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Risk & Trading Conference RiskMathics

I'll present my new book, Advances in Financial Machine Learning.



Advances in Machine Learning Morningstar

The impending machine learning revolution in Finance.


QuantMinds International

Advances in Machine Learning QuantMinds International

Round table on AI and ML applications to scientific research and businesses.


FinHub ML Conference

The 7 Reasons Most Machine-Learning Funds Fail University of Toronto

Some of the most common pitfalls when applying ML techniques in Finance.



Advances in Financial Machine Learning Quantopian

A review of recent breakthroughs in Financial ML.


Goldman Sachs

Stagnation in Academic Finance: Causes and Solutions Goldman Sachs

A presentation on the reasons why Finance has not made substantial scientific progress over the past decades.


Cornell University

Portfolio Management in the Machine Learning Age Johnson School

Class at the PhD program.


Society for Quantitative Analysis

Financial Machine Learning SQA

The state of machine learning research and production in Finance.



Machine Learning & AI in Quant Finance QuantTech

ML and the introduction of industrial scale research to asset management.


Evercore ISI

Financial Machine Learning Evercore ISI

A review of how ML is changing financial research.



Machine Learning in Finance BAML

In this panel we will discuss how ML is changing Finance, and what will be the greatest disruptions in the near future.


Cornell University

The 7 Reasons Most Machine-Learning Funds Fail CornellTech

The rate of failure in quantitative finance is high, and particularly so in financial ML. However, that is a rare outcome, for reasons that will become apparent in this seminar.



Machine Learning Portfolio Construction Quantopian

I will discuss the issues involved in the current generational transition, from old quant approaches to ML.


Columbia University

OOS Portfolio Construction Mathematics in Finance

A key challenge in building an optimal portfolio is whether it will underperform out-of-sample. We will discuss procedures to improve out-of-sample performance.


Institutional Investor

CIO Roundtable

U.S. Institute

Pitfalls and common mistakes made by investment firms entering the ML field.


Aronson, Z.

A Solution to the Research Crisis Stevens Institute of Technology

A Heath Lecture at Stevens, on the research crisis and one possible solution.


CFA Institute

Equity Research & Valuation 2016 CFA Institute Conference

Why most discoveries in financial research are wrong, and what can we do about it.


Society of Quantitative Analysts

Advances in Portfolio Construction SQA

Recent breakthroughs in a post-Markowitz finance.


Cubist Systematic Strategies

Hierarchical Risk Parity Cubist Systematic Strategies

An example of ML-based portfolio construction.


Kolm, P.

Mathematics and Economics: A Reality Check New York University

A presentation at Courant, on modern mathematics applied to Finance.



The Trading Show 2016 Terrapin

My presentation will describe Quantum Computing applications to Finance.



Quantum Computing meeting Los Alamos National Laboratory

A gathering of players in the Quantum Computing space, including: NASA, Google, LANL, IBM and others.


Meucci, A. ARPM Bootcamp NYU A presentation on Machine Learning applications with Python.


Evercore ISI Annual Quant Conference Evercore ISI Mathematical techniques to deliver out-of-sample performance.


Risk Magazine Quant Summit USA 2016 Risk Magazine I will discuss Machine Learning applications to portfolio mangement.



Exponential Finance 2016 Singularity U.

In New York, I will present our results on quantum computing applications to Finance. Past speakers include Blythe Masters, Ray Kurzweil, Daniel Nadler and Bob Pisani.



Quantum Computing in Finance Global Derivatives Trading & Risk Management 2016

In Budapest, I will discuss applications of quantum computing algorithms to financial problems. Other speakers include Damiano Brigo, Peter Carr, Rama Cont, Emanuel Derman, Darrell Duffie, Bruno Dupire, Jim Gatheral, Paul Glasserman, John Hull, Alex Lipton, Dilip Madan, Fabio Mercurio, and Riccardo Rebonato.



Building Portfolios that Outperform Out-Of-Sample

Bloomberg HQ

A machine learning application to portfolio construction.



Quant Conference 2016


Other speakers include Emanuel Derman, Michael Kearns and Wes McKinney.


Columbia University & Bloomberg

Hierarchical Risk Parity: A machine learning application

Columbia University

I will discuss a method to build diversified portfolios that outperform quadratic optimizers out-of-sample.


Kolm, P.

Quant Seminar at Courant Institute of Mathematical Sciences

New York University

This talk will discuss how to build portfolios that outperform out-of-sample.


Institutional Investor

CIO Roundtable

U.S. Institute

My talk will discuss the current role of Big Data, Machine Learning and HPC technologies in investment management.


Princeton University

Quantitative Asset Management

Princeton University

I will talk about Financial Big Data & Machine Learning at this graduate course.



Quantum Computing in Finance

Bloomberg HQ

A talk on quantum computing applications to Finance.


Cornell University

Optimal Execution Cornell University Ph.D. seminar on execution strategies.



Financial Quantum Computing

The Trading Show 2015

I will discuss advances in quantum computing applications to Finance.


Incisive Media

Quant Congress USA 2015

Risk Magazine

I will give the plenary address.

05/18/2015 ICBI Correcting for Backtest Overfitting & Selection Bias Global Derivatives Trading & Risk Management 2015 In Amsterdam, I will discuss recent advances on Strategy Selection. Other speakers include: Riccardo Rebonato (PIMCO), Attilio Meucci (KKR), Buzz Gregory (Goldman Sachs), John Hull (U. Toronto), Darrell Duffie (Stanford), Emanuel Derman (Columbia), Paul Glasserman (Columbia), Jim Gatheral (Baruch), Rama Cont (Imperial College).

Battle of the Quants

Quantitative Meta-Strategies

Battle of the Quants, NYC

I will discuss advances in quantitative approaches to manage investment strategies.

05/12/2015 Nomura Global Quantitative Investment Strategies Conference Nomura I'll be discussing recent advances in Quantitative Meta-Strategies. Other speakers include: Andrew Ang (U. Columbia), Mark Carhart (Kepos), Ross Garon (Cubist Systematic Strategies), Brett Hammond (MSCI), Scott Williamson (BlackRock), etc.
05/01/2015 Geczy, C. Lucky Factors Jacobs Levy Center Forum Paper discussant with Prof. Campbell Harvey (Duke University). Other participants include Rob Stambaugh (Wharton), Bryan Kelly (Chicago), Cliff Asness (AQR), Bob Litterman (Kepos), Ron Kahn (BlackRock), Mark Carhart (Kepos), etc.


Kolm, Petter

Mathematics in Finance

Courant Institute of Mathematical Sciences, NYU

I will discuss selection bias, or why most published investment strategies are likely to be wrong.


Berkeley Lab

Quant Conference at U.C. Berkeley

U.C. Berkeley

I will give a talk on recent advances in financial Big Data, Machine Learning and High-Performance Computing.


Industrial Engineering & Operations Research

Why Most Published Investment Strategies Are Likely To Be False Positives

U.C. Berkeley

I will discuss how Selection Bias may have compromised many Financial studies published in the academic literature, and what can be done to overcome this crisis.


Cornell Financial Engineering Manhattan

What to look for in a backtest


The majority of backtests marketed to investors or published in academic journals do not report the number of trials carried out in order to achieved a particular result. We will discuss the implications for Out-Of-Sample performance.


International Association for Quantitative Finance

The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-Normality

New York University

I will present our new research on how to deflate the Sharpe ratio for various inflationary effects, including backtest overfitting. It is based on this new paper, forthcoming in the Journal of Portfolio Management.


Incisive Media

Quant Congress USA 2014

Risk Magazine

I will give the plenary address.



Risk Management & Trading Conference


I will speak about Smart Execution Algorithms. Other speakers include John Hull, Emanuel Derman, Marco Avellaneda, Paul Wilmott and Nick Leeson.


Carr, P.

Morgan Stanley Quant seminar

Morgan Stanley

I will discuss recent papers.


International Association for Quantitative Finance

2014 Annual Conference


I will take part in the panel on High Frequency Trading, with Bob Litzenberger and Larry Tabb.


Bloomberg University

The effects of Backtest-Overfitting on Out-Of-Sample performance

Bloomberg Quant Seminar

At Bloomberg University, NYC, I will discuss some of the reasons why systematic funds fail.


Columbia University

Optimal Execution Horizon

Mathematics of Finance Program

At Columbia, I'll discuss the Optimal Execution Horizon (OEH) model.


Princeton University

The Probability of Backtest Overfitting

Princeton Quant Trading Conference

At Princeton, I'll discuss the Probability of Backtest Overfitting (PBO).


Risk Magazine / Incisive Media

Algorithmic Trading, Execution and Market Making

Risk's Algorithmic Conference

In London, I will discuss techniques to conceal trading intentions and prevent adverse selection.


Battle of the Quants

Investing in Backtesting: How to Spot Overfitting

Battle of the Quants, NYC

David H. Bailey and I will discuss the consequences that Backtest Overfitting has on Out-Of-Sample performance, in absence and in presence of memory effects. It is based on our paper, forthcoming in the Notices of the American Mathematical Society.


International Association for Quantitative Finance (IAQF) / Thalesians

Pseudo-Mathematics and Financial Charlatanism

New York University

In this talk, I will discuss some of the reasons why quantitative investments often do not perform as advertised, and ways experienced investors are misled by charlatans. It is based on a recent paper co-authored with Jon M. Borwein, David H. Bailey and Jim Zhu.


High Frequency Trading World

Quant Invest 2013


In NYC, Marcos will explain how to estimate the time that a strategy or trader may remain under water, and the implications for hedge fund managers.


High Frequency Trading World

Interview by Total Trading


A recent interview.



Portfolio Optimisation & Quantitative Investment Summit


The event will take place in Chicago. I will discuss robust portfolio optimization with higher moments. Other speakers include John Jull, Bruno Dupire, Emanuel Derman, Paul Glasserman, Dilip Madan, Lisa Goldberg, George Constantinides, Mike Giles, etc.



International Algorithmic and High Frequency Trading Summit


I will speak about Smart Execution Algorithms. Other speakers include John Hull, Emanuel Derman, Marco Avellaneda, Nassim Taleb and Nick Leeson.


Risk Magazine

Risk USA 2013

Incisive Media

At the 20th edition of the Risk USA Conference, I will present new developments in drawdown risk management.


Risk Magazine

Risk USA 2013

Incisive Media

I'll be chairing the conference's stream on Risk Management. Speakers include Vineer Bhansali (Managing Director, PIMCO), Jayesh Bhansali (Managing Director, Head of Global Derivatives and Quantitative Portfolio Management, TIAA-CREF), Fred Gjerstad (Senior Vice President & Head of Investment Risk, STATE STREET), Benjamin Bowler (Global Head of Equity Derivatives Research, BANK OF AMERICA MERRILL LYNCH) and Maureen O'Hara (Professor of Finance, CORNELL UNIVERSITY and Chairman of the Board, ITG).


JPMorgan Equity Trading

How long does it take to recover from a drawdown?


We will explain how to model the probability that a hedge fund or portfolio manager recovers from a drawdown, and how long it will take.


Cont, R.

Backtesting the performance of trading strategies: pitfalls and solutions

Imperial College London

We prove that high performance is easily achievable after backtesting a relatively small number of alternative strategy configurations, a practice we denote “backtest overfitting”. Because financial analysts rarely report the number of configurations tried for a given backtest, investors cannot evaluate the degree of overfitting in most investment proposals.



Execution of large blocks


In London, I will discuss new developments in the High-Frequency Trading space.


Kolm, P.

Mathematics in Finance

Courant Institute of Mathematical Sciences

At the Courant Institute (NYU), Marcos will discuss his research on portfolio optimization with higher moments.


Stoikov, S.

The Triple Penance Rule

Cornell University

At Cornell Financial Engineering Manhattan (CFEM), I will discuss the "Triple Penance Rule" and how it affects hedge funds' hiring and firing practices of portfolio managers.


Quantitative Work Alliance

How long does it take to recover from a Drawdown?


In NYC, I will discuss the "Triple Penance Rule", and a new procedure to set up the stop-out limits of investment strategies.


Risk Magazine

Quant Congress USA 2013

Incisive Media

In NYC, Marcos will present a paper recently published by the Journal of Investment Strategies. The title of the presentation is "Managing Risks in a Risk-On/Risk-Off Environment". Other speakers include Emanuel Derman, Riccardo Rebonato, Dilip Madan, Peter Carr, Damiano Brigo, etc.


SAC Capital

Scientific Horizon's Seminar

SAC Capital

I will discuss advances in quantitative performance evaluation and capital allocation.


High Frequency Trading World

Quant Invest 2013


In Chicago, Marcos will give a presentation with the title "The Sharp Razor: Deflating the Sharpe ratio by asking for a Minimum Track Record Length". Other speakers include C.F.T.C. Commissioner Bart Chilton, Singapore Exchange CIO Bob Caisley, David Leinweber, etc.



High Frequency Trading Workshop


I will discuss recent advances in Big Data, Machine Learning and High Frequency Trading. Other speakers include John C. Hull, Marco Avellaneda and World Chess Champion Garry Kasparov.


Quantitative Work Alliance

The Sharpe Ratio Efficient Frontier


In NYC, Marcos will present the paper of the same title, which appeared last Winter in the Journal of Risk.


Financial and Risk Engineering Department

Big Data Finance

New York University

The workshop “Big Data Finance” will assess the importance of Big Data in Finance today and in the near future, and will consider the impact of big data on financial engineering, financial analysis, management and regulation. Other speakers include CFTC Commissioner Scott O'Malia, Robert Almgren and Petter Kolm.


Kolm, P.

Mathematics in Finance

Courant Institute of Mathematical Sciences

At the Courant Institute (NYU), Marcos will discuss his research on "Drawdown-based Stop-Outs and the 'Triple Penance' Rule".


International Association of Financial Engineers (IAFE) / Thalesians

Concealing the trading footprint by determining the Optimal Execution Horizon

New York University

A presentation on our recent paper "Optimal Execution Horizon" (with Maureen O'Hara and David Easley), forthcoming in Mathematical Finance.


Standard & Poor's Capital IQ

Low-Latency and the Dynamics of Real-Time Decision-Making

Standard & Poor's

A presentation at the annual S&P investors' event, in NYC.



The CLA Python class for Portfolio Optimization


At NYC's Cornell Club, Marcos will present his recent paper "An Open-Source Implementation of the Critical Line Algorithm for Portfolio Optimization".


Global SIP 2013

Symposium on Signal and Information Processing in Finance and Economics


Technical Committee for the IEEE GlobalSIP-2013 Symposium on Signal and Information Processing in Finance and Economics.


Trader Forum

The Volume Clock: Insights into the High Frequency Paradigm

Institutional Investors

In NYC, I will speak at the Trader Forum organized by Institutional Investor's Conferences Division. The topic of the presentation will be the paper of the same title, which appeared last Fall in the Journal of Portfolio Management.


Deutsche Bank Quantitative Strategies

2012 Global Quantitative Strategy Conference

Deutsche Bank

Marcos will present the paper "Markowitz meets Darwin: Portfolio Oversight and Evolutionary Divergence".



International Algorithmic and High Frequency Trading Summit


I will speak about Smart Execution Algorithms. Other speakers include John Hull, Marco Avellaneda and David Leinweber.


Risk Magazine

Risk USA 2012

Incisive Media

Marcos will coordinate the workshop: "Advances in execution and liquidity discovery".


Center for Financial Engineering

19th Annual Workshop on Financial Engineering: Quantitative Asset Allocation

Columbia University

My talk will address the need for deflating Sharpe ratios by asking for the proper track record length.


JPMorgan Equity Trading

Equity Quantitative Conference 2012


Marcos will talk about the choices available to low frequency traders in high frequency markets, in London.


Mathematics Department

Lecture at Rutgers' Mathematical Finance Program

Rutgers University

I will discuss Optimal Execution Strategies.



Event at the "Advanced Risk and Portfolio Management" program

New York University

Attilio Meucci invited Maureen O'Hara and me to give a talk and participate at SYMMYS' Annual Charity event.


Risk Magazine

Quant Congress USA 2012

Incisive Media

I will coordinate the High Frequency stream at the Quant Congress USA, and give the evening plenary address.



Low Frequency Traders in High Frequency Markets: A Survival Guide

International Association of Financial Engineers

Marcos will speak at the 20th Annual Conference. Robert Engle will receive the 2011 IAFE/SunGard Financial Engineer of the Year Award.



Eurex Quant Seminars


In NYC, I'll discuss why the May 6 2010 Flash Crash was a liquidty crisis, and what exchanges can do to minimize the impact of similar episodes in the future.


Risk Magazine

Quant Congress USA 2011

Incisive Media

Marcos will discuss the measuring of flow toxicity in the high frequency domain.









Guggenheim Partners

Statement From Guggenheim Partners Regarding Quantitative Investment Strategies Unit


"Guggenheim Partners today agreed to transfer its Quantitative Investment Strategies (“QIS”) unit to Dr. Marcos Lopez de Prado, who built that business and its technology as a Senior Managing Director of Guggenheim."


Wigglesworth, Robin

Renaissance, DE Shaw look to quantum computing for edge

Financial Times

Marcos Lopez de Prado, a quant researcher and fellow at the Berkeley Lab, says: “You need to decode markets and find the invisible patterns. The people that do that best have the best models and the most powerful computers. It gives you an edge. It's amazing what we could do with quantum computers."


Segal, J.

How Universities Are Failing Finance Students

Institutional Investor

"The presence of financial academia is fading, something that was unthinkable 10 years ago," writes López de Prado. "The edge is not yet another reincarnation of the capital asset pricing model [...] FinTech, big data, machine learning, and even quantum computing will render formal finance education even more irrelevant, he believes."


Asmundsson, J.

Quantum Computing Might Be Here Sooner Than You Think

Bloomberg Markets

Marcos López de Prado, a senior managing director at Guggenheim Partners LLC who’s also a scientific adviser at 1QBit and a research fellow at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory, says it’s all about context. “The reason quantum computing is so exciting is its perfect marriage with machine learning,” he says. “I would go as far as to say that currently this is the main application for quantum computing.”


Hope, B.

The Quants Run Wall Street Now

Wall Street Journal

"Guggenheim Partners LLC built what it calls a “supercomputing cluster” for $1 million at the Lawrence Berkeley National Laboratory in California to help crunch numbers for Guggenheim’s quant investment funds, says Marcos Lopez de Prado, a Guggenheim senior managing director. Electricity for the computers costs another $1 million a year."


Melin, M.

JPMorgan: Hierarchical Risk Parity Portfolio Building Method Beats Markowitz


"Harry Markowitz’s modern portfolio theory has been a staple concept among many noncorrelated portfolio builders [...] JPMorgan’s Quantitative and Derivatives Strategy team thinks there is a better method to construct portfolios [...] In the studies, the HRP portfolio method outperformed based on several noncorrelated standards."


Bauer, M.

Quantum computing is going commercial with the potential to disrupt everything


Comments on IBM's announcement that they will produce a commercial quantum computing, with services delivered via cloud.


Steenbarger, B.

Reason And Rationality: The Psychological Keys To Investing Success


"A remarkable post recently appeared on Google Plus. A quiet researcher in mathematical finance who manages a large portfolio decided to speak out."



D-Wave Systems Launches Quantum for Quants Online Community

Inside HPC

Launch of QuantumForQuants.org.


Dawes, T.

D-Wave launches Quantum for Quants at Budapest derivatives conference

CanTech Letter

Launch of QuantumForQuants.org.


Thomas, Z.

Quantum computing: Game changer or security threat?


A BBC discussion on the future of quantum computing.


Mack, B.

What can Quantum Computing achieve for Quants?

Global Derivatives

An interview on financial applications of quantum computing.


Cater, S.

Machine learning with Marcos Lopez de Prado

Global Derivatives 2016

An interview on Machine Learning applications to investing.


Zweig, J.

Chasing Hot Returns in ‘SmartBeta’ Funds Can Be a Dumb Idea

Wall Street Journal

Because computers and access to data are proliferating, the odds that strategies are based on “statistical flukes without theoretical support” is rising, warns Marcos López de Prado, a senior managing director at Guggenheim Partners, an investment firm in New York that manages about $240 billion. “For now, our best shot is to educate the public,” he says, “because not everyone in the industry is going to come clean.”


Clark, J. and S. Kishan

Quantum Computers Entice Wall Street Vowing Higher Returns

Bloomberg News

Bloomberg features a recent paper with Peter Carr (Courant Institute), Kesheng Wu (Berkeley Lab) and scientisits from 1QBit.

06/01/2015 Orr, L. The Backtesting Crisis Chief Investment Officer "Managers who cherry-pick for optimal results aren’t even the worst abusers, argues Guggenheim’s top quant."
05/27/2015 Automated Trader Machine Learning is the new C++ Automated Trader Article on Global Derivatives 2015's round table about Big Data.
04/26/2015 Bailey, D. and J. Borwein Lessons from the “Flash Crash” regulatory fiasco The Huffington Post "[...] Regulators have admitted that the Flash Crash was due to order imbalance, as Easley et al. had explained five years earlier."
04/06/2015 Hope, B. How Computers Trawl a Sea of Data for Stock Picks Wall Street Journal Professors from University of California, Davis, and several other institutions warned in an April 2014 research paper of a trend of “overfitting” in math-based trading by hedge funds and other money managers, in which random correlations are interpreted wrongly as strong relationships. They concluded that “pseudo-mathematics” and “financial charlatanism” were running rampant on Wall Street. Such bad math, they wrote, “is a large part of the reason why so many algorithmic and systematic hedge funds do not live up to the elevated expectations generated by their managers.”
03/09/2015 Scott, C.

Journal of Portfolio Management Announces Advisory Board Member

Journal of Portfolio Management

"The Journal of Portfolio Management (JPM) announces that Marcos López de Prado, Senior Managing Director at Guggenheim Partners and Research Fellow at Lawrence Berkeley National Laboratory, has been named to the Journal’s Advisory Board, effective March 1, 2015."

02/25/2015 Bershidsky, L.

Russia's Insider Traders Know Putin's Plans


"On Feb. 27 the VPIN for the RTS index spiked, reaching 52.5 percent -- way above the norm [...] March 3 was the first trading day after Saturday, March 1 -- the day Crimea's new, pro-Russian local government asked Russia for help in "securing peace" and Putin asked his rubber-stamp Parliament for permission to send troops to Ukraine. The RTS index dropped 12 percent as the rest of the market caught up with the insiders..."

01/27/2015 Scott. C. Practical Applications of The Deflated Sharpe Ratio Institutional Investor Journals A Q&A on backtest overfitting and how to deflate the Sharpe ratio.
01/16/2015 Bengani, P. Fiddling with figures Automated Trader Automated Trader features our work on backtest overfitting.
10/30/2014 Regan, Michael Beware Overfitting Models Even if They Win Baseball Bets Bloomberg News An article intoducing readers to our Backtest Overfitting web application.
10/25/2014 Blumenthal, Robin; Salzman, Avi Ghost in the Machine Barron's A quote regarding Prof. Harvey's revolutionary paper on cross-sectional returns and multiple-testing.


Scott, Cathy

El-Erian, Bogle, Malkiel Among 30 Luminaries Discussing Hot-Button Issues in Finance

Business Wire

"What do the top luminaries in finance really think about smart beta, momentum investing, performance inflation and the ability to predict stock market crashes? Thirty well-recognized luminaries have written their frank assessment of these burning issues, and much more, for The Journal of Portfolio Management’s 40th Anniversary Issue."


Zweig, Jason

Huge Returns at Low Risk? No So Fast: The wild world of 'backtesting' -- and why investors need to be on guard.

Wall Street Journal

WSJ features our research on backtest overfitting.


Rekenthaler, J.

Voodoo Investment Strategies Morningstar

A nice essay on our work on backtest overfitting.


Jacobs, Ryan

The Dangerous Mathematical Con of Hedge Funds and Financial Advisers

Pacific Standard

"Using too many trials to design investment algorithms renders them statistically useless and potentially devastating."


Institutional Investor Journals

Interview with Dr. David H. Bailey

Institutional Investor Journals

IIJournals interviewed David H. Bailey at the conclusion of our presentation at the Battle of the Quants 2014.


Conway, B.

Is a too perfect ETF backtest fraud?


“If an investment process is driven by what looks good historically, there’s a greater chance the attractive-looking result is just a fluke.”


Foley, S.

When use of pseudo-maths adds up to fraud

Financial Times

“By calling it fraud, the academics command attention, and investors would be wise to beware. With interest rates about to turn, and a stock market bull run ageing fast, there have never been such temptations to eschew traditional bond and equity investing and to follow the siren sales patter of those who claim to see patterns in the historical data.”



Computer Models Often Use Unsound Math, Researchers Say

Bloomberg News

Bloomberg News article discussing our latest article at the Notices of the American Mathematical Society.

"[M]athematicians in the 21st century have remained disappointingly silent with the regards to those in the investment community who, knowingly or not, misuse mathematical techniques such as probability theory, statistics and stochastic calculus. Our silence is consent, making us accomplices in these abuses."



‘Smoke and mirrors’ strategy costing Mum and Dad investors billions

University of Newcastle

Press Release by the University of Newcastle on occasion of the publication of our paper on Backtest Overfitting.


American Mathematical Society

Press Release by the American Mathematical Society

AMS, ScienceDaily & Eurekalert

Press Release by the AMS on occasion of the publication of our paper on Backtest Overfitting.


Risk Magazine

Interview by Risk Magazine

Incisive Media

Interview published by Risk Magazine and the organizers of the Trading and Investment Risk 2014 Conference.


Algorithmic Finance

One Minute with Marcos Lopez de Prado

Algorithmic Finance

Interview published by the journal Algorithmic Finance.


Total Trading

HETCO’s Head of Quant Trading & Research Marcos Lopez de Prado at the Trading Show NYC 2013


A summary of my presentation at Trading Show NYC 2013.


Faille, C.

Doing Penance for the Draw-down


A nice summary of what the "triple penance rule" is about.


O'Hara, M. and D. Easley

Financial markets are at risk of a ‘big data’ crash

Financial Times

"Being fast is not enough. We, along with Marcos Lopez de Prado of the Lawrence Berkeley National Laboratory, have argued that HFT companies increasingly rely on “strategic sequential trading”. This consists of algorithms that analyse financial big data in an attempt to recognise the footprints left by specific market participants."


Murphy, B.

Enthought Introduces Enthought Canopy, a Python Analysis Environment for Scientific and Analytic Computing


Press release announcing the introduction of Enthought Canopy.


Krieger, L.

Supercomputers could generate early-warning system for stock market crashes

Mercury News

"[...] Using the lab's Cray XE6 "Hopper" supercomputer, the Leinweber team found one precursor to a flash crash that a supercomputer could identify. Called Volume-synchronized Probability of INformed trading, or VPIN, it detected an imbalance between buy and sell orders, and growing volatility, about 45 minutes before [the] crash".


Zweig, Jason

Could Computers Protect the Market From Computers?

Wall Street Journal

The Wall Street Journal reports on the collaboration between Lawrence Berkeley National Laboratory and the inventors of VPIN.



Sub-Committee on Automated and High Frequency Trading

U.S. Commodity Futures Trading Commission

The CFTC uses two of our papers in setting the legal definition of High Frequency Trading.


Lash, Herbert

Post 'flash crash' monitoring emerges at Berkeley


This Reuters article discusses how VPIN could be used to design dynamic circuit breakers.


Carver, Laurie

US regulators ask DOE lab to study flash-crash forecasting tool

Risk Magazine

Risk Magazine reports that U.S. regulators have asked a National Laboratory to study methods to prevent flash-crashes, VPIN being one of the options considered.


Carver, Laurie

OTC flash crash: Dealers consider risks of HFT invasion

Risk Magazine

Risk Magazine features VPIN as a possible way to prevent OTC flash crash.


Grant, Justin

Formula May Pave Way to Stopping Flash Crashes

Advanced Trading

Interview with "Advanced Trading" Magazine.


Demos, Telis

US panel on flash crash urges rule changes

Financial Times

Financial Times refers to Maureen O'Hara's research on the "flash crash".


Glaser, Linda

Stock market 'flash' crashes now predictable, thanks to Cornell-developed metric

Cornell Chronicle

Cornell University featured the VPIN papers in its newspaper.


Kardos, Donna

'Toxicity' Metric May Help Avoid Another Flash Crash: Study

Dow Jones

Richard Ketchum, chairman and chief executive of the Financial Industry Regulatory Authority, mentioned the VPIN study Friday during a meeting of the Joint CFTC-SEC Advisory Committee.


Mehta, Nina

`Toxic' Orders Can Predict Likelihood of Stock Market Crashes, Study Says

Bloomberg News

A formula for measuring how fast the best-informed traders increase their share of market volume may help regulators prevent crashes such as the May 6 plunge. It became the second most read news article that day.










Registered clinical trials make positive findings vanish


Like in most experimental research areas, Financial studies should pre-register the trials to be conducted. Otherwise, empirical finance will become a pathological science, a collection of "cold fusion" claims.

06/09/2015 Jiang, J. Volume-Synchronized Probability of Informed Trading (VPIN), Market Volatility, and High-Frequency Liquidity Brock University St. Catharines, Ontario "Summarizing from our empirical research, we conclude that VPIN can be employed as an effective risk management tool and can be put into practice in the prevalent high-frequency trading mechanism of the current financial world."
05/03/2015 The Economist False Hope: Most trading strategies are not tested rigorously enough The Economist The Economist features Cam Harvey's excellent paper on backtesting, which in turn refers to our NAMS article (May, 2014), "Pseudo-Mathematics and Financial Chalatanism".
04/21/2015 Miedema, D. and S. Lynch Flash Crash Arrest Lays Bare Regulatory Lapses at All Levels Reuters In "The Microstructure of the Flash Crash", Profs. Easley, O'Hara and I explained how the flash crash of May 6th 2010 was caused by order imbalance. Our explanation contrasted with the official SEC-CFTC report, which blamed a large mutual fund's order of 75,000 futures contracts for the debacle (supposedly originated by Waddell & Reed). Five years after that event, the U.S. Department of Justice has finally filed criminal charges against a high-frequency trader for causing that order imbalance:

"His conduct was at least significantly responsible for the order imbalance that in turn was one of the conditions that led to the flash crash," CFTC head of enforcement Aitan Goelman told a conference call with journalists.
04/19/2015 Onan, M., A. Salih and B. Yasar Determinants of Implied Volatility Slope of S&P500 Options European Financial Management Association "We document that order flow toxicity measured by Volume Synchronized Probability of Informed Trading (VPIN, Easley et al., 2012) is an important determinant of the slope of the volatility skew besides transactions costs and net buying pressure [...] Model-free risk-neutral skewness measure which is highly correlated with slope is also significantly associated with VPIN."
02/25/2015 Silva, F. and E. Volkova

Can VPIN Forecast Geopolitical Events? An Application to the Crimean Crisis

Cornell University

"We compute the Volume-synchronized Probability of Informed Trading (VPIN) for the Russian main equity index and for individual stocks, finding that for the index level and for most of the stocks it raises considerably between one and three trading days before market prices reflect the invasion [...] Our results provide additional support for the use of VPIN as a measure of monitoring the likelihood of undesirable (geopolitical) events."

01/18/2015 Cheung, W., R. Chou, A. Lei Exchange-Traded Barrier Option and VPIN Journal of Futures Markets "In this study, we provide the first direct evidence of the validity of VPIN outside the US market [...] Our results show that VPIN has significantly incremental predictive power on MCE after controlling for volatility and volume."
12/28/2014 CFA Institute The Volume Clock (Digest Summary) CFA Digest CFA recommended reading.
12/28/2014 CFA Institute Flow Toxicity & Liquidity (Digest Summary) CFA Digest CFA recommended reading.


Panayides, Marios; Shohfi, Thomas; Smith, Jared

Comparing Trade Flow Classification Algorithms in the Electronic Era: The Good, the Bad, and the Uninformative

Proceedings of the Northern Finance Association, 2014

"We find that, despite the use of quote data, Lee and Ready underperforms the other methods, particularly during intervals of high trade and/or quote frequency. The bulk volume algorithm (BVC) demonstrates superiority with respect to data efficiency, accuracy, and the ability to capture informative trade flow."


Michaels, Dave

SEC Finds Misrepresentations by Hedge Funds, Bowden Says

Bloomberg News

Some hedge funds misrepresent their performance in advertising and marketing materials. "SEC examiners also found examples of hedge funds presenting modeled or back-tested performance as actual results and flipping between valuation methodologies, Bowden said." My co-authors and I denounced some of these practices in the May 2014 issue of the Notices of the American Mathematical Society.


Bechler, Kyle; Ludkovski, Michael

Optimal Execution with Dynamic Order Flow Imbalance

University of California, Santa Barbara

Profs. Bechler and Ludkovski examine how VPIN helps achieve optimal execution by adding market microstructure features to the standard transaction cost minimization problem.


Rush, Stephen

Twenty Years of VPIN

University of Connecticut

Prof. Rush implemented VPIN in R, and applied this microstructural theory on a large dataset of stocks. He concludes that VPIN evidences an increased probability of toxicity contagion over the last 20 years.


Barry, M.

Package PBO: Probability of Backtest Overfitting

R/Finance 2014: Applied Finance with R

An implementation of our PBO method in R language.


Song, J, K. Wu and H. Simon

Parameter Analysis of the VPIN (Volume Synchronized Probability of Informed Trading) Metric

Constantin Zopounidis, Editor. Quantitative Financial Risk Management: Theory and Practice. 2014. Wiley.

"VPIN (Volume synchronized Probability of Informed trading) is a leading indicator of liquidity-induced volatility. It is best known for having produced a signal more than hours before the Flash Crash of 2010. On that day, the market saw the biggest one-day point decline in the Dow Jones Industrial Average, which culminated to the market value of $1 trillion disappearing, but only to recover those losses twenty minutes later (Lauricella 2010)."


Haran, B.

π and Four Fingers


Numberphile recently featured my friend, coleague and co-author David H. Bailey. This video explains how David's Spigot algorithm was used in The Simpsons "Marge in Chains" episode.


Yildiz, S., R. Van Ness and B. Van Ness

Analysis of the Determinants of VPIN, HFTs' Order Flow Toxicity and Impact on Stock Price Variance

Univ. Mississippi

"While trade intensity is negatively related to VPIN, return volatility is positively related to VPIN. VPIN has predictive power for future volatility in equity markets, even after controlling for trade intensity. FVPIN contract is a useful hedge tool against toxicity."


Edesess, M. and K.L. Tsui

How Many Monkeys Does it Take to Find a Successful Strategy?

Advisor Perspectives

“We would like to raise the question of whether mathematicians should continue to tolerate the proliferation of investment products that are misleadingly marketed as mathematically founded.”


Russell, K.

Overfitted Backtests

Timely Portfolio

Kenton Russell has published the code in R language that computes the Minimum Backtest Length (MinBTL).


J. MacIntosh

High Frequency Traders: Angels or Devils?

C.D. Howe

Prof. MacIntosh (U. Toronto) cites our work on the Flash Crash in his new study.



High Frequency Trading – An Asset Manager’s Perspective

Norges Bank Investment Management

A good summary of the state of the debate regarding High-Frequency Trading.



Concept Release on Risk Controls and System Safeguards for Automated Trading Environments


The newly published CFTC proposal on Risk Controls cites the VPIN model as a plausible mechanism for preventing flash crashes.


Wu, J. et al.

Testing VPIN on Big Data: Response to "Reflecting on the VPIN dispute"

Lawrence Berkeley National Laboratory

Scientists at Berkeley Lab discuss multiple errors in Torben Andersen and Oleg Bondarenko's study of VPIN.


Wung, C. et al.

Informed Trading and Price Discovery Around the Clock

Journal of Alternative Investments

An analysis of the presence of informed traders in the Eurodollar Futures market, using the VPIN model.


Bailey, D.H., J. M. Borwein, A. Mattingly and G. Wightwick

The computation of previously inaccessible digits of π2 and Catalan's constant

Notices of the American Mathematical Society

My co-author David H. Bailey has recently published an article in AMS' flagship journal in which he reflects on the implications of the celebrated Bailey-Borwein-Plouffe formula for the calculation of π, the standard HPC benchmark.


Zagaglia, P.

PIN: Measuring Asymmetric Information in Financial Markets with R

Universita di Bologna

Prof. Zagaglia has developed a module in R Language to estimate PIN.


Brakke, T.

The Sharpe Edifice

The Research Puzzle

An interesting piece on the state of the discussion regarding Sharpe ratios.


Gollapudi, N. and A. Bose

Current Swap market imbalances and what they mean

Citibank Research

A team of Citibank Researchers find that the BVC algorithm for Bulk Volume Classification signals useful information about Swaps market positioning.


Wei, W., D. Gerace and A. Frino

Informed Trading, Flow Toxicity and the Impact on Intraday Trading Factors

A.A. Business and Finance Journal

This study shows that different capitalization stocks exhibit different VPIN characteristics. It finds that flow toxicity measured through VPIN is able to predict and explain to an extent future quote imbalance, price volatility and volume bucket duration or trade intensity.



A Big Data Approach to Analyzing Market Volatility

Lawrence Berkeley National Laboratory

Berkeley Lab scientists have applied Big Data techniques to complete the largest study ever on volatility. It uses a massive amount of tick data from the one hundred most liquid futures contracts worldwide over a period of five years. They conclude that short-term volatility can be forecasted with false positive rates as low as 7%.


Themis Trading

Front Running – “Strategic Sequential Trading”

Themis Trading

Themis Trading comments on our research on High Frequency Trading and Big Data.


Hunsader, E.

May 6'th 2010 Flash Crash Analysis


NANEX finds several inconsistencies in the CFTC analysis of the Flash Crash. The same study was also criticized by the CME, on similar grounds. The CME and NANEX rarely agree on High-Frequency Trading analyses, as they are on opposite sides of the debate.


Journal of Financial Markets

The Journal of Financial Markets has announced the withdrawal of the paper titled "VPIN and the Flash Crash", written by Torben G. Andersen and Oleg Bondarenko. This paper had been accepted for publication six months earlier, and claimed that "VPIN is a poor predictor of short run volatility".  We had expressed our concerns regarding Andersen and Bondarenko's implementation of VPIN in our paper "VPIN and the Flash Crash: A Comment". Sadly, the withdrawal of this paper has not been given as much publicity as its initial publication [1, 2]. However, withdrawing a paper from an academic journal is an exceptional action, and I commend JFM's editors as well as Andersen and Bondarenko for taking that step. [04/12/2013 UPDATE: Retraction Watch features this retraction in their website (link)]


Menkveld, A. and B. Yueshen

Anatomy of the Flash Crash

VU University Amsterdam; Tinbergen Institute

Menkveld and Yueshen examine VPIN during the flash crash, and show that "the large seller's relative presence in the market co-moves negatively with flow toxicity. This finding is consistent with strategic trading: she sells passively during upturns (her limit sell orders are taken out), sells aggressively right after an upturn, and does not trade in downturns."


Berman, M., V. Krouglov and E. Olin

RAPA Score Triumphs

RAPA Cap Intro

RAPA's whitepaper argues that their PSR-based capital allocation leads to superior fund performance.



Celebrating Pi Day

U.S. Department of Energy

On Pi day, the U.S. Department of Energy paid tribute to the work of Prof. David H. Bailey.


Wolchover, N.

In Computers We Trust?

Simons Foundation

The Simons Foundation asked David H. Bailey to discuss the growing role of Computational Mathematics in Mathematical Research. Best known for the Bailey-Borwein-Plouffe formula, Prof. Bailey is a leading authority in Experimental Mathematics, and has co-authored with Marcos five papers in Mathematical Finance.


Barclay Insider Report

Are hedge funds firing too many managers?


Barclay's Insider Report features our recent paper, "Drawdown-based Stop-Outs and the Triple Penance rule".


R. Wood, J. Upson and H. McInish

The Flash Crash: Trading Aggressiveness, Liquidity Supply, and the Impact of Intermarket Sweep Orders


Consistent with our findings about the Flash Crash, Wood et al. present evidence of  informed trading in the early part of that day, which drove returns over the crash period.


Hwang, L., S. Lim, K. Park and W. Lee

Does information risk affect the implied cost of equity capital? An analysis of PIN and adjusted PIN

Journal of Accounting and Economics

The authors find that estimates of PIN based on Lee-Ready tend to be inaccurate. Using the actual aggressor side information, they obtain PIN estimates that are useful in explaining the ICOE (implied cost of equity capital. This result is consistent with our findings in connection with the Tick Rule, the actual aggressor side, and Bulk Volume Classification (BVC).


Berman, M., V. Krouglov and E. Olin

Release of the new RAPA Ranking Algorithm


Since January of 2013, RAPA CAP Intro will be ranking portfolio managers worldwide following the Probabilistic Sharpe Ratio (PSR) methodology introduced in our paper "The Sharpe Ratio Efficient Frontier".


Klein, L., V. Dalko and M. Wang

Regulating Competition in Stock Markets: Antitrust Measures to Promote Fairness and Transparency through Investor Protection and Crisis Prevention


Lawrence Klein (Nobel Prize, 1980) has teamed up with Harvard professor Viktoria Dalko and RICE's Vice President Michael Wang. The book discusses financial crisis prevention, with references to the VPIN theory.


Corcoran, C.

Systemic Liquidity Risk and Bipolar Markets: Wealth Management in Today's Macro Risk On / Risk Off Financial Environment


Clive Corcoran's new book contains a chapter titled "Detecting mini bubbles with the VPIN metric", in which this author demonstrates how the VPIN theory can be used to monitor the probability of toxicity-induced liquidity crises.


Johnson, T. and E. So

A Simple Multimarket Measure of PIN


Johnson and So propose a new PIN metric that combines information from multiple markets.


Abad, D. and J. Yague

From PIN to VPIN: An Introduction to Order Flow Toxicity

Span Rev Financ Econ

Consistent with a previous study by Lawrence Berkeley National Laboratory, this paper confirms VPIN's forecasting power on stocks' toxicity-induced volatility.


Deutsche Bank Quantitative Strategies

Academic Insights

Deutsche Bank

DB features our new paper: "Balanced Baskets: A new approach to Trading and Hedging Risks".


O'Malia, Scott

“I Have One Word for You: Technology”

U.S. Commodity Futures Trading Commission

CFTC Commissioner O'Malia comments on our recent paper "The Volume Clock: Insights into the High Frequency Paradigm".


Deutsche Bank Quantitative Strategies

Academic Insights

Deutsche Bank

DB features our two newly published paper: "Optimal Execution Horizon" and "The Volume Clock: Insights into the High Frequency Paradigm".


Bethel, W. et al.

Federal Market Information Technology in the Post Flash Crash Era: Roles for Supercomputing

Journal of Trading

In a paper published by the Journal of Trading, a U.S. National Laboratory confirms our results on the "flash crash" and further concludes that "This [VPIN] is the strongest early warning signal known to us at this time."


Deutsche Bank Quantitative Strategies

Academic Insights

Deutsche Bank

Deutsche Bank features the paper "Advanced Cointegration and Subset Correlation Hedging Methods".


UK's Government Office for Science

The Future of Computer Trading in Financial Markets


Maureen O'Hara discusses VPIN in the context of this British Government study.


Carver, Laurie

US regulators ask DOE lab to study flash-crash forecasting tool

Risk Magazine

Risk Magazine reports that U.S. regulators have asked a National Laboratory to study methods to prevent flash-crashes, VPIN being one of the options considered.


Carver, Laurie

OTC flash crash: Dealers consider risks of HFT invasion

Risk Magazine

Risk Magazine features VPIN as a possible way to prevent OTC flash crash.


Deutsche Bank Quantitative Strategies

Academic Insights

Deutsche Bank

This investment bank features "The Sharpe Ratio Efficient Frontier" in their list of selected academic research.


Deutsche Bank Quantitative Strategies

Academic Insights

Deutsche Bank

DB's Global Quantitative Stratregies group discusses the introduction of a new performance measure called "Probabilistic Sharpe Ratio" (PSR), which corrects for the inflationary effects associated with Non-Normal returns.


Deutsche Bank Quantitative Strategies

Academic Insights

Deutsche Bank

This investment bank featured "The Microstructure of the Flash Crash" in their list of selected academic research.


Luo, Yin et al.

Frequency Arbitrage

Deutsche Bank

This Research Note discusses the alpha generated by PIN-style models, and the potential of VPIN for liquidity risk applications.