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Why Aussie Stock App?

My name is Carol Hargreaves. I am developing an Aussie Stock App that focuses on rating stocks on their financial health on a scale of 1-10 and rating stocks on the likelihood of their stock price going up on a scale of 1-10. Learn more at https://www.youtube.com/watch?v=5flHo5LGxdM

Here’s my story…5 years ago I didn’t know anything about technology or developers. But one thing I did know, is statistical analysis, and how to rate products on the likelihood of being sold or how to rate customers on the likelihood of being a credit risk or how to rate a transaction on the likelihood of being fraudulent.

Another, thing about me, I enjoy challenges. Selecting which stocks to buy is challenging as there is a large amount of uncertainty in the stock market. But, I have a passion for stock trading & analytics, so even though stock trading is challenging, I still enjoy it. So, too with analytics, even though problem solving is challenging, I enjoy the challenge!

So, with my statistical and analytical knowledge, I started to analyse all the stocks in the Australian stock market before buying a stock. I could see that I had something going…my stock trading strategy and selection of stocks were helping me to selection stock portfolios that outperformed the market.

The problem I had, it took a long time to analyse all the stocks in the Australian market, and in the process, I was missing out on some opportunities in the market because I was manually analysing the stock data.

As scoring customers, or scoring products using analytical techniques is my daily job, I decided, why not start scoring stocks using these same analytical techniques. So, I build a stock trading system that automated my analytical process and helped me to save time in analysing the data. My stock trading system uses sophisticated statistical techniques to identify the trends and patterns in the stock data which indicate which stocks are likely to go up in price. The Aussie Stock App also uses machine learning techniques to identify which stocks are financially healthy.
Over the past 18 months, I worked with data analysts to back-test and refine my trading strategy and, also worked with developers to build my Aussie Stock App (Minimum Viable Product (MVP)).

My goal is to help beginner stock traders to make informed decisions when selecting stocks. I believe that by analysing the stock data, we make unbiased, robust decisions about a stock, based on what the stock data tells us. My stock trading method is short term. I would say typically 0 – 3months.

If you want to learn how to trade stocks in the ASX market, you can use Aussie Stock App to help you choose good stocks and then ‘paper trade’. In other words, no actual money is required. All you do, you assume that you bought the stock and then to manage your risk of losing money in the stock market, you place the stock in a watch list, you will set your target price (maybe 50% more than the current stock price) when to sell and your stop loss price (maybe 3% less than the current stock price) when to sell. This way you will gain experience and confidence in stock trading without losing any of your money.

If you are interested in the Aussie Stock App, it is free. After 1 month, there are optional in-app payments for the Stock Financial Health Ratings (scale 1-10) and the Stock Rating for the stock price likely to go up (scale 1-10). You can learn more about Aussie Stock App at http://www.aussiestocktrader.com

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If you have any questions or feedback, please do not hesitate to contact me on carol.hargreaves@aussiestocktrader.com

Artificial Intelligence: Is it all good? Are there no Risks?

Artificial Intelligence

Artificial Intelligence is growing in its application and is going to grow even more….it’s going to be big! Every organisation and every industry will be applying Artificial Intelligence to help them make smart decisions, faster & cheaper.

Artificial Intelligence helps all businesses to reduce or get rid of mundane manual processes. It also improves the business operations and helps to reduce processes and costs.

There are many use cases of Artificial Intelligence across all different industries, and to-date, the use cases are extremely valuable to businesses. But is it possible that one day, the Robots or Machine Learning Algorithms can get so smart that it may be to our detriment?

Let’s get the discussion going…Do you know what is #Artificial #Intelligence? Is your organisation or industry applying Artificial Intelligence to different aspects of its business? What do you find interesting about Artificial Intelligence? Is Artificial Intelligence working for your company? Do you think Artificial Intelligence can get the human race in trouble one day? What’s your thoughts on Artificial Intelligence?

#AI @DataAnalytic @DataAnalyticx

Should you be Learning more about Machine Learning Algorithms?

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More and more businesses are switching from reacting to situations to anticipating them. How do they do this?

In order to anticipate or predict a situation, an organization must have a business question in mind. Questions such as:

Is this a fraudulent transaction or not?

Will the stock price in the next week go up or not?

Is this particular person a credit risk or not?

Will this customer buy item ‘A’ or not?

How many units will be sold next week?

What will the stock price be tomorrow? etc

The best way to make business decisions is to analyse the relevant historical data and to identify the patterns in the data. To identify the relevant data, it is important that the analyst speaks with the domain experts to help them identify the relevant data. Further, it is not only the analysis of the historical data (being reactive always) that can help answer the above business questions. It is also important that businesses use predictive data (being proactive and sometimes preventing negative activity) to help answer the above questions.

Machine Learning is a method for data analysis, in particular, Machine Learning Algorithms focus on using the relevant data inputs to make Predictions for the business or Classify the business products, services or customers.

Machine Learning is an algorithm that explores the data for patterns and identifies the key data (factors) that will help the business to predict/classify its target outcome of interest (like the above business questions). Machine Learning uses statistical techniques (such as the logistic regression, neural networks, decision tress, etc) and computer programming languages (such as Python, R, SAS, Matlab, etc) to automate the predictive/classification models using algorithms that iteratively learn from the data and find the hidden insights that humans would not usually have known about. These hidden insights are like ‘gold for the business’ as they usually improve the business predictions/classifications without being explicitly programmed where to look. The Machine Learning Algorithms further improve when they are regularly updated with new data and knowledge.

For Machine Learning Algorithms to be effective, it is important for businesses to be able to capture the relevant, good quality data in real time or almost real time and to allow the right people in the business to apply the predictions/classifications timely and thereby gain advantage over their competitors.

Are you interested in learning more about machine learning algorithms and how your business can improve its sales/predictions and become ore efficient? Contact me at carol.hargreaves@dataanalyticsexperts.com

Business Data Analytics Solutions

Analytics

 

Every company has lots of customer data, product data, business services data, social media data, website data, financial data, etc. Data is extremely valuable today as it allows businesses to make decisions smarter and faster. But, are businesses using their data wisely? Can businesses answer questions they have fast?

The Application of Statistical Techniques to relevant data is the core method for understanding business data and solutions for business challenges. Do organisations have statistcially trained talent? How are decisions being made in organizations today? Do organizations have an in-house Analytics Team to help them make decisions faster and smarter?

Business Data Analytics Solutions Pty Ltd has just been launched to help organizations build up their Analytics Team and to assist organizations in understanding and solving their business problems.

Do you want to know more about how Business Data Analytics Solutions Pty Ltd can help you to build your in-house Analytics Team or provide you with the relevant Analytics Training which your organization needs, contact us at http://www.dataanalyticsexperts.com See link below: https://www.youtube.com/watch?v=qVJ6tmlO5_8

 

 

What makes a Good Analyst?

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To be a great analyst you need to be able to think clearly and ensure that you understand the problem at hand well. A great analyst will ask many intelligent questions with regards to the problem and would be able to determine through speaking with a domain expert, which variables will be relevant for solving the problem. A great analyst is a very detailed person who would ask lots of questions and ensure that key information has been considered and collected.

In addition, a great analyst would select the right visual display to demonstrate the results of his/her analysis. Good communication skills are also a key trait as often the statistical results are too complex for the client to understand. So, the analyst needs to present the results in an easy to understand manner. Analysts who present the results in a story like manner with great visuals and good use of technology will be well liked for their presentation skills.

Further, accuracy is very important in the analytical world. So a great analyst will build predictive models as part of their solutions, but will always compare and evaluate the accuracy of their model with a few other models and also ensure that the accuracy is of a reasonable and acceptable level. Further, a great analyst will test their model results by validating the model against unseen data and against the actual data when it becomes available.

In a nut shell, a great analyst is passionate about solving challenging problems and works hard to ensure that the analytical solution while being highly accurate is at the same time making business sense and offers business value for the client. A great analyst will always exceed expectations and deliver more insightful information than the client expects and is paying for.

If you have any questions, please do not hesitate to ask me. You are also most welcome to share your thoughts here, on what makes a good analyst. If you would like to learn more about ‘Analytics’ or how to start ‘Analytics’ in your company, learn more at http://www.datanalyticsexperts.com or contact me.

How Did I Start My Career in Analytics?

 

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People often ask me, “How did I start my career in Analytics?”. It was actually, quite by accident. In my first year at university I wanted to do the key science subjects such as Mathematics, Physics, & Chemistry but I needed a fourth subject and based on my time table options, Statistics was the only science course available for me. I had no idea what Statistics was about but I fully believed in myself that I could do it, even though there were many stories that Statistics is not easy to pass and the pass rate was only 40%.

I quite enjoyed the Statistics lectures and my professor, Prof Calitz told interesting stories and often challenged us with tricky problem solving questions. I worked hard at solving these problems and often went to my professor to share my solution and ask questions.

Prof Calitz never gave me a straight answer, he always rather probed me with one question after the next and sent me back to complete my solution. At that time, I thought Prof Calitz was a hard man and not very helpful but looking back, I can say that it is through him that I now have a good knack of asking lots of questions while problem solving. And you know what, during my university studies I had to work hard at my other courses such as Mathematics but didn’t really open a book for Statistics and still passed it with a Distinction!

I am today, very passionate about Analytics and enjoy working through business problems, which are quite challenging and more complex.I am very thankful to Prof Calitz for his good teaching approach!