• ITVI.USA
    16,014.360
    14.660
    0.1%
  • OTLT.USA
    2.799
    -0.006
    -0.2%
  • OTRI.USA
    22.430
    0.240
    1.1%
  • OTVI.USA
    15,995.600
    10.280
    0.1%
  • TSTOPVRPM.ATLPHL
    2.930
    -0.020
    -0.7%
  • TSTOPVRPM.CHIATL
    3.620
    0.010
    0.3%
  • TSTOPVRPM.DALLAX
    1.330
    -0.040
    -2.9%
  • TSTOPVRPM.LAXDAL
    3.570
    0.020
    0.6%
  • TSTOPVRPM.PHLCHI
    2.390
    0.070
    3%
  • TSTOPVRPM.LAXSEA
    4.130
    0.020
    0.5%
  • WAIT.USA
    127.000
    0.000
    0%
  • ITVI.USA
    16,014.360
    14.660
    0.1%
  • OTLT.USA
    2.799
    -0.006
    -0.2%
  • OTRI.USA
    22.430
    0.240
    1.1%
  • OTVI.USA
    15,995.600
    10.280
    0.1%
  • TSTOPVRPM.ATLPHL
    2.930
    -0.020
    -0.7%
  • TSTOPVRPM.CHIATL
    3.620
    0.010
    0.3%
  • TSTOPVRPM.DALLAX
    1.330
    -0.040
    -2.9%
  • TSTOPVRPM.LAXDAL
    3.570
    0.020
    0.6%
  • TSTOPVRPM.PHLCHI
    2.390
    0.070
    3%
  • TSTOPVRPM.LAXSEA
    4.130
    0.020
    0.5%
  • WAIT.USA
    127.000
    0.000
    0%
American ShipperShippingTrade and Compliance

DNB pioneers carrier earnings forecast model

DNB Markets has partnered with ocean freight rate benchmarking platform Xeneta to develop a “crystal ball” for carrier financials.

   DNB Markets has partnered with ocean freight rate benchmarking and market intelligence platform Xeneta to develop what it is calling a “crystal ball” for carrier financials.
   The Oslo-based investment bank says it already has used its long- and short-term ocean freight rate data to accurately forecast the world’s-largest container carrier Maersk Line’s first-quarter earnings prior to their release to the public.
   According to Nicolay Dyvik, head of shipping research at DNB Markets, Xeneta’s crowd-sourced database of over 55 million contracted ocean freight rates covering 160,000 global port-to-port pairings “sheds light on the complex container shipping market.”
   The new earnings forecasting model works by estimating average container rates across relevant global trade lanes and weighting those averages to produce an overall average rate, which can then be used to predict actual reported average freight rates and, in turn, detailed forecasts of revenue, profit and share price. The goal of the model is to “glean unique insights and make informed recommendations to customers seeking to buy and sell stock,” said Dyvik, and Xeneta said it “showed a close correlation with [Maersk’s] actual reported rates within the period, with an R2 (financial performance measurement) of 0.93.”
   “We are constantly looking for data that can have true market impact,” Dyvik explained. “Xeneta is the only source that provides this for container freight. It delivers detailed, global coverage of both long and short-term rates, allowing us to provide research that accurately predicts changes in earnings for shipping lines.”
   Xeneta CEO Patrik Berglund said it was “pleasing to see how our data is now being used within new sectors, such as financial research, to accurately analyze and predict performance,” adding that the company now aims to build on its position as an “established name” in the freight rate benchmarking world and “add an even greater depth of data, from our ever-expanding community of contributors, to unlock further insight and value for anyone looking to understand the complex and fast-moving world of freight rates.”
   Xeneta, which is also headquartered in Oslo, in late 2017 added similar rate intelligence tools to its platform for the air cargo sector in an effort to “help customers generate optimal value from negotiations in a segment that shares ocean freight’s rate volatility.”

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