also explore the effects of bank’s portfolio choice but focus on maturity transformation

and the gap between long and short-term interest rates in a general equilibrium setting,

linking financial intermediation with fluctuations in term premia.

Lastly, our paper relates to the literature that analyse leverage cycles. Danielsson,

Shin, and Zigrand (2012) provide a framework linking financial intermediation, leverage,

volatility and risk premium, stressing the role of bank’s balance sheet in asset price determination.

However, their mechanism relies on fluctuations in bank capital. Leverage in

our framework fluctuates as an outcome of the securitization markets while bank equity

is held constant. In fact we show that our empirical results remain the same when we

control for movements in banking capital. Fostel and Geanakoplos (2012) also look at

financial innovations and leverage, and as here stress the importance of tranching to generate

leverage. However, they focus on the final investors’ demand based on heterogenous

beliefs leading to asset price bubbles while we focus on the the importance of pooling and

tranching in shaping the portfolio decisions of banks, establishing a link between financial

intermediation and asset prices.

The paper is organized as follows. Section 2 presents our empirical analysis. The

theoretical model and its solution are presented in Section 3. Section 4 discusses the main

implications of our results. Finally, Section 5 concludes.

2. Empirical Analysis

Our empirical analysis focuses on establishing whether variations in the volume of securitized

credit assets affect different asset markets, particularly by looking at the dynamic

patterns of risk premia in fixed income and equity markets. Our starting point is a general

vector autoregression (VAR) for asset returns used by Campbell and Viceira (1999)

and Campbell, Chan, and Viceira (2003). Campbell, Chan, and Viceira (2003) employ

a VAR containing the returns of the main fixed income and equity assets, namely the

short-term rate, the excess return on government bond (bond premium) and the equity

excess return (equity premium). Additionally, they include the dividend-price ratio and

the yield/term spread (difference between short and long term rates). Given our focus

on securitization we add the variation in the volume of securitized assets traded as an

additional variable. Our main interest, therefore, is in assessing whether there is additional

information content in fluctuations in securitization for explaining variations in excess

market and bond returns and establishing the effect of a shock to this additional variable

on the dynamic responses of asset returns. In order to identify these shock responses we

follow the identification structure of Christiano, Eichenbaum, and Evans (1999). As such,

the VAR moving average representation is given by

z t = B(L)u t , (1)


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