Faculties and Research

CEA Seminars and Events

Recent seminars

25 July 2017

Speaker: Professor Robin Lumsdaine (Kogod School of Business, American University, Washington)

Paper Title: “An Epidemiological Model of Crisis Spread Across Sectors in the United States”  (joint with EvaF.Janssens and Sebastian H.L.C.G Vermeulen)

Room: 5010, 5th Floor, Cass Business School, Bunhill Row from 12:00 – 13:00

As the spread of the mortgage crisis of 2007 from the household sector to the domestic financial sector illustrated, understanding contagion across sectors is essential for policy makers. This article develops a discrete-time epidemiological model for the spread of crises across sectors in the United States for the period 1952-2015. It is the first model to apply an epidemiological approach to consider the spread of economic crises across sectors using macroeconomic Flow of Funds data. By extending the usual one-period Markov model to a two-period setting, we incorporate the concept of downturns that may either precede a crisis or from which the sector may recover and avert a crisis. The estimated model demonstrates that especially the (non)corporate nonfinancial business sector and the private depository institutions & money market mutual funds are highly contagious and a crisis in these sectors is very likely to spread to other sectors in the United States. These conclusions are robust to a variety of changes to the model specification. A split sample analysis indicates a decrease in contagiousness of the private depository institutions and money market mutual funds and a strong increase in contagiousness for the insurance companies sector over time.
Keywords: Flow of Funds, economic downturns, Susceptible-Infected-Removed (SIR) JEL classification codes: E37, E32, E01, G01

27 March 2017:

Speaker: Dacheng Xiu (Chicago Booth School of Business) University of Chicago,

Paper Title: "Using Principal Components Analysis to Estimate a High Dimensional Factor Model with High-Frequency Data" (joint with Yacine Ait-Sahalia, Princeton University and NBER.)

Room: 2005, Cass Business School, Bunhill Row, 13:00 – 14:00

This paper constructs an estimator for the number of common factors in a setting where both the sampling frequency and the number of variables increase. Empirically, we document that the covariance matrix of a large portfolio of US equities is well represented by a low rank common structure with sparse residual matrix. When employed for out-of-sample portfolio allocation, the proposed estimator largely outperforms the sample covariance estimator.

27 February 2017:

Speaker: Dobrislav Dobrev (FED, Washington D.C.)

Paper Title: "High-Frequency Cross-Market Trading: Model Free Measurement and Applications" (joint with Ernst Schaumburg, Federal Reserve Bank of New York)

Room: 2005, Cass Business School, Bunhill Row, 13:00 – 14:00

We propose a set of intuitive model-free measures of cross-market trading activity based on publicly available trade and quote data with sufficient time stamp granularity. By virtue of capturing the offset at which co-activity peaks, as well as its magnitude and dispersion, the measures allow us to shed new light on the distinct features of the high-frequency cross-market linkages in US Treasury and equity markets. First, the measures avoid reliance on noisy return series often used in the literature and demonstrate sharp identification of the prevailing lead-lag relationships between trading activity across markets. Second, we show how the measures can be used to examine price impact and liquidity provision in (near) arbitrage linked markets. In particular, we provide new evidence pointing to the fact that price discovery in US Treasury, equity and EUR/USD FX markets primarily takes place in futures rather than cash markets and we give a strong rationale for considering the cross-market price impact between arbitrage linked markets. Finally, we show that our measures of cross-market activity are closely linked with observed market volatility even after controlling for commonly used measures of individual market activity such as trading volume and number of transactions. Overall, our empirical findings suggest that accounting for cross-market trading activity is important when studying volatility and liquidity in US Treasury and equity markets.