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Quantitative agreement between experimentally determined M–C bond dissociation energies (BDE) and DFT predictions (M06-2X/TZ//TPSSTPSS/DZ) can be reached by choosing the correct anchor for experimentally derived BDE. For the example of the archetypical metallocene catalyst Cp 2 TiCl 2 , it is shown that titanium–carbon bonds are very weak under polymerization conditions and fluctuate; steric strain is introduced after 2,1 insertion and via olefin capture. Thus, homolysis can become competitive with chain propagation. Depending on the catalyst and temperature, 2,1 insertion can be only a temporary inconvenience (dormancy) or a definitive decay event. It is then shown for a set of nine common Ti and Zr polymerization catalysts how ligand variation affects the metal–carbon BDE. Predicted stabilities of the M(IV) oxidation state with respect to homolysis are in nice agreement with the experimentally observed temperature tolerance of the various catalysts: homolysis is easier for Ti than for Zr, and cyclopentadienyl groups in particular facilitate homolysis, especially in bis-cyclopentadienyl systems.

When faced with the challenge of forming a portfolio containing a risky and a risk-free asset, investors tend to apply the same portfolio weights independently of the volatility of the risky asset. This “percentage heuristic” can lead to different levels of portfolio risk when the same investor is presented with a more or a less risky asset. Using three experiments, we show that asking investors to choose the return distribution for their portfolio while keeping the exact portfolio weights unknown leads to greater similarity in levels of portfolio volatility (across different levels of risk of the risky asset) than asking investors to choose this distribution while additionally facing the portfolio weights. Higher consistency in risk taking is obtained both between and within test subjects.

We analyze why investors chose funds with performance fees even if expected fees are higher than in a fund with a pure management fee. Performance fees are meant to influence performance positively but they can also lead to a higher fund risk. The expected higher performance cannot fully account for the height of the performance fees chosen in our survey study. Controlling for various other explanations, we find that loss aversion is a main driver for the propensity to chose a performance fee fund.

This paper investigates two research questions: Do investors see a relationship between risk attitude and the amount invested risky? Further, do investors adjust their investments if provided with assets with different volatilities? In an experimental study, investors allocate an amount between a risky and a risk-free asset. Investors' risk attitude predicts risk taking. Investors are, however, unable to adapt to risky assets with different volatilities; they choose almost the same allocation to the risky asset independently of its volatility, thus amassing significantly different portfolios.