We propose a financial market model in which speculators follow a linear mix of technical and fundamental trading rules to determine their orders. Volatility clustering arises in our model due to speculators’ herding behaviour. In case of heightened uncertainty, speculators observe other speculators’ actions more closely. Since speculators’ trading behaviour then becomes less heterogeneous, the market maker faces a less balanced excess demand and consequently adjusts prices more strongly. Estimating our model using the method of simulated moments reveals that it is able to explain a number of stylized facts of financial markets quite well. Various robustness checks with respect to the model setup reveal that our results are quite stable.

https://www.econstor.eu/bitstream/10419/129615/1/852490070.pdf

Herding behaviour and volatility clustering in financial markets

https://www.econstor.eu/bitstream/10419/173161/1/1010358618.pdf

Interactions between stock, bond and housing markets

We study if central banks can manage market expectations by means of forward guidance in a New Keynesian learning-to-forecast experiment. Subjects observe public inflation projections by the central bank along with the historic development of the economy and subsequently submit their own inflation forecasts. We find that the central bank can significantly manage market expectations through forward guidance and that this management strongly supports monetary policy in stabilizing the economy.

https://www.econstor.eu/bitstream/10419/168063/1/VfS-2017-pid-1854.pdf

The Stabilizing Role of Forward Guidance: A Macro Experiment

Based on a behavioral stock-flow housing market model in which the expectation formation behavior of boundedly rational and heterogeneous investors may generate endogenous boom-bust cycles, we explore whether central banks can stabilize housing markets via the interest rate. Using a mix of analytical and numerical tools, we find that the ability of central banks to tame housing markets by increasing the base (target) interest rate, thereby softening the demand pressure on house prices, is rather limited. However, central banks can greatly improve the stability of housing markets by following an interest rate rule that adjusts the interest rate with respect to mispricing in the housing market.

/pdf/housing-markets-expectation-formation-and-interest-rates-35e4gr1ix2.pdf

Housing markets, expectation formation and interest rates

Artificial intelligence (AI) is starting to pervade the economic and social life rendering strategic interactions with artificial agents more and more common. At the same time, experimental economic research has increasingly employed computer players to advance our understanding of strategic interaction in general. What can this strand of research teach us about an AI-shaped future? I review 90 experimental studies using computer players. I find that, in a nutshell, humans act more selfishly and more rational in the presence of computer players, and they are often able to exploit these players. Still, many open questions prevail.

https://www.econstor.eu/bitstream/10419/209654/1/1685901425.pdf

The behavioral economics of artificial intelligence: Lessons from experiments with computer players

We develop a simple agent-based financial market model in which speculators’ market entry decisions are subject to herding behavior and market risk In addition, speculators’ orders depend on price trends, market misalignments and fundamental news Using a mix of analytical and numerical tools, we show that a herding-induced market entry wave may amplify excess demand, triggering lasting volatility outbursts Eventually, however, higher stock market risk reduces stock market participation and volatility decreases again Simulations furthermore reveal that our approach is also able to produce bubbles and crashes, excess volatility, fat-tailed return distributions and serially uncorrelated price changes Moreover, trading volume is persistent and correlated with volatility

/pdf/market-entry-waves-and-volatility-outbursts-in-stock-markets-8mlpxumhwi.pdf

Market entry waves and volatility outbursts in stock markets

We develop a simple agent-based financial market model in which speculators' market entry decisions are subject to herding behavior and market risk. Moreover, speculators' orders depend on price trends, market misalignments and fundamental news. Using a mix of analytical and numerical tools, we show that a herding-induced market entry wave may amplify excess demand, triggering lasting volatility outbursts. Eventually, however, higher stock market risk reduces stock market participation and volatility decreases again. Simulations furthermore reveal that our approach is also able to produce bubbles and crashes, excess volatility, fat-tailed return distributions and serially uncorrelated price changes.

Ivonne Blaurock

Papers

Market entry waves and volatility outbursts in stock markets

Market entry waves and volatility outbursts in stock markets