Knowledge Base Articles
Part III: Asset and Liability Management Using LSMC - Allocation Optimisation
In the third and concluding article in the ALM using LMSC series, we focus on analyzing the optimal asset allocations in the context of changing asset classes as well as finding the optimal allocation by maximizing the risk-adjusted net asset value. The estimates based on the LSMC method are then compared to the estimates obtained from the full nested Monte Carlo method.
Those of us working in financial services are tasked with trying to quantify the impact the pandemic is having on the global economy. If for the purpose of this analysis alone, we selectively classify the outbreak as a financial crisis, we see a familiar pattern of behaviour: A flight to safety away from risky assets has certainly been evident in the past 6 or so weeks. Bonds, the dollar and (to some degree) gold have all benefited from the market volatility. The global financial crisis of 2008-9 is a relatively recent reminder of the last time we witnessed similar moves in asset prices. Therefore, it is absolutely reasonable to look for a correlation between that crisis and where we might head in the coming months and years.
Mitigating Risk: A Joint Model for High-Yield and Investment-Grade Credit Indices
Today, there are many flawed corporate bond pricing models. However, there is also a novel credit-spread approach that can simulate index prices and accurately capture probability of default, enabling better risk management and regulatory compliance.
The Volatility Components and Their Effect on the Macroeconomy.
It is well known that the behaviour of volatility can be characterised by two components, one slowly varying long run component and a strongly mean-reverting short run component, but how do they differ in their impact on the macroeconomy?
KIIDs SRRI and the Swedish Mutual Funds Market
One of the key components of the KIID is the Synthetic Risk and Reward Indicator which is used in the process of identifying funds' risk and reward disclosure. Whilst its relationship to risk is trivial, its connection to return might not be as trivial. In order to study this relationship, we have analysed return data over 5 years from a large number of Swedish mutual funds with varying SRRI levels.