# Tag Info

31

Because of: The (extreme) dominance of noise over signal The prevalence of non-repeating patterns (many of which we know are not going to repeat) A pathetic sample size for cross-validation Regime changes due to exogenous events. These are typically in the cross-val window which makes it even worse. (GFC, financial integration, trade law changes, interest ...

20

I know that I have seen things like this in the past. Wasn't there something recently that used Twitter? Here are a few recent papers as examples, although I will be brutally honest that I don't know if they speak to your decent quality requirement: "Trading Strategies to Exploit Blog and News Sentiment" (Zhang, Skiena 2010) "The Predictive Power of ...

20

I recently read "Modeling financial data with stable distributions" (Nolan 2005) which gives a survey of this area and might be of interest (I believe it was contained in "Handbook of Heavy Tailed Distributions in Finance"). Another more recent reference is "Alpha-Stable Paradigm in Financial Markets" (2008). I'm not aware of anything covering "risk of ...

19

Yahoo rounds the adjusted price to 2 decimals even though dividend amounts often have 3 decimal places. Since they apply the adjustment formula to adjusted prices, if you go far enough back in time, the value they give for Adjusted Price will be different than it would be if there were no rounding. edit: For example, for C (Citigroup), on January 2, 1990, ...

19

The way you do it in the first place is a discretization of the Geometric Brownian Motion (GBM) process. This method is most useful when you want to compute the path between $S_0$ and $S_t$, i.e. you want to know all the intermediary points $S_i$ for $0 \leq i \leq t$. The second equation is a closed form solution for the GBM given $S_0$. A simple ...

17

There are several application of Lévy alpha-stable distributions to finance, especially in insurance and reinsurance. I believe that Embrechts-Kluppelberg-Mikosh's "Modelling Extremal Events for Insurance and Finance" is still an excellent reference. However, in the modeling of stock prices, this line of research is essentially inactive. The reason is that ...

17

VIX measures volatility. It doesn't always go up if stocks go down.

16

From what I remember, there is no real relation between Markov and Martingale, and my intuition was confirmed by this post. Basically, it says that you can say neither of the following: If A is Markov, then A is a martingale. If A is a martingale, then A is Markov. further down the post, you can find two counter examples: $dX_t = a dt + \sigma dW_t$ is ...

16

Let's assume there is no adjustment and that a stock's price is the same after a dividend payment as before. Then I could get free money simply by buying a stock the day before the ex-date and then selling the stock right after the dividend distribution. Clearly no such arbitrage opportunity exists. Therefore, the price of the stock after the dividend ...

13

Do not passively use Yahoo where you need reliable historical data; it will just fail at one point (from what I have seen due to corporate actions/dividends not properly implemented). Paying for a single alternative data source will not save you either (Bloomberg sometimes reports crazy intraday prices); the only way is to write some data cleaning routines (...

13

You can forecast stock prices thru time-series models, cross-sectional, or panel models. There is considerable variation within these categories. In time-series models you would use an auto-regressive model such as an AR(1) where the independent variable is the dependent variable lagged by one period. Naturally, an AR(2) would consist of 2 lags and so on. ...

13

Interactive Brokers does have a .NET API, albeit a free (as in speach) one written by Karl Schulze, not IB themselves. http://www.dinosaurtech.com/utilities/ It's written in C# (and IMHO well written). I've examined both it and the Java API and find the .NET version more to my liking. That's probably just because I'm more familiar with .NET than I am ...

13

I will defer to others answering the parts of your question concerning the relationship between Markov processes and martingales (@SRKX has already given a good explanation of the relationship) and concerning statistical testing. Broadly, however, it is not possible to "prove" either assumption, but only to fail to reject them. A Non-Random Walk Down Wall ...

12

For "maximum pessimism" you should calculate thus: for longs - enter at the bar high and exit at the bar low on bar following signal bar for shorts - enter at the bar low and exit at the bar high on bar following signal bar I had previously heard this approach to back testing called the "torture test."

11

Just FYI the Reuters product is called NewsScope. The selling point is that they provide a sentiment reading per news item so the user doesn't have to do any NLP. If you have a Reuters sales rep or contact them then they can get you several research/white papers that are interesting. Here are the ones I have been able to find online (my sales rep has ...

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 ...

10

The $R^2$s are usually close to zero for single stock regressions. The big $R^2$s that a lot of asset pricing research shows is by forming portfolios. Forming portfolios cancels a lot of the idiosyncratic returns, which has a smoothing effect. The $R^2$s should be low here, although I don't see any in the paper for you to compare. This probably means they ...

10

VIX also has a lot of complexities that make it a less-than-ideal hedging tool if you're buying a VIX ETF. http://vixandmore.blogspot.com/ goes into it at length and can probably also answer any questions you have about the VIX as a hedge. To expand on what @barrycarter said, the VIX is better as a hedge against kurtosis, not against downward movements.

10

I am still a beginner to this topic, and have been working through Cont and Tankov's textbook Financial Modelling With Jump Processes (2003), which is a fairly elementary treatment of the subject. I think a revised second edition is to come out later this year. One interesting area of applications that has become more prominent with a recent wave of papers ...

10

Google and Yahoo finance have a survivorship bias -- they only include firms that are still around. I know of no free source that provides the data you seek. I get my data from Compustat and CRSP via the Wharton Resource Data Service, but these (or Bloomberg or Reuters) are likely too expensive for an individual. Have you asked your broker if they will sell ...

10

You should consider an unsupervised learning algorithm such as K-nearest neighbor ('KNN'). KNN will measure the distance amongst the observations in your space. You can and probably should consider alternative distance functions (besides euclidean) particularly if you are clustering on features such as returns which have outliers. There are quite a few ...

10

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-...

10

You can pull a list of all stocks easily. See this question. You can get nasdaqlisted.txt and otherlisted.txt from here. nasdaqlisted.txt is clearly Tape C. otherlisted.txt contains an Exchange column which can be used to determine Tape A or B. If it is N it's listed at NYSE and therefore Tape A, otherwise it's Tape B. Also, NYSE publishes a symbol list ...

9

I just ran across an interesting presentation comparing the effectiveness of Normal, Cauchy, and Student's-t distributions in modeling the S&P. It concludes that the normal distribution underestimates extreme movements, the Cauchy overestimates them (although a comment on the presentation points out that Mandelbrot used different parameters than the ...

8

Yahoo's historical data is sometimes missing dividends. For example: http://finance.yahoo.com/q/hp?s=VWINX&a=00&b=1&c=2010&d=11&e=20&f=2011&g=v (VWINX) is missing two dividends for 2011, though it has the ones for 2010. Also, this paper: http://arxiv.org/PS_cache/arxiv/pdf/1105/1105.2956v1.pdf from 2010 reports Yahoo finance ...

8

Sell Side Macquarie Quant - Venkat Eleswarapu Bernstein Research - Vadim Zlotnikov Nomura - Joe Mezrich JPMorgan Investment Strategies series Societe Generale - Alain Bokobza Independent CXO Advisory Empirical Finance Blog Russell Indexes: Research and Insights MSCI Research Papers Axioma Research Papers

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 recommend reading Cao, Hansch, and Wang (2004) "The Informational Content of an Open Limit Order Book". They present a simple model for an order-book price called the weighted price ($\mbox{WP}$): $$\mbox{WP}^{n_1 - n_2} = \frac{\sum_{j=n_1}^{n_2} (Q_j^d P_j^d + Q_j^s P_j^s)}{(Q_j^d + Q_j^s)}$$ Where: $n$ is the order book level $Q_j$ is the size at ...

7

This is the separable differential equation for simple continuous compounding! See this very accessible article for a step-by-step derivation (esp. under continuous compounding): http://plus.maths.org/content/have-we-caught-your-interest

7

You can consider the following two methods: If you have Matlab, you can use the following code: Volume Weighted Average Price from Intra-Daily Data This package allows you to [1] retrieve intra-daily stock price data from Google Finance, [2] calculate the VWAP at the end of each trading day and [3] transform intra-daily data to a daily format. If ...

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