This smartwatch looks cool, doesn’t it? I would like to have this one.

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I like looking at watches.  Especially since the Apple watch was released,  I am wondering when and what I should buy a smart watch.  Now I use CASIO OCEANUS (picture below).  I bought it in 2008. I like it very much. I do not think I should replace it until smartwatch is getting attractive to me.

 

The problem is the appearance of smartwatch. For me, watches are a kind of fashion items, rather than IT devices. So the Apple watch is not my taste because it looks IT device for me. I like the traditional taste of watches because I feel good about it.

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When I found this smartwatch made by Huawey, I did not think it is a smart watch because it looks a traditional watch. It looks so cool! I think it is easy to replace my old watch to this new smart watch smoothly. I do not know how much it costs so far. I hope it is reasonable.

This is a good example of  how the design of products is important.  When technologies have got matured, it is getting difficult to differentiate the products from others in terms of functionality.  So the design of products is getting more important.

I do not say the Apple watch is not good because it does not look a traditional watch. Some consumers love it.  My taste is just mine, so I do not want to comment on which are good or bad.  This is a matter of  individual preference. But the more choices we have, the happier we are. Therefore, competitions in the smartwatch market can lead the market to expand by itself.

 

Smart watches might have a lot of new functions in the future because it fits our bodies directly. It enables us to  measure the pulse of heart beats and heat of our body, for example. It means that smartwatch can collect a lot of data about our body and health. So we can create new services for healthcare, communications and so on. Therefore, smartwatch will be not just watches in the future.

In my view,  smartwatch might have artificial intelligence in it and answer any questions from owners. It needs more powerful and smaller computer-chips to realize it. So it takes time to develop these applications. But I do not think it is impossible. In future, when we go abroad, all we have to do is just carrying smartwatch and we can go anywhere we want without maps and guidebooks because smartwatch has the latest international information in it and can translate many languages automatically. It will track our health conditions during our trips. If emergencies like sicknesses happen, it leads us to hospitals nearby. Smartwatch can show doctors what happens in our body during the trip by using data so that diagnoses can be more accurate. This is a kind of “dream” watch.  Oh, We need it in the space trip to the moon, too!?    Do you like it?

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Can you be next “Mark Zuckerberg” with open source software?

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I like open source software because it is  almost free to use,  modify and distribute. For example,  I use “R language” for data analysis as I can share code to anyone without cost.  R is an example of open source software. When I used to be a risk manager more than 10 years ago, I used MATLAB.  This is an awesome software for data analysis. However, we need to buy a license to use it. So I cannot recommend it for everyone.  But I can do that for R as it is free.

 

Open source software is strong enough to change the landscape of developing computer programs. Especially I look at the movement driven by Facebook, it looks like a big tsunami to take over the industry. It has more than 200 open source software projects from mobile application development to artificial intelligence according to the article. Mark Zuckerberg,  Founder and CEO of Facebook, have been taking initiative open source movement for many years.  For new start-up, it is very good and helpful because

 

1.  It accelerates development of applications

Because startups usually do not have enough resources to develop the applications from scratch, it is very helpful for them to use open source software. All they should do is modify the software to make applications. Facebook is also built by using open source software, although it becomes one of the biggest IT companies in the world.

 

2. There are more choices provided by open source softwares

When there are several kinds of open sources for specific purposes, we can choose the best one for our own purpose. All we should do is  to assess each of them.  For example, when you are interested in artificial intelligence, there are many major open source softwares,  such as TheanoPylearn2Torch, OpenDeep, Chainer and so on.  Each of them is a little different in terms of functionality and structures. Therefore, we should choose the best one for our own purpose. When we have the best choice. it allows us to develop applications rapidly and effectively.

 

3.  Open source softwares can lower the entrance barriers

It is usually difficult for start-ups to develop complex programs, such as deep learning, from scratch. But supported by open source software, start-ups can learn and develop the applications at the same time. It is very important in the digital economy as the supply of experts in such fields are always less than the demands in labor markets.

 

 

Going forward, I would like to develop an economic analysis system by using open source software and make it available for everyone who is interested in.  I hope everyone can analyze the economy in his/her own country by him/herself in the business.

Can China keep growing steadily in 10 years from now?

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If you are interested in investments in stock markets, you may hear a lot of stories in China this year since it has been rising dramatically and its market capitalization hit 10 trillion USD for the first time. I am not an investment adviser for stocks. However, I am interested in sustainability of Chinese economy in the long run.  Because China is already the biggest economy in the world  in terms of GDP using purchasing power parity (PPP) according to the IMF.  It means that the growth of Chinese economy affects a lot of the other countries’ economies such as Asean countries.

One of the easy way to understand what is going on in China is to compare with Japan.  There is no need for complex economic theories here.  Just compare to find out what are similar and different between them.  I would like to compare Japanese economy in the 1970s, 1980s and the current situation in China.  First, I would like to compare the GDP per capita between Japan and China in order to understand the path of economic growth.

 

1.  China is similar to Japan in 1970s in terms of GDP per capita

In this article by the BBC, it is pointed out that GDP per capita of China based on PPP is 11,868USD.  This number is similar to the number of Japan in 1968 (11,292USD) according to FRED.

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In the 1970s and 1980s, Japanese economy managed several crises such as oil crises and Yen appreciations. In these two decades, GDP per capita (PPP based) was getting more than two times bigger.  It means that China has opportunities to grow more in the long run if it can manage obstacles effectively in the future.

 

2. Data technologies play a key role to develop Chinese economy.

One of the biggest differences between Japan in 1980s and Current China is “Data technology”.   Cloud, Mobile devices, Internet, IOT and Big data are available in major countries all over the world now.  There was nothing like that in Japan 1980s. It means that every industry can be developed rapidly, effectively and with less impact to the environment if they can introduce data technologies effectively. China has already suffered from air pollutions in cities such as Beijing. So developments, with less impact against the environment are desperately needed to make economic growth sustainable.

 

3. Capitalism vs Communism

Another big difference is that Japan introduces capitalism and China introduces communism.  Yes, it is a big difference. But China learned and will learn a lot from capitalism and improve its social system. Especially China can learn Japanese failure since 1990, which is called “lost decades“.  As the result of that, entrepreneurs are more active  in China than Japan now. Alibaba, Tencent and Xiaomi are good examples of that while most of Japanese young guys want to work in traditional big companies, rather than create their startups. So I am sometimes confused which country has which system in reality.

 

No one knows exactly what happens in China in 10 years.  I would like to keep watching what is going on there. Are you an optimist or a pessimist of China?

 

Note: Toshi’s opinions and analyses are personal views and are intended to be for informational purposes and general interest only and should not be construed as individual investment advice or solicitation to buy, sell or hold any security or to adopt any investment strategy.  The information in this article is rendered as at publication date and may change without notice and it is not intended as a complete analysis of every material fact regarding any country, region market or investment.

Data from third party sources may have been used in the preparation of this material and I, Autor of the article  has not independently verified, validated such data. I accept no liability whatsoever for any loss arising from the use of this information and relies upon the comments, opinions and analyses in the material is at the sole discretion of the user. 

Facebook, Twitter, Google and “new wave” of economic analysis

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On Saturday, I found that the report from Bank of England.  This report is about economic analysis in central banks with Big data such as social network services. It is good not only for economic researchers, but also business personnels to consider how Big data should be used. So I would like to consider it based on this report for a while.

Before considering usage of Big data, I would like to define “Big data”. Big data is data sets that are granular, in real time basis and  non-numeric data as well as  numeric one.   These data are completely opposite in nature compared with data which are currently analyzed in Central banks.  Because such data are usually “aggregated,  periodical and numeric”.  One of the examples is financial statements of companies.  Big data are different from such data.  For example Twitter are generated by individuals in real time. These are usually text, images and video. Then the questions come.

 

1. Can we build up macro economic models based on big data?

Central banks are responsible for the stability of the financial system in the country.  Is it possible for central banks to collect data of each loan from private banks and assess credit risk of each, then confirm financial stability as a whole country?  It can be applied to private companies, too. Is it possible that the company collect data of each customer, forecast the amount of purchase by each customer and predict the revenue of the company next fiscal year?  Big data may enable us to do so even though it takes time.

 

2. Is the method used “theory based” or “data driven”?

Even though they cannot be clearly distinguished in practice,  these are two approaches to analyze Big data in economic analysis. Someone puts importance to economic theories. Let us call it “theory based”.  Others take another approach of “Let the data speak for themselves”.   We may call it “data driven”.  Their opinions are sometimes against each other even though they analyze the same data. So we should have well-balanced approach between them.

 

3. Should we change the processes to make business decisions?

Big data comes to us in a real time basis.  But our decision making process in organizations is usually periodical. For example, board of directors meetings and executive committees in companies are generally held on a monthly basis.  Should they be held more flexibly in a timely manner based on outputs from analysis of Big data, rather than periodical one?  The bigger companies become, the more difficult it is to change the process in practice.

 

FRB in the US is currently wondering when they should raise the interest rate of the US.  Chairwoman of FRB has been always saying  “It is based on economic data“.  But I am not sure she cares about data (conversations) on social networking services in the US. What do you think?