St

Stock Market Alerts and Reports

Hacker News

Stock Market Alerts and Reports

Hello Hackers, I thought of showing following stock market reports to you which I am using for my own investing purposes from last 5 years. Stocks are most volatile during earnings reporting period. Stocks rise or fall during this time anywhere between 4% - 35%. So your call to buy or sell during this time can make you lot of money. It is one of the perfect examples of being at right place at right time. If I get enough interest from you then I will put up this system online as self service. Following are the reports that I am using for my own investing decision purposes if you like them then please let me know at lazyload at hotmail.com . I will add you in my system. Once it is online then you can manage your portfolio by yourself. It will require some effort to bring this thing online so I thought of first showing this to you. If there is not enough interest then I will put my attention on some other project. I also booked a domain for this project - www.stockmarketreports.us Thanks, MJ Live Stocks Monitoring By Price. Shows you the price change of a stock since the market opened today - http://1drv.ms/13RfAnf Live Stocks Monitoring By Volume - http://1drv.ms/13RfImO Portfolio Performance. You can create your own portfolio and see its performance - http://1drv.ms/1xHJ2dx Stock Earnings Dates - http://1drv.ms/17bu8R3 Strong Stocks. The stocks which are up from last x days - http://1drv.ms/1AonjVS Viral Stocks. Stocks which are rising high in double digits % with in last 5 days - http://1drv.ms/17buiaW Weak Stocks. Stocks which are continuously down from last x days - http://1drv.ms/17bukQf ExStocks Performance Report - http://1drv.ms/1xuuWdj

Visit product View on Hacker NewsJan 4, 2015

Actual performance

2points

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: using, open · Missing: mac, agents, macos

26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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