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Carbon Premium

Carbon Premium

To compare the Excess Returns of a fund with the Excess Carbon it generates. To assess the correlation between carbon emissions and the skills of the fund manager used in generating alpha.

Overview

Climate change has been associated with financial risk, yet it also enables investors to identify opportunities that will aid in the maximization of returns. The carbon premium model identifys the risks and opportunities form a company's carbon emissions. The model provides comparative insights on the asset manager's ability to generate returns over their respective benchmarks, while simultaneously comparing the carbon performance of the asset class with the carbon emissions from the respective benchmark.At 15 Rock, we use AI and Machine Learning models to precisely forecast future emissions at a company and fund level. We provide insights as to the future returns of fund by combining our forecasting model and the Carbon premium model.

Each fund or asset manager has a relevant benchmark for its performance, this benchmark is in accordance with their funds investment style. For example, the funds Allocating 80% or more in US Large Cap Equities will benchmark the funds total returns against the returns of the S&P 500, also called market returns. As various funds have various investing styles, these benchmarks need to be variable as well, i.e. the client can choose the most appropriate index that can act as a benchmark for the fund under analysis. A exhaustive list of benchmarks will be available to choose from.

Similarly, we create the basis for carbon comparison as well. The carbon attributable to the fund compared to the carbon generated by the relevant benchmark. As there a discrepancy between the benchmarks, to allow for inter fund comparison. the excess carbon will be converted into a ratio, The Carbon Premium.

Intuition and Interpretation

By looking at the Carbon Premium, one can analyze the carbon performance of the fund relative to its benchmark, per dollar of excess return being generated. For example, if the carbon premium is 4, this indicates that per 1% of excess return being generated (return greater than the benchmark), the emission were 4 times greater than benchmark's emissions.

Design and Modeling

Assumptions

  • A list of various indices, with pricing data is available and accessible in the database to be used as available benchmarks
  • Fund holdings will also have tickers, which can then be called to get their respective carbon
  • We also have Total Carbon calculated for all the indices available as benchmarks

Inputs

  • Fund holdings
  • {{fund_holding.FundTicker.HoldingTicker}} (names will be converted into ticker before implementation)
  • Holding's carbon
  • {{carbon.HoldingTicker.year}}
  • Gather carbon data for all previous years
  • Holdings weight
  • {{fund_holding.FundTicker.HoldingTicker.weights}}
  • S&P 500 Carbon
  • S&P 500 accumulative Carbon Figure for all previous years starting from 2000
  • (Take S&P holdings, extract tickers, run a post command on postman to get carbon)
  • S&P 500 Returns
  • {{EOD_price.GSPC.INDX}}
  • Fund NAV
  • {{Fund_data.FundTicker.nav}}

Modeling

  • Weighted holding's carbon
  • ({{fund_holding.FundTicker.HoldingTicker.weights}} / 100) * {{carbon.HoldingTicker.year}}
  • Should generate a time series for all years
  • Fund Carbon (carbon table with company tickers)
  • accumulate weighted holding's carbon for:
  • all holdings in 2019,
  • all holdings in 2018,
  • % change in Fund Carbon
  • (fund Carbon 2019-fund carbon 2018) / fund carbon in 2018
  • % change in S&P 500 carbon
  • (S&P Carbon 2019 - S&P carbon 2018) / S&P carbon in 2018
  • Excess Fund Carbon
  • % change in fund carbon - % change in S&P 500 Carbon
  • S&P 500 returns
  • LN ({{EOD_price.GSPC.INDX}} 2019 / {{EOD_price.GSPC.INDX}} 2018)
  • Excess Returns
  • NAV Returns 2018 - S&P 500 returns 2018
  • CARBON PREMIUM
  • Excess Fund Carbon 2018 / Excess Return 2018