SUN Ran

This paper analyses the purchase and redemption behaviour of mutual fund investors and its implications on fund liquidity risk. We collect a novel set of proprietary data which contains a large number of French investors holding funds with various degrees of asset liquidity. We build a Self-Exciting Poisson model capturing fund flows' clustering effects and over-dispersion. The model improves the forecast accuracy of future flows and provides a reliable risk indicator (Flow Value at Risk.) Accordingly, we introduce the notion of liability risk where investor's behaviour increases mutual fund liquidity risk. We further decompose fund flows into investor categories. We find that investors exhibit high heterogeneous behaviour, and a lead-lag relation exists between them. Finally, we control flow dynamics for various economic conditions. We show that although flows evolve with economic conditions, investor's behaviour stays the main significant determinant of flows' randomness. Our findings encourage fund manager to adopt an ALM approach.

No summary available.

We propose a new family of bivariate nonnegative integer-autoregressive (BINAR) models for count process data. We first generalize the existing BINAR(1) model by allowing for dependent thinning operators and arbitrary innovation distribution. The extended family allows for intuitive interpretation, as well as tractable aggregation and stationarity properties. We then introduce higher order BINAR(p) and BINAR(∞) dynamics to accommodate more flexible serial dependence patterns. So far, the literature has regarded such models as computationally intractable. We show that the extended BINAR family allows for closed-form predictive distributions at any horizons and for any values of , which significantly facilitates non-linear forecasting and likelihood based estimation. Finally, a BINAR model with memory persistence is applied to open-ended mutual fund purchase and redemption order counts.

This thesis studies the behaviour of investors in open-end mutual funds and its implications to the liquidity risk. We seek to help the fund managers to avoid the "fund run" scenarios where they loss their clients in a sudden way. We begin our research by collecting a unique data set which records the micro-transactions of fund investors. It allows us to monitor investors’ behaviour at the individual level and to accomplish three research articles around this topic. In the first article, we develop a self-exciting counting process to model the stylized facts of fund flows. Therefrom, we highlight a novel risk linked to the fund liability which is different than the asset-related risk documented by the previous literature. We also identify a liquidity contagion among different investors in a same fund. In the next chapter, we study the dispersion in the investing horizons of individual fund clients. These horizons are strongly determined by investors’ characteristics and economic conditions. We show that the fund managers suffer a pre-mature redemption risk, i.e. clients shorten their investing horizons and redeem pre-maturely. Especially, we observe a heterogeneity among investors: long-term ones bring a higher pre-mature redemption risk. In the last chapter, we are interested in the rebalance behaviour. We find that numerous investors hold a multi-funds portfolio and rebalance it to keep the target asset allocation.

This thesis studies the behavior of investors in open-end mutual funds and its implications for liquidity risk. The objective of this research is to help fund managers avoid the "fund run" scenario where they suddenly lose their clients. The first step of this study is to collect a new database that records investors' "micro-transactions". This allows us to analyze their behavior at the individual level and to conduct three research papers on this topic. In the first paper, we develop a self-exciting counting model that captures stylized facts of the fund flow series. From this, we show a fund liability risk that is different from the asset risk already documented in the previous literature. We also identify a contagion of liquidity shocks across different clients in the same fund. In the next chapter, we study the investment horizons of individual clients. These horizons are strongly related to investor characteristics and economic conditions. We also show that fund managers face a premature exit risk related to the shortening of their clients' investment horizons. We then observe heterogeneity among investors: long-term investors behave differently than short-term investors. Finally, in the last chapter, we focus on rebalancing activities. We find that many investors hold a portfolio containing several funds and rebalance it to keep the same asset allocation.

No summary available.