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Best Quant Papers of 2018 from Savvy Investor

The Best Quant Papers of 2018 from Savvy Investor

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The Best Quant Papers of 2018 from Savvy Investor

Quantlabs is pleased to be partnering with Savvy Investor, the world’s leading knowledge network for institutional investors. You may wish to consider joining their platform – it’s entirely free.

Fama and French win “Best Quant Paper 2018”

Savvy Investor curates the best pensions and investment white papers from around the world. Having uploaded more than 25,000 papers since launch, they have a unique platform from which to host these Awards. The Savvy Investor Awards are judged on the basis of the quality and readability of the paper and its appeal to their institutional investor audience.

Call us sentimental, but we’re delighted to be awarding the Savvy Investor trophy for the best quant paper of 2018 to Eugene Fama and Kenneth French. Unlike some earlier papers authored by this duo, the winning paper is in no way ground-breaking. However, it reminds us all of the nature of equity market volatility, and the implications for long-term investment returns. As the name suggests, it is a “volatility lesson” for professional investors, coming from two of the most respected names in the business.

See the winning papers below, or visit Savvy Investor for the full list of winners and short-listed papers across all 15 categories. 

Best Quant Paper 2018

Volatility Lessons (Financial Analysts Journal – CFA Institute)
In this paper, Fama and French examine the return distribution of equities versus cash over a variety of time periods, and show that the probability of negative equity returns over three and five-year periods is substantial. Interestingly, for longer-term horizons (say 10 or 20 years) there is a marked increase in right skewness and kurtosis. In other words, compared to a normal distribution of returns, the left tail almost disappears and the likelihood of negative equity returns versus cash diminishes substantially. Another key conclusion from the data relates to drawing inferences about future risk premia from observed returns over 3-, 5- or 10-year periods. The duo argue that, due to the high volatility, the evidence from such a “short” time period will be too “noisy” to be reliable.

Robust Asset Allocation for Robo-Advisors (Amundi Asset Management)
Quant researchers from Amundi Asset Management examine the challenges faced by robo-advisors attempting to automate the portfolio allocation and rebalancing process. This is a detailed, complex and formula-rich paper which will appeal primarily to quant managers and analysts involved in portfolio optimization, specifically using a mean-variance approach.

The Correlation See-Saw (Axioma)
The correlation of returns between different asset classes is critical to overall portfolio risk. However, these relationships are not necessarily stable over time. Axioma analyzes the way that shifts in cross-asset correlations impact overall portfolio risk, examining a case study of the first five months of 2018 when there was an unusual pattern of correlation reversals. How should this impact an investor’s approach to risk analytics?

Combining Investment Signals in Long/Short Strategies (Goldman Sachs Asset Management)
This paper examines the best way to combine quantitative investment signals in the context of managing a long-short portfolio. Is it better to create one combined signal, or is it preferable to consider the portfolio exposures indicated by each signal and combine the different exposures? The authors carry out their own empirical study and compare the results with other academic evidence.

If We Don’t Believe Markets are “Efficient”, What Do We Believe? (Winton)
Despite the well-known faults that are inherent in the efficient market hypothesis, it still underpins several prominent investment strategies. The authors of this paper examine an ecological theory that could be more applicable to financial markets.

The Current State of Quantitative Equity Investing (CFA Institute Research Foundation)
In this 74-page paper, CFA Institute Research Foundation reviews the concepts of risk and return, anomalies and the onset of factor investing, as well as the influence of big data on the quantitative equity field.

Pulling the Goalie: Hockey and Investment Implications (Cliff Asness/Aaron Brown)
Harkening back to the 1980 ‘Miracle on Ice,’ the authors build a model to determine the precise time that a hockey coach should choose to pull the goalie when behind. They then apply these lessons to a portfolio management environment.

About Savvy Investor

Savvy Investor is the world’s leading resource hub for the institutional investors. Since launch in March 2015, more than 33,000 members from across the globe have registered for the site, with 200-250 new members joining every week.

Savvy Investor allows you to search and immediately find the top white papers on any investment topic, ranked by popularity.

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The Most Popular Quant Papers of 2016

Savvy Investor’s Andrew Perrins shares some of the most popular Quant Papers in the year so far.

 (This is my first guest blog posting)

The Research Team at Savvy Investor has curated this list of the most popular quant white papers from 2016 to date. The papers are listed in date order (from most recent to earliest) and cover a wide range of topics including short-selling, factor investing, alpha generation, momentum strategies, diversification, correlation, volatility and illiquid assets.

 

The Long and the Short of It: The Quant Shorting Advantage (QMA, 2016)

Active extension, equity long-short, and equity market neutral products can be attractive for investors at any particular time, given investors’ varied investment objectives and needs. That said, each of the three categories of shorting-enabled products can help address distinct issues facing investors today. QMA’s paper describes how short selling can allow investors to find alpha in often overlooked places, explains the three main categories of shorting-enabled equity products, and highlights the benefits of a systematic quantitative process.

 

Will Your Factor Deliver? Factor Robustness and Implementation Costs (FAJ, 2016)

Within the indexing world, multifactor investing has become very popular in recent years. Both practitioner and academic researchers have recorded several hundred equity factors. But which of these are likely to profit investors once implemented? This original research was conducted by Noah Beck, Jason Hsu, Vitali Kalesnik and Helge Kostka. It was published in CFA Institute’s Financial Analysts Journal.

 

Academic Lessons on Factor Investing (EDHEC, 2016)

This paper analyses what academic research has to say on equity factors. Our objective is to understand which lessons we can learn from such research in terms of designing and evaluating factor indices. When analysing academic publications on equity factor investing, five important lessons emerge, which provide useful perspective on practical questions about factor indices. This paper looks at the empirical analysis required to identify rewarded factors. It then turns to the economic rationale behind these factors, and looks into the role of diversification for a given factor tilt. Moreover, it discusses the issue of implementation costs and addresses the question of crowding risks. Finally, the paper discusses how popular practical implementations relate to the academic groundings.

 

101 Ways to Generate Alpha (Savvy Research Blog, Sept 2016)

Active equity managers use many different investment strategies and processes to meet the challenge of consistently creating alpha within their portfolios. This Savvy Blog post highlights a list of the top papers, which help equity investors to build successful alpha-generating processes.

 

Trend Following: Equity and Bond Crisis Alpha (Man AHL, 2016)

The authors of this paper study time-series momentum strategies in commodities, currencies, bonds, and equity indices during the period 1960-2015. Their research reveals that there was consistent performance both before and after 1985 – periods that were marked by strong bull and bear markets in bonds. The authors also record a number of important risk factors.

 

Equity/Bond Correlation: History and Future (BlackRock, July 2016)

The correlation between equity and bond markets is of vital importance to asset allocators; for risk control and portfolio construction, for assessing the market outlook, and for building models of how markets work (equity market valuation models, for example). In this 6-page paper, Nuno Luis and David Caplan of BlackRock examine the history of the equity/bond correlation and discuss the likely future path.

 

Understanding and measuring the illiquidity risk premium (Willis Towers Watson)

Illiquidity risk is a potentially appealing means of generating additional yields in a low-return world. The authors of this 10-page document discuss three different dimensions of illiquidity risk premium that investors should demand for a given asset.

 

The Free Lunch: The Value of Decoupling Diversification and Risk (Salient, 2016)

The authors of this very interesting paper discuss why considering diversification and risk independently may help investors build more efficient portfolios. They argue that asset allocators should rethink the impact of low volatility diversifiers in higher risk portfolios. Some low vol asset classes (e.g. hedge funds) may primarily have a “de-risking” impact, but not a “diversifying” impact. The paper demonstrates that, perhaps counter-intuitively, high volatility diversifiers can sometimes be very effective, and allocators should consider these strategies.

 

Multifactor Indexes: The Power of Tilting (FTSE Russell, 2016)

In recent years, institutional investors have become increasingly convinced of the benefits of factor investing, facilitated by the creation of a variety of indices, each focusing on a specific risk factor. The creation of these new indexes has allowed investors to access factor exposure efficiently and at low cost. However, as with any investment strategy, the return from a single-factor index will vary over time, often following different patterns. For instance, the quality risk factor tends to exhibit counter-cyclical performance, whereas the payoff from the value factor normally follows a more cyclical pattern. This paper examines alternative processes for building multifactor indexes, in order to benefit from a diversified exposure to the various source of factor return.

 

Predicting Volatility (Lazard, Jan 2016)

It is widely accepted that financial models always carry the risk of uncertainty. Volatility forecasting, therefore, has huge implications for investors especially employing risk parity, volatility targeting and asset allocation strategies. This paper examines volatility prediction – its characteristics and the effectiveness of different approaches.

 

Savvy Investor www.savvyinvestor.net is the world’s leading platform for the distribution of white papers to global institutional investors. Registration is free, and provides access to over 15,000 white papers, as well as a personalised newsletter, keeping you up to date with investment news and research.

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Join this site for quant research papers

Join this site for quant research papers

This is where you can find some of the best papers out there

https://www.academia.edu/

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6-day intensive quant course Bootcamp and Research papers

6-day intensive quant course Bootcamp and Research papers
One day, I might do this course as it is worth every penny!
Less then a month before the ARPM Bootcamp!
The ARPM Bootcamp provides in-depth understanding of buy-side modeling from the foundations to the most advanced statistical and optimization techniques, in nine heavily quantitative hours each day for six days, with theory, live simulations, review sessions and exercises.
Topics include portfolio construction, factor modeling, liquidity and execution, risk modeling, and much more (accreditation for 40 CE units CFA Institute and 40 CPD units GARP)

The ARPM Bootcamp features a Gala Dinner with world-renowned quants (Rob Almgren, Peter Carr, Emanuel Derman, Bruno Dupire, Alex Lipton, Bob Litterman, Fabio Mercurio, Steven Shreve, …). We also make donations to several charities via One More Reason (to see video, photos, feedback and more from last year’s ARPM Bootcamp, click here)
Much support comes from our Educational Supporters (GARP, CFA Institute, PRMIA, Society of Actuaries, …); our Corporate Supporters (PricewaterhouseCoopers, Mathworks, Axioma, Northfield, MSCI, NAG,…); and several Masters in Financial Engineering (CQF, Washington, MIT, Carnegie Mellon, NYU, Cornell, …)

For program and overview, click here. To register, click here.

http://www.symmys.com/arpm-bootcamp

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Looking for collaborators on the following papers

Paul Cottrell is looking for those interested in the following research

paulpapers. Reach out here: http://the-studio-reykjavik.com/

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Will these Markov Chain Monte Carlo Papers in Matlab be useful for quant trading

Will these Markov Chain  Monte Carlo Papers in Matlab be useful for quant trading

Learn more though our FREE newsletter how we will deploy these 

http://www.columbia.edu/~mh2078/MCS04/MCS_framework_FEegs.pdf  <– decent framework with code
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1964923
http://fmwww.bc.edu/ec-p/software/matlab/mbook.pdf  — 300 pages of Matlab Econometrics tutorial
http://stanfordphd.com/Markov_Chain_Monte_Carlo.html <– paid ??
http://homepages.inf.ed.ac.uk/imurray2/teaching/09mlss/slides.pdf <–start here but no code

https://www.uni-ulm.de/fileadmin/website_uni_ulm/mawi.inst.110/mitarbeiter/stenzel/MCMC/Schmidt_MCMC_2010.pdf <– 90 page complex with no source code
http://www.stat.duke.edu/~hw27/SSUR.html <–another detailed framework with source code
http://stanfordphd.com/Markov_Chain_Monte_Carlo.html

http://www.quantcode.com/modules/mylinks/viewcat.php?cid=3&orderby=titleD
http://www2.math.uu.se/fmb/courseinfo_statistics/Dat07-script8.pdf (research paper from QuantCode link above)
http://www.people.fas.harvard.edu/~plam/teaching/methods/mcmc/mcmc.pdf <– slide deck 200+ Pages (BEST end to end  intro with FULL walkthru for beginners) and R code)

http://www2.math.uu.se/fmb/courseinfo_statistics/Dat07-script8.pdf (90 pages with code and complex thoery based)
http://www.quantcode.com/modules/mylinks/viewcat.php?cid=3&orderby=titleD (Visit The Monte Carlo Framework, Examples from Finance and Generating Correlated Random Variables)

http://www.columbia.edu/~mh2078/MCS04/MCS_framework_FEegs.pdf (from quantcode.com link)

GBM=Geometric Brownian Motion

 

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Looking for papers/material about HFT

Looking for papers/material about HFT

I am looking for papers and/or material of any kind that explains the basic techniques used in HFT. Most of them are, of course, proprietary, but there must be some material with basic principles. So far, I haven’t found much on the internet.

 

==

Please have a look into http://www.ssrn.com/

You can find a lot of papers, though don’t know whether explaining the basic techniques or not. Good luck

 

 

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Any researcher here with papers on ABM for modeling financial markets?

Any researcher here with papers on ABM for modeling financial markets?

I would be interested in getting in contact with researchers who have published papers on agent based modeling for financial markets. Thanks.

—–

I spend some time on ABMs, you can check out findings in my thesis downloadable from the profile page.

 

 

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Any ones knows the papers or the scholar research about big data? I only know one paper ‘Starfish: A self-tuning system for big data analytics’ in CIDR2011!

Any ones knows the papers or the scholar research about big data? I only know one paper ‘Starfish: A self-tuning system for big data analytics’ in CIDR2011!

—–

quite lengthy paper from McKinsey but interessting.
Sorry if that is not what you are looking for, wasn’t sure but thought to post it in case you are also into surveys

http://www.mckinsey.com/mgi/publications/big_data/index.asp

——

Don’t know how far back you want to go, but you checking out Google’s MapReduce and BigTable papers could be worthwhile.

 

The nosql summer reading group has a comprehensive list:http://nosqlsummer.org/papers

 

 

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