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    Friday, March 9, 2018

    Stock Market - Markets recapture late Feb. dip; Nasdaq back at ATHs

    Stock Market - Markets recapture late Feb. dip; Nasdaq back at ATHs


    Markets recapture late Feb. dip; Nasdaq back at ATHs

    Posted: 09 Mar 2018 10:35 AM PST

    Noob question here

    Posted: 09 Mar 2018 05:53 AM PST

    When do you guys sell your stock? Do you wait for it to hit a certain % gain? Is it more of a gut feeling? Do you look for it to be overvalued? Just curious as to how people approach this aspect of the market because I'm not sure how to go about selling.

    submitted by /u/AlexG_51
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    What's the best app/site for a noob to use for day trading?

    Posted: 09 Mar 2018 07:26 AM PST

    I'm VERY new to investing. My father has been using a broker in town and has been encouraging me to start with them...but being so new to all this, I'm nervous about throwing $5000 at them just to open an account. I'd be much more comfortable investing a few hundred dollars on my own to learn how this all works, then after I've gotten my feet wet...maybe dive in a bit deeper.

    What are some good apps/sites to use for noobs who want to get involved in a little bit of day trading?

    Other suggestions/tips are also welcomed.

    submitted by /u/MattIsHulk
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    Can someone please tell me what I did wrong with ENT?

    Posted: 09 Mar 2018 07:52 PM PST

    Thought Golden Eagle Entertainment was a good buy this morning, but it lost all day. (In @ 1.74) Hoping some nice Redditors can give me some insight/clues as to what i'm missing. TYVM

    submitted by /u/DontTradeMeBRO
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    I posted my sentiment research tool here a couple of weeks ago and you guys liked it -- lots of progress has been made since -- easily track the sentiment of news surrounding over 3000 securities and follow a ML system which classifies thousands of companies everyday

    Posted: 09 Mar 2018 08:18 AM PST

    Here's the original post: https://www.reddit.com/r/StockMarket/comments/7ypjga/easily_track_prevailing_sentiment_for_over_2500/

    Here's a link to the site: https://quikfo.com
    Here's the link to the Twitter bot: https://twitter.com/myQuikfo
    Before anyone needs to ask: this tool was, and remains, entirely free to use!

    Since the last time I posted I have:
    1. Reworked the UI/optimized mobile to some degree
    2. Reworked the entire classification system to use industry specific training data rather than one market-wide weighting of words
    3. Added comment sections so that users can post their own thoughts/ideas/feedback/etc
    4. Have begun analyzes article content and summarizing this content into key sentences for use in the classification, allowing the system to move past just basic headline analysis.
    5. Fixed about 1000 bugs behind the scenes lol
    6. Implemented a login/follow/newsfeed system so now you can create an account and follow all of the companies that you're most interested in... these companies will appear ranked by qScore in your newsfeed
    7. I built out a significant portion of the API so that other developers can begin to play around with the data

    Here's a glimpse at what's on the horizon:
    1. My major goal over the next few weeks in to build and implement a huge spam filtering system. Basically a big system which will learn from user feedback and reports of "bad data" and be able to remove bad data, duplicate data, etc before it makes its way into the scoring algorithms, or worse yet, the training data.
    2. I want to further optimize the frontend UI for mobile and desktop
    3. I want to build out more charts and visuals like the bubble chart
    4. The API could use more parameters to add power to the potential queries

    Your feedback was super helpful last time I posted this, and lots has been developed since then, so I wanted to bring it back for another round of testing and feedback!

    For those of you who didn't read the last post, Quikfo is a system which I'm making for my senior thesis. It uses a basic machine learning model which loops through data collection, data preparation, data modeling, and data analysis to train a bayesian classifier and produce rankings regarding which companies have news which most closely matches the news of companies who are about to see upward or downward price movements. So, that was a mouthful, let me break it down for you:
    -the system collects news data on companies everyday
    -at the end of everyday Quikfo analyzes which companies did extraordinarily well or poorly and finds patterns between these out-performers' news and their price movement
    -this data news and its patterns with next-day upward and downward price movement are then loaded into training sets for a classifying program which employs bayes theorem
    -using this training data and the current news surrounding a company, this classifier can now create a prediction and score the company from 0 to 100; this score can effectively be considered "the probability that this company's news matches the news of the positive set of companies"

    This system is nothing more than a helpful research tool, as companies often get scored highly because they have, for example, a lack of significant data so there is just one article with some well placed words. While this isn't a great tool for blindly throwing your money into investments at the whim of a robot, it can be greatly useful in funneling down the Russell 3000 into 10 or 20 companies which may be worth researching for short-run investment opportunities.

    The system works quite well so far. Looking back on the SP500, for example, the optimal trading strategy has been to buy at market open and sell at market close anything which is scored >=85. This strategy would have returned >13% between the beginning of December 2017 and the end of February 2018.

    And yes, I'm aware that some of the positive/negative word associations seem crazy. How can a good word be bad or a bad word be good, one might ask. Well all this does is indicate that when a word appears, it more often than not leads to a specific market movement. One could notice that 'Fraud' is particularly green...perhaps this is because when everyone is talking about fraud, then it's already priced in and may have found a bottom. The question of why can't really be answered by the system, that's more up to the inferences of the user.

    Looking for feedback from the community, please let me know what you think. There is tons of data being collected that I haven't even gotten around to building a front-end interface for. The possibilities are endless and I would love to tailor the project based upon the direction that this, and other communities, would like to see.

    Also, if you're interested in using any data that can't be pulled via the API yet, or you would just like to talk to me about a project that you would use my API in, then please feel free to reach out! The other day, for example, I copied the entire articles table that I've collected since November over to a friend of mine who likes to do static data analysis on sites like Kaggle. If you're interested in that at all then just drop me a message!

    Thank you!

    submitted by /u/TheLoneDonut
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    S&P 500 corrections: Historical overview

    Posted: 09 Mar 2018 10:05 AM PST

    Since 1980, the avg max intra-year correction for the S&P 500 is 13.7%. 19 of the previous 38 yrs had a max correction of 10% or more, but 13 of those 19 times the SPX finished the yr higher. The avg return when the SPX has a correction is still +7.2%.

    A graphical overview of the issue can be seen here: http://pbs.twimg.com/media/DV2cz10XcAIwKhY.jpg

    submitted by /u/gorillaz0e
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    It's Market Deja Vu: Jobs Beat, Wages Miss, and Stocks Rally

    Posted: 09 Mar 2018 02:15 PM PST

    It's a familiar sequence: Payrolls beat estimates, wages miss, and stocks rally. Everyone can relax, the "Goldilocks" scenario is again alive and well in the U.S. economy.

    Published by Bloomberg.com (Bloomberg Markets)

    Link (Source): https://www.bloomberg.com/news/articles/2018-03-09/it-s-market-deja-vu-jobs-beat-wages-miss-and-stocks-rally

    submitted by /u/snack-fu-bling
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    How likely is it to make 6 figures with only $500 in a brokerage account?

    Posted: 09 Mar 2018 05:48 PM PST

    I am building an API for a smaller Stock Market. What are some crucial functions, features and calculations should it have out of the box?

    Posted: 09 Mar 2018 01:04 PM PST

    So this is for a stock exchange in a different country than the US. But I want it to be good if not great. This is also an ongoing experiment by the way.

    So far, the API can return:

    • price
    • price change
    • previous close
    • open
    • average daily volume
    • stock exchange name
    • market cap
    • book value
    • ebitda
    • dividend share
    • dividend yield
    • earnings share
    • day's high
    • day's low
    • year high
    • year low
    • 50 day moving average
    • 200 day moving average
    • price earnings ratio
    • price earnings growth ratio
    • price sales
    • price book
    • short ratio
    • trade datetime
    • historical (start date, end date)
    • stock information
    • refresh

    What other stuff should I add? Nothing too niche, but i definitely want to add more stuff. Suggestions most welcome!

    submitted by /u/chirau
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    Best online brokerage for Index funds

    Posted: 09 Mar 2018 05:20 AM PST

    I currently use TD Ameritrade. I was wondering if I should switch to a different brokerage like Schwab or Vanguard if I want to use their S&P 500 index funds. Will I save on commission fees? I already have a Fidelity Roth IRA where I can buy Fidelity index funds. Is there one brokerage that is the "best" for index funds?

    Just extra info, in Schwab I'm interested in SWPPX.

    submitted by /u/theofficialorange
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    SCHB as 50% of my portfolio for 30 years? Is it worse than VTI or SPY?

    Posted: 09 Mar 2018 08:10 AM PST

    Y’all are sleeping on WWE

    Posted: 09 Mar 2018 05:09 AM PST

    It's the time to buy WWE stock on the road to wrestle mania. WWE stocks are set to be the next bitcoin so don't be a fool and miss out.

    submitted by /u/JerrythebeanSeinfeld
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