# Research articles for the 2020-02-09

SSRN

In this primer, we review the classical methods for assessing the performance of a financial portfolio. The analysis relies on benchmarking the return on the portfolio with that of a peer group. We define and discuss the pros and cons of four performance metrics that are theoretically consistent with the CAPM and widely used in the industry: The Sharpe Ratio, the Treynor Ratio, Jensenâ€™s alpha, and the Information Ratio. We examine the practical as well as the statistical significance of these measures in the case where the returns on the underlying assets are i.i.d. Gaussian. Numerical implementation of these methods is illustrated through a simplified, yet realistic example.

SSRN

Climate-related financial risks (CRFR) are now recognised by central banks and supervisors as material to their financial stability mandates. But while CRFR are considered to have some unique characteristics, the emerging policy agenda for dealing with them has largely focused on conventional market-based solutions. Current policy emphasises information gaps that prevent the accurate assessment of market risk. The assumption is that these gaps can be remedied via disclosure, transparency, scenario analysis and stress testing, which will enable markets to self-correct. We argue this approach is misguided as CRFR are characterised by radical uncertainty and hence â€˜efficientâ€™ price discovery is not possible. Instead, a â€˜precautionaryâ€™ policy approach is proposed. Since climate change poses a severe and potentially irreversible threat, lack of scientific certainty as to its exact nature or timing should not prevent regulatory action to mitigate its impact. Such an approach justifies fully integrating CRFR into financial policy, including both prudential and monetary policy frameworks. Central banks and financial supervisors can and should actively steer market actors in a clear direction â€" towards a managed transition â€" to ensure a scenario that minimises harm to the financial system and the wider economy in the future.

arXiv

We examine Kreps' (2019) conjecture that optimal expected utility in the classic Black--Scholes--Merton (BSM) economy is the limit of optimal expected utility for a sequence of discrete-time economies that "approach" the BSM economy in a natural sense: The $n$th discrete-time economy is generated by a scaled $n$-step random walk, based on an unscaled random variable $\zeta$ with mean zero, variance one, and bounded support. We confirm Kreps' conjecture if the consumer's utility function $U$ has asymptotic elasticity strictly less than one, and we provide a counterexample to the conjecture for a utility function $U$ with asymptotic elasticity equal to 1, for $\zeta$ such that $E[\zeta^3] > 0.$

arXiv

We study the approximation of backward stochastic differential equations (BSDEs for short) with a constraint on the gains process. We first discretize the constraint by applying a so-called facelift operator at times of a grid. We show that this discretely constrained BSDE converges to the continuously constrained one as the mesh grid converges to zero. We then focus on the approximation of the discretely constrained BSDE. For that we adopt a machine learning approach. We show that the facelift can be approximated by an optimization problem over a class of neural networks under constraints on the neural network and its derivative. We then derive an algorithm converging to the discretely constrained BSDE as the number of neurons goes to infinity. We end by numerical experiments. Mathematics Subject Classification (2010): 65C30, 65M75, 60H35, 93E20, 49L25.

SSRN

This study sheds light on a new type of sustainable investment approach, namely environmental, social, and governance (ESG) momentum. We provide both a theoretical discussion and an empirical comparison of this new approach and put it in perspective to traditional weighting schemes considered by sustainable portfolio managers. In order to provide a clear basis for our argumentation and avoid any conflicting effects, we solely focus on the environmental aspect of ESG ratings in Europe and pay particular attention to strategiesâ€™ carbon footprint as a central measure of a portfolioâ€™s environmental friendliness. Although the empirical results demonstrate inferior environmental ratings for ESG-momentum portfolios and mixed results in respect to risk-adjusted returns across alternative rating components, there might still be a case for investing in sustainable momentum stocks.

arXiv

In this paper, we consider the problem of equal risk pricing and hedging in which the fair price of an option is the price that exposes both sides of the contract to the same level of risk. Focusing for the first time on the context where risk is measured according to convex risk measures, we establish that the problem reduces to solving independently the writer and the buyer's hedging problem with zero initial capital. By further imposing that the risk measures decompose in a way that satisfies a Markovian property, we provide dynamic programming equations that can be used to solve the hedging problems for both the case of European and American options. All of our results are general enough to accommodate situations where the risk is measured according to a worst-case risk measure as is typically done in robust optimization. Our numerical study illustrates the advantages of equal risk pricing over schemes that only account for a single party, pricing based on quadratic hedging (i.e. $\epsilon$-arbitrage pricing), or pricing based on a fixed equivalent martingale measure (i.e. Black-Scholes pricing). In particular, the numerical results confirm that when employing an equal risk price both the writer and the buyer end up being exposed to risks that are more similar and on average smaller than what they would experience with the other approaches.

SSRN

Are government guarantees or financial regulation a more effective way to prevent banking crises? I study this question in the presence of a negative feedback loop between the fiscal position of the government and the health of the banking sector. I construct a model of financial intermediation in which the government issues, and may default on, debt. Banks hold some of this debt, which ties their health to that of the government. The governmentâ€™s tax revenue, in turn, depends on the quantity of investment that banks are able to finance. I compare the effectiveness of government guarantees, liquidity regulation, and a combination of these policies in preventing self-fulfilling bank runs. In some cases, a combination of the two policies is needed to prevent a run. In other cases, liquidity regulation alone is effective and adding guarantees would make the financial system fragile.

SSRN

I propose a regime-switching generalization of instrumented principal components analysis (IPCA) that yields new insights about the relation between characteristics, factor loadings, and expected stock returns. Using a two-regime specification, I find evidence of a high-volatility regime in which individual stocks have high conditional expected returns. This contrasts sharply with the pattern of bull and bear regimes that is obtained by analyzing only market returns. Although exact factor pricing can be rejected, characteristics are more strongly related to priced covariances in the high-volatility regime. Furthermore, regime-switching predictability makes a substantial incremental contribution to the out-of-sample explanatory power of IPCA estimates.

SSRN

We suggest that forward guidance, via â€œbindingâ€ the central bankâ€™s actions and creating associated expectations, fundamentally affects bank-lending decisions independently of other forms of monetary policy. To test this hypothesis, we build a forward guidance measure based on the language used in the Federal Open Market Committee meetings and match this measure with syndicated loans. Our results show that expansionary forward guidance decreases corporate loan spreads and that this effect is stronger for well-capitalized banks lending to riskier firms. Moreover, banks more easily initiate new lending relationships with lower spreads, and the loan syndicates are less concentrated.

SSRN

I study how liquidity management affects fragility, or vulnerability to fund flows, in mutual funds and their underlying assets. Using the SEC Rule on mutual fund liquidity risk management in 2016 as an exogenous shock, I show that mutual funds which mainly invest in illiquid assets shift their portfolios towards liquid assets. Using this variation, I find that higher mutual fund ownership in liquid assets may create fragility in mutual funds and their underlying assets. The regulation increases comovement among liquid assets and volatility of liquid funds' returns. However, I find little evidence of stabilized fund flows and flow-performance sensitivity. Overall, liquidity management could be costly for investors.

SSRN

In this study, we examine the effect of worldwide board reforms on the cost of debt financing. We find an overall increase in loan spreads in countries that initiate board reforms versus those without the reforms, which suggests that board reforms strengthen the power of shareholders at the cost of debtholders. The effect is larger for firms with greater inherent conflicts between shareholders and debtholders. Moreover, we find reform components related to board independence and separation of CEO and chairman lead to the increase of debt costs, whereas the component to improve audit committee independence help decrease debt costs.

arXiv

This paper studies the bail-out optimal dividend problem with regime switching under the constraint that the cumulative dividend strategy is absolutely continuous. We confirm the optimality of the regime-modulated refraction-reflection strategy when the underlying risk model follows a general spectrally negative Markov additive process. To verify the conjecture of a barrier type optimal control, we first introduce and study an auxiliary problem with the final payoff at an exponential terminal time and characterize the optimal threshold explicitly using fluctuation identities of the refracted-reflected Levy process. Second, we transform the problem with regime-switching into an equivalent local optimization problem with a final payoff up to the first regime switching time. The refraction-reflection strategy with regime-modulated thresholds can be shown as optimal by using results in the first step and some fixed point arguments for auxiliary recursive iterations.

arXiv

In a recent paper, we have demonstrated how the affinity between TPUs and multi-dimensional financial simulation resulted in fast Monte Carlo simulations that could be setup in a few lines of python Tensorflow code. We also presented a major benefit from writing high performance simulations in an automated differentiation language such as Tensorflow: a single line of code enabled us to estimate sensitivities, i.e. the rate of change in price of financial instrument with respect to another input such as the interest rate, the current price of the underlying, or volatility. Such sensitivities (otherwise known as the famous financial "Greeks") are fundamental for risk assessment and risk mitigation. In the present follow-up short paper, we extend the developments exposed in our previous work about the use of Tensor Processing Units and Tensorflow for TPUs.

SSRN

The International Financial Reporting Standards (IFRS) must pass a formal endorsement process to become binding for companies based in the European Union (EU). In an unparalleled instance, the EU recently endorsed â€œAmendments to IFRS 4â€ with a modification labeled as â€œtop upâ€ by allowing European financial conglomerates to defer the application of IFRS 9 â€œFinancial Instrumentsâ€ in their insurance sectors. This paper explains the background of this decision, identifies the â€œtop upâ€ as an unprecedented case of carveâ€in, and discusses the key implications for regulation and practice.

arXiv

Foreign exchange rates movements exhibit significant cross-correlations even on very short time-scales. The effect of these statistical relationships become evident during extreme market events, such as flash crashes.In this scenario, an abrupt price swing occurring on a given market is immediately followed by anomalous movements in several related foreign exchange rates. Although a deep understanding of cross-currency correlations would be clearly beneficial for conceiving more stable and safer foreign exchange markets, the microscopic origins of these interdependencies have not been extensively investigated. We introduce an agent-based model which describes the emergence of cross-currency correlations from the interactions between market makers and an arbitrager. Our model qualitatively replicates the time-scale vs. cross-correlation diagrams observed in real trading data, suggesting that triangular arbitrage plays a primary role in the entanglement of the dynamics of different foreign exchange rates. Furthermore, the model shows how the features of the cross-correlation function between two foreign exchange rates, such as its sign and value, emerge from the interplay between triangular arbitrage and trend-following strategies.

arXiv

In this paper we study a class of time-inconsistent terminal Markovian control problems in discrete time subject to model uncertainty. We combine the concept of the sub-game perfect strategies with the adaptive robust stochastic to tackle the theoretical aspects of the considered stochastic control problem. Consequently, as an important application of the theoretical results, by applying a machine learning algorithm we solve numerically the mean-variance portfolio selection problem under the model uncertainty.

SSRN

The European Commission passed MiFID II, in part, to unbundle brokersâ€™ execution and research services. We find that the trading volume generated by brokers issuing recommendations declined significantly after the enactment of MiFID II. Further, MiFID II appears to have had a positive effect on the informativeness of analystsâ€™ recommendations and no discernible impact on forecast accuracy while narrowing the forecast accuracy and bias differential between analysts employed by brokers and non-brokers. Finally, we find that MiFID II coincided with a significant decline in the supply of analystsâ€™ research activity (e.g. coverage, frequency), indicating a â€œchilling effectâ€ of MiFID II.