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Unconscious conditioned fear response in the right amygdala (see Figure 2.4)

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Peerings are generally a zero cost exchange of routing information between two networks over which the neighbours announce their own networks and those of their customers (but not those of other peers and transit providers). Because traf c to or from these neighbours neither earns nor costs money, pre xes learned from these neighbours should be preferred over those learned from transit providers but should be less favoured than otherwise identical pre xes learned from customers. Normally, peers only receive pre xes originated locally or learned from your customers. In order to implement this policy, it is necessary to be able identify routes originated locally or learned from customers, peers and transit providers (see below). This can be achieved with communities. By marking each pre x on ingress (or at the point of origin) with a community representing the source of the pre x, it is possible to use that community at the point of egress to select the routes to be announced based on the source of the pre x (see Table 6.10).

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profit to maximum drawdown (P:MD) for the system with the stop loss is larger and the time percentage required to achieve this same P:MD is smaller. Therefore, the addition of the stop loss yielded a greater return vis -vis risk while tying up less investor capital over time.

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public class PrePaidClient { private static final byte[] PREPAID_AID = {(byte)0xa0, 0x00, 0x00, 0x00, 0x62, 0x03, 0x01, 0xc, 0x8, 0x01 }; public static void main(String[] argv) throws RemoteException { try { // initialize OCF SmartCard.start(); // wait for a smart card CardRequest cr = new CardRequest(OCFCardAccessor.class); SmartCard sc = SmartCard.waitForCard(cr); // obtain an OCFCardAccessor for Java Card RMI CardAccessor ca = (CardAccessor) sc.getCardService(OCFCardAccessor.class, true);

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The data-backed return to normalcy unraveled because, once LTCM suffered a bit of trouble, the rest of the market began to trade against their portfolio, that is, began to bet against normality. As a result, things became more, not less, abnormal than ever. Courtesy of the uniquely unique presence of an entity like LTCM at that very precise point in time. New people and new circumstances can render old-timers hopelessly irrelevant. The widespread presence of quantitative investors (or quant funds), now a ubiquitous element of the markets, may be a particularly acute case of what could be deemed the new kids on the block phenomenon, and of how under such situations past data becomes extra unreliable. Quant punters (in more or less intense fashion) are in the habit of employing very advanced technological and scienti c tools in the quest for making money. They also tend to (a la LTCM) take a hard statistical look at the historical rearview mirror as guidance for position taking and risk measurement. The problem with this is that, of course, never before had so many smart scientists and computer geniuses coincided in the markets, often playing exactly the same type of investment games, often armed with billions of monetary units in ammunition. So when they look at past data (notwithstanding how extremely sophisticated the lenses may be) they don t nd themselves. They couldn t, because they weren t there. In the case of certain speci c strategies maybe one or two early pioneers had been going at it as far as two or three decades ago, but nothing remotely close to today s reality, both in terms of the crowded number of players, the size of their wallets, and the technological prowess. Today s quant funds are employing computers and mathematical models that simply did not exist until quite recently. When the data captures neither the people nor the tools, it is impossible to con dently borrow much from such ancient wisdom. Thus, the presence of quanty folks using cutting-edge modernish technologies to trade and with a habit to statistically analyze the past may be akin to a catch-22 situation (on occasions, at least): The historical guide is rendered faulty by the very current (and not past) existence of those folks. Take risk. A quant fund may measure the riskiness of a strategy by back-testing its past performance and building devices such as Value at Risk. But those numbers would not account for the aliveness of that fund and its contemporary siblings, clouding the picture by not re ecting the possibility, for instance, that a liquidation by one member

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