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Algorithmic Trading and Market Microstructure
Man vs. Robot on the bleeding edge of computational finance
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Quant-Day: Technical(and not technical) strategy testing

Quant-Day: Technical(and not technical) strategy testing | Algorithmic Trading and Market Microstructure | Scoop.it
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Trading Community Looks To Big Data To Uncover Patterns of Abuse

Heralding the next big thing in financial market enforcement, regulators, exchanges and trading firms are turning their attention from specific alerts of insider trading to identifying larger patterns of abuse.

Via Hayden Richards
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Latency Arbitrage, Market Fragmentation, and Efficiency: A Two-Market Model

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Thomson Reuters Gives Elite Traders Early Advantage - CNBC.com

Thomson Reuters Gives Elite Traders Early Advantage - CNBC.com | Algorithmic Trading and Market Microstructure | Scoop.it
Thomson Reuters Gives Elite Traders Early Advantage
CNBC.com
More than 100,000 shares traded hands in the first ten millisecond of the burst of activity, reports the analysis firm Nanex, LLC.
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The distribution of financial returns made simple | Portfolio Probe | Generate random portfolios. Fund management software by Burns Statistics

The distribution of financial returns made simple | Portfolio Probe | Generate random portfolios. Fund management software by Burns Statistics | Algorithmic Trading and Market Microstructure | Scoop.it
Why returns have a stable distribution As A tale of two returns points out, the log return of a long period of time is the sum of the log returns of the
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More evidence that Thomson Reuters data may be leaking out earlier than it's ... - Quartz

More evidence that Thomson Reuters data may be leaking out earlier than it's ... - Quartz | Algorithmic Trading and Market Microstructure | Scoop.it
More evidence that Thomson Reuters data may be leaking out earlier than it's ...
Quartz
The data leak led to $28 million in trades, according to trading consultancy Nanex, LLC, partly because the data came in particularly weak.
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Tom @ HStarr's curator insight, June 11, 2013 3:53 AM

Given the world of HFT Trading that we now live in, a full two seconds difference is huge for data to be released and is something that could Thomson Reuters in some trouble. It'll be interesting to see how it will play out. 

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Unraveling Monday's Early Data Release To Traders - CNBC.com

Unraveling Monday's Early Data Release To Traders - CNBC.com | Algorithmic Trading and Market Microstructure | Scoop.it
Unraveling Monday's Early Data Release To Traders CNBC.com But analysts at Nanex LLC, a Chicago-area analysis firm spotted a sharp downward market reaction just before 10 a.m., setting up a mystery: How did some traders appear to know the data...
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Reuters Admits It Accidentally Leaked Key Market Data To High Frequency ... - Business Insider Australia

Reuters Admits It Accidentally Leaked Key Market Data To High Frequency ... - Business Insider Australia | Algorithmic Trading and Market Microstructure | Scoop.it
Reuters Admits It Accidentally Leaked Key Market Data To High Frequency ...
M. Edward (Ed) Borasky's insight:

"Accidentally"?? Bullshit!

 

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Video Shows How Insane Trading Goes Right Before Important Data Drops - Business Insider

Video Shows How Insane Trading Goes Right Before Important Data Drops - Business Insider | Algorithmic Trading and Market Microstructure | Scoop.it
Video Shows How Insane Trading Goes Right Before Important Data Drops Business Insider Eric Hunsader the CEO of market research firm Nanex, told Business Insider that the strange activity was most likely a case of 'banging the beehive.' That's the...
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Tom @ HStarr's curator insight, May 31, 2013 3:25 AM

This is very similar to a video from around a month ago but again it provides a fascinating insight into how HFT traders can affect the market. Well worth a watch for anyone interested in the markets. 

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There’s no such thing as an objective filter: Why designing algorithms that tell us the news is hard

There’s no such thing as an objective filter: Why designing algorithms that tell us the news is hard | Algorithmic Trading and Market Microstructure | Scoop.it
Technologists and humanists take different approaches — and speak different languages.
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Nanex ~ 10-May-2013 ~ Tighter Spreads? Not at Market Open

Nanex ~ 10-May-2013 ~ Tighter Spreads? Not at Market Open | Algorithmic Trading and Market Microstructure | Scoop.it
RT @nanexllc: If #HFT lowers spreads, why is $MSFT spread at the open 2 - 3 x wider than before? http://t.co/q7NdEtz8rd
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Optimal limit order execution in a simple model for market microstructure dynamics

Optimal limit order execution in a simple model for market microstructure dynamics | Algorithmic Trading and Market Microstructure | Scoop.it
Market participants who have the task of acquiring a certain position in a listed security at a predetermined price on behalf of a third party with no time urgency,...
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Conference Board fears diversion of economic data - Fresno Bee

Conference Board fears diversion of economic data - Fresno Bee | Algorithmic Trading and Market Microstructure | Scoop.it
Conference Board fears diversion of economic data Fresno Bee WASHINGTON — The Conference Board will no longer provide its economic reports in advance to news organizations because it suspects the data is being diverted early to computer-driven...
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Oracle Java virtual machine putting the brakes on high frequency trading, says ... - PC Advisor

Oracle Java virtual machine putting the brakes on high frequency trading, says ... - PC Advisor | Algorithmic Trading and Market Microstructure | Scoop.it
Oracle Java virtual machine putting the brakes on high frequency trading, says ...
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Adam Green's comment, June 19, 2013 6:16 PM
I feel like a dinosaur standing around with a bunch of other dinosaurs talking about the strangely cold weather ...
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Quantile Autoregression in R

Quantile Autoregression in R | Algorithmic Trading and Market Microstructure | Scoop.it
In the past, I wrote about robust regression. This is an important tool which handles outliers in the data. Roger Koenker is a substantial contributor in this area.
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Introduction to stable distributions for finance | Portfolio Probe | Generate random portfolios. Fund management software by Burns Statistics

Introduction to stable distributions for finance | Portfolio Probe | Generate random portfolios. Fund management software by Burns Statistics | Algorithmic Trading and Market Microstructure | Scoop.it
A few basics about the stable distribution. Previously The distribution of financial returns made simple satirized ideas about the statistical distribution
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A tale of two returns | Portfolio Probe | Generate random portfolios. Fund management software by Burns Statistics

A tale of two returns | Portfolio Probe | Generate random portfolios. Fund management software by Burns Statistics | Algorithmic Trading and Market Microstructure | Scoop.it
It was the best of times, it was the worst of times. As you may have guessed, this is a mashup of a novel by Charles Dickens and an explanation of financial
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Amazon Does 100,000 Quotes per Second

The stock of Amazon hit a rate exceeding 100,000 quotes/sec (107 in a millisecond).
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The 15-millisecond head start that led to $28 million in trades

The 15-millisecond head start that led to $28 million in trades | Algorithmic Trading and Market Microstructure | Scoop.it
Thomson Reuters is taking the heat for a glitch that on Monday (June 3) caused the US's ISM manufacturing data to go out to high-frequency traders 15 milliseconds before it was supposed to.
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Amazon.com: Trading Systems and Methods (Wiley Trading) eBook: Perry J. Kaufman: Kindle Store

Trading Systems and Methods (Wiley Trading) - Kindle edition by Perry J. Kaufman. Download it once and read it on your Kindle device, PC, phones or tablets.
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The Future of Financial Engineering by Charles Tapiero :: SSRN

The Future of Financial Engineering by Charles Tapiero :: SSRN | Algorithmic Trading and Market Microstructure | Scoop.it
Convergence of financial theory and practice heralded by the seminal and fundamental economic research by Arrow and Debreu in the early 1950’s has led in the ha

Via Hayden Richards
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Hayden Richards's curator insight, May 18, 2013 7:10 AM

By Charles S Tapiero.


Abstract:      
Convergence of financial theory and practice heralded by the seminal and fundamental economic research by Arrow and Debreu in the early 1950’s has led in the hands of financial engineers to an extraordinary financial innovation in the 70’s and ever since. The theoretical ability to price future assets has led to an explosive growth of financial trading, liquidity and to the growth of finance and its citadels. Options and credit derivative markets, securitization of non or partially liquid assets have provided extraordinary opportunities to “unearth” frozen assets for trade and profit. 

The 2007-2009 financial crisis has evoked a greater awareness that traditional financial dogma is based on assumptions that have become increasingly difficult to justify. Globalization, the growth of "Too Big To Fail" (TBTF) firms, insiders trading, information and power asymmetries and the growth of regulation have, among other factors, conspired to render the assumption of complete markets to be unsustainable. Deviant behaviors in financial markets, non-transparency of transactions, complexity and dependence on a global scale have created a fragile and contagious global economy, where systemic risks are no longer an exception but a permanent threat. 

By the same token, the explosive growth of information and data fueled by the internet and social media as well as an IT has created far greater dependence of financial systems and institutions on Information Technology (IT) emphasizing information as assets they seek to use for both financial management and competitive advantage. Technology, engineering and financial trends and developments have combined to yield an extraordinary growth of complexity, regulation and globalization, providing new opportunities and risks and undermine the traditional model based approaches to finance.

The purposes of this paper are to outline a number of factors, economic or otherwise that undermine the finance’s fundamental theories, their practice, regulation and their implications to the future of finance. In particular, we emphasize a strategic and multi-polar finance, beset by complexity, chaos and countervailing forces leading a multi-agent finance, computational and financial data-analytics driven rather than simple risk models of uncertainty.

A number of pricing models based on a strategic finance and a micro-matching of economic and financial states are also summarized and their practical implications drawn. In addition, topics such as Big Data finance and multi-agent financial modeling are outlined to provide elements for future theoretical and practical developments. This paper is a work in progress and therefore its intent is to attract greater attention to some elements (however selective and partial) that would contribute to potential transformations of a financial engineering future.


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The Algorithmic Trading Freak Show

The Algorithmic Trading Freak Show | Algorithmic Trading and Market Microstructure | Scoop.it
Their exhibition in Trafó Gallery shows through three installations the curiosities of algorithm based trading and they give an overview on the history of the automatisation of the stock exchange, from the now out of date technologies to mechanisms...
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