Research Review | 15 March 2019 | Nowcasting

Factor Timing Revisited: Alternative Risk Premia Allocation Based on Nowcasting and Valuation Signals
Olivier Blin (Unigestion), et al.
10 September 2018
Alternative risk premia are encountering growing interest from investors. The vast majority of the academic literature has been focusing on describing the alternative risk premia (typically, momentum, carry and value strategies) individually. In this article, we investigate the question of allocation across a diversified range of cross-asset alternative risk premia over the period 1990-2018. For this, we design an active (macro risk-based) allocation framework that notably aims to exploit alternative risk premia’s varying behavior in different macro regimes and their valuations over time. We perform backtests of the allocation strategy in an out-of-sample setting, shedding light on the significance of both sources of information.

Nowcasting Recessions Using the SVM Machine Learning Algorithm
Alex James (Paraconic Technologies US), et al.
21 December 2018
We introduce a novel application of Support Vector Machines (SVM), an important Machine Learning algorithm, to determine the beginning and end of recessions in real time. Nowcasting, “forecasting” a condition about the present time because the full information about it is not available until later, is key for recessions, which are only determined months after the fact. We show that SVM has excellent predictive performance for this task, and we provide implementation details to facilitate its use in similar problems in economics and finance.

Nowcasting Private Consumption: Traditional Indicators, Uncertainty Measures, Credit Cards and Some Internet Data
Maria Gil (Banco de España), et al.
11 December 2018
The focus of this paper is on nowcasting and forecasting quarterly private consumption. The selection of real-time, monthly indicators focuses on standard (“hard”/“soft” indicators) and less-standard variables. Among the latter group we analyze: i) proxy indicators of economic and policy uncertainty; ii) payment cards’ transactions, as measured at “Point-of-sale” (POS) and ATM withdrawals; iii) indicators based on consumption-related search queries retrieved by means of the Google Trends application. We estimate a suite of mixed-frequency, time series models at the monthly frequency, on a real-time database with Spanish data, and conduct out-of-sample forecasting exercises to assess the relevant merits of the different groups of indicators. Some results stand out: i) “hard” and payments cards indicators are the best performers when taken individually, and more so when combined; ii) nonetheless, “soft” indicators are helpful to detect qualitative signals in the nowcasting horizon; iii) Google-based and uncertainty indicators add value when combined with traditional indicators, most notably at estimation horizons beyond the nowcasting one, what would be consistent with capturing information about future consumption decisions; iv) the combinations of models that include the best performing indicators tend to beat broader-based combinations.

Getting a Jump on Inflation
Alan Armen and Evan F. Koenig (Federal Reserve Bank of Dallas)
7 September 2017
Accurate official estimates of Fed policymakers’ preferred PCE inflation measure take months, and sometimes years, to become available. A small set of timelier indicators offers realtime power to “nowcast” PCE inflation. Those indicators provide as much accuracy as initial government estimates and remain informative even after official estimates have been published.

Gauging the Globe: The Bank’s Approach to Nowcasting World GDP
Gene Kindberg-Hanlon and Andrej Sokol (Bank of England)
21 September 2018
Global activity is a key driver of UK GDP and a bellwether of prospects. Nowcasting global GDP growth, or predicting outturns ahead of their release, is therefore a key input into the Monetary Policy Committee’s assessment of the UK economic outlook. The Bank uses a suite of models to assess the momentum in the world economy in real time. A wide range of financial market, survey-based and high-frequency output indicators are used to inform the suite. The statistical suite of global nowcasting models tends to provide an accurate assessment of global activity growth, and significantly outperformed a simple model that did not benefit from the use of high-frequency data during the financial crisis.

One thought on “Research Review | 15 March 2019 | Nowcasting

  1. Pingback: Quantocracy's Daily Wrap for 03/15/2019 | Quantocracy

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