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PUBLICATIONS

There is nothing more practical than a good theory. My "day job" for the last 15+ years has primarily been as a quantitative portfolio manager at leading financial institutions. As someone with a passion for understanding the mechanics of financial markets, I have found that many models successfully applied in scientific fields are tremendously useful in addressing critical investment management problems. In order to facilitate this cross-pollination, I have complemented my investment manager "day job" with an academic "night job". In that pursuit, I have been fortunate enough to meet and work extensively with some of the leading figures in Pure Mathematics, Mathematical Finance, Machine Learning, Market Microstructure and Econometrics. Most of our findings are kept proprietary. From time to time, however, we decide to publish some of them, hence the irregular frequency of the following publications.

For additional publications and working papers, visit: http://ssrn.com/author=434076. My Mathematical Reviews (MathSciNet) ID is 1026893.

 

RECENT PEER-REVIEWED JOURNAL ARTICLES

 

AUTHORS

TITLE

REFERENCE

INDEX

NOTABLE INNOVATION

Bailey, David H.; Borwein, Jon M.; Lopez de Prado, Marcos; Zhu, Jim

Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-Of-Sample Performance

Notices of the American Mathematical Society, 61(5), pp. 458-471. May 2014.

MathSciNet; Zentralblatt MATH

We prove that high simulated 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. This is one of the first Mathematical Finance papers published in the Notices of the AMS, the official membership journal of the American Mathematical Society.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

Optimal Execution Horizon

Mathematical Finance, 2014. Forthcoming.

JCR (5Y IF = 1.662)

MathSciNet; Zentralblatt MATH

Execution traders know that market impact greatly depends on whether their orders lean with or against the market. And yet, the literature on optimal execution strategies rarely incorporates order imbalance in the modeling of transaction costs. We introduce the OEH model, which considers this fact when determining the optimal trading horizon for an order, an input required by many sophisticated execution strategies.

Bailey, David H.;
Lopez de Prado, Marcos

Stop-Outs Under Serial Correlation and "The Triple Penance Rule"

Journal of Risk, Forthcoming. 2014.

JCR (5Y IF = 1.794)

We develop a framework for informing the decision of stopping a portfolio manager or investment strategy once it has reached a loss or time under water limit for a certain confidence level. Under standard portfolio theory assumptions, we show that it takes three times longer to recover from the expected maximum drawdown than the time it takes to produce it, with the same confidence level. Mathematical Appendices available here.

Lopez de Prado, Marcos;
Foreman, Matthew

A Mixture of Gaussians Approach to Mathematical Portfolio Oversight: The EF3M Algorithm

Quantitative Finance, 14(5), pp. 913-930. 2014.

JCR (5Y IF = 0.957)

MathSciNet; Zentralblatt MATH; Scopus

We solve the "Nonic Polynomial problem" posed by Karl Pearson in the 1894 edition of the Philosophical Transactions of the Royal Society. We apply quantitative methodologies originated in the Mathematical Theory of Evolution to model the dynamics of investment styles within a fund.

Bailey, David H.;
Lopez de Prado, Marcos

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

Journal of Portfolio Management, 40 (5), pp. 94-107. 2014 (40th Anniversary Special Issue).

JCR (5Y IF = 0.562) The Deflated Sharpe Ratio (DSR) corrects for two leading sources of performance inflation: Selection bias under multiple testing and non-Normally distributed returns.

In this interview, Prof. Bailey speaks about our work.

Calkin, Neil; Lopez de Prado, Marcos

Stochastic Flow Diagrams

Algorithmic Finance, 3(1), pp. 21-42. 2014.

We introduce Stochastic Flow Diagrams (SFDs), a new mathematical approach to represent complex dynamic systems into a single weighted digraph. This topological representation provides a way to visualize what otherwise would be a morass of equations in differences.

Proceedings SC'14

Song, Jung H.; Lopez de Prado, Marcos; Simon, Horst D.; Wu, Kesheng

Exploring Irregular Time Series Through the Non-Uniform Fourier Transform Proceedings of the International Conference for High Performance Computing, IEEE, 2014.   We explore the frequency domain of irregular time series by applying a Non-Uniform Fast Fourier Transform (NUFFT) on Natural Gas Futures prices. We show that High-Frequency Traders are responsible for a growing number of cyclical patterns. In particular, we observe the emergence of a new power law in the Fourier spectra in recent years.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

VPIN and the Flash Crash: A Rejoinder

Journal of Financial Markets, 17(1), pp. 47-52. 2014.

JCR (5Y IF = 1.505)

Discusses implementation cautions with regards to VPIN empirical studies.

Calkin, Neil; Lopez de Prado, Marcos

The Topology of Macro Financial Flows: An Application of Stochastic Flow Diagrams

Algorithmic Finance, 3(1), pp. 43-85. 2014.

We construct a network of financial instruments and show how Stochastic Flow Diagrams (SFDs) allow researchers to monitor the flow of capital across the financial system. Because our approach is dynamic, it models how and for how long a financial shock propagates through the system.

Bailey, David H.;
Lopez de Prado, Marcos

An Open-Source implementation of the Critical-Line Algorithm for Portfolio Optimization

Algorithms, 6(1), pp. 169-196. 2013.

MathSciNet; Zentralblatt MATH; Scopus-SciVerse

We fill a gap in the literature by providing a well-documented, step-by-step open-source implementation of the Critical-Line Algorithm (CLA) in a scientific language. We discuss the logic behind CLA following the algorithm’s decision flow. In addition, we have developed several utilities that facilitate the answering of recurrent practical problems.

Bailey, David H.;
Lopez de Prado, Marcos

The Strategy Approval Decision: A Sharpe Ratio Indifference Curve Approach

Algorithmic Finance, 2(1), pp. 99-109. 2013.

The problem of capital allocation to a set of strategies could be partially avoided, or at least greatly simplified, with an appropriate strategy approval decision process. This paper proposes such procedure, by splitting the capital allocation problem into two sequential stages: Strategy approval and portfolio optimization.

Bailey, David H.;
Lopez de Prado, Marcos

The Sharpe Ratio Efficient Frontier

Journal of Risk, 15(2), pp. 3-44, Winter. 2012.

JCR (5Y IF = 1.794)

Introduced the Probabilistic Sharpe Ratio (PSR), a new uncertainty-adjusted investment skill metric that corrects the inflationary effect that Non-Normality has on Sharpe Ratio estimates. It also determines the Minimum Track Record Length (MinTRL) needed to evidence skill. A Sharpe Ratio Efficient Frontier (SEF) arises, based on return-on-risk rather than return-on-capital.

Bailey, David H.;
Lopez de Prado, Marcos

Balanced Baskets: A new approach to Trading and Hedging Risks

Journal of Investment Strategies, 1(4), pp. 21-62. Fall, 2012.

 

Introduced the notion of Balanced Baskets, which are portfolios of instruments that evenly spread risks or exposures across their constituents without requiring a change of basis, like PCA. It also developed the algorithms needed to compute such baskets in hedging as well as trading applications. Finally, it also contributed a new procedure for covariance clustering.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

The Volume Clock: Insights into the High Frequency Paradigm

Journal of Portfolio Management, 39(1), pp. 19-29. Fall, 2012.

JCR (5Y IF = 0.562)

This paper has been cited by Market Regulators [1, 2, 3] for deepening their understanding of the phenomenon of High Frequency Trading (HFT), beyond the simple notion of "speed trading". In particular, it argues that at the heart of HFT is a new investment paradigm based on making decisions in Volume Time.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

Flow Toxicity and Liquidity in a High Frequency World

Review of Financial Studies, 25(5), pp. 1457-1493. 2012.

JCR (5Y IF = 5.367)

Developed a new procedure to estimate the flow toxicity impacting market makers, the Volume Synchronized Probability of Informed Trading (VPIN). This metric has been shown to anticipate liquidity crises (including the Flash Crash) and to be a good predictor of toxicity-induced volatility. CFTC's HFT guidelines cite this publication.

Lopez de Prado, Marcos;
Leinweber, David

Advances in Cointegration and Subset Correlation Hedging Methods

Journal of Investment Strategies, 1(2), pp. 67-115. Spring, 2012.

 

Introduced two new hedging methods, called Dickey-Fuller Optimization (DFO) and Mini-Max Subset Correlation (MMSC). The former is a dynamic, cointegration based method while the latter is a static, balanced-basket method to evenly distribute exposure among portfolio constituents. It also generalized the Box-Tiao Canonical Decomposition (BTCD) method.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

The Exchange of Flow Toxicity

Journal of Trading, 6(2), pp. 8-13. Spring, 2011.

 

It introduced the concept of "Market Makers' Asymmetric Payoff Dilemma", which characterizes a liquidity provider as the seller of a real-option to be adversely selected. Since that option cannot be dynamically replicated, a new contract is proposed to allow market makers to hedge such risks.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

The Microstructure of the ‘Flash Crash’: Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading

Journal of Portfolio Management, 37(2), pp. 118-128. Winter, 2011.

JCR (5Y IF = 0.562)

This has become one of the most read papers in Finance, according to SSRN. It analyses the "Flash Crash" from a microstructure perspective, and concludes that it was a liquidity crises which resulted from market makers receiving persistently toxic order flow for at least 2 hours before the crash actually unfolded.

Lopez de Prado, Marcos;
Peijan, Achim

Measuring Loss Potential of Hedge Fund Strategies

Journal of Alternative Investments, 7(1), pp. 7-31. Summer, 2004.

 

It developed a new risk framework for assessing hedge funds' loss potential, considering Non-Normal and Serially-Correlated returns. It shows that the IID Normal assumption, ubiquitous in financial risk modeling, leads to a great underestimation of the loss potential of hedge funds.

 

PEER-REVIEWED ACADEMIC BOOKS

 

AUTHORS

TITLE

REFERENCE

NOTABLE INNOVATION

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen
(Coord.)

High Frequency Trading: New Realities for Traders, Markets and Regulators

Risk Books,  2013.

An overview of high frequency trading (HFT) strategies, with a particular focus on how low frequency traders can survive in a high frequency world.

Contributors include leading practitioners and academics in this field: Robert Almgren (Quantitative Brokers, New York University), Wes Bethel (Lawrence Berkeley National Laboratory), Ming Gu (Lawrence Berkeley National Laboratory), Terry Hendershott (U.C. Berkeley), Charles Jones (Columbia University), Michael Kearns (S.A.C. Capital, University of Pennsylvania), David Leinweber (Lawrence Berkeley National Laboratory), Oliver Linton (University of Cambridge), Albert Menkveld (University of Amsterdam), Yuryi Nevmyvaka (University of Pennsylvania), Richard Olsen (Olsen Ltd.), Oliver Ruebel (Lawrence Berkeley National Laboratory), George Sofianos (Goldman Sachs), Michael Sotiropoulos (Bank of America Merrill Lynch), Kesheng Wu (Lawrence Berkeley National Laboratory), and Jean-Pierre Zigrand (London School of Economics).

Lopez de Prado, Marcos

Advances in High Frequency Strategies

Complutense University, 2011.

This is the author's second doctoral dissertation. The generalization of electronic markets and ubiquitous automation of financial transactions has rendered many established models and theories obsolete. This work presents a new scientific framework for the study of some of the most relevant questions concerning High Frequency Trading.

Lopez de Prado, Marcos

Invertir en Hedge Funds

Díaz de Santos, 2003.

This is the author's first doctoral dissertation, which dealt with portfolio optimization, risk management and capital allocation to hedge funds. Once hedge funds' hidden risks are taken into account, optimal allocations are much smaller than proposed by the standard Markowitz approach.

 

WORKING PAPERS AND BOOKS

AUTHORS

YEAR

TITLE

NOTABLE INNOVATION

Lopez de Prado, Marcos; Rebonato, Riccardo

2014

Kinetic Component Analysis

We introduce Kinetic Component Analysis (KCA), a state-space application that extracts the signal from a series of noisy measurements by applying a Kalman Filter on a Taylor expansion of a stochastic process. We show that KCA presents several advantages compared to other popular noise-reduction methods such as Fast Fourier Transform (FFT) or Locally Weighted Scatterplot Smoothing (LOWESS).

Carr, Peter; Lopez de Prado, Marcos

2014

Determining Optimal Trading Rules without Backtesting

We present empirical evidence of the existence of optimal trading rules (OTRs) for the case of prices following a discrete Ornstein-Uhlenbeck process, and show how they can be computed numerically. Although we do not derive a closed-form solution for the calculation of OTRs, we conjecture its existence on the basis of the empirical evidence presented.

Bailey, David H.; Ger, Stephanie; Lopez de Prado, Marcos; Sim, Alexander; Wu, Kesheng

2014

Statistical Overfitting and Backtest Performance

We present an online backtest simulation tool that evidences how easy is to overfit an investment strategy when the number of trials is not controlled. The implication is that most investment strategies published in the academic literature are likely to be false positives.

Bailey, David H.; Borwein, Jon M.; Lopez de Prado, Marcos; Zhu, Jim

2013

The Probability of Backtest Overfitting

Most firms and portfolio managers rely on backtests (or historical simulations of performance) to select investment strategies and allocate them capital. Standard statistical techniques designed to prevent regression overfitting, such as hold-out, tend to be unreliable and inaccurate in the context of investment backtests. We propose a framework that estimates the probability of backtest overfitting (PBO) specifically in the context of investment simulations, through a numerical method that we call combinatorially symmetric cross-validation (CSCV). We show that CSCV produces accurate estimates of the probability that a particular backtest is overfit.

Lopez de Prado, Marcos; Vince, Ralph; Zhu, Jim

2013

Optimal Risk Budgeting Under a Finite Investment Horizon

Growth Optimal Portfolio (GOP) theory determines the path of bet sizes that maximize long-term wealth. This multi-horizon goal makes it more appealing among practitioners than myopic approaches, like Markowitz's mean-variance or risk parity. The GOP literature typically considers risk-neutral investors with an infinite investment horizon. In this paper, we compute the optimal bet sizes in the more realistic setting of risk-averse investors with finite investment horizons.

Easley, David;
Lopez de Prado, Marcos;
O'Hara, Maureen

2012

Bulk Classification of Trading Activity

We propose a new trade classification method "in bulk", and show that its accuracy is comparable to that of "trade-by-trade" classification methods, such as the "tick-rule", with much smaller data requirements and greater explanatory power over the trading range.