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Not all stock market losses have been created equal – there is a clear hierarchy and we feature Ben Carlson from Ritholtz exploring it. Also, a great piece on what the next trends in asset management are and why nearly 90% of U.S. stock market funds failed to beat their indexed benchmark over the past 15 years.
Trends That Matter in Asset Management (A Wealth of Common Sense) It’s not all about fundamentals – professionals overtaking amateurs, a surge in target-date funds and quants replacing star managers now matter too.
Don’t Take Their Word For It: The Misclassification of Bond Mutual Funds (NBER) This working paper examines empirical evidence to explain how mutual fund managers could misclassify their holdings, and how such misreporting behaviours are more incentivised after continuous periods of large negative returns.
The Hierarchy of Stock Market Losses (A Wealth of Common Sense) Ben Carlson explains how people may lose money in the stock market differently – this depends on if they’re in developed markets, emerging markets, or just individual stocks.
A number of uncertain macro factors are weighing down on equity valuations while at the same time value stocks are making a comeback, riding the volatility and possible undervaluations.
Tracking Macro Factors In Portfolio Strategies(The Capital Spectator) Runs a number of regressions to estimate the impact of different macro factors on diversified ETF portfolios. Finds that influence of such factors varies by market and over time.
The Revival In The US Equity Value Factor Rolls On(The Capital Spectator) Explores the recent revival in value stocks. It’s likely caused by heightened concern over slowing economic growth refocusing the market’s attention on undervalued assets. [Bullish value factor]
Using Payment System Data to Forecast Economic Activity(Aprigliano, Ardizzi, Monteforte) Models large amounts of retail payments data in Italy to show that tracking such transactions more closely helps make better GDP predictions.
It might be hard to trade Trump’s erratic decisions –but a bunch of investors have made a fortune from his tweets. The question is whether they have used insider information. Plus, there could be an unbeatable model to predict fund performance and no one has taken much notice.
The Best Predictor of Stock-Fund Performance (Morningstar) Turns out buying stocks held by successful funds is a reliable trading strategy for success.
“There Is Definite Hanky-Panky Going On”: The Fantastically Profitable Mystery of the Trump Chaos Trades (Vanity Fair) Investigates a number of large e-mini trades on the S&P500, often made right before the market closes and strangely right before a big geopolitical market shaker. Argues that this could be a case of insider trading and calls for heavier regulatory watch.Gulp.
The Banking View of Bond Risk Premia (Haddad, Sraer) Shows that the net exposure of the banking sector to interest rate risk, as measured through banks’ average income gap, strongly forecasts future bond excess returns.
We feature a paper looking at utilising machine learning in predicting crisis and why oil modelling remains robust.
Predicting Bank Distress in the UK with Machine Learning (Suss, Treitel) Looks at the benefits of machine learning techniques for providing regulators with a warning of firm distress. This gave an approach that is better aligned to help intervene ahead of failure.
Refining the Workhorse Oil Market Model (Zhou) Paper makes adjustments to previous work which has a model considered as the go-to for analysis of global oil markets. The 5 refinements he tries had no effect on the substantive conclusions made – so the original model is still the one to use.
Value, Momentum and Carry – Is It Time for Equity Investors to Switch? (In the Long Run) For the active investors, value factors may offer a better risk reward profile, but, given the individual stock volatility dispersion, a market neutral defensive factor model, along the lines proposed by AQR, may deliver the best risk adjusted return of all.
A number of insightful pieces exploring how tech and machine learning in particular are breaking into finance. But models aren’t always perfect – mispricing risk can lead to a chain reaction and a downturn.
World Wide Currency (VOX EU) Is it possible to introduce a globally recognised electronic currency in the future alongside the national currencies? Researchers test this idea with a two-country model and conclude that it’s theoretically doable. Although for monetary policymakers, there’s certainly so much more to do to get them prepared for this futuristic trend.
A Volatility Smile-Based Uncertainty Index (Central Bank of Brazil) Introduces a new index to measure uncertainty: the “Volatility Smile-Based Uncertainty” (VSU). It looks at the discrepancy of the implied volatility of exchange rate options, and after calculating this value for five major emerging economies, concludes that VSU is negatively associated with industrial production and has peaks close to turbulent periods.
Ten Applications of Financial Machine Learning (SSRN/Cornell University) Explores how the core of machine learning – studying past data to predict future outcomes – can be revolutionary for the financial services industry. However, it also warns that machine learning tools are vulnerable to input selection biases and that can lead to undesired consequences.
Perceiving Risk Wrong: What Happens When Markets Misprice Risk? (Bank Underground) Risk perceptions are extremely subjective and hard to quantify. This paper examines how overpricing and underpricing market risks can both eventually lead to an economic downturn in the manner of a chain reaction.
FinTech, BigTech, and the Future of Banks (NBER) Explores areas in which non-bank fintech firms can outplay their banking rivals. Being less regulated than banks gives fintech firms an important competitive advantage. Large tech firms are also challenging traditional banking businesses such as consumer finance and loans due to their capability to tap into large amounts of unique user data.
Collateralized Loan Obligations in the Financial Accounts of the United States (Fed) Two new data series on CLOs have been introduced into US Financial accounts. The blog also describes how to navigate the tables to find these series and others relating to CLOs
Derivatives Trading in OTC Markets Soars (BIS) Latest triennial survey shows daily turnover in FX and rates derivatives has jumped from $11 trillion to 2016 to $19 trillion this year. The share of trading exchanges has also fallen.
Tracking the Sources of Robust Payments Growth: McKinsey Global Payments Report (McKinsey) Deep dive on payments landscape by region and player (including non-bank ones). Asia-Pac is the largest region by revenue.
Why Private Equity Is Ripe for Vanguard-Style Disruption (Institutional Investor) Argues that the average 7% fees for private equity is ripe for disruption. A Warren Buffet-style passive approach to holding private companies could be one path for this.
John C Williams: LIBOR – the Clock is Ticking (BIS) NY Fed President argues that market participants are not prepared enough for the end of LIBOR. Despite mentioning recent repo turmoil, he didn’t draw any connections between LIBOR reform and repo (there are some linkages)
Two great papers – one on modelling retail sales in almost real time and another on imperfect decision making.
From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending (Federal Reserve) They find that daily retail transaction data from First Data Merchant Services can replicate monthly official retail sales data in almost real-time.
Modeling Imprecision in Perception, Valuation and Choice (Columbia, Michael Woodford) A piece on imprecise decision. It gives a summary of psychophysics which models the relationship between objective physical properties of a person’s environment and the way these are subjectively perceived.
Entrepreneurial Personalities (VOX) Finds that entrepreneurs have a higher tolerance for risk, stronger self-belief, sense of controlling one’s destiny and need for achievement than nono-founding CEOs, inventor employees and other employees.
New Index Tracks Trade Uncertainty Across the Globe (IMF) The Fund creates trade uncertainty indices for 143 countries starting in 1996.
Why We Should Care About Economic Uncertainty (Econlife) Describes some uncertainty indices and where to find them. They do impact growth.
Puzzling Exchange Rate Dynamics and Delayed Portfolio Adjustment (VOX) In theory, FX carry trades shouldn’t make money, so many ideas have emerged to explain this puzzle. This column argues that the slow response of investors to interest rate changes is the answer.
Predicting Returns with Text Data (Ke, Kelly, Xiu, working paper) Outlines single stock trading strategy around text-mining newswires. The daily models deliver sharpe ratio of between and 1 and 2 (after t-costs). Impressive stats.
Replacing LIBOR (Money and Banking, 8 min read) LIBOR will cease at the end of 2021. This piece raises concerns around the lack of clarity around how many contracts referencing LIBOR have fallback language for the switch. Could pose a systemic risk at some point.
3 Shockers from Yesterday’s RPI Plans (M&G investments, 2 min read) UK inflation-linked bonds will soon RPI inflation measure to the CPI measure. Biggest shocker is that linkers maturing beyond 2030 are at risk of having RPI calculations changed at the discretion of statisticians not the Chancellor.
Satellite Data Economics, Night Lights, and More (Conversable Economist, 3 min read) Useful blog that touches on and contains references on how satellite data can be used to measure growth.