A policy tool that puts a price on \(CO_2\) to incentivize reductions
Mechanism: Two approaches are used
Shifts costs from affected communities to producers of \(CO_2\)
Polluters evaluate if the cost of their activity outweighs the benefits of reductions
Two types of financial instruments used in carbon pricing:
Pros: predictable costs
Cons: no guaranteed emission cap
Allows agents to sell their extra allowances (e.g., EU ETS)
Creates a marketplace: low emitters profit by selling spare permits (e.g., Tesla earned $1.8B selling credits)
Pros: guarantees reductions while keeping emissions below the pre-allocated budget
Cons: price volatility
Implementation Issues:
“Climate washing”: lead to misleading offsets
Shell’s “carbon-neutral” liquid natural gas (LNG)
Research into Verra (carbon credit registry) found 90% of their rainforest offsets were “phantom credits” (2023)
Structural Flaws:
Fragmentation: 70+ global systems with uneven prices
Low prices: IMF estimates the global average of carbon at $6/ton ($75/ton needed)
Growth of Carbon Markets:
Global ETS surged to $865B in 2023 (World Bank)
New systems launching (China, Indonesia, Mexico)
Carbon futures trading volume up 30% YoY (CEF 2023)
Investment Opportunities:
Low correlation with traditional assets (S&P 500, bonds)
Potential hedge against policy shocks
How portfolio analysis can explain market dynamics:
Market Efficiency
Volatility Profile
How does carbon’s volatility compare to stocks/bonds?
Are they driven by policy shocks or energy prices?
Macroeconomic Sensitivity
Diversification Benefits (and more broadly, investment attractiveness)
Carbon Exposure:
| ETF/Asset | Carbon Coverage |
|---|---|
| Global Carbon ETF (GRN) | Global Carbon Futures (EU only) |
| KraneShares ETF (KRBN) | Multi-region ETS (EU, CA, US) |
Traditional Assets:
Equities: S&P 500 (SPY)
Commodities: Dow Jones Commodity Index (DJCI)
Fixed Income:
Government: T-bills (SHV), 7-10Y treasuries (IEF)
Corporate: High-yield (HYG), investment-grade (LQD)
| Asset | Daily Mean (%) | Annual Mean (%) | Std Dev | Annual Vol | Skewness | Excess Kurtosis | VaR 95% |
|---|---|---|---|---|---|---|---|
| UST | -0.051 | -12.758 | 0.010 | 0.156 | 0.185 | -1.976 | -0.016 |
| SPY | 0.052 | 13.119 | 0.010 | 0.165 | -0.317 | -1.226 | -0.017 |
| DJCI | 0.007 | 1.763 | 0.003 | 0.052 | 3.100 | 92.149 | 0.000 |
| GRN | 0.085 | 21.344 | 0.027 | 0.426 | -0.280 | 1.542 | -0.039 |
| KRBN | 0.027 | 6.886 | 0.021 | 0.327 | -1.540 | 12.372 | -0.030 |
| HYG | -0.006 | -1.393 | 0.005 | 0.077 | -0.113 | 1.996 | -0.008 |
| LQD | -0.020 | -5.103 | 0.006 | 0.088 | 0.009 | -1.369 | -0.010 |
| SHV | -0.000 | -0.057 | 0.001 | 0.010 | -5.330 | 27.590 | -0.000 |
| IEF | -0.022 | -5.551 | 0.005 | 0.078 | 0.138 | -1.766 | -0.008 |
Mixed results as an investment opportunity:
Benefits of investing in carbon assets:
Demonstrated growth potential in the past, but has tapered off
Low correlation with other equities means they have upside as a diversifier or hedging option
Modestly improved diversified portfolio performance
Why investors might stay away:
Tail risk needs to be carefully managed
Policy-driven volatility demands active management
Unexpected findings over the course of the project:
Carbon credits are neither traditional commodities nor pure ESG plays, but a distinct asset class requiring their own specialized frameworks
Lack of correlation with bonds (despite both being policy driven)
Future steps:
Expand analysis to more carbon assets
Dynamic allocations strategies (e.g., options-based tail hedging)