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A common approach to comparing financial systems across countries is by looking at the role banks play in providing the real economy with credit. The Bank for International Settlements (BIS) has great data sets on measures of credit across many economies in the world that make it very easy to do such a comparison. Plotting the share of bank credit relative to total credit across time reveals some interesting patterns.px.gif

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Bond market returns are typically analysed as time series data (where changes in yield are tracked over time) or across maturities (where interest rates on different contract lengths are chained together to produce the yield curve for any given date). For the US government bond market, the St. Louis Fed's FRED database provides data for a whole range of US Treasury Bonds and US Treasury Bills, allowing you to do either of these exercises. Sometimes, however, it can be useful to get a sense of how the shape of the yield curve evolves over time in a 3D graph. Here is how to create one using plotly in R.px.gif

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Every now and then, I need to get a quick overview of international government bond markets to assess changes over time or compare countries. Usually, places like the Financial Times provide the necessary information, but when you need to dig a little deeper, manual work is required. In the past, I would simply get the data from whatever database was available to me (like the IMF's database), but starting over every time becomes cumbersome, so I decided to automate a few things in R.px.gif

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The AsianBondsOnline portal of the ASEAN+3 Asian Bond Markets Initiative (ABMI) provides a wealth of information on Asian bond markets, including market size, currency of denomination, pricing information, and liquidity statistics, among others. I need to get a quick overview of the market every few months, so I put together a little R script to do the job for me. The script gets the latest data on local currency bonds and foreign currency bonds from AsianBondsOnline, aggregates the data for government bonds and corporate bonds and outputs the result as static and interactive graphs.px.gif

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It was time to update to the latest Ubuntu LTS (Long Term Support) release again recently, and it turned out that setting up Fcitx wasn’t quite as simple this time around. Here is what I had to do to get it to work.px.gif

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I have recently been doing a lot of work in R, a statistical programming language, and have started accumulating a small collection of functions that I regularly use. One of the tools I have particularly come to rely on is this function to obtain data from the United Nation's Comtrade database, a great source for country-to-country trade statistics. Since there seemed to be no R package that provides access to their new API (which is still in beta), I simply wrote a function for myself based on the sample code on their homepage and kept it with my personal files. Motivated by posts like this one, however, I decided to put the code into an R package and share it here for others to use.px.gif

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If you have recently updated your Android device to the latest Android version 5 “Lollipop”, you may have noticed that the “Gallery” app has been replaced by Google's brand-new “Photos” app which depends on Google Plus. If you don't like the idea of linking your photos to Google's social network, or if you have disabled/uninstalled the Google Plus app altogether, there is a way to get back the familiar Gallery app without compiling it yourself: by pulling it from a CyanogenMod rom image. Here is how.px.gif

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After recently upgrading to Ubuntu 14.04 Trusty Tahr (LTS), I decided to give Fcitx, the default input method framework on Ubuntu's Chinese sister project Ubuntu Kylin, a try and I was pleasantly surprised. Not only is Fcitx rock-solid and actively developed, it also offers input methods for Japanese, Korean, Vietnamese and a bunch of other languages in addition to the default Chinese input methods. Here is how you get it to work on Ubuntu 14.04.px.gif

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I recently had to work on a Matlab assignment that required the use of fminbnd() to find local extrema. As I typically work in Octave rather than Matlab I ran into some problems getting my code to work within both programmes. As it turned out, Matlab and Octave handle the function slightly differently, so I thought I'd share my findings to save others some headache.px.gif

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Monitoring a server can be a lot of work, but thankfully handy tools like fail2ban or logwatch make the task a lot easier. Fail2ban, for example, monitors the log files of services running on your system and blocks incoming connections when it detects a break-in attempt (using iptables or hosts.deny). These need to be defined using a regex filter, and while a great number of templates are already available for the most-used services (Apache, SSH, etc.), OpenVPN thus far has not been included. Setting this up isn't too difficult, though.px.gif

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