### 统计代写|风险建模代写Financial risk modeling代考|News effects on the exchange rate

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## 统计代写|风险建模代写Financial risk modeling代考|News effects on the exchange rate

As shown in the previous section, transaction volume tends to surge during a particular time of the day. One of the reasons for a surge in transactions is a concentrated arrival of new macro information in the markets. The possible existence of private information may cause a different trading response by dealers, some of them informed and some uninformed, to the arrival of new information. Then the trading may be intensified between these two types of dealers, as described in the “private information model” of Easley and O’Hara (1992).

In this section, the exchange rate reaction to the release of major macroeconomic statistics is examined. In particular, this section examines how the dollar/yen exchange rate market digests information contained in the various macroeconomic statistics’ releases – to what extent transactions and prices react to the macroeconomic statistics’ news, how long the news effect lasts and which news has the most/least impact on the exchange rate. In the analysis, the unexpected component of macroeconomic announcements, a “surprise,” is defined by the difference between the actual indicator announcement and the average of predicted indicators by the market. The sample period is from 2001 to 2005 and we examine the impacts from 12 Japanese macroeconomic statistics’ releases on the exchange rate returns, volatility and the transaction volume.

## 统计代写|风险建模代写Financial risk modeling代考|Japanese macroeconomic announcements

Chaboud et al. (2004) study the impact of US macroeconomic announcements on exchange rates using the following US macro variables: payroll, GDP advanced, PPI, retail sales, trade balance and Fed funds rate (target). These authors found a significant impact on exchange rate returns from a surprise component in the announcement. In the European perspective, Ehrmann and Fratzscher (2005) used GDP, Ifo business climate index, business confidence balance, PPI, CPI, retail sales, trade balance, M3, unemployment, industrial production and manufacturing orders as proxies for Germany news releases. 22

In contrast to US macroeconomic announcements, most of which come out at $8.30 \mathrm{am}$ (EST), the release time of Japanese news announcements varies from news to news. Some of the announcements are released in the morning and others in the afternoon. Most of the major macroeconomic statistics come out at either $8.30 \mathrm{am}, 8.50 \mathrm{am}, 10.30 \mathrm{am}$, $2.00 \mathrm{pm}$ or $2.30 \mathrm{pm}$.

After 2001, the announcement time for Japanese macroeconomic statistics has become fairly standardized. Until 2000 , however, a lot of news was released one hour earlier than the current release time, while some news releases were fixed later or went back and forth. For example, the current CPI release time was set at $8.30$ only in 2002 . Release time of three news announcements (balance of payments [8:50], trade balance [8:50] and retail sales [14:30]) changed once in early 2000 and moved back to the original time about six months later.

Figures $3.6$ and $3.7$ show the average of number of deals on newsrelease days and non-announcement days for Tankan (Bank of Japan, business survey) and GDP preliminary (GDPP, at $8.50 \mathrm{am}$ JST). This announcement time is just before the first peak in transactions within the day and, therefore, this surge of activity may likely reflect the impact of news releases. ${ }^{23}$ Each figure plots the 15 -minute averages in the number of transactions from 6 am to 12 noon for 2001-2005. The red line shows the benchmark of no macro announcement, and the black line shows the deal activity on announcement days. The top panel of the figure shows the difference in the number of deals between news-announcement days and non-announcement days.

## 统计代写|风险建模代写Financial risk modeling代考|Impact of surprises on exchange rate activities

When an announcement has unexpected content the announcement is expected to be followed by a change in the exchange rate, because market participants react to this unexpected part by rebalancing their portfolio positions. That is, a surprise would result in changes – positively or negatively – in the exchange rate returns through changes in the number of deals. The release of a news announcement itself, regardless of surprises, may affect price volatility. Suppose that the actual announcement of a macro announcement is exactly the same as the average of market expectations. Then there should not be any positive or negative returns that follow the announcement of no surprise. However, even if the “average” expectation is confirmed by the actual announcement, individuals may be heterogeneous and some are positively surprised and some negatively surprised. Hence, those who were off the average have incentives to trade and price volatility may rise with returns being zero. The total amount of deals may increase at the time of macroeconomic announcement. Unless market participants are homogeneous in expectations on the news – which is very unlikely – some deals are bound to occur right after the announcement. When there is a surprise component in the news, additional deal activities will be stimulated.

Hashimoto and Ito (2009) examined whether and how much an unexpected component of a macroeconomic news announcement, a “surprise, ” will affect returns, volatility and the number of transactions in the dollar/yen exchange market with the following estimations: ${ }^{24}$ Return regression:
\begin{aligned} \Delta s(t, u) &=\sum_{i(u)=1}^{n(u)} \alpha_{i(u)} N_{i(u)}(t, u)+\varepsilon(t, u) \ \Delta s(t, u) &=\sum_{i(u)=1}^{n(u)} \alpha_{i(u)} N_{i(u)}(t, u)+\delta \Delta s(t, u-k)+\theta N D(t, u-k)+\varepsilon(t, u) \end{aligned}

## 统计代写|风险建模代写Financial risk modeling代考|Japanese macroeconomic announcements

2001年以后，日本宏观经济统计数据的公布时间已经相当规范。然而，直到 2000 年，很多新闻都比当前发布时间提前了一个小时发布，而一些新闻发布则更晚一些，或者来回走动。例如，当前 CPI 发布时间设置为8.30仅在 2002 年。三个新闻公告（国际收支[8:50]、贸易平衡[8:50]和零售[14:30]）的发布时间在2000年初改变了一次，大约六个月后又回到了原来的时间。

## 统计代写|风险建模代写Financial risk modeling代考|Impact of surprises on exchange rate activities

Hashimoto 和 Ito (2009) 研究了宏观经济新闻公告中的意外组成部分，即“意外”，是否以及在多大程度上会影响美元/日元交易市场的回报、波动性和交易数量，并做出以下估计：24返回回归：
Δs(吨,在)=∑一世(在)=1n(在)一种一世(在)ñ一世(在)(吨,在)+e(吨,在) Δs(吨,在)=∑一世(在)=1n(在)一种一世(在)ñ一世(在)(吨,在)+dΔs(吨,在−ķ)+θñD(吨,在−ķ)+e(吨,在)