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 ;{)}


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 ...


10

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, ...


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 ...


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 ...


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


7

@quantivity is an aggregator of interesting papers, as is http://www.thewholestreet.com/ Beyond that, I guess you must find the isolated communities of practitioners who can guide you or (or course) just follow up all the references of papers. Wilmott has a pretty solid message board for quant finance, quantopian is trying to build one for algo trading ...


7

http://replication.uni-goettingen.de/ (The below text was added by Jan Höffler who founded the wiki.) This site is a replication project for papers, so far mainly in economics but open to any field. It serves as a database of empirical studies, the availability of replication material for them and of replication studies. It can help teaching replication ...


6

This is the equity premium puzzle. (See that article for references.) My thoughts are that individual investors are rational to be risk-averse and demand a premium for bearing a type of market risk that cannot be diversified away. This risk is actually worse and more insidious than it appears, because "personal" circumstances tend to correlate in ...


6

SMM stands for single-month mortality and CPR stands for constant (or conditional) prepayment rate. They're both units of voluntary prepayment rates ($CPR = 1-(1-SMM)^{12}$). They could be based on either estimated or actual prepayments. Where to get actual MBS prepayment data will depend on what type(s) of MBS pools you're modeling (e.g. agency, ...


6

I basically agree with @John, let me expand: We want to model $y$ using a simple linear model, the most basic setup is $$ y = c + \mathbf{X}\beta $$ with $y$ the $N$ observations, $c$ a constant, $\mathbf{X}$ the $N \times M$ matrix of regressors and $\beta$ a $M$-dimensional vector of coefficients. This model has $M$ parameters, the elements of $\beta$. ...


6

What you need is more mutual information rather than Shannon entropy. It is dedicated to capture the influence of one variable on another (you can think about it as a non linear version of Pearson correlations). They are closely related since the mutual information $I$ between two variables $X$ and $Y$ reads: $$I(X;Y) = H(X,Y) - H(X|Y) - H(Y|X)$$ where $H$ ...


5

HFT, when they implement market-making like strategies, are a key element of a fragmented market to build "arbitrage bridges" between trading venues. There is a cost that for: we are all paying (probably around a fraction of the actual spread) to them, and the resiliency of the order books suffers because of their presence. As usual, there are positive and ...


5

This is the question I've been waiting for! I work at a large outsourced CIO shop and spend a lot of time evaluating different managers and the strategies they come to us with. I also know a number of people I went to school with that are now at quant funds. There are a couple of important points to keep in mind: Every respectable quantitative manager has a ...


5

Speech recognition signal processing is complex and possibly similar to the complexity of financial markets. They are similar as per characterictics the non stationarity, noise types and other aspects such us the existence of a cepstrum etc conceptual frequency and the grammar to construct and articulate concepts is not evenly and randomly distributed; so ...


5

In my opinion you should question EVERYTHING. Recently I read this article Ten Things We Should Know About Time Series by Michael McAleer which is to my opinion a good summary of some common issues in time series analysis. These ten things are: Knowledge of Econometrics and Statistics is Essential Be Aware of Measurement Errors Test for Zero Frequency, ...


5

To brush up on some of the basics, Yale has the following: http://oyc.yale.edu/economics Three of four are financial.


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