Endogenous market risk: updated primer

Endogenous risk arises from the interaction of financial market participants, as opposed to traded assets’ fundamental value. It often manifests as feedback loops after...

Crowded trades: measure and effect

One measure of the crowdedness of trades in a portfolio is centrality. Centrality is a concept of network analysis that measures how similar one...

A theory of hedge fund runs

Hedge funds’ capital structure is vulnerable to market shocks because most of them offer high liquidity to loss-sensitive investors. Moreover, hedge fund managers form...

Endogenous market risk

Understanding endogenous market risk (“setback risk”) is critical for timing and risk management of strategic macro trades. Endogenous market risk here means a gap...

The dangerous disregard for fat tails in quantitative finance

The statistical term ‘fat tails’ refers to probability distributions with relatively high probability of extreme outcomes. Fat tails also imply strong influence of extreme...

Identifying asset price bubbles

A new paper proposes a practical method for identifying asset price bubbles. First, one estimates deviations of prices from fundamentals based on three different...

Basic theory of momentum strategies

Systematic momentum trading is a major alternative risk premium strategy across asset classes. Time series momentum motivates trend following; cross section momentum gives rise...

Clues for estimating market beta

A new empirical paper compares methods for estimating “beta”, i.e. the sensitivity of individual asset prices to changes in a broad market benchmark. It...

The downside variance risk premium

The variance risk premium of an asset is the difference between options-implied and actual expected return variation. It can be viewed as a price...

How to use financial conditions indices

There are two ways to use financial conditions indicators for macro trading. First, the tightening of aggregate financial conditions helps forecasting macroeconomic dynamics and...

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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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