Lucrezia Reichlin London Business School & Now-Casting Economics Ltd and Silvia Miranda Agrippino, Now-Casting Economics Ltd

Transcription

1 NOW-CASTING AND THE REAL TIME DATA FLOW Lucrezia Reichlin London Business School & Now-Casting Economics Ltd and Silvia Miranda Agrippino, Now-Casting Economics Ltd PRESENTATION AT BIS, HONG KONG 22 ND JULY, 2014

2 NOW AND THEN: WHY WAIT? Forecast GDP growth for the Euro Area in th April th July 2014 Since 8 th April: monthly data releases (x3) for industrial production, trade, retail sales, employment, PMIs, etc.? Now- Casting IMF WEO Now- Casting IMF WEO

3 What is now-casting and why should we care? (1) Contraction of the terms Now and Forecasting Meteorology Now-casting forecasting up to 6-12 hours ahead long tradition, since 1860 Economic Now-casting forecasting the near future, the present and even the recent past In early days focus has mainly been on GDP Idea: exploit early monthly or even higher frequency information to obtain a timely estimate of quarterly GDP MOTIVATION: GDP data are published late and they are subject to large revisions Giannone, Reichlin and Small (2008): first to propose a formal framework

4 GDP forecastability: none beyond the now-cast

5 What is now-casting and why should we care? (2) Since then we have broadened the concept of now-casting and defined a comprehensive framework for reading in a coherent way all the relevant data as they get published in real time See Banbura, Giannone, Modugno and Reichlin, Handbook of Econometrics 2013 for a review The idea is to mimic market reading of the data flow in a formal model

6 The Now-Casting Approach Our objective is to track the real time data flow, using a single, coherent framework We want to model jointly all relevant data potentially many using a parsimonious model And we want to update the model every time there is a new data release or whenever there is news in the data flow The approach is entirely model based free of judgment

7 THE NOW-CASTING PLATFORM Calendar of data releases New data release * NEWS * Model run Model forecasts Factor update NCI GDP now-cast Other series now-casts Real time data vintages Model forecasts

8 The Model Observed Variable x i,t = m θ(i) (common factors t ) + noise i,t signal Variables can be at any frequency m θ : is a linear function; θ(i) parameters to be estimated Common factor unobserved; must be estimated NB: Disregard the noise!

9 Co-movements in economic data The factor: NCI^TM

10 Estimation Estimate model parameters ϴ Given m θ and Info (v) estimate the factor by Maximum Likelihood Est. factors t = Proj [factors t Info (v); m θ ] The forecast of each variable x i,t is: forecast x i,t = m θ(i) (factors t ) = Proj [ x i,t Info (v) ] Info (v): vintage of data available at time v; v is the date of a particular data release; v, v+1 are two consecutive data releases (possibly few minutes away) Characteristics of Info(v): jagged edged, mixed frequency, large

11 Updating and news For each variable x(i,t), i=1,, n compute the projection each time new information is released according to the calendar Proj [ x i,t Info(v+1) ], Proj [ x i,t Info(v+2) ].. NEWS example of news or model based surprise: x 1,t - Proj [ x 1,t Info(v+1) ] = news(x 1,v+1 ) x 2,t - Proj [ x 2,t Info(v+1) ] = news (x 2,v+1 ). UPDATING Proj [ x i,t Info(v+1) ] - Proj [ x i,t Info(v) ] =Weighted sum of surprises related to all variables included in the model NOT A BLACK BOX: CAN UNDERSTAND WHAT MOVES THE UPDATE!

12 The very short run: the slowdown The model started predicting a decline in early May Source: Now-Casting Economics Ltd

13 The first negative signals arrive from IP on May 7 th : they refer to March Source: Now-Casting Economics Ltd

14 But it is not only about GDP Products: Calendar of releases News Now-cast of all variables The now-casting Index (NCI ): this is the factor: it weight all variables including employment, construction, production, surveys, it disregards variablespecific dynamics

15 20 largest countries by share of world GDP Country Share of world GDP (%) Country 1 US India 2.5 Share of world GDP (%) Live on Now- Casting In development 2 Euro Area Canada China Australia Japan Mexico Germany South Korea France Indonesia UK Turkey 1.1 Now-Casting currently tracks 68% of world GDP 8 Brazil Saudi Arabia Russia Argentina Italy South Africa 0.5

16 NCI geographic coverage Rank Country Share of world GDP* (%) 1 US Euro Area China Japan UK Brazil 3.3 NCI tracks 65% of world GDP The same model is used for all countries; so index values are consistent and comparable

17 Release calendar e.g., the US Releases relating to June 2014 NCI Kansas City Fed Mfg ISM Non- Mfg Chicago Fed NAI MNI Bus Barometer Nonfarm Payrolls Industrial Production ISM Mfg Retail Sales June July

18 US NCI long history with NBER recessions Jan-91 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14

19 Euro Area NCI - long history with CEPR recessions Jan-91 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14

20 NCIs for the US, euro area and UK NCI@EA NCI@US NCI@UK

21 US and Euro Area NCI recent history

22 NCI Bloomberg tickers Brazil UK Euro Area Japan China US NCIXBZ NCIXUK NCIXEA NCIXJP NCIXCN NCIXUS

23 WHAT HAVE WE LEARNED IN YEARS OF RESEARCH AND THREE YEARS OF RUNNING THE PLATFORM IN REAL TIME? Timely data matter: the precision of the now-cast improves as more data are included in the model Surveys are important, but only at the beginning of the quarter However they can be forecasted On average we do as well as the professional forecasters for GDP and many of the other variables Best performing models are relatively simple in the parameterization and include only real economy aggregate indicators

24 And all other countries Euro Area ar dfm BB FF EC F N B Germany ar dfm BB FF EC F N B Italy France ar dfm BB FF EC F N B ar dfm BB FF EC F N B

25 And all other countries UK US ar dfm BB FF NIESR EC F N B ar dfm BB FF SPF F N B ar dfm BB JCER F N B Japan ar dfm BB BCB F N B Brazil

26 HISTORICAL PERFORMANCE VS SPF The US Quarterly GDP - US Actual GDP Now-Casting model Survey of Professional Forecasters Feb 2001 Feb 2002 Mar 2003 Apr 2004 Apr 2005 May 2006 May 2007 Jul 2008 Jul 2009 Source: Liebermann (2010) Real-time nowcasting of GDP: factor model versus professional forecasters, MPRA Paper, University Library of Munich

27 HISTORICAL PERFORMANCE ANALYSIS Current quarter: root mean squared forecast errors (RMFSE) US 1996Q1-2005Q4 US 1996Q1-2011Q1 EA 2003Q1-2011Q Germany 2003Q1-2011Q1 France 2003Q1-2011Q1 Italy 2003Q1-2011Q Key: N-C = Now-Casting; OOS = out of sample; IS = in sample; AR(2) = auto regressive projection; SPF = Survey of Professional Forecasters; GB = Federal Reserve Green Book ; EC = European Commission

28 WHY NOW-CASTING: A GOOD PREDICTOR Using the same model, Now-Casting predicts individual series Standard deviation of Now-Casting forecast errors; one day before release* Euro Area Germany UK NCI Bloomberg Survey * Average performance in historical reconstruction (January 2008 December 2013), using revised data

29 The China model in some detail Silvia Miranda Agrippino

30 The calendar Source: Giannone, Miranda, Modugno 2014

31 The Root Mean Squared Errors (RMSE) in relation to the real time data flow Source: Giannone, Miranda, Modugno 2014

32 The Root Mean Squared Errors (RMSE) in relation to the real time data flow Source: Giannone, Miranda, Modugno 2014

33 The Root Mean Squared Errors (RMSE) in relation to the real time data flow Source: Giannone, Miranda, Modugno 2014

34 The news impact Source: Giannone, Miranda, Modugno 2014

35 Annual Forecasts Source: Giannone, Miranda, Modugno 2014

36 Annual Forecasts Source: Giannone, Miranda, Modugno 2014

37 By-product: news index A News Index can be constructed by computing the weighted sum of news normalizing it with respect to one variable e.g., GDP Next chart shows the index for the US as constructed in real time starting from s = 2004q1 until t = 2013q1 Plain index: We report the three month rolling window

38 Quarterly rolling news index and quarterly returns of S&P CORRELATION = 0.487

39 But does macro matter for financial variables? Mixed evidence in the literature. but some people make money Research based on surveys to traders shows that macroeconomic news matter for financial variables provided that high frequency variation is smoothed away See previous chart quarterly rolling window of news index Research in our team confirms this result

40 What drives exchange rates? Bandwagon Effects Over reaction to news Speculative Forces Economic Fundamentals Technical Trading Intraday Medium Run (up to 6 months) Long Run (over 6 months) Other Proportion of respondents answering the question: Select the single most important factor that determines exchange rate movements in each of the three horizons listed. Source: Cheung, Chinn and Marsh (NBER WP 7524) How do UK based foreign exchange dealers think their market operates?

41 Aggregating the daily now-cast of GDP to a daily rolling forward quarter

42 Macro (Bloomberg) news and bond returns Daily change of bond returns at maturity τ: Aggregate over different time spans and compute R^2 Results: filtering from high frequency dynamics improves the goodness of fit Macroeconomic news matters at lower frequency

43 From Altavilla, Giannone and Modugno, 2014

44 Why should one buy the Now-Casting service? Quant we have a signal in continuous time about macroeconomic indicators and macroeconomic surprises automatically produced and updated can include in models on a routine basis Benchmarking: cross-check with your own judgemental view of the state of the economy Transparency and coherence: can see why your view moves in relations to surprises of new data publications Don t need a lot of PhD economists employ them to do something more interesting!

45 Summary: what is special about Now- Casting? Feature 1 Outputs generated entirely by machine 2 Outputs published automatically 3 Input set is large and heterogeneous 4 Decomposition shows effect of each release 5 Focus on current quarter Benefit Judgement free. No behavioural biases (herding, caution, competition, political bias) High frequency, and therefore timely. Can pick up signals before others Efficient. Extracts maximum information content from the newsflow. Processes information the way the market does, not the way professional forecasters do Transparent. Provides a clear, quantitative way of reading the newsflow Relevant: where we are now matters. Key to identifying turning points and key to any medium-term analysis The current quarter is also the only quarter which we can forecast with any accuracy

46 END

47 WHY NOW-CASTING: A GOOD PREDICTOR UK GDP GROWTH IN Q PATH OF REVISIONS % growth, QoQ Dates of ONS releases Official estimates from the Office of National Statistics (ONS) Estimate using now-casting analysis; see Is the UK still in recession?, Vox, 23 rd November, 2009, Giannone, Reichlin, Simonelli Source: Office of National Statistics

48 IMPROVING ACCURACY OVER FORECAST PERIOD Root Mean Squared Forecast Errors; Average for Euro Area Q Q For each quarter (the target quarter ), we start publishing an estimate of that quarter s GDP growth from the beginning of the prior quarter, and we finish when the first official estimate (the flash ) is published usually 4-6 weeks after the end of the target quarter. Over the course of this 7+ month forecasting period, the accuracy of our now-cast steadily improves, as we are able to take into account more and more information Now-Casting.com model - out of sample - in sample European Commission AR(2) Sources: Haver Analytics, European Commission