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15

Ledoit and Wolf shrinkage methods ("Honey I shrunk the sample covariance matrix") Ceria and Stubbs - Robust optimization literature (2006) Stock & Watson (2002ab) - papers on large N small P estimation Rockafellar & Uryasev (2000) - "Optimization of CVaR and coherent risk measures" Sorensen, Qian, Hua - "Quantitative Portfolio Management" Ang ...


11

Very good question! I think part of the answer lies in the structure of the financial industry. Some anomalies have a certain kind of structure which cannot be exploited by the players that are big enough to let the anomaly disappear. I would put e.g. the Turn-of-the-month effect (TOTM) into this category since big funds just can't turn their whole ...


11

These are all examples on Ito Formula in its general form (with quadratic variations):


9

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 Hedge Fund Performance and Generalized Sharpe Ratios I would go with the first paper.


8

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 persistance of certain anomalies. A good starting ...


8

I believe this is a nice paper for you to start with. Check out what references it cited and who cited it. Markov Chain Monte Carlo Analysis of Option Pricing Models "Use the Markov Chain Monte Carlo (MCMC) method to investigate a large class of continuous-time option pricing models. These include: constant-volatility, stochastic volatility, price ...


7

Grinold and Kahn (2000) remains the bible for people just starting to get into quantitative portfolio management. Some readers may prefer the treatment in Litterman (2003). Both of these, however, are thorough books covering all the foundational material. Most of the recent work in portfolio management has built upon the research covered in those books. ...


7

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, ...


7

The first book that comes to mind that is written in the style of Definition - Proposition - Proof is: Bjork - Arbitrage Theory in Continuous Time It's pretty well written and can get quite technical. Probably a more common reference is the two-volume set: Shreve - Stochastic Calculus for Finance I & II The first part deals with the binomial ...


7

Stochastics are usually applied in the field of derivatives pricing. In this setting the task is to price a derivative such that it fits into the landscape of tradable instruments (no-arbitrage). We work using the risk-neutral measure - usually denoted by $Q$. The measure is derived from other traded instruments. In risk analysis (e.g. calculate the VaR, ES ...


6

Check this document out: link to pdf file Also, if you are concerned with actual performance of your code and want to implement efficient code then gsl libraries would be the first place look at: link. It's got everything you need.


6

Check Noncommutative Geometry and Stochastic Calculus: Applications in Mathematical Finance


6

Tsay's Analysis of Financial Time Series should be what you're looking for.


5

Forward interest rates are negative whenever the yield curve is negatively sloped. The US term structure was inverted most recently around 2007. Hard to find bank deposits that have negative yields (find countries experiencing deflation and you may find it), however, treasury bills during recent times of financial stress have yielded a negative rate. The ...


5

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 ...


5

Introductory: "Introduction to the Mathematics of Financial Derivatives"; Salih Neftci More mathematical: "Stochastic Calculus for Finance I and II"; Steven Shreve


5

There is Monte Carlo Simulation and there is Monte Carlo Simulation. If you are referring to a simple question like simulating dice or calculation of $\pi$ or even vanilla option price calculation, it is one thing and "concisely" available. I recommend get a gist of small examples from CS books and then get on with finance. But if you are referring ...


5

I think that "An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)" suggested by KarolisR could be useful but too much machine learning oriented. Moreover, such a book is for beginners. As a thorough book (PhD level) on statistics, I suggest "Statistical Inference" by Casella and Berger.


5

Two theoretical explanations regarding the long memory are given by: The mixture of distributions hypothesis of Tauchen and Pitts (1983). Essentially this hypothesis states that trading volume and return are driven by the same information flow process, therefore trading volume and return volatility should share the same long range dependence. ( see ...


4

Here example of practical application of Markov ideas to trading.


4

I think you might be interested by an article I mentioned in this post: Carlo Acerbi from MSCI presents in this presentation an innovative approach to liquidity risk. The idea is basically to model how liquid an asset is and how your portfolio allocation should take this risk into account. This way of seeing risk is in my opinion pretty interesting an ...


4

Theta Calculus, a system for representation of complex financial instruments. Kupper & Drapeau's unification of risk concepts. Several papers by Schmid, Bodnar, Okhrin on optimal portfolio weights and tests of same. For example, A test for the weights of the global minimum variance portfolio in an elliptical model. Similarly, Kan and Smith's work on the ...


4

I wouldn't put too much faith in IBES forecasts. You may remember this situation: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=889322 (In case the above link doesn't work, Google "Rewriting History Alexander Ljungqvist"). You'll find lots of excuses for worthless forecasts: http://www.princeton.edu/~hhong/rje-analyst.pdf Below is a graph that I ...


4

Here are a few more papers about MCMC and alike methods for derivative pricing and co. : Blanchet-Scalliet, Patras - Counterparty risk valuation for CDS Jasra, Del Moral - Sequential Monte Carlo Methods for Option Pricing Frey, Schmidt - Filtering and Incomplete Information in Credit Risk Peters, Briers, Shevchenko, Doucet - Calibration and Filtering for ...


4

Joel Greenblatt's "magic formula" is similar in spirit to classic value styles. He has a discussion of why he thinks it will continue to work (despite it's simplicity and public knowledge) around p. 73 in his Little Book that Beats the Market (see ...


4

I would even stick to the original paper by Sharpe (1966): Mutual Fund Performance. The Journal of Business Vol. 39, No. 1, Part 2 pp.119--138 If you look at the numbers on Page 6 you can see that the funds sharpe ratios roughly are between $0$ and $1$. Since the Sharpe ratio already adjusts for the risk-free rate, you cannot really argue about its ...


4

I would start with explaining random walk (this should be fairly simple) and then making a connection to heat equation in discrete time. This paper is doing exactly this and by leaving out technicalities you should make this pretty intuitive for students. Basically the intuition is as follows: At each integer time unit, the heat at each point is spread ...


4

I thought this was an interesting example to add. It concerns a "ratio model" of habit (as opposed to a "difference" model of habit). See, for example, Abel (1990, American Economic Review). Let $$ x_t = \lambda \int_{-\infty}^t e^{-\lambda(t-s)} c_s ds. $$ (For context, $x_t$ is a log habit index that is given by a geometric average of past consumption, ...


4

There are plenty of books on portfolio issues built according to formula "some theory + some R code (or Matlab, or S - which is very similar to R)". See for example Pfaff B. Financial Risk Modelling and Portfolio Optimization with R.// 2013. Best M.J. Portfolio Optimization. Chapman & Hall, 2010. W├╝rtz D. et al. Portfolio Optimization with ...



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