The big story over the past two weeks has been the unwinding of the yen carry trade. This trade involves borrowing yen at low rates in Japan and investing the funds in higher-yielding foreign currencies, such as the US dollar or the Mexican peso. Many have argued that a surprise rate hike from the Bank of Japan on 31 July and disappointing US labour market data on 2 August triggered the collapse of this trade. As a result, the yen surged, equities stumbled, and government bonds rallied. While not much is known about the exact scale of the yen carry trade, this post explores two methods of proxying it.
Central banks in recent years have paid a lot of attention to “inflation expectations” when setting monetary policy. But measuring these expectations isn't always easy. Expectations can vary widely depending on whether you're asking businesses, households, or professional forecasters. One of the more straightforward methods for gauging inflation expectations is by analysing bond market data. This post provides a quick rundown of how this works.
Japanese FX intervention has been in the news a lot lately, as the yen's depreciation has prompted Japanese authorities to step into markets multiple times over the past two years to prop up the currency. According to media reports, the Japanese Ministry of Finance and the Bank of Japan likely intervened this past Thursday, July 11, after the release of surprisingly soft U.S. inflation data, causing the yen to jump to almost 157 JPY/USD from nearly 162 JPY/USD. Official data to confirm whether intervention took place won't be available until 31 July, so here's how you can estimate the scale of the intervention using BOJ accounts and money market broker forecasts.
When analyzing time series data in R, I often draw on a small set of helper functions to quickly visualize information. These use the excellent plotly package to create interactive charts. I thought others might find these useful as well and decided to put the code up here. This post provides a quick rundown of how these functions work.
I spend a lot of time looking at how the Bank of Japan (BOJ) manages financial institutions' current account balances, more commonly known as “reserves”. The amount and price of these reserves influence financial institutions' net income, so discussions on the BOJ's monetary policy options often look at how these could be tweaked. RStudio's Shiny package is a great tool to make sense of it all.
Sometimes, I need a quick overview of a large dataset for a particular economy. For example, I might want to examine all the available data from the Bank for International Settlements (BIS) for the U.K. Compiling the relevant data from their various datasets can be quite the task, so making the process replicable is key. This post shows you how to set up an interactive BIS data dashboard using R Markdown, and flexdashboard together with the BIS R package.
When the European Central Bank hosted its annual Forum on Central Banking in Sintra, Portugal earlier this year, one presentation at the Young Economists' Session stood out to me: Cían Allen's research on current accounts and sectoral balances. His paper prompted me to dig up some code I wrote during my dissertation to compile sectoral balances data for a number of economies and update it with some additional data for the US and Japan.
After looking at the balance sheets of the US Fed and the Bank of Japan (BOJ) a while ago, let's take a look at the balance sheets of the European Central Bank (ECB) and the Bank of England (BOE) next. These four central banks have all dabbled in quantitative easing in recent years, so comparing their balance sheets should bring to light some interesting similarities and differences.
Five years have passed since the Bank of Japan (BOJ) rolled out its quantitative and qualitative easing (QQE) programme in April 2013 under Governor Kuroda. After taking a closer look at the US Fed's balance sheet a few weeks back, I decided to do the same for the BOJ's balance sheet to see what we can learn.
Ten years ago, the U.S. Fed launched the first of several rounds of Quantitative Easing in response to the Global Financial Crisis. This drastically increased the size of its balance sheet. Since then, the Fed has been looking to roll back this expansion in an effort to “normalise” monetary policy. Let's see what this looks like.
