Lutz Johanning

Value-at-Risk-Modelle zur Ermittlung der bankaufsichtlichen Eigenkapitalunterlegung beim Marktrisiko im Handelsbereich

Nach der vom Basler Ausschuß für Bankenaufsicht im Januar 1996 vorgelegten „Änderung der Eigenkapitalvereinbarung zur Einbeziehung der Marktrisiken“ sollen die Banken zukünftig die Eigenkapitalunterlegung ihrer Marktrisiken im Handelsbereich nicht nur wie bisher mit den vordefinierten Standardverfahren (Building-Block-Ansatz), sondern alternativ auch mit eigenen Value-at-Risk-Modellen berechnen dürfen. Der Beitrag arbeitet die Vorteile und Defizite der Vorschläge des Basler Ausschusses für Bankenaufsicht und des Pre-Commitment-Ansatzes heraus, den der Federal Reserve Board der Vereinigten Staaten als Alternative zu den Basler Vorschlägen unterbreitet hat. Es wird insbesondere untersucht, welche - möglicherweise adversen - Anreize für die Banken bei der Anerkennung interner Modelle entstehen können und inwieweit die Risikokennziffer „Value-at-Risk“ überhaupt für die Zwecke der Bankenaufsicht geeignet ist.

Information Signaling and Competitive Effects of M&A: Long-Term Performance of Rival Companies

In this paper, we investigate the long term performance of rival companies related to acquisition targets. Using a sample of 2,511 deals from 1985 to 2005, we document an under-reaction of capital markets to the information contained in M&A announcements. Following 6,138 large rival gain events due to positive information signaling and 5,408 large rival loss events due to the negative competitive effects of the deal, we observe a return drift for up to 12 months after the announcement. Hence, our results indicate that capital markets do not immediately incorporate the effects of M&A announcements into rival stock prices.

Do Markets Anticipate Changes in Risk after Major Corporate Events? Evidence from SEOs

This paper examines the relationship between stock and option markets around SEO events. We compare option-implied volatility and realized volatility to show that option markets do not fully predict risk dynamics following equity issues. Moreover, we show that straddle strategies that explore the difference between option-implied and realized volatility following SEO events can lead to significant risk-adjusted (by common risk factors) positive returns. We also find that risk-adjusted returns can be partially explained by uncertainty (approximated for by option market liquidity). We interpret this as compensation for writing options during times of high uncertainty around the SEO event, where long options are more valuable.

Umfassendes Rating für Zertifikate: Ziele, Konzept und Nutzen

Die Insolvenz der amerikanischen Investemtbank Lehman Brothers hat institutionellen und privaten Anlegern das Bonitatsrisiko deutlich vor Augen gefuhrt: Eine Insolvenz tritt in der Regel nur mit einer geringen Wahrscheinlichkeit ein, im Falle des Falles kann der Anlageschaden aber erheblich sein. So mussen die Besitzer von Lehman-Zertifikaten mit einem Totalverlust bzw. sehr hohen Verlust ihrer Anlage rechnen. Die jungste Finanzkrise hat aber neben dem Bonitatsrisiko noch zwei weitere Kapitalmarkteigenschaften von Finanzprodukten verdeutlicht. Der Beginn der Finanzkrise war dadurch gekennzeichnet, dass vormals liquide Produkte plotzlich illiquide wurden, also am Markt nicht mehr verauserbar waren. Viele Anleger haben erst in dieser Marktphase bewusst wahrgenommen, dass Liquiditat, also die jederzeitige und billige Handelbarkeit, ein Qualitatskriterium von Wertpapieren ist. Zudem wurde wieder einmal deutlich, dass sich die Risiken sehr schnell, also dynamisch andern konnen. Im Laufe der Krise erhohten sich beispielsweise die impliziten Volatilitaten und Credit Spreads erheblich.

Is It Really There? Predictability of Supplier Returns After Large Customer Price Changes

Cohen and Frazzini (2008) examine economically linked firms and document widespread cross-asset return predictability at monthly horizons, specifically from customers to their suppliers. They argue that limited investor attention is responsible for their results. We extend this investigation to the extremes of the return distribution. We examine return predictability for economically linked firms at the daily level by analyzing supplier stock price reaction after large customer price changes. In contrast to Cohen and Frazzini (2008), we conclude that investor attention is only ‘partially limited’ when examining the large, attention-grabbing customer price changes investigated in this paper: return predictability mainly occurs in the first week after the event, does not apply to the largest supplier stocks, and has disappeared, at least for negative events, in the more recent past.

Risk Budgeting with Value at Risk Limits

Our analysis focuses on the risk budgeting process for banks using value at risk limits. In this context, we investigate three major practical problems: a) differences in time horizons between the bank’s total risk budget and the trading divisions’ activities; b) adjustment for accumulated profit and losses to risk budgets, and c) incorporation of correlations between assets into the risk budgeting process. To analyze these practical problems, we use Monte Carlo simulation. Thereby, it can be shown that differences in time horizons among risk budgets and trading units can be adjusted by the square root of time rule. Three types of limits are proposed for the adjustment of accumulated profit and losses: the fixed, stop loss and dynamic limits. While the two latter restrict the maximum loss to the ex ante specified limit and show a symmetric profit and loss distribution, the dynamic limit’s distribution is skewed to the right. We further illustrate that the average usage of total risk capital is only 31.45 % for a trading division with thirty independently deciding traders. This shortfall is due to diversification effects. This setting is compared with a benchmark model in which total risk capital is always used at the full capacity of 100 %. The comparison shows that the average profit in the former model is only 33.13 % of the generated profit in the benchmark model. The results may have interesting organizational implications on the banking sector.