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The volatility in the indices long ago was similar in magnitude to what it is today. The problem you are seeing in your plots is one of compounding and scaling. Think of it this way- back in the mid 70's the magnitude of NASDAQ pricing was around \$100. Today it is on the order of \$4000, a change of 40x. In linear terms, a 1% change in the index today (\...

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The solution to my question can be found at the following webpage : http://rankandfiled.com/#/data/tickers For every stock you have on which stock exchange it is being traded, and the CIK (Central index key) which is exactly what I was searching for. I post it here since it will probably be very useful to many people.

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In case of NYSE equities rule 7.6 reads: "The minimum price variation ("MPV") for quoting and entry of orders in securities traded on the NYSE Arca Marketplace is USD 0.01, with the exception of securities that are priced less than USD 1.00 for which the MPV for quoting and entry of orders is USD 0.0001." For NASDAQ equities rule 4701 (k) reads: "The term "...

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NASDAQ provides a list of traded stocks. It is available on their FTP server: ftp.nasdaqtrader.com. There you will find two files of interest: nasdaqlisted.txt and otherlisted.txt. nasdaqlisted.txt lists the NASDAQ stocks. otherlisted.txt contains a field that identifies the exchange, which includes NYSE. None of these will give you the CIK, but the ...

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As @babelproofreader mentioned, I recently blogged about the Roll model (see the original paper), which provides a very simple method for inferring the bid/ask spread based on trade prices. In short, you can estimate the cost using using the covariance: $c = \sqrt{\gamma_1}$. Where $\gamma_1$ is the $Cov(r_t, r_{t-1})$. (The R code is provided in my post). ...

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Neither. Nasdaq publishes a close price at 4:01:30 p.m. ET known as the Nasdaq Official Close Price ("NOCP"). Nasdaq also amends this price up to 5:15 p.m. ET if any trades that were used to calculate the NOCP are canceled or corrected. You can get NOCP prices directly from Nasdaq each day on their website.

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First, have a look at Market Microstructure in Practice (Laruelle et L) to have generic explanations about all this. In short: Equity markets are fragmented: it means to buy or sell shares, you connect (via a broker) to a server on which you send a message with a side (buy or sell), a max/min price and a quantity. these servers are technically matching ...

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Your best bet might be to find lists of the companies on each exchange and cross-reference them with a list of the companies on the Russell 2000. It shouldn't be too hard to write a little script in python or something that does the comparison for you. It appears that nasdaq.com has a tool that allows you to download csv lists of the stocks listed on the ...

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Simply put, no, you won't find this. The most basic one-port ITCH feed with no redistribution rights runs \$750/mo. Historical ITCH data which is useful for backtesting is \$1,000/mo. with a 12 month initial minimum contract. Fees for distributors are much, much more expensive (all costs can be found on the NASDAQ OMX website), and the restrictions on ...

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ITCH does not disseminate any identifiers for the buy-side. They have a match number (used to correct or break trades) and a reference number (for displayed liquidity) and that's it. No other identifying features are present.

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To construct best bid/ask from ITCH you must build a book incrementally from the messages in the data. Every message, except for system oriented messages, and non-displayed Trades, represent an order or an action on an order. Process the data, build a book, and you will naturally be left with the best bid/ask at the top of each side.

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I was able to identify significant participants by order size on CME exchange. I think ITCH is even more informative that CME's data format. The trick is to learn very closely the incremental data and the order in which this data arrives. We can assume that exchange's Matching Engine and its market data distribution algorithm are programmed machines, ...

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Each listing exchange maintains lists of exchange-initiated and issuer-initiated delistings. Per the exchanges, an issue will appear on this list the first trading day after the issuer provides the venue with notification of its intent to voluntarily delist. An issue will also appear on this list if it has been suspended for failure to meet continued listing ...

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What Tick data you have in mind? NASDAQ ITCH is tick data but you have to construct the limit order book yourself to keep track of the best bid and ask price for each stocks. Not a trivial task. If you get TAQ data, you will get the best bid and ask (NBBO) but TAQ data has some issues like no odd-lot trades and trades are not mark buyer or seller initiated.

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As suggested by @Bob Jansen: QA Direct - it is quite expensive though. I've used it in past in the form MS SQL database. It has good enough documentation and query like the one in the question are quite possible to implement in single SQL statement.

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http://tsp.finra.org/finra_org/ticksizepilot/TSPilotSecurities.txt The relevant field being "Tick_Size_Pilot_Program_Group", Gx or C categorization. There is no formula to determine this as this rule is new, on a trial basis and the participating listings aren't chosen completely objectively. It's designed to help market making firms at the expense of ...

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The way I managed to solve this was by scrapping the broker website and compile a list containing Symbol, Primary Exchange, Tick Increment, ISIN, CONID, ASSETID of 6589 Equities from NASDAQ, NYSE and AMEX. Here's a gist of the list:

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4.2.7 Limit Up – Limit Down (LULD) Auction Collar Indicates the auction collar thresholds within which a paused security can reopen following a LULD Trading Pause Name Offset Length Value Notes Message Type 0 1 “J” LULD Auction Collar

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Date of IPO completion Company name or ticker (better yet, both) Total US\$ amount raised in IPO Total number of shares sold in IPO Renaissance Capital has this data. They do have an option to sign up for a free 1-week trial. I don't know what the free trial gives you compared to being a member as I have had a membership for years. ...

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Usually you can extract information/data like this from financial data vendors (Bloomberg, Reuters, etc.). I am going to explain how you can get volumes of a stock traded on different exchanges using Bloomberg: Type in the search box AAPL Hit Type in VWAP Then you can play around with different parameters like period, price, volume, etc. Under the ...

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I can see that you are mentioning quantmod so you are probably using R, but in python it's quite straightforward to download the FF values through pandas. Please see this for a sample implementation and you can find further info about the data downloaded here Hope that helps.

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From a feed perspective, you can take a look at the feed spec, it should be mentioned among descriptions of the data types e.g. fixed point integer with 4 implied decimal places and be applied across all symbols. This should be universal so you could hardcode it. Thereafter, you can look up the MPV in the rule books - see this answer: https://quant....

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Since NYSE merged with ARCA about 10 years ago. No specific legislation. All stocks may be traded on ECN's as well as their primary markets. The line that distinguishes them nowadays is quite obscured. The main differences are liquidity (create/take) fees, order types accepted, opening/closing auctions, etc. For the average person the differences are ...

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First consider if you really need to be connected to just the Nasdaq or should you be using a broker that can connect you to all exchanges. Almost certainly the answer is the later. If that is the case then Interactive Brokers is probably the way you want to go. I've setup several CTAs to get started with IB and its probably the best 3rd party to get ...

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The built in data does not seem go quite 5 years back, but you can access dividend data within Mathematica / WolframCloud as well: FinancialData["NASDAQ:AAPL", "Dividend", {"Jan. 1, 2010,", "Nov. 4, 2015"}] To get a list of all symbols on the NASDAQ: list = FinancialData["NASDAQ:*", "Lookup"] To get/organize data for several symbols on this list (first 5 ...

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I developed a RESTful JSON API (https://mapping-api.herokuapp.com/) for this purpose. You can provide the exchange name, and the API returns all companies listed at the exchange in JSON format. You can also send any CIK, company ticker, or company name, and the API returns the mapping. Examples List Companies by Exchange Request: GET https://mapping-api....

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I use the following approach to find CIKs for all (read:most) listed companies: Obtain a list of all stock symbols (tickers). I use the daily Nasdaq Traded file published to the Nasdaq FTP: ftp://ftp.nasdaqtrader.com/SymbolDirectory/nasdaqtraded.txt Note that this file isn't officially documented by Nasdaq on their Symbol Directory Definitions page but my ...

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Always use a semi-logarithmic scale when looking at prices. It makes percentage moves of equal heights on your graphs.

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Regarding the second part of your question, - if you have relatively precise timestamps, you can use those to distinguish the cases you're interested. E.g. if one party took all three levels, the timestamps will be very close, or identical.

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The cross-validation procedure does not turn on the choice of algorithm. Yes - calculate the prediction error of the fitted models when predicting the V'th part of the data. Combine the V estimates of prediction average using a simple average. Subsets should be randomly sampled (roughly equally sized). 2a. Subsets should not overlap. No. As long as the ...

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