News-Driven Expectations and Volatility Clustering

Abstract

Financial volatility obeys two fascinating empirical regularities that apply to various assets, on various markets, and on various time scales: it is fat-tailed (more precisely power-law distributed) and it tends to be clustered in time. Many interesting models have been proposed to account for these regularities, notably agent-based models, which mimic the two empirical laws through a complex mix of nonlinear mechanisms such as traders switching between trading strategies in highly nonlinear way. This paper explains the two regularities simply in terms of traders’ attitudes towards news, an explanation that follows from the very traditional dichotomy of financial market participants, investors versus speculators, whose behaviors are reduced to their simplest forms. Long-run investors’ valuations of an asset are assumed to follow a news-driven random walk, thus capturing the investors’ persistent, long memory of fundamental news. Short-term speculators’ anticipated returns, on the other hand, are assumed to follow a news-driven autoregressive process, capturing their shorter memory of fundamental news, and, by the same token, the feedback intrinsic to the short-sighted, trend-following (or herding) mindset of speculators. These simple, linear models of traders’ expectations explain the two financial regularities in a generic and robust way. Rational expectations, the dominant model of traders’ expectations, is not assumed here, owing to the famous no-speculation, no-trade results.

Microfounding GARCH Models and Beyond: A Kyle-inspired Model with Adaptive Agents

“…We mention that a framework similar to ours has been recently proposed in Ref. [38] and [39], and previously in Ref. [40]; however, to our knowledge, this is the first model that accounts for volatility clustering, excess volatility, price impact and, therefore, an interplay between trades and prices which can ignite liquidity crises and flash crashes.…”

Bounded strategic reasoning explains crisis emergence in multi-agent market games

“…Likewise, volatility clustering is consistently observed in markets [ 18 ], with temporal correlations in volatility breaching the traditional economic assumption of heteroskedasticity. The EMH suggests that such phenomena occur due to rational agents reacting to external news in the market [ 19 ]. However, when such dynamics emerge endogenously, i.e.…”

Research on Chinese Stock Market during COVID-19—Based on Random Matrix Theory

“…However, diferent markets show various forms in different periods, especially in the stock market, where there are many stylized facts [2][3][4], such as volatility clustering [5][6][7], fat tails [8][9][10], and long memories [11,12], which are difcult to explain by modern fnancial theory. Terefore, modern fnancial theory based on efcient market hypothesis and rational expectation theory is not accurate enough in the risk management.…”