Order Flow Matters for Exchange Rate Determination

我们提出的议程是围绕一个简单但具有挑战性的想法组织的：订单流对汇率决定很重要。这个想法是挑衅性的，因为订单流在大多数汇率模型中不起作用。然而，要使订单流不起任何作用，就需要对市场出清价格的实际确定做出强有力的假设，从理论上讲，这些假设很难得到辩护。它们也很难在经验基础上进行辩护。现在有强有力的证据表明，订单流发挥着重要作用，传统模型无法捕捉到这一作用。 通过放松这些强有力的假设，我们的模型提供了一个工具，了解价格制定者如何找到清算价格，以及这个价格是基于什么。从经验上看，我们的初步结果表明，订单流可以解释每日汇率变化的一半，这一比例远远高于利率等传统宏观基本面。我们的项目代表了一个明显不同的研究议程，因为这些结果与现有的宏观经济或微观结构的方法很难调和。我们的研究议程从宏观经济和微观结构的方法借用自由，但不能被视为包括在任何一个。该议程并没有像微观结构方法中的典型做法那样，将汇率与宏观基本面脱钩。因此，它牢牢地扎根于更广泛的资产定价背景下。该议程也没有像宏观经济方法中的典型做法那样，将汇率视为在常识环境中确定的。要脱离常识，就需要处理信息的汇总问题。我们充分利用微观结构文献中的工具来解决这个aggregation.The项目使用了两个新的数据集，涵盖了1996年5月1日至8月31日四个月期间的即期外汇市场活动。 一个数据集包含九种货币的实际交易的时间戳、逐时数据。这组数据有三个特点值得注意。首先，它提供了整个银行间市场24小时交易日的交易信息，而早期的数据集通常只覆盖一个交易商，而且只覆盖一天的部分时间。其次，个体参与者并没有真实的及时观察这些市场范围内的数据，这使得我们能够进入价格决定的“黑匣子”。第三，多种货币和相对较长的时间跨度使我们能够从资产定价的角度来处理价格决定问题，我们的两个数据集中的第二个数据集的范围远小于第一个数据集，但它涵盖了一个市场部分，到目前为止，这个市场部分仍然超出了市场学家的范围--公众交易。到目前为止，所有外汇交易数据都来自银行间交易。 第二个数据集包含了一家大型银行在第一个数据集所涵盖的同一个四个月期间收到的所有公开交易。就外汇市场份额而言，那家银行是世界第一。这一数据集使我们能够首次将交易商的交易和价格与经济中的潜在需求来源联系起来。我们将通过拟议的研究解决的问题包括：汇率变化中有多大比例可归因于订单流？ 订单流的哪些组成部分传递了最多的信息？宏观经济公告的价格效应是否与订单流无关？ 汇率决定是否取决于宏观经济基本面、订单流和价格？ 订单流如何与外汇市场的学习、羊群效应和噪音交易联系起来？ 反馈交易是否解释了订单流和价格之间的部分相关性，例如，弗里德曼的稳定投机者？来自央行的指令流何时可能对价格产生最大影响？

Our proposed agenda is organized around a simple but provocative idea: order flow matters for exchange-rate determination. The idea is provocative because order flow plays no role in most exchange rate models. For order flow to play no role, however, requires strong assumptions about how market-clearing prices are actually found. On theoretical grounds, these assumptions are difficult to defend. They are difficult to defend on empirical grounds too. There is strong evidence now that order flow plays an important role, a role that traditional models are not designed to capture. By relaxing these strong assumptions, our models provide a vehicle for understanding how price-setters find the clearing price, and what that price is based upon. Empirically, our initial results show that order flow can account for half of daily exchange-rate variation, a far greater share than traditional macro fundamentals such as interest rates. Our project represents a distinctly different research agenda because these results are hard reconcile with either the existing macroeconomic or microstructure approach.Our research agenda borrows liberally from both the macroeconomic and microstructure approaches, but cannot be viewed as encompassed by either. The agenda does not treat exchange rates as decoupled from macro fundamentals, as is typical within the microstructure approach. It is thus firmly anchored in the broader context of asset pricing. Nor does the agenda treat exchange rates as determined in a common-knowledge environment, as is typical within the macroeconomic approach. Departing from common knowledge requires a treatment of information aggregation. We make ample use of tools from the microstructure literature for addressing this aggregation.The project uses two new data sets that cover activity in the spot foreign exchange market over a four-month period, May 1 to August 31, 1996. One data set contains time-stamped, tic-by-tic data on actual transactions for nine currencies. Three features of this data set are noteworthy. First, it provides transaction information for the whole interbank market over the full 24-hour trading day whereas earlier data sets typically cover one dealer, and only part of the day. Second, individual participants do not observe these market-wide data in real time, which allows us to get inside the "black box" of price determination. Third, multiple currencies and a relatively long time span allow us to address price determination from more of an asset-pricing perspective.The second of our two data sets is much less extensive than the first, but covers a segment of the market that has, until now, remained beyond the reach of empiricists - trading by the public. Until now, all transaction data in foreign exchange have come from interbank trading. This second data set contains all the public trades in DM/$ received by a large bank over the same four-month period covered by our first data set. That bank is number one worldwide in terms of foreign exchange market share. This data set allows us, for the first time, to connect dealers' trading and prices to the underlying sources of demand in the economy.The questions we will address with the proposed research include: What share of exchange rate variation is attributable to order flow? What components of order flow convey the most information? Are the price effects of macroeconomic announcements uncorrelated with order flow? Does exchange rate determination work from macroeconomic fundamentals, to order flow, to price? How does order flow link to learning, herding, and noise trading in foreign exchange markets? Does feedback trading account for part of the correlation between order flow and price, e.g., Friedman's stabilizing speculators? When is order flow from central banks likely to have the most price impact?