Time Series

Learn how to analyze time-ordered historical data to forecast future behavior using BigML Time Series.

Investing In Healthcare Stocks

In this video we take a look at investing in the Healthcare industry using REIT stocks. We will cover a few of the top Healthcare REITs and go over their yearly dividends and also the stock price increase.

If you are interested in investing in the healthcare industry please watch this video. Due to the huge increase in people over the age of 70 healthcare investing will be a strong sector in the years to come.

The investments we cover in this video are healthcare REITs who invest in healthcare real estate like senior living facilities, hospitals, medical offices, and other medical buildings. Instead of investing directly into healthcare companies like a drug company you can invest in the companies who provide real estate to the healthcare industry.

Please note that I’m not a professional investor and you need to do your own research on these healthcare stocks before buying any of them. The past is not prediction of the future and i’m simply showing people what healthcare stocks (REITs) are out there and which stocks have had fairly good track records.

If you want to know more about what a REIT investment is then check out one of my other videos located here:

Thanks for watching and good luck on investing in healthcare.
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How To Make Money Trading Penny Stocks While In College

How To Make Money Trading Penny Stocks While In College

-Market Mastery https://mctradings.weebly.com

-Tradenet- https://www.tradenet.com

-Spread Sheet- https://youtu.be/Ho7n0r2deps

-Email: Wes_cox@ymail.com

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-How To Make Money Trading Penny Stocks While In College

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My Recession Proof Investing Plan For 2020

Here is my recession proof investment plan for 2020, exactly where my money is going, and how this should stay profitable long term – Enjoy! Add me on Instagram: GPStephan

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First, let’s discuss something that a lot people have been asking about:
Data shows that any short term drops in the stock market had very little effect on overall home prices. Instead, real estate values are largely driven by the age old saying: LOCATION, LOCATION, LOCATION. Real estate prices are heavily influenced by specific market conditions of demand, proximity to employment, and current supply of inventory…this will vary DRAMATICALLY from Location to Location, not necessarily by what’s going on with the overall economy.

Second, Real Estate values will be HEAVILY influenced by how high…or low…the mortgage interest rates are….and, right now, they’re INSANELY low. The FED just dropped rates a half a point, and they’re expected to lower rates even further, which happens to make Real Estate wayyy less expensive to own.

And third, GENERALLY speaking…people aren’t buying and selling homes multiple times a day like they might do with stocks. The MAJORITY of people buy real estate with the intention of holding it a very long time, meaning that the value of their home doesn’t make much a difference in the short term. Not only that, but valuing the specific price of the home is rather complex…so, for that reason, we don’t notice a huge swing in prices between one home to another.

Now, let’s talk stocks. I think that IF we end up seeing a big correction coming in the near future, and prices drop further…I’ll probably ramp up my contributions a little bit, but otherwise, everything stays the same. I know there’s been some talk about investing in Bonds, Gold, or trying to Short the stock market…but, honestly, that just seems a little unnecessary for me, and most people would be best off just dollar cost averaging into the markets, and letting their money sit.

So, as far as where I think stocks will go from here…I don’t know. No one knows. It’s pretty irrational, but all we can do – based on the last 100 years of stock market data…is just to continue buying, and eventually, things will rebound.

And that leaves me with my “Recession Proof Investing Plan” – one, continue to hold and buy real estate, which won’t typically fluctuate much in price, and even if it does – data shows that rents remain fairly consistent, regardless of what happens – and, really, that’s all I care about at the end of the day.

Second, I’ll continue buying into the stock market as usual…it’ll be a mix of US Equities, International Stocks, and Bonds….and that’s it. This is all meant to be money I won’t be needing for the next 20-30 years, so whatever their values are before then doesn’t make much of a difference, since I won’t be cashing out.

And, third…I always make sure to keep a big safety fund on the side. And, if you don’t currently have that…then that’s something you should immediately be working towards.

And I know that even if the markets DO go down…only invest money you don’t need for the long term, only buy properties that you can afford, where the rental income could sustain all of your payments, and only get fixed, low interest, long term mortgages.

For business or one-on-one real estate investing/real estate agent consulting inquiries, you can reach me at GrahamStephanBusiness@gmail.com

*Some of the links and other products that appear on this video are from companies which Graham Stephan will earn an affiliate commission or referral bonus. Graham Stephan is part of an affiliate network and receives compensation for sending traffic to partner sites. The content in this video is accurate as of the posting date. Some of the offers mentioned may no longer be available.

Best Stock Trading Apps In Germany 2020 (Beginners Guide) – FxBeginner.Net

Here’s the best stock trading apps in Germany that accepts German stock traders.

IQ Option App – https://www.fxbeginner.net/app/iqoption

ExpertOption App – https://www.fxbeginner.net/app/expertoption

Binomo App – https://www.fxbeginner.net/app/binomo

Olymp Trade App – https://www.fxbeginner.net/app/olymptrade

eToro App – https://www.fxbeginner.net/app/etoro

Pocket Option App – https://www.fxbeginner.net/app/pocketoption

Link to article: https://www.fxbeginner.net/best-stock-trading-apps-in-germany/

Finding the best stock market app as a German investor can be a difficult process. Most especially getting the ones that accept German stock traders and would let you trade stocks on your iOS or android device. Don’t worry, we’ve got you covered!

We’ve listed the top best stock investment apps that would let you as a German stock trader, trade Growth stocks, Tech stocks, Small-cap, Mid-cap and Large-cap stocks.

News Sentiment & Reinforcement Learning in Finance & Algorithmic Trading

This is the recording of the 1st Cross-Meetup-Group Virtual Event. General slides are found under https://hilpisch.com/virtual_meetup_01.pdf.

Talks are:

Dr. Richard L. Peterson & Anthony Luciani (MarketPsych Indices):
Creating Market Forecasts with News and Social Media Data using Jupyter Notebooks
Slides: https://go.aws/2yBjF4u

Dr. Yves Hilpisch (The Python Quants | The AI Machine):
Reinforcement Learning: From Playing Games to Trading Stocks
Slides: https://hilpisch.com/rlearn_finance.pdf
Notebook: https://hilpisch.com/rlearn_finance.html

The event is co-organized by The Python Quants and Refinitiv.

Stocks VS ETFs – What's a Better Investment – Investing for Beginners

Art of Finding Great Long Term Stocks: https://youtu.be/FcDMdlMOCc4

In this video, we look at what is a better investment, stocks or ETFs.

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Get a Free Stock with RobinHood: https://join.robinhood.com/jamesc10724

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Investing Basics Playlist
https://goo.gl/ky7CJq

Investing Books I like:
The Intelligent Investor – https://amzn.to/2PVhfEL
Common Stocks & Uncommon Profits – https://amzn.to/2DAV8h9
Understanding Options – https://amzn.to/2T9gFSp
Little Book of Common Sense Investing – https://amzn.to/2DfFGG2
How to Value Exchange-Traded Funds – https://amzn.to/2PWSkRg
A Great Book on Building Wealth – https://amzn.to/2T8AKZ1
Dale Carnegie – https://amzn.to/2DDAk8w
Effective Speaking – https://amzn.to/2DBncAT
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DISCLAIMER: I am not a financial advisor. These videos are for educational purposes only. Investing of any kind involves risk. Your investments are solely your responsibility and we do not provide personalized investment advice. It is crucial that you conduct your own research. I am merely sharing my opinion with no guarantee of gains or losses on investments. Please consult your financial or tax professional prior to making an investment.

#LearnToInvest #StocksToWatch #StockMarket

bootstrapped prediction intervals

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Time Series Analysis - 2 | Time Series in R | ARIMA Model Forecasting | Data Science | Simplilearn

This Time Series Analysis (Part-2) in R tutorial will help you understand what is ARIMA model, what is correlation & auto-correlation and you will alose see a use case implementation in which we forecast sales of air-tickets using ARIMA and at the end, we will also how to validate a model using Ljung-Box text.

Link to Time Series Analysis Part-1: https://www.youtube.com/watch?v=gj4L2isnOf8

You can also go through the slides here: https://goo.gl/9GGwHG

A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this video and understand what is time series and how to implement time series using R.

Below topics are explained in this “ Time Series in R Tutorial “ –

1. Introduction to ARIMA model
2. Auto-correlation & partial auto-correlation
3. Use case – Forecast the sales of air-tickets using ARIMA
4. Model validating using Ljung-Box test

To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning

Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment.

Why learn Data Science with R?
1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc
2. According to marketsandmarkets.com, the advanced analytics market will be worth .53 Billion by 2019
3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is 8,709
4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT

The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies and includes R CloudLab for practice.
1. Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R.
2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing.
3. As a part of the data science with R training course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and the Internet. Four additional projects are also available for further practice.

The Data Science with R is recommended for:
1. IT professionals looking for a career switch into data science and analytics
2. Software developers looking for a career switch into data science and analytics
3. Professionals working in data and business analytics
4. Graduates looking to build a career in analytics and data science
5. Anyone with a genuine interest in the data science field
6. Experienced professionals who would like to harness data science in their fields

Learn more at: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Time-Series-Analysis-Y5T3ZEMZZKs&utm_medium=Tutorials&utm_source=youtube

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Multivariate Time Series Prediction with LSTM and Multiple features (Predict Google Stock Price)

Build a Artificial Neural Network (ANN) with Long-Short Term Memory (LSTM) to predict value which can be impacted by multiple different features.

In this video I demonstrate how to use LSTM to predict Google Stock price (you can use any other case) by taking into consideration multiple predictors (features). Let’s say, the final stock price can be predicted by finding importance of such features as historical low price, high price, volume, adj. price, etc.

Link to github notebook: https://github.com/vb100/multivariate-lstm/blob/master/LSTM_model_stocks.ipynb

The video has 3 parts:
– Part 01. Data pre-processing (4:11)
| Step 01: Read data.
| Step 02: Data pre-processing (shaping and transformations).

– Part 02. Create a LSTM model and train it. (10:39)
| Step 03: Building-up the LSTM based Neural Network.
| Step 04: Start training.

– Part 03. Make future predictions. (13:50)
| Step 05: Make predictions for future date.
| Step 06: Visualize the predictions.

In this tutorial I used Tensorflow 1.15.0 and Keras 2.3.1

Download data from: https://finance.yahoo.com/quote/GOOG/history (check 1:59 in video).

This is real life Python code example for demonstration purposes, so the model is not very accuracy and of course could be improved or tuned.

My goal of this Python tutorial is to demonstrate how to perform LSTM predictions with multiple features (complex dataset).

Hoping it will help to undersant the way it could be implemented in real Data Science or Data Analysis projects. TIme Series forecasting with LSTM is the good choice if you want to manipulate with multiple different data features and see which ones has impact to predictions and which ones do not.

If you are interested how to run Tensorboard on this LSTM Keras model, check this tutorial: https://youtu.be/-9-Hy5dWKLE

Sorry for video quality. There were some unexpected issues with resolution.
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