Working papers

Who Benefits from Insider Information?

It is widely acknowledged that insiders profit from their access to privileged information. However, recent empirical findings suggest that the dollar profits of insiders may be relatively modest. This naturally raises two important questions: Can insider trading still pose a serious “lemon market” problem? Are insiders truly the primary beneficiaries of their insider information? I propose a model à la Kyle, where insiders trade through brokers that then relay the information about the insiders’ trades to their other clients, who in turn play the role of followers. I show theoretically that insiders can relinquish the dominant fraction of their profits to followers merely because of a timing disadvantage: they are in a vulnerable position because they act first. In turn, followers compete with insiders, amplifying insiders’ trades and taking most of the profits.

Securities lending and information transmission: a model of endogenous short-sale constraints

I study short-sale constraints in a market with asymmetric information. I offer a novel approach endogenizing short-sale constraints by including an asset-borrowing market in my model. Short-sellers have to borrow an asset and therefore reveal information to a lender. The lender trades on her own account in addition to charging fees, which motivates the short-seller to hide the information and hinders short sales. I contribute to the literature by modeling the mechanism behind short-selling in the absence of explicit short-selling restrictions that are currently less relevant in practice. The model has new implications for profit distribution, market efficiency, and volatility.

Informed trading, short-sale constraints, and leverage effect in equity returns

I model informed trading subject to short-sale constraints and find that short-sale constraints can cause the asymmetric volatility effect (also known as the “leverage effect”). I offer an infinite-horizon model with overlapping generations of private information and stationary time series of returns. This model builds up on the framework of Kyle (1985) model augmented with a short-sale constraint. I consider a collection of settings and find that the magnitude of the leverage effect is driven by the assumptions of the probability distribution of the asset’s fundamental value. Additionally I find that fat-tailed fundamental values can generate a persistent volatility effect irrespective of the short-sale constraints.

Unawareness in safety-first portfolio optimization (joint with N. Kolani, M. Madotto, and F. Severino)

Loss protection can be very challenging when investors are unaware of some possible tail events that affect returns. Investors may recognize that their knowledge is incomplete and react with fear or excitement. This unawareness can, in turn, be exploited by professional portfolio managers who have full knowledge of the possible market scenarios. Using a safety-first approach, we show that moderate degrees of both unawareness fear and unawareness excitement have no impact on portfolio choices. By contrast, sufficiently high degrees of unawareness fear lead investors to prefer safer strategies and foresee lower returns, allowing portfolio managers to withhold substantial profits from them. In this case, safety-first portfolios turn out to be independent of the threshold return and risk tolerance initially set by investors. Finally, as unawareness fear reaches even higher levels, portfolio choices start exhibiting behaviors that are opposite to those under full awareness.

Work in progress

When interest rate shock defies expectations: A precise methodology of stress testing for bond portfolios

(Joint with A. Matyunina and F. Severino)

Large interest rate changes pose a solvency and liquidity risk to financial institutions, as illustrated by the recent failure of Silicon Valley Bank linked to losses on long-term Treasuries. Conventional stress-testing methodologies for bonds typically rely on polynomial price approximations, whose accuracy deteriorates markedly under large rate movements. We develop a simple yet accurate approach to approximate bond prices: we construct a fictitious two-cash-flow bond that matches the duration and convexity of the original bond. This method yields precise bond price estimates under extreme scenarios. Our methods allow us to confine the bond price in a narrow interval and enhances the portfolio losses estimation under changes in the yield curve shape. Additionally, we propose a regulatory framework in which regulators have incomplete information about the investors’ bond portfolios: only aggregate duration and convexity of the entire portfolio—as opposed to data on individual bonds. Even with limited information, our approximation methods will allow regulators to precisely evaluate portfolio losses under extreme stress scenarios.

Dissimulation of informed trades on OTC fixed income markets

I propose a model à la Easley and O’Hara (1987). In my model, the traders have a larger decision space than in the Easley and O’Hara model. The traders chose their order size in a continuum of values. If the asset fundamental value is binary, my model yields a unique partially-separating mixed strategy equilibrium. In equilibrium, the price is a non-linear function of the order size, and moreover, a non-smooth function. The orders whose size does not exceed a given threshold have no effect on the price. At the threshold, the price graph (as a function of the order size) has kinks. There is a kink on each side: purchases and sales. For the orders whose size exceeds the threshold, the bid-ask spread expands as a function of the order size.

The Chicken and the Egg of WACC

The trade-off capital structure theory contends that firms choose their financial leverage so as to balance between exploiting the interest tax shield and avoiding the escalation of expected bankruptcy costs and agency conflicts. In practice, buy-side analysts are in a setting with incomplete information. Managers know about the firm’s capital structure target more than the outsides. Moreover, the insiders are likely to have incentives to mislead the market regarding the capital structure target to manipulate the stock price. To apply the discounted cash flow technique, an analyst needs the weighted average cost of capital (WACC). Two common recipes are known: (1) rely on the firm’s public announcements about targeted capital structure, (2) find the capital structure from the firm value. The first recipe is straightforward but it suffers from lack of credibility of the public announcements. The second method is more economically sound but it requires  solving an evil loop: the firm value depends on the WACC, which depends on the financial leverage, which in turn depends on the value of the firm. Existing literature proposes an iterative method to solve this circular problem. Usually, this methodology works but the convergence is not guaranteed. I scrutinize the circular problem and identify the conditions for existence and uniqueness of solutions. In addition, I propose an alternative concise method to solve the circular problem featuring much faster and more certain convergence. In practice, this means that financial analysts will be equipped with a simple yet powerful tool to find mutually consistent capital structure and the value of equity in two to three iterations.