In this a paper a non-linear macro-stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It develops a framework in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset and thus allow to estimate the a stressed future state. It will be shown that contagion can be directly derived from the proximities while iterating the proximity based contagion leads to nat- urally defined feedback effects. This procedure allows accurate forecast of events under stress and thus allows to forecast the emergence of a potential crisis. The framework also estimates a set of the most influential economic indicators lead- ing to the potential crisis, which can then be used as indications of remediation or prevention of that crisis. Since the methodology is Random Forests based the framework is suitable for big data analysis.
This paper examines potential impacts of banks' leverage on their incentives to manage their liquidity. We analyze a model where banks control their liquidity risk by managing their liquid asset positions. In the basic framework, a model with a single bank, where the possibility of selling long-term assets when in need of liquidity is not taken into account, we find that the bank chooses to prudently manage its liquidity risk only when its leverage is low. In a model with multiple banks and a secondary market for long-term assets, we find that a banking system where banks are highly leveraged can be prone to liquidity crises. Our model predicts a typical pattern of liquidity crises that is consistent with what was observed during the 2007-2009 crisis.
The following paper proposes a portfolio performance measure to optimize, mostly bond asset portfolios usually held for regulatory purposes from a risk focused perspective. The measure is based on variations of the proximity measure introduced by the Random Forests framework, leading to a proximity based performance ratio. The proximities are modeled using a recursive conditional partitioning type of Random Forests, which allows for a ranking as well as an analysis of the risk drivers of the portfolio performance. The proximity based performance ratio is shown to, on average, outperform nine different and commonly known risk and performance ratios as well as the 1/N-balanced portfolio in three different tests, in- and out of the sample. The proximity based performance ratio can consider a large amount of risk rivers and is suitable for big data analysis for big and small financial institutions.
The term “shadow banking” refers to credit intermediation performed outside the regulated perimeter of traditional lenders. Banks, however, do play a significant role in it. The authors review the origins and characteristics of the shadow banking system, investigate how banks control various steps of the securitization process, and analyze the nexus with competition. They use a double-output formulation of the Lerner index to disentangle the market power of lending and non-traditional activities. They find important differences in the two indicators, consistently with the common narrative. The market power related to non-traditional activities is both larger in magnitude and more pro-cyclical than that estimated for traditional lending. The authors’ findings suggest that banks might engage in less traditional business lines to alleviate the competitive pressure borne on core activities.
We study properties of structured financial products optimizing a utility functional of a customer. The conventional method may have the disadvantage that the a priori restriction to a certain number of assets could make it impossible to find the optimal portfolio. So instead of optimizing the distribution of given assets, we impose only the price constraint as given by the CAPM and optimize the return distribution. In particular on nowadays markets where a multitude of asset types is available, it seems helpful to optimize first in the general framework, assuming a complete market, and then to find assets whose return distribution and conjoint probability distribution with the market portfolio resemble the theoretically optimal portfolio as closely as possible. We introduce a method to construct such optimal portfolios numerically and present some results for the cases of expected utility and cumulative prospect theory
We study the relation of financial development and the pace of technological advance in a dynamic agency theoretic model. A firm which is financed by outside shareholders but run by managers has the prospect of a process innovation which arrives stochastically. Adopting the innovation requires firing old management and hiring new with skills appropriate for the new technique. We show that subgame perfect equilibria in this game can be of two types. In entrenchment equilibrium once the new techniques has been announced old style management raises their dividend payout sufficiently to pre-empt the innovation. In maximum rent extraction equilibrium managers are unable or unwilling to match the impending productivity improvement and instead respond by increasing their perquisites for the remaining time of their tenure. We show that both equilibria involve several types of inefficiencies and can result in underinvestment in positive NPV projects. We discuss the role of financial innovation in reducing the inefficiencies identified.
The paper models fixed rate tenders, where a central bank offers to lend central bank funds to financial institutions. Bidders are constrained by the amount of collateral they have. We focus on the strategic interaction between bidding in the tender and trading in the interbank market after the tender, where short squeezes could occur. We examine how the design of the tender affects equilibrium bidding behavior and the incidence of short squeezes. Important elements in the analysis include the type of policy implemented by the central bank as well as bidders' initial endowments of liquidity and collateral. Three instruments for softening short squeezes are identified: the tender rate, the tender sizes, and admissible collateral. Increasing the tender rate or size tends to decrease the probability and severity of a short squeeze. The possibility of a short squeeze may induce bidders to oversubscribe even if the tender rate is higher than the competitive rate.
This article develops a theory of multiunit auctions where short squeezes can occur in the secondary market. Both uniform and discriminatory auctions are studied and bidders can submit multiple bids. We show that bidders with short and long preauction positions have different valuations in an otherwise common value setting. Discriminatory auctions lead to more short squeezing and higher revenue than uniform auctions, ceteris paribus. Asymptotically, as the auction size approaches infinity, the two formats lead to equivalent outcomes. Shorts employ more aggressive equilibrium bidding strategies. Most longs strategically choose to be passive. Free riding on a squeeze by small, long players has no impact on these results, but affects revenue in discriminatory auctions.
We examine the role of allocation rules in determining the set of equilibrium prices in uniform- price auctions. Beginning with Wilson (1979), the theoretical literature has argued that these auctions are subject to possible low equilibrium prices. We show that this is due to the way the asset is being divided. We focus on allocation rules that specify the way the asset is divided in cases of excess demand. This may have a dramatic effect on the set of equilibrium prices. In particular, we show that a simple allocation rule (pro rata) eliminates underpricing, while the allocation rule used in practice has a negative effect on equilibrium prices.
