32

Many of them are on my website at emanuelderman.com. Others I probably have anyway. Feel free to email me


25

Hah! There is no such thing as the “rigorous mathematical underpinning” of high frequency trading - because HFT, like all trading, is not primarily a mathematical endeavour. It’s true that many people who work in HFT have a mathematical background, but that’s because the tools of applied math and statistics are useful when analysing the large amounts of ...


23

In fact you have three papers available to go further: The Avellaneda-Stoikov one, with proper model and an approximate solution The Bayraktar-Ludvkosli one, with a solution for the linear utility function The L-Guéant-Fernandez one, with a full solution for a generic utility function I prefer the last one ;{)}


18

Nick Higham's specialty is algorithms to find the nearest correlation matrix. His older work involved increased performance (in order-of-convergence terms) of techniques that successively projected a nearly-positive-semi-definite matrix onto the positive semidefinite space. Perhaps even more interesting, from the practitioner point of view, is his ...


16

A very conservative stand is to distinguish between anomalies and arbitrage opportunities. Roughly speaking, while an arbitrage opportunity is risk-free by definition, an anomaly allows for unaccounted risk factors. It is the magnitude of these unidentified risk factors that might determine the long term persistence of certain anomalies. A good starting ...


15

Eric Zivot's Introduction to Computational Finance and Financial Econometrics on Coursera.


15

ArXiv is the standard resource of preprints in the field of physics. Almost all papers in physics are uploaded here before they are submitted to a journal. They also have a quantitative finance part: http://arxiv.org/archive/q-fin This section is not nearly as active as the physics-part of ArXiv though. Hopefully this will change in the future. There is ...


12

Here are couple references. Especially the first link to Andy Lo's paper contains a list of Sharpe ratios of popular mutual and hedge funds: The Statistics of Sharpe Ratios Dow Jones Credit Suisse Hedge Fund Index Generalized Sharpe Ratios and Portfolio Performance Evaluation I would go with the first paper.


11

I find this one very helpful: Re-Examining the Hidden Costs of the Stop-Loss by Wilson Ma, Guy Morita, Kira Detko Abstract: In this paper, we present general implications of the impact of stop-losses to future returns. The use of stop-losses change return distributions, but not in the way that one would typically expect. We find that while stop-...


11

The answer your are looking for might be the story in "Benchmarking Measures of Investment Performance with Perfect-Foresight and Bankrupt Asset Allocation Strategies", by Grauer (Journal of Portfolio Management). While this work main concerns are the differential ranking of various performance measures and with negative betas for market timing strategies, ...


11

I had read some of them; actually, it does not exist an on-line library that collected them (or, better, it existed here, but it seems the website does not work anymore). I reported here below some of them that you did not find: More Than You Ever Wanted To Know* About Volatility Swaps Model Risk The Volatility Smile And Its implied Tree Enhanced Numerical ...


11

I would argue, taking a note from John von Neumman, that quantitative finance lacks rigorous underpinnings. Von Neumann warned in 1953 that many things that look like proofs in economics and finance depended on problems that were yet to be solved in mathematics, and where economists were assuming solutions into existence. As the problems were solved in math,...


10

Joel Hasbrouck (imho, a leading expert in market microstructure) has a paper on this: http://people.stern.nyu.edu/jhasbrou/Research/Working%20Papers/HS10-11-10.pdf From the abstract: Our conclusion is that increased low-latency activity improves traditional market quality measures such as short-term volatility, spreads, and displayed depth in the limit ...


9

At strikes distant from the forward value, pretending that options have some meaningful implied volatility gets kind of silly. Options really have prices (both bids and offers), and we all just translate that to volatility because doing so provides a convenient normalization. Just to take one example, discrete price quoting completely obfuscates the ...


9

Indeed, algorithmic trading is a very hidden subject. All I can help you with are some industry-specific terms which might speed up your search for relevant papers and information: Risk of ruin tables (Peak-to-valley) drawdown (maximum drawdown, duration of drawdown etc.) Number of consecutive losses Confidence intervals Empirical distributions (for risk ...


9

If you want to address interesting problems that are interesting for financial mathematics, I do not believe you have the good list. Pricing. For instance, most of explicit formulas for pricing that are not available yet will never be. In this direction, you should have a look at simulation techniques. See for instance Nonlinear Option Pricing. Interesting ...


9

I would say that most ML methods risk overfitting and it depends very much on the asset class. The only area where more sophisticated ML methods such as deep learning appear to make a major difference is in cash equities, where the feature space is very rich (NLP, news and announcements, corporate earnings, other financials) and the data is relatively good, ...


8

Deutsche Bank's Quantitative Strategy (US) team put together the following piece on this topic (note: their research is available for clients, but I found that somebody uploaded the piece to a sketchy web site). In case the link dies, some of the academic papers they site are: Akbras, F., E. Kocatulum, and S. Sorescu, 2008, “Mispricing following public ...


8

By definition, the average investor holds the market portfolio. Risk aversion can be measured as the slope (i.e. ratio of expected returns to volatility) on the efficient frontier. Therefore, the risk aversion of the average investor assuming the S&P500 is the proxy for the market portfolio is the expected returns of the S&P 500 divided by the ...


8

While not strictly quantitative finance, for the first year in the PhD I found this Youtube-Channel extremely helpful: http://www.youtube.com/user/mathematicalmonk I covers almost only math, but does a very good job at explaining the basics of probability theory. Most people will already have mastered that stuff, but it will surely help those unfamiliar ...


8

In Oracle Crystal Ball, we use an old algorithm, that works pretty well and converges fast. It is from Iman-Conovar. Here is the reference: Iman, R.L., Conover, W.J. 1982. A distribution-free approach to inducing rank correlation among input variables. Commun. Statist.-Simula. Computa. 11, 311-334. That said, Prof. Higham's method based on optimization ...


8

Well as far as I know it is a really hard but interesting question. Asymptotics of smile in the strike direction is not known in a model free way as far as I know. I think I can remember that nevertheless you have upper and lower bounds if you know something about the underlying dynamics and especially the first moment of explosion. I can't remember the ...


8

There's a strong theoretical argument that makes the case for active management that is also supported by empirical research. First, check out Jonathan Berk's paper "Five Myths of Active Management". The paper reads like a clever Gedankenexperiment. Starting with a theoretical approach is better than starting with an empirical approach because as Berk ...


7

A cautionary tale on all these approaches it told by Tim Loughran and Bill MacDonald in the Journal of Finance, 2011 (When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks, here). In their analysis they show that the commonly used Harvard Psychosociological Dictionary is inadequate for sentiment classification in a financial ...


7

The short answer is that I don't know, but your question gives some hints about how to find out. The key thing for me is that you want a minimum variance portfolio. I don't think you should be thinking about some abstract mathematical operation that is "best", but rather look over a few mathematical operations and see which seems to work best for your ...


7

As far as I know the short answer is negative: there isn't a well developed theory of how to forecast cross-sectional realized volatility. From the perspective of statistics/econometrics, most of the recent research is still trying to find its way around estimation of cross-sectional realized volatility, and so far even in these area the progress is slow. ...


7

Personally, I am very skeptical of the claims in "Twitter mood predicts the stock market". There are several other papers with similar claims, but not so much good quality research is available. Arguably, the sweet bits of these approaches are not public. A sounder approach is to dig at the relationship between social media activity and relate it to the ...


7

I highly doubt there are useful studies around. Think about it, the answers of such data sets must be highly skewed simply because there are price takers in the market that are extremely secretive about profits and losses. You will only get one side of the story and it most likely skews the results by quite a bit. Also, keep in mind many institutions do ...


7

If you have the mathematical sophistication, you should review the original papers referenced on the Equity Premium Puzzle page, particularly Mehra and Prescott (1985). Note, however, that contrary to other opinions on this page, the puzzle is NOT that there is an equity risk premium. On the contrary, the puzzle is that the premium had been so high, at ...


7

Though it is not an extensive list , this is what I know of. Other may add more. Journals Journal of Financial and Quantitative Analysis (JFQA) Risk Papers SSRN ARXIV Conferences quantcongresseurope More at Risk Website HPC and Wall Street GARP


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