How market liquidity causes price distortions
Liquidity is a critical force behind market price distortions (and related trading opportunities). First, the cost of trading in and out of a contract...
The price effects of order flow
Order flow means buyer- or seller-initiated transactions at electronic exchanges. Order flow consumes liquidity provided by market makers and drives a wedge between transacted...
Rebalancing and market price distortions
Price distortions are an important source of short-term trading profits, particularly in turbulent markets. Here price distortions mean apparent price-value gaps that arise from...
Equity return anomalies and their causes
The vast range of academically researched equity return anomalies can be condensed into five categories: return momentum, outperformance of high valuation, ...
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...
Market noise
The term “market noise” refers to transactions that are erratic and unrelated to fundamental value. Theory suggests that without market noise profitable trading would...
How salience theory explains the mispricing of risk
Salience theory suggests that decision makers exaggerate the probability of extreme events if they are aware of their possibility. This gives rise to subjective...
Multiple risk-free interest rates
Financial markets produce more than one risk-free interest rate. This is because there are several separate market segments where structured trades replicate such a...
A brief history of quantitative equity strategies
Understanding quantitative equity investments means understanding a significant portion of market positions. Motivated by the apparent failure of the capital asset pricing model and...
Beta herding
Beta herding means convergence of market betas of individual stocks that arises from investors’ biased perceptions. Adverse beta herding denotes the dispersion of such...
RECENT ARTICLES
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’...