Transition versus physical climate risk pricing in European financial markets:A text-based approach

Under its climate regulation, the EU is expected to become the first continent with a net-zero emissions balance. We study the pricing of climate risks, physical and transition, within European markets. Using text-analysis, we construct two novel (daily) physical and transition risk indicators for the period 2005-2021 and two global climate risk vocabularies. Applying our climate risk indices to an asset pricing test framework, we document the emergence of economically significant transition and physical risk premia post-2015. From a firm-level analysis, using firms’ GHG emissions, GHG emissions intensity, environmental, and ESG scores, we find that rises in transition (physical) risk are typically associated with an increase (decrease) in the return of green (brown) stocks. Firm-level information is used by investors to proxy firms’ climate-risks exposure, especially for transition risk since 2015, whereas the sectoral classification appears to proxy firms’ exposures to physical risk. From a country-level analysis emerges an intensified connection between European stock markets and climate risks post-2015, yet with some heterogeneity. Our results have important economic implications and show that investors demand compensation for their exposure to both climate risk types. Our novel climate risk vocabularies and indicators find several applications in identifying, measuring, and studying climate risks

Climate risks and predictability of the trading volume of gold : evidence from an INGARCH model

DATA AVAILABILITY : Data is available from Bloomberg with access.We investigate whether text-based physical or transition climate risks forecast the daily volume of gold trade contracts. Given the count-valued nature of gold volume data, we employ a log-linear Poisson integer-valued generalized autoregressive conditional heteroskedasticity (IN-GARCH) model with a climate-related covariate. We detect that physical risks have a significant predictive power for gold volume at 5- and 22-day-ahead horizons. Additionally, from a full-sample analysis, it emerges that physical risks positively relate with gold volume. Combining these findings, we conclude that gold hedges physical risks at 1-week and 1-month horizons. Similar results hold for platinum and palladium, but not for silver.http://www.elsevier.com/locate/resourpolhj2023Economic

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Pricing Interest Rate Derivatives in a Negative Yield Environment

The main purpose of this thesis is to price interest rate derivatives in the today negative yield environment. The plain vanilla interest rate derivatives have now negative strikes and negative values of the underlying asset, the forward rate. The Black’76 model fails because of its assumption of log-normal distribution of the underlying that does not allow the underlying to be negative. The normal model gives a solutions to this problem since it assumes the underlying being normally distributed and then it can takes every value also negative. The shifted Black model has the same hypothesis of the Black-Scholes model but it adds a shift value in order to overcome the issue generated by the negativity of the strike values and of the current forward rate, with the only restrictions that the sum of the shift and the strike and the sum between the underlying value and the strike are positive. The shifted SABR model is used to find the shifted black volatilities for different strikes to plug later on the shifted Black formula to price interest rate derivatives. A comparison between the models and a brief analysis on delta hedge strategies are made.MSc in Financ