Category Archives: behavioral finance

3/5/21: Margin Debt: Things are FOMOing up…

 Debt, debt and more FOMO...


Source: topdowncharts.com and my annotations

Ratio of leveraged longs to shorts is at around 3.5, which is 2014-2019 average of around 2.2. Bad news (common signal of upcoming correction or sell-off). Basically, we are witnessing a FOMO-fueled chase of every-rising hype and risk appetite. Meanwhile, margin debt is up 70% y/y in March 2021, although from low base back in March 2020, now back to levels of growth comparable only to pre-dot.com crash in 1999-2000. Adjusting for market cap - some say this is advisable, though I can't see why moderating one boom-craze indicator with another boom-craze indicator is any better - things are more moderate. 

My read-out: we are seeing margin debt acceleration that is now outpacing the S&P500 acceleration, even with all the rosy earnings projections being factored in. This isn't 'fundamentals'. It is behavioral. And as such, it is a dry powder keg sitting right next to a campfire. 

3/5/21: Margin Debt: Things are FOMOing up…

 Debt, debt and more FOMO...


Source: topdowncharts.com and my annotations

Ratio of leveraged longs to shorts is at around 3.5, which is 2014-2019 average of around 2.2. Bad news (common signal of upcoming correction or sell-off). Basically, we are witnessing a FOMO-fueled chase of every-rising hype and risk appetite. Meanwhile, margin debt is up 70% y/y in March 2021, although from low base back in March 2020, now back to levels of growth comparable only to pre-dot.com crash in 1999-2000. Adjusting for market cap - some say this is advisable, though I can't see why moderating one boom-craze indicator with another boom-craze indicator is any better - things are more moderate. 

My read-out: we are seeing margin debt acceleration that is now outpacing the S&P500 acceleration, even with all the rosy earnings projections being factored in. This isn't 'fundamentals'. It is behavioral. And as such, it is a dry powder keg sitting right next to a campfire. 

30/6/20: Long-Term Behavioral Implications of COVID19 Pandemic


My article on the behavioural economics and finance implications of COVID19 pandemic is now available on @TheCurrency website: https://www.thecurrency.news/articles/19675/debt-distress-and-behavioural-finance-the-post-pandemic-world-be-marked-by-deep-and-long-lasting-scars.


Hint: dealing with COVID19 impact will be an uphill battle for many and for the society and economy at large.

This is a long read piece, covering general behavioural fallout from the pandemic, and Ireland-specific data.

21/1/20: Investor Fear and Uncertainty in Cryptocurrencies


Our paper on behavioral biases in cryptocurrencies trading is now published by the Journal of Behavioral and Experimental Finance volume 25, 2020:



We cover investor sentiment effects on pricing processes of 10 largest (by market capitalization) crypto-currencies, showing direct but non-linear impact of herding and anchoring biases in investor behavior. We also show that these biases are themselves anchored to the specific trends/direction of price movements. Our results provide direct links between investors' sentiment toward:

  1. Overall risky assets investment markets,
  2. Cryptocurrencies investment markets, and
  3. Macroeconomic conditions,
and market price dynamics for crypto-assets. We also show direct evidence that both markets uncertainty and investor fear sentiment drive price processes for crypto-assets.

9/1/20: Herding and Anchoring in Cryptocurrency Markets


Our new paper, with Daniel O'Loughlin, titled "Herding and Anchoring in Cryptocurrency Markets: Investor Reaction to Fear and Uncertainty" has been accepted to the Journal of Behavioral and Experimental Finance, forthcoming February 2020.

The working paper version is available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3517006.

Abstract:
Cryptocurrencies have emerged as an innovative alternative investment asset class, traded in data-rich markets by globally distributed investors. Although significant attention has been devoted to their pricing properties, to-date, academic literature on behavioral drivers remains less developed. We explore the question of how price dynamics of cryptocurrencies are influenced by the interaction between behavioral factors behind investor decisions and publicly accessible data flows. We use sentiment analysis to model the effects of public sentiment toward investment markets in general, and cryptocurrencies in particular on crypto-assets’ valuations. Our results show that investor sentiment can predict the price direction of cryptocurrencies, indicating direct impact of herding and anchoring biases. We also discuss a new direction for analyzing behavioral drivers of the crypto assets based on the use of natural language AI to extract better quality data on investor sentiment.