# Tag Info

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Both free and paid access to data sets conatianing company financial statement items is available from Quandl. The free data sets are sourced from the SEC based on compnay electronic filings and go back about five years. For example, you could obtain five years of MSFT's quarterly net income using the R call Quandl("RAYMOND/MSFT_NET_INCOME_Q") Lists of ...

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Surely, there is; search for aggregational gaussianity in Google Scholar or ScienceDirect. In fact, 5 minutes returns are leptokurtic and fat-tailed; then as you increase timeframe, returns become more and more normal. Yearly data is almost normal, if you have enough points.

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This mean that the reason why apple stock price went from 3 to 100 in 10years is the overnight variation in price. This is quite unexpected, if there was no overnight variation the stock price would have died a long time ago... Why is that ? Have we been lying to us ? This is because many business and financial news are reported at market close, either ...

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SEC tends to keep CUSIPS handy: http://www.sec.gov/divisions/investment/13flists.htm

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VG belongs in the family of variance-mean mixture models. Given a horizon $T$ the distribution of log-returns $f$ is a mixture of Gaussians $f_G$ with randomised mean and variance. The randomisation density is $g$ and its mean and variance increase with $T$. For the VG process this randomised factor is Gamma-distributed. More concretely, denote with ...

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As you've mentioned, it depends on the trading venue and the exact market data product that you're subscribed to. Unless otherwise stated, the data is usually updated at every occurrence of an event (explains the irregualr intervals), and often, the data is not disseminated immediately and multiple events may be batched in a single message informing you of ...

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If you're looking for all transactions against any or a given set of securities on whatever exchange, you can get that from a data provider like IQFeed or eSignal. Most of them will have tick level data going back for at least several weeks. Some people have been collecting tick and market data for quite sometime against a variety of securities, and as ...

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My main reference will be "Dan Xu, Christian Beck - Transition from lognormal to chi-square superstatistics for financial time series" Non-equilibrium statistical mechanics (more specifically, superstatistics) gives some ideas of explaining the relation between time frame and its distribution: "...to regard the time series as a superposition of local ...

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In the long term you will underperform buy & hold because you need an accuracy of at least 65%. See these papers for more: Bauer, R.; Dahlquist, J.: „Market Timing and Roulette Wheels Revisited“, CFA Institute, 2012. http://www.cfapubs.org/doi/pdf/10.2469/irpn.v2012.n1.10 Sharpe, W.: “Likely Gains from Market Timing”, Financial Analysts Journal, ...

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It's not bad but you have to backtest the method out-of-sample. Say you have discovered an indicator that works 100% in history, you still cannot be sure if it works next time. Another advise is you might want to investigate the distribution of loss when your system fails to work. If your system delivers 1% every time you trade, and loses 10% each time it ...

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The round-trip latency from point A to a matching engine at point B can be thought of being comprised of two components: $RTT_{total,A \rightarrow B} = RTT_{network\_transit,A \rightarrow B} + MPL_{matching\_engine,B}$ Where $RTT$ is the round-trip time and $MPL$ is the message processing latency (how long it takes to receive a message and produce an ...

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Most literature focus on comparing fund returns using a model alpha. A good overview is: Cahart (1997) and Berk and Binsbergen (2015). Basically you regress the fund returns on most common used factors (market return, HML, SMB, Liquidity and Momentum factors) and compare alphas after fees.

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Quantopian provides both the fundamental data (from Morningstar), as well as the backtest platform to reproduce results from the books you mentioned. Here's the introduction to our fundamentals offering: https://www.quantopian.com/posts/fundamental-data-from-morningstar-now-available-for-backtesting (disclosure: I'm the ceo of quantopian)

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If you are investing an amount $M$, split over deals indexed by $i$ and with a weight $w_i$, then your dollar position in each share will be $w_i M$. The exposure to the index will be $\sum \beta_i w_i M$ You should realize that this will not hedge idiosyncratic risks. In general, the more deals you have, the better this type of hedge should work (assuming ...

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Start with: http://www1.nyse.com/pdfs/closings.pdf which covers all closings through 2011 then use the following... 2012/2013: http://www1.nyse.com/press/1294398514465.html Weather related closures happened on Monday, Oct. 29, 2012 and Tuesday, Oct. 30, 2012. (http://markets.nyx.com/nyse/trader-updates/view/11507) 2014/2015: ...

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As background, Floating point precision is a way of storing numbers such that the precision is relative to the largest digit. For instance, the number $0.00123$ stored in fixed precision needs 6 digits of precision (3 zeros and the 3 non-zero numbers). However, this same number stored as floating point precision $1.23 \cdot 10^{-3}$ needs only 3 ...

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I faced the same issue some years ago and I solved by implementing the R script reported here; now, with new Yahoo disclaimer rules, it seems to be broken, but, anyway you should be able to replicate the data mining process using that script together with this. If you're pretty confident with R, you should be able to do that. Alternatively, you can visit ...

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Some of the issues with this sort of request is: a) Today's S&P 500 components are not the same from 1 Jul 2013. By using today's components you are introducing pre-inclusion/survivorship bias. Are you going to be able to find data on the delisted stocks? eg. Since 1 Jul 2013, Sprint Corporation, BMC Software, NYSE Euronext, Molex, Life Technologies, ...

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$\sigma S$ is in units of dollars per square root of a unit of time. $\sigma$ is usually quoted as an annual or daily percentage. $dX ^2$ is in units of time, as $E[(dX)^2] = dt$. Here is an online tutorial which you may find helpful. EDIT by kotozna: $\sigma$ has dimensions 1/(square root of time) and $dX$ has dimensions square root of time. ...

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I'll assume the rest of the world doesn't have access to a similar oracle. Indeed if it did future returns would converge to the risk free rate instantly. In this case, I would prefer holding the AAA bond instead of the stock because the rest of the world would consider it to be much less risky. As a financial institution, reducing the risk of your ...

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The January effect is easy to demonstrate. Always the same dates for multiple shares.

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The easy answer would be to look for exchanges that only have pit trading, ie people in a room that match up buyers and sellers. As far as I know no such exchange exists any more. In my opinion the best you are going to be able to do is to compare the NYSE now with the NYSE in 1998, which is to say you wont be able to do much of a comparison at all as ...

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The TA_lib Technical Analysis library here has open source code for numerous indicators.

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Both R and Python can do this very nicely. For Python you would need the pandas package and its dependencies. pandas has a lot of basic statistics, but for more advanced statistics like it looks like you want to do, you can use the statsmodels package, which can work directly with pandas data types. It can also download the csv files directly off the ...

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Quote: Starting in 2003, the NYSE started disseminating automatically, with a software called autoquote, any change in the best quotes in its listed stocks. Before that specialists had to update manually new inside quotes in the LOB. This implementation considerably accelerated the speed at which algorithmic traders receive information Endquote Source: ...

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Directional forecast is insufficient. You could have a signal that has 100% accuracy and you would not necessarily be able to profit from it because of transaction cost, implementation etc.

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It's not unusual to find a financial time series with positive trend samples biased between 55-60%, depending on the period sampled. Stocks tend to have an upward drift over the long run. When you account for the drift, I would say, that number is really not much better than chance. A better way to verify your question would be to make certain to build ...

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Having locked markets is bad in the sense it freezes the price formation process. Ideally we would like to have a price on as much instruments as possible so that we know their value. it prevent investors to buy (or sell) it and thus adds frictions, transaction costs, etc. We would like to enable investors to buy or sell when they need/want, to let the ...

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The adopting release of Reg NMS http://www.sec.gov/rules/final/34-51808.pdf discusses the problem(s) they were looking to solve. That will provide the SEC's thought process.

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I think you are confusing the goal with the means. The calculation of the PE is not the goal, the true goal is assessing whether a particular stock is an interesting investment opportunity (cheap) under an investment thesis (set of hypotheses). Therefore, there is an infinite number of ways to calculate PE ratios, as a results of a set of different ...

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