Volatility
Search engine study shows limits of alternative data
Google Trends adds nothing to volatility predictions, researchers find
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…
ETF investing – Building better portfolios
At the Asia ETF Forum 2019, Hong Kong Exchanges and Clearing (HKEX) welcomed industry experts from around the region to six key Asian exchange-traded fund (ETF) cities, offering attendees an updated view on the growing ETF market in Asia. This article…
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
Warrants issuers battle algo predators in Hong Kong
Threat of high-frequency traders forces banks to spend big on tech
From log-optimal portfolio theory to risk measures: logarithmic expected shortfall
In this paper, the authors propose a modification of expected shortfall that does not treat all losses equally. We do this in order to represent the worries surrounding big drops that are typical of multiperiod investors.
Alternative Liquidity Measures
Is book depth a sufficiently representative measure of market liquidity? A look at trade matching performance under different market volatility environments
Volatility scaling unravels as market patterns shift
Waning power of quant approach could be a reason for trend following’s malaise
China Minsheng and SocGen team up for quant index product
CMBC Macro 1 signal index attracts $580 million as investors adapt to products without performance guarantees
Podcast: Hong on quanto derivatives and Asia’s quant drought
Credit Suisse quant talks about new paper on valuing quanto options
Tail-risk mitigation with managed volatility strategies
This paper examines strategy performance from an investment practitioner perspective. Using long-term data from the Standard & Poor’s 500, the authors show that these strategies offer an improvement in risk-adjusted return compared with a buy-and-hold…
Roughening Heston
El Euch, Rosenbaum, Gatheral combine a rough volatility model with the classical Heston model
HKEX clearing head talks margin and auctions post-Nasdaq
CCPs have work to do to restore confidence in clearing, but Roland Chai has a plan
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
Risky notes replace easy money for exotics desks
Dealers insist ‘it’s different’ as flat US curve revives bonds that sank the Street in 2008
Fed repo facility may fix SOFR’s image problem
‘Overnight standing repo facility’ could stop year-end rate spikes, and extend Fed’s reach
Capturing alpha in Asia’s ETF market – Trends to watch in 2019
As the inclusion of China A-shares into major indexes could potentially lead to record inflows into China, 2019 is set to be an exceptional year for the Asian exchange-traded funds (ETFs) market. Meanwhile, investors in the region are increasingly eyeing…
Finding potential in a volatile commodities market
Macquarie is uniquely positioned to offer clients a range of products, expertise and experience across the commodities space. Nick O’Kane discusses the bank’s approach to commodity markets and what he expects next
US banks boost sales of CDS, reversing two-year trend
BofA Securities increased CDS notionals the most, adding $30.3 billion to its portfolio
US G-Sibs’ VAR-based charges jump 23% in Q4 2018
On aggregate, the eight G-Sibs posted a VAR-based capital charge of $2.9 billion
Range-based volatility forecasting: an extended conditional autoregressive range model
This paper proposes an extended conditional autoregressive range (EXCARR) model to describe the range-based volatility dynamics of financial assets.