Quench propagation and protection analysis of the ATLAS Toroids

The ATLAS superconducting magnet system consists of the Barrel Toroid, two End Cap Toroids and the Central Solenoid. However, the Toroids of eight coils each are magnetically separate systems to the Central Solenoid. The Toroids are electrically connected in series and energized by a single power supply. The quench protection system is based on the use of relatively small external dump resistances in combination with quench-heaters activated after a quench event detection to initiate the internal dump of stored energy in all the coils. A rather strong quench-back effect due to eddy-currents in the coil casings at the transport current decay is beneficial for the quench protection efficiency in the event of heater failures. The quench behaviour of the ATLAS Toroids was computer simulated for normal operation of the quench protection system and its complete non-operation (failure) mode. (3 refs)

Quench propagation and detection in the superconducting bus-bars of the ATLAS magnets

The ATLAS superconducting magnet system comprising Barrel (BT) and End-Cap Toroids (ECT) and also Central Solenoid (CS) will store more than 1.5 GJ of magnetic energy. The magnet system will have many superconducting busbars, a few meters long each, running from the current leads to Central Solenoid and Toroids as well as between the coils of each Toroid. Quench development in the busbars, i.e., the normal zone propagation process along the busbar superconductors, is slow and exhibits very low voltages. Therefore, its timely and appropriate detection represents a real challenge. The temperature evolution in the busbars under quench is of primary importance. Conservative calculations of the temperature were performed for all the magnets. Also, a simple and effective method to detect a normal zone in a busbar is presented. A thin superconducting wire, whose normal resistance can be easily detected, is placed in a good thermal contact to busbar. Thus, the wire can operate as straightforward and low-noise quench-detector. (4 refs)

Volatility forecasting in the Chinese commodity futures market with intraday data

Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms

Breaking into the blackbox: Trend following, stop losses and the frequency of trading - The case of the S&P500

In this article, we compare a variety of technical trading rules in the context of investing in the S&P500 index. These rules are increasingly popular, both among retail investors and CTAs and similar investment funds. We find that a range of fairly simple rules, including the popular 200-day moving average (MA) trading rule, dominate the long-only, passive investment in the index. In particular, using the latter rule we find that popular stop-loss rules do not add value and that monthly end-of-month investment decision rules are superior to those which trade more frequently: this adds to the growing view that trading can damage your wealth. Finally, we compare the MA rule with a variety of simple fundamental metrics and find the latter far inferior to the technical rules over the last 60 years of investing

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Liquidity risk premia : an empirical analysis of european corporate bond yields

In this study we highlight the importance of liquidity risk, especially in periods of market stress, and advocate in favour of an explicit consideration of a liquidity premium when using mark-to-model methodologies to value financial assets. For European corporate bonds, we show that the liquidity premium, calculated as the difference between the yield spread of corporate bonds and the spread of credit default swaps, grew significantly during the recent market turmoil not only in absolute terms but also in relative terms. Although liquidity premiums were far from stable during the time frame of analysis-from 1 January 2005 to 31 December 2009 - on average roughly 40% of corporate yield spreads can be interpreted in terms of liquidity premia. We propose direct matching between the CDS and the underlying reference assets when computing liquidity premia. This differs from what seems to be the industry standard, which is simply to use indices when trying to infer market implied liquidity premia. Although computationally more demanding, the method we use is sounder from a theoretical point of view and produces richer results and analysis. With this method we are able present an analysis of liquidity risk premia per sector of activity

Transaction Costs, Liquidity and Expected Returns at the Berlin Stock Exchange, 1892-1913

We estimate effective spreads and round-trip transaction costs at the Berlin Stock Exchange for the period 1892-1913 using daily stock market returns for a sample of 27 stocks. Our results show that transaction costs at the main stock exchange in a bank-based financial system at the turn of the 20th century were quite low and about comparable to transaction costs in modern markets. Nonetheless, transaction costs varied substantially over time and across securities, whereby the cross-sectional variation could be substantially explained by firm size and time variation by crises. Furthermore, we find surprising evidence that transaction costs decrease the expected excess returns. Thereby size and momentum premia are of expected signs while market beta has no significant influence on the cross-sectional return variation