It is intended to reduce the amount of work necessary to write a financial MAS and hence allows researchers to focus on the economic questions instead of worrying about code design patterns and basic functionality. The software is open source and published under the GNU GPL v3. You can find the latest version at sourceforge. 2 August 2012

Posted on: 19 September 2012 | 8:10 am

DataSift Launches Social Feeds for the Financial Services Industry

Research Library: The evolution of algorithmic classes (pdf)

Lajos Gergely Gyurko Mathematical Institute, University of Oxford. Introduction This paper aims to explore the key factors that drive the evolution of algorithmic classes. We analyse the impact of changes in regulation, the development of new trading venues, technological innovations, the economic environment, changes in market micro-structure, the availability and quality of data/information, and the progress in academic research. In many of the cases the joint impact of two or more of these factors leads to the appearance, mutation or decline of trading strategies, and we aim to explore such phenomena as well. We consider algorithmic classes to be (not necessarily disjoint) sets of systematic trading strategies with similar objectives. One can differentiate between algorithmic classes by the types or number of assets involved, by the markets the trading is executed on, by the typical holding period /speed of turnover of capital etc (see section on the “Typology of Algorithmic classes”). Algorithmic classes constantly evolve. We will focus on large scale evolution, in particular on the birth, transformation, mutation, renaissance, decline and extinction of classes, moreover on co-evolution. First, from a historical perspective, we identify the key factors that drive the evolution and shape the universe of algorithmic classes through observed scenarios. Then, we consider possible scenarios for the future. The typical scenario of the life cycle of an algorithmic (sub)class is as follows. Favourable circumstances - such as economic environment, decrease of trading costs, deregulation of markets, new trading venue (e.g. electronic communications networks, dark pools etc.), new product (e.g. exchange traded funds, commodity indices, etc.), extended access to existing products, technological development (trade execution at increased speed), etc. - result in the appearance of new trading strategies. In the beginning, a few market participants (“first-to-market traders” - Aldridge 2010) discover and exploit these opportunities making significant profits. These players are often smaller companies specialising in the new strategies. The availability of profit gradually attracts more players who adapt versions of the strategies. To obtain/maintain the market share, players invest into generating advantage (technology, market research, etc). Typically, bigger players – who might have been prudent at the appearance of the strategy – enter the game. The profit opportunities start to diminish due to the increased number of competitors, the advantage of the smaller players is lost to the bigger players. Often, only a few big diversified companies remain in the game making a portion of the profit that was available earlier. The new opportunities are often due to some market inefficiencies, the spread of the strategies generates efficiency, and the almost complete extinction is induced by the increased efficiency maintained by the few remaining participants. Very often, the strategies mutate and adapt to the modified circumstances, or extinct if the favourable circumstances cease to exist. Examples of co-existence and co-evolution are also common. E.g. the liquidity taken by certain classes is provided by the followers of certain other strategies. The circumstances favourable to both classes gradually develop – often reinforced by the spread of the strategies – transforming the strategies into part of the common practice. Another example is “fishing” and “gaming” simultaneously in dark pools and lit markets, strategies that have become common since the appearance of dark pools. This review has been commissioned as part of the UK Government’s Foresight Project, The Future of Computer Trading in Financial Markets. The views expressed do not represent the policy of any Government or organisation.

Posted on: 3 September 2012 | 10:40 am

Research Library: UK Gov Foresight Project - Economic impact assessments on MiFID II policy measures related to computer trading in financial markets

Oliver Linton, Cambridge University Maureen O’Hara, Cornell University J.P. Zigrand, London School of Economics Published: August 2012 Computer trading has changed markets in fundamental ways, not the least of which is the speed at which trading now occurs. There are a variety of policies proposed to address this new world of trading with the goals of improving market performance and reducing the risks of market failure. These policies include notification of algorithms, circuit breakers, minimum tick size requirements, market maker obligations, minimum resting times and minimum order-to-execution ratios. The Foresight Project has commissioned a variety of studies to evaluate these policies, with a particular focus on their economic costs and benefits, implementation issues and empirical evidence on effectiveness. This working paper summarises those findings.(pdf) The key findings relating to the different policies are as follows, starting with those which were most strongly supported by the evidence: Overall, there is general support from the evidence for the use of circuit breakers, particularly for those designed to limit periodic illiquidity induced by temporary imbalances in limit order books. Different markets may find different circuit breaker policies optimal, but in times of overall market stress there is a need for coordination of circuit breakers across markets. There is also support for a coherent tick size policy across similar markets. Given the diversity of trading markets in Europe, a uniform policy is unlikely to be optimal, but a coordinated policy across competing venues may limit excessive competition and incentivise limit order provision. The evidence offers less support for policies imposing market maker obligations. For less actively traded stocks, designated market makers have proven beneficial, albeit often expensive. For other securities, however, market maker obligations run into complications arising from the nature of high frequency market making across markets, which differs from traditional market making within markets. Many high frequency strategies post bids and offers across correlated contracts. A requirement to post a continuous bid-offer spread is not consistent with this strategy and, if binding, could force high frequency traders out of the business of liquidity provision. Voluntary programmes whereby liquidity supply is incentivised by the exchanges and/or the issuers can improve market quality. Similarly, minimum resting times, while conceptually attractive, can impinge upon hedging strategies which operate by placing orders across markets and expose liquidity providers to increased ‘pick-off risk’ if they are unable to cancel stale orders. The effectiveness of proposed measures to require notification of algorithms or minimum order-to-execution ratios are also not supported by the evidence. The proposed notification policy is too vague, and its implementation, even if feasible, would require excessive costs for both firms and regulators. It is also doubtful that it would substantially reduce the risk of market instability due to errant algorithmic behaviour, although it may help regulators understand the way the trading strategy should work. An order-to-execution ratio is a blunt policy instrument to reduce excessive message traffic and cancellation rates. While it could potentially reduce undesirable manipulative trading strategies, beneficial strategies may also be curtailed. There is insufficient evidence to ascertain these effects, and so caution is warranted. Explicit fees charged by exchanges on excessive messaging and greater regulatory surveillance geared to detect manipulative trading practices may be more effective approaches to deal with these problems. Introduction by Professor Sir John Beddington This working paper presents important interim findings of the international Foresight project: The Future of Computer Trading in Financial Markets. In particular, it considers the costs, risks and benefits of six possible regulatory measures which are currently being considered within the European Union’s Markets in Financial Instruments Directive 2 (MiFID II). It precedes the final project report which will be published later in 2012, and which will consider a broader set of issues surrounding computer-based trading (CBT) over the next ten years. Algorithmic trading (AT) and high frequency trading (HFT) have grown rapidly in use in recent years. As such, they have also fuelled increases in complexity as well as new system dynamics, making markets ever harder to understand and to regulate. In particular, there is continuing controversy concerning the extent to which they improve or degrade the functioning of financial markets, and also influence market volatility and the risk of instabilities. For example, such trading has been implicated by some as a contributory factor in the May 6th 2010 Flash Crash. For such reasons, computer-based trading is now attracting the close attention of policy makers and regulators worldwide. However, the debate on high frequency and algorithmic trading has been hampered by the availability of evidence and analysis. This is of significant concern since regulation that is not soundly based risks being ineffective, or worse, could lead to unhelpful and unforeseen consequences. By drawing upon the available science and evidence from across the world, the Foresight project seeks to provide independent advice to policy makers. More specifically, this working paper has involved some 35 leading academics from nine countries and presents analysis that has been subject to independent peer review. As such, it does not represent the views of the UK or any other government. In view of the rapid pace of the MiFID II regulatory process, I have pleasure in making this paper freely available now, in advance of the full Foresight report. Professor Sir John Beddington CMG, FRS Chief Scientific Adviser to HM Government and Head of the Government Office for Science Get the Latest Working Paper here. Get the Previous Interim Report here. Check out the Supplementary Materials put together for the Previous Report here.

Posted on: 3 September 2012 | 10:10 am

Wired Magazine asks how Wall Street Got Addicted to High-Frequency Trading

The high-frequency trading debate has been polarising opinion for years now, and with little impact on the march of the technologies which are enabling it. Here at MoneyScience, we try not to take a view on the ethics or cultural impact of HFT - we like the evolution of technology as a rule, but dislike speculation when it comes at the expense of markets which would otherwise provide a socially meaningful role. Progress is generally good, we feel - but to paraphrase Spiderman, 'with great power comes great responsibility' - and financial markets as a rule haven't done a great job in recent history of demonstrating they can handle it. We may have the technology to trade ultra-fast, but whether we have the scientific or economic infrastructure to understand and control it is the core of the debate.read more...

Posted on: 7 August 2012 | 1:21 am

Link Library: Tobias Preis's GPGPU Research Page

Dr Tobia Preis has compiled a fantastic list of selected publications in GPGPU Computing: A recent trend in computer science and related fields is General-Purpose computation on Graphics Processing Units (GPGPU), which can yield impressive performance, i.e. the required processing times can be reduced to a great extent. The Compute Unified Device Architecture (CUDA) is a programming approach for performing scientific calculations on a Graphics Processing Unit (GPU) as a data-parallel computing device. The programming interface allows to implement algorithms using extensions to standard C language. With continuously increased number of cores in combination with a high memory bandwidth, a recent GPU offers incredible resources for general purpose computing.

Posted on: 3 August 2012 | 10:51 am

Research Library: Noncomputability, unpredictability, undecidability, and unsolvability in economic and finance theories (pdf)

Ying-Fang Kao, V. Ragupathy, K. Vela Velupillai, Stefano Zambelli Abstract We outline, briefly, the role that issues of the nexus between noncomputability and unpredictability, on the one hand, and between undecidability and unsolvability, on the other hand, have played in Computable Economics (CE). The mathematical underpinnings of CE are provided by (classical) recursion theory, varieties of computable and constructive analysis and aspects of combinatorial optimization. The inspiration for this outline was provided by Professor Graca's thought-provoking recent article.

Posted on: 3 August 2012 | 1:10 am

Algorithmic Trading Glitch Costs Knight Capital $440 Million

Via Slashdot:read more...

Posted on: 2 August 2012 | 2:02 pm

FIA European Principal Traders Association Market Integrity Framework: Best Practices to Preserve Market Integrity

As part of ongoing efforts to safeguard market integrity, FIA European Principal Traders Association today published a set of best practices to help principal trading firms prevent market manipulation and reduce risks. read more...

Posted on: 27 July 2012 | 6:32 am

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