Magnetic and electrical transport properties of artificial spin ice

This thesis explores the mechanisms of the magnetic reversal of permalloy artificial spin ice arrays. The main research foci include the influence of domain wall propagation on the magnetic reversal of honeycomb artificial spin ice, the low temperature behaviour of honeycomb artificial spin ice and the classification of inverse permalloy opals as three dimensional artificial spin ice. Room temperature imaging of the magnetisation configuration of the nanobars through the magnetic reversal, via scanning transmission X-ray microscopy, photoemission electron microscopy and Lorentz transmission electron microscopy, showed non random domain wall propagation through the frustrated vertices of the honeycomb artificial spin ice arrays. OOMMF simulations suggest that the origin of such non-randomness lies in the domain wall chirality. Boundary conditions necessary for domain wall injection into artificial spin ice arrays were investigated. A reduction of the edge nanobars width of 2/3 was needed to prevent random domain wall nucleation from the array edges. Electrical transport measurements showed evidence of a change in the magnetic reversal, driven by domain wall propagation, of honeycomb permalloy artificial spin ice below 15 K. The transition temperature was found to be proportional to the square of the saturation magnetisation of the ferromagnetic material used. The change in the magnetic reversal was associated with the non-random vertex domain wall positioning below the transition temperature due to the influence of vertex dipole interactions. Room temperature Lorentz transmission electron microscopy images and temperature dependent electrical transport measurements of three dimensional permalloy inverse opals showed the potential of magnetic inverse opals to act as three dimensional artificial spin ice systems.Open Acces

Charakteristika vs. Carry - Outperformance in Devisenmärkten

Die optimale Währungsallokation ist eine der Kernfragen des international agierenden Investors. Ich teste in diesem Zusammenhang empirisch den Mehrwert des Portfoliooptimierungsverfahrens von Brandt et al. (2009) im Devisenkontext und vergleiche das Ergebnis mit einer diversifizierten Carry-Strategie und weiteren Benchmarks. Da im Zuge dieses Verfahrens sogenannte Charakteristika als Inputsignale für die Allokation benötigt werden, selektiere ich auf Basis bereits vorhandener Literatur zur Prädiktabilität von Währungsrenditen die Faktoren Carry, Momentum, realer Wechselkurs, Leistungsbilanzsaldo, Produktionslücke und Volatilität und untersuche die Performance der auf Basis dieser Signale generierten Portfolios über den Zeitraum von Anfang 1990 bis Ende 2017. Ich finde die stärkste Evidenz für Carry, aber auch Momentum, der reale Wechselkurs und der Leistungsbilanzsaldo wirken mitunter als Signal für die Allokation der optimalen Portfoliogewichte interessant. Ebenfalls kann ich feststellen, dass die Profitabilität beinahe aller untersuchten Strategien maßgeblich vom gewählten Anlageuniversum abhängt, wobei bei gegebener Datenverfügbarkeit eine breite Definition mit Industrie- und Entwicklungsländern zu bevorzugen ist. Des Weiteren kann ich teils interessante Diversifikationseigenschaften und positive Wechselwirkungen zwischen den Charakteristika dokumentieren, welche sich durch Kombination mittels des gewählten Optimierungsansatzes realisieren lassen. Auch stelle ich fest, dass Transaktionskosten im Schnitt einen wesentlichen negativen Einfluss auf die Renditen der Strategien haben. Die Sensibilisierung des Verfahrens durch Inklusion eines entsprechenden Transaktionskostenterms führt jedoch zu einer Performance-Regeneration

JPMorgan Chase London Whale C: Risk Limits, Metrics, and Models

Value at Risk (VaR) is one of the most commonly used ways to measure and monitor market risk. At JPMorgan Chase (JPM), very large derivative positions established by Bruno Iksil in the Synthetic Credit Portfolio (SCP) caused the bank’s Chief Investment Office (CIO) to exceed its VaR limit for four days in a row in January 2012. In response, the CIO changed to a new VaR model on January 30, which appeared to immediately reduce VaR by half. However, JPM soon discovered that this new VaR model had not been properly implemented and the bank went back to using the previous model. In addition, Iksil, other SCP staff, and their managers also disregarded several other risk metrics and limits during the first quarter of 2012. However, after JPM’s Chief Investment Officer learned on March 23 that Iksil and the SCP had breached the CIO’s mark-to-market Credit Spread Widening 10% risk limit the day before, she ordered trading of the SCP to be halted immediately

JPMorgan Chase London Whale G: Hedging Versus Proprietary Trading

In December 2013, the primary United States financial regulatory agencies jointly adopted final rules to implement Section 619 of the Dodd-Frank Wall Street Reform and Consumer Protection Act, which is often referred to as the “Volcker Rule”. Section 619 prohibits banks from engaging in activities considered to be particularly risky, including proprietary trading and owning hedge funds or private equity funds. Banking regulators designed the final rule against proprietary trading in part to prevent losses like the $6 billion London Whale loss that took place in 2012 at JPMorgan Chase. Given the controversial nature of the Volcker Rule, it is not surprising that the regulatory agencies received 18,000 comment letters, including a 67-page letter from JPMorgan Chase

JPMorgan Chase London Whale B: Derivatives Valuation

After consistently producing positive results through 2011, the JPMorgan Chase (JPM) traders who oversaw the bank’s Synthetic Credit Portfolio (SCP) grew alarmed by a consistent string of losses beginning in January 2012. (The SCP was maintained by JPM to help hedge default risk and was the source of the 2012 London Whale trading loss.) To minimize the losses reported to their superiors until such time that market prices hopefully turned in their favor, the SCP traders began valuing their largest derivative positions in a manner that was not consistent with Generally Accepted Accounting Principles (GAAP) and JPM policy. The fair values recorded by the SCP traders were reviewed by the Valuation Control Group, as required by banking regulators, and by JPM’s Controller, but neither review raised any objection. However, after the JPM Task Force that investigated the 2012 London Whale incident uncovered evidence that the SCP traders had not estimated fair values in good faith, the bank restated its first-quarter 2012 earnings on July 13, reducing consolidated total net revenue by $660 million (2.5$459 million (8.5%)

JPMorgan Chase London Whale H: Cross-Border Regulation

As a global financial service provider, JPMorgan Chase (JPM) is supervised by banking regulatory agencies in different countries. Bruno Iksil, the derivatives trader primarily responsible for the $6 billion trading loss in 2012, was based in JPM’s London office. This office was regulated both by the Office of the Comptroller of the Currency (OCC) of the United States (US) and by the Financial Services Authority (FSA), which served as the sole regulator of all financial services in the United Kingdom (UK). Banking regulators in the US and the UK have entered into agreements with one another to define basic parameters for sharing information gathered during bank examinations and even assisting one another with bank inspections under certain circumstances. However, even as JPM sought to stifle OCC and FSA supervision, cooperation between the US and UK regulators was minimal

Ireland and Iceland in Crisis B: Decreasing Loan Loss Provisions in Ireland

All public companies in the European Union, including Ireland’s major banks, were required to adopt IAS 39 for their annual accounting periods beginning on or after January 1, 2005. Under the “incurred loss” model of IAS 39, banks could set aside reserves for loan losses only when objective evidence existed that a loan was impaired, not in anticipation of future losses. As a result, Irish banks saw their aggregate reserve for bad loans drop from 1.2% of loan balances at the end of 2000 to only 0.4% by 2006-07, just before the collapse of the banking industry caused loan losses to soar. In the aftermath of the global financial crisis, financial regulators and accounting bodies recognized the weakness of the pro-cyclical incurred loss model. As a result, they have proposed alternative “expected loss” models that allow reserves for expected losses to be built up over the life of a loan in a counter-cyclical fashion

JPMorgan Chase London Whale E: Supervisory Oversight

As a diversified financial service provider and the largest United States bank holding company, JPMorgan Chase (JPM) is supervised by multiple regulatory agencies. JPM’s commercial bank subsidiaries hold a national charter and therefore are regulated by the Office of the Comptroller of the Currency (OCC). Since the bank’s Chief Investment Office (CIO) invested the surplus deposits of JPM’s commercial bank units, the OCC was also CIO’s primary regulator. During the critical period from late January through March 2012, when CIO traders undertook the failed derivatives strategy that ultimately cost the bank $6 billion, JPM did not provide the OCC with required monthly reports that included CIO performance data and CIO’s internal reviews of the fair values assigned by traders to their derivative positions. However, OCC supervisors also failed to request the missing data, and thus found themselves surprised by the April 6 news stories unmasking the London Whale

JPMorgan Chase London Whale D: Risk-Management Practices

JPMorgan Chase (JPM) prided itself on having the best risk-management practices in the financial industry, having survived the 2007-09 financial crisis in better shape than many competitors. Chief Executive Officer Jamie Dimon often spoke of the bank’s “fortress balance sheet.” A keen focus on risk management is vital to JPM’s longevity, as is the case with all highly leveraged financial institutions. However, the JPM Task Force that investigated the $6 billion 2012 London Whale trading loss concluded that risk-management practices at the bank’s Chief Investment Office (CIO), the unit in which the loss occurred, were given less scrutiny by senior management than those of the bank’s client-facing businesses, despite the fact that the Chief Investment Office managed$350 billion in assets, an amount almost double JPM’s total stockholders’ equity at December 31, 2011

JPMorgan Chase London Whale A: Risky Business

In December 2011, the Chief Executive Officer and Chief Financial Officer of JPMorgan Chase (JPM) instructed the bank’s Chief Investment Office to reduce the size of its Synthetic Credit Portfolio (SCP) during 2012, so that JPM could decrease its RiskWeighted Assets as the bank prepared to adopt the impending Basel III bank capital regulations. However, the SCP traders were also told to minimize the trading costs incurred to reduce Risk-Weighted Assets, while still maintaining the opportunity to profit from unexpected corporate bankruptcies. In an attempt to balance these competing objectives, head SCP derivatives trader Bruno Iksil suggested in January 2012 that the SCP expand a strategy first implemented in 2011 of buying large volumes of certain credit derivatives, while simultaneously selling large volumes of other credit derivatives. The strategy quickly proved unsuccessful, and JPM’s Chief Investment Officer ordered Iksil and the other SCP traders to halt this strategy on March 23. However, losses continued to mount as the credit derivative positions were unwound, ultimately reaching $6.2 billion by December 2012