Forecasting
At CIBC, update to loan-loss model lifts credit provisions 38%
Darker economic outlook justified a shift in ECL model weightings
When the data’s not there, expert-led models could help
Missing data is a problem. Expert elicitation taps the knowledge of many, say consultants
Sandbar's focus on idiosyncratic factors sets it apart from its peers in equity market‑neutral
With investors sometimes struggling to find hedge funds that deliver uncorrelated, consistent returns, Sandbar Asset Management stands out from its peers. Its success in running an equity market-neutral strategy is a reflection of its founder and chief…
Cat risk: why forecasting climate change is a disaster
Forecasters are poles apart on climate-driven catastrophes; insurers fear worse ahead
When climate risk starts to bite
Energy firms under increased pressure to assess physical climate risk
Forecasting value-at-risk
Alvin Stroyny and Tim Wilding build a dynamic risk framework for multi-asset global portfolios
House of the year, Singapore: OCBC
Asia Risk Awards 2019
Rating migrations of US financial institutions: are different outcomes equivalent?
This study employs a competing risks approach to examine the rating migrations of US financial institutions (FIs) during the period 1984–2006.
A tech-driven transformation
A panel of experts explores how greater collaboration between risk and finance teams can garner significant benefits and add value, how technological innovation is making the regulatory landscape more complicated to navigate and produce transformative…
Risk and finance – Better together
Changing regulations and new accounting standards are creating enormous challenges for financial organisations. Thorsten Hein, principal product marketing manager, risk research and quantitative solutions at SAS, explores why, to successfully meet these…
One size does not fit all – Adapting to meet investment goals
Guillaume Arnaud, global head of quantitative investment strategies (QIS), and Sandrine Ungari, head of cross-asset quantitative research at Societe Generale, explore the benefits of QIS for investors, why flexibility is crucial for investors to meet…
Risk premia strategies – Lessons learned for the future
After a difficult 2018, investors are increasingly wary of risk premia, concerned that factors leading to underperformance might be a recurring problem. Imene Moussa, executive director at UBS, clarifies this issue
Canadian banks see loan-loss reserves diverge
Provisions rise at Scotiabank and BMO; drop off at TD Bank, CIBC and RBC
Fund houses get picky over where to use machine learning
Buy-siders limit usage of deep learning techniques due to haziness over their inner workings
Podcast: Ronn on using a financial-economics approach to forecast crude oil spot prices
Professor of finance talks about using equity, index and crude oil options to forecast spot prices
Incorporating volatility in tolerance intervals for pair-trading strategy and backtesting
This paper incorporates volatility forecasting via the exponentially weighted moving average model into traditional tolerance limits for pair-trading strategies, and illustrates how the proposed method helps uncover arbitrage opportunities via the daily…
Ensemble models in forecasting financial markets
In this paper, the authors study an evolutionary framework for the optimization of various types of neural network structures and parameters.
Quantification of model risk in stress testing and scenario analysis
In this paper, the author's aim is to empirically analyze the numerical quantification of model risk, yielding exact buffers in currency amounts (for a given model uncertainty).
Quants clash: machine learning or linear models?
Some studies say the algorithms beat the common models; other studies say the opposite