Why and when financial markets are herding

Herding arises from deliberate decisions of informed traders to follow others. It can create inefficiency, dislocations and, hence, profit opportunities. A paper by German...

Unproductive debt

Credit and related interest income have historically been viewed as service and related payment for lending productively. However, in a highly collateralized and risk-averse...

The dollar as barometer for credit market risk

The external value of the USD has become a key factor of U.S. and global credit conditions. This reflects the surge in global USD-denominated...

Liquidity risk in European bond markets

There are signs of liquidity decline and liquidity illusion in euro area government bond markets. Citibank research suggests that liquidity risk is rising due to increased capital...

The role of macroprudential policy

Macroprudential measures are often seen as a counterweight to ultra-easy monetary policy in the developed world. BIS research cautions against this expectation. Macroprudential policies are...

The “collateral channel” of monetary policy

The importance of collateralized transactions for the global financial system has greatly increased since the financial crisis. Moreover, the influence of central banks on...

Understanding global liquidity

A new IMF policy paper defines global liquidity as the ease of funding in global financial markets. The concept is useful for understanding the...

Using volatility to predict crises

A long-term empirical study finds two fundamental links between market volatility and financial crises. First, protracted low price volatility leads to a build-up of leverage and risk, making the...

Insurance companies and systemic risk

The contribution of life insurers to systemic risk has increased, according to the IMF Global Financial Stability Report. They now hold about 12% of...

Functions and risks of shadow banking

Shadow banking encompasses credit intermediation outside the regulated banking system, mostly through investment funds, money market funds, structured finance vehicles, broker-dealers, and finance companies....

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R tidyverse for macro trading research

The tidyverse is a collection of packages that facilitate data science with R. It is particularly powerful for macro trading research because it...

Nowcasting with MIDAS regressions

Nowcasting macro-financial indicators requires combining low-frequency and high-frequency time series. Mixed data sampling (MIDAS) regressions explain a low-frequency variable based on high-frequency variables and...

Market-implied macro shocks

Combinations of equity returns and yield-curve changes can be used to classify market-implied underlying macro news. The methodology is structural vector autoregression. Theoretical ‘restrictions’...

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