Research paper
Research Papers

A collection of our white papers and peer-reviewed research articles related to macro / multi-asset investor behavior, hedging, risk regimes, liquidity risk, private assets, portfolio construction, and more.

Mar 14, 2024

By Mark Kritzman, Huili Song, and David Turkington.

 

We show how warping time renders stock price bubbles comparable, revealing common patterns that investors can use to detect new bubbles and time exposure to their rise and fall.

 

Can history offer a guide to understanding future stock-price bubbles? The answer is yes, but we have to learn how to bend time. Thankfully, a method called dynamic time warping offers the solution. Previous bubbles occur at different paces: some rise fast and others slowly, some crash after weeks while others persist for years. By stretching and shrinking the timeline of thousands of bubble events, we systematically place them side by side and find more commonalities in their attributes' patterns than a calendar view suggests. We then use various attributes collectively to assess the likelihood of a developing bubble and identify its lifecycle stage, from inception to peak to conclusion. A simple trading rule seeking to invest in bubble run-ups and post-crash over reactions, while avoiding the peak, generates compelling performance in out-of-sample backtests.

 

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By Mark Kritzman, Huili Song, David Turkington
Jan 11, 2024

By Alexander Cheema-Fox, Megan Czasonis, Piyush Kontu and George Serafeim

 

We explore the world’s first set of financial accounting data on firms’ sustainable activities.

 

Though sustainable investing has grown in popularity over the past decade, measuring sustainability remains a key challenge. Investors often rely on environmental criteria—such as analyst ratings and carbon emissions—that are insufficient or rely on qualitative analysis. However, for the first time, with the advent of the EU’s Taxonomy for Sustainable Activities, investors have access to financial accounting data that follows standardized and transparent criteria for quantifying the percentage of a firm’s revenues and expenditures that align with sustainable activities. In a recent paper, we explore this novel dataset for a cross-section of large European firms, documenting patterns and analysing how firms’ aligned activities relate to fundamentals and environment ratings. We find that the EU Taxonomy data provide information that is distinct from existing sources and offers insights that can help investors and regulators, alike.

 

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By Alex Cheema-Fox, Megan Czasonis, Piyush Kontu, George Serafeim
Jan 9, 2024

By Megan Czasonis, Mark Kritzman, and David Turkington.

 

We propose a new currency hedging technique called full-scale hedging, which accounts for the complexities of diversification.

 

Diversification is nuanced and summary statistics, such as correlation, fail to capture complexities that lie below the surface. For investors, these complexities matter—accounting for them can make the difference between an effective, or ineffective, hedging strategy. In the case of currencies, investors often determine risk-minimizing hedge ratios based on the portfolio’s betas to those currencies or with mean-variance optimization. In both cases, the optimal solution depends crucially on the correlation between the currencies and assets in the portfolio. But correlation is an unreliable estimate of the diversification investors actually care about: the co-occurrences of the cumulative returns of the portfolio and currencies over the investment horizon. We propose a new currency hedging technique called full-scale hedging, which addresses these challenges by considering the full distribution of co-occurrences between currencies and the portfolio.

 

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By Megan Czasonis, Mark Kritzman, David Turkington
Dec 19, 2023

By Mark Kritzman, Huili Song, and David Turkington.

 

We show how warping time renders stock price bubbles comparable, revealing common patterns that investors can use to detect new bubbles and time exposure to their rise and fall.

 

Can history offer a guide to understanding future stock-price bubbles? The answer is yes, but we have to learn how to bend time. Thankfully, a method called dynamic time warping offers the solution. Previous bubbles occur at different paces: some rise fast and others slowly, some crash after weeks while others persist for years. By stretching and shrinking the timeline of thousands of bubble events, we systematically place them side by side and find more commonalities in their attributes' patterns than a calendar view suggests. We then use various attributes collectively to assess the likelihood of a developing bubble and identify its lifecycle stage, from inception to peak to conclusion. A simple trading rule seeking to invest in bubble run-ups and post-crash over reactions, while avoiding the peak, generates compelling performance in out-of-sample backtests.

 

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By Mark Kritzman, Huili Song, David Turkington
Nov 20, 2023

By Mark Kritzman, Cel Kulasekaran, and David Turkington.

 

We introduce a more flexible way to forecast risk and return based on the most relevant historical periods.

 

As economic regimes shift, investors who choose to adapt must build portfolios that match their evolving view of the future. Forecasts of asset risk and return should account for regime-specific trends. The question is how to implement this idea in practice. Typically, an analyst will find every time an economic indicator like inflation or growth was above (or below) a fixed threshold, and she will pay equal attention to every data point that qualifies. While this approach seems sensible, it also has dramatic limitations. Ideally, we should recognize that the regime labels of past events are not simple yes/no answers; they are ambiguous. We should pay more attention to some past events than others, based on their relevance. We should weigh the impact of many variables rather than just one. And we should accept that some events are relevant to more than one regime. A statistical measure of relevance, based on the Mahalanobis distance, empowers investors to analyze these nuances of regimes with rigor. We show how to estimate expected risk and return as weighted averages of the relevant past, and how these forecasts of asset performance lead to intuitive portfolios optimized for a range of possible regimes.

 

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By Mark Kritzman, David Turkington
Oct 26, 2023

By Alberto Cavallo, Megan Czasonis, William Kinlaw, and David Turkington

 

We show how unstructured price data from online retailers can anticipate inflation shifts and enable investors to hedge inflation risk dynamically. 

 

Investors and academics have been studying inflation, and how it affects asset prices, for more than four decades. Their findings are discouraging: there just aren’t many assets that offer a reliable hedge against inflation. Treasury Inflation Protected Securities (TIPS), introduced in 1997, represent the only U.S. asset class whose returns are linked explicitly to inflation, but they have drawbacks. For one, their yields are lower than normal treasury bonds during most periods, when inflation is low. In an ideal world, investors would capture the higher yield of treasuries when inflation is benign and shift into TIPS to capture their price appreciation when inflation expectations rise. To do this, they need a good leading indicator of the market’s collective inflation expectations. In this paper, we show how unstructured price data from online retailers, spanning millions of products captured by PriceStats®, can be used to forecast the relative performance of TIPS and treasuries.

 

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By Alberto Cavallo, Megan Czasonis, William Kinlaw, David Turkington
Oct 17, 2023

By Musa Amadeus, Rajeev Bhargava, Michael Guidi, Marvin Loh, Gideon Ozik, and Ronnie Sadka

 

Read between the lines: The measurement of Fed members’ monetary tones facilitates an understanding of the dynamics of the individual monetary policy stances underlying aggregated, consensus (top-down) Fed tones.

 

Amadeus et al. (2022) observe that aggregated, consensus (top-down) central bank monetary tones in media contain predictive information pertaining to future weekly yield fluctuations. This article elucidates the more granular, stratified (bottom-up) dynamics underlying these relations. The predictive relationships between Fed consensus tones and yields are primarily driven by an underreaction of yields to the Fed Board of Governors’ tones between monetary policy meetings. Over short-term horizons, Treasury yields appear to price voting FOMC members’ (Board of Governors’ and Regional Bank Presidents’) tones while relatively longer-term horizon yields appear to reflect both voting and non-voting tones. Fed Regional Bank Presidents’ monetary tones are more responsive to regional inflation fluctuations than to unemployment. The analysis of the heterogeneous impacts of Fed members’ tones over distinct yield horizons provides insights pertaining to the pricing of voting and non-voting Fed members’ tones in Treasury markets.

By Michael Guidi, Marvin Loh, Gideon Ozik, Ronnie Sadka
Sep 7, 2023

By Megan Czasonis, Mark Kritzman, and David Turkington

 

Relevance-based prediction is a new approach to data-driven forecasting that serves as a favorable alternative to both linear regression analysis and machine learning. It follows from two seminal scientific innovations: Prasanta Mahalanobis’ distance measure and Claude Shannon’s information theory. Relevance-based prediction rests on three key tenets:

 

1) relevance, which measures the importance of an observation to a prediction;

 

2) fit, which measures the reliability of each individual prediction task;

 

3) codependence, which holds that the choice of observations and predictive variables should be determined jointly for each individual prediction task

By Megan Czasonis, Mark Kritzman, David Turkington
Sep 5, 2023

By William Kinlaw, Mark Kritzman, Michael Metcalfe, and David Turkington

 

Published in the Journal of Investment Management, Third Quarter 2023 and recipient of the 2023 Harry Markowitz Award.

 

We use novel statistical techniques to measure the time-varying influence of cost push, demand pull, inflation expectations, monetary policy, and fiscal policy on inflation regimes. 

 

It can be hard to pin down what causes inflation, and often a range of views are put forth. The shifting nature of inflation regimes makes this challenge even more daunting. In our latest research we take a data-driven view of the key drivers of inflation, comparing the economic circumstances at any point in time to those that prevail during various historical regimes. We identify four prototypical inflation regimes: stable, rising steady, rising volatile, and disinflation. And we apply a method originally introduced for predicting the business cycle to disentangle and attribute the determinants of U.S. inflation to eight macroeconomic variables. The results are intuitive and carry interesting policy implications. As of early 2022, fiscal spending stands out as the main determinant of the current inflation regime. 

 

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By William Kinlaw, Mark Kritzman, Michael Metcalfe, David Turkington
Jul 31, 2023

By William Kinlaw, Mark Kritzman, and David Turkington

 

Conventional statistics hide important realities that investors need to know.

 

The correlation coefficient often fails to capture what really matters to investors. There are two reasons for this. First, investors often measure correlations using monthly data and assume that they also hold over one-year, five-year or ten-year periods. Unfortunately, in the real world, they often don’t. The second reason has to do with a fundamental misconception about diversification. The fact is, investors don’t always want it. Sure, they want it on the downside, in order to offset the poor performance of one or more assets. But on the upside they prefer all assets to rise in unison, which is the opposite of diversification. Put differently, they’d be happy to place their eggs, conveniently, in a single basket provided nobody steals it. Our research shows that correlations can vary through time based on a range of conditions including the level of interest rates, the degree of turbulence in financial markets, and the performance of major equity markets. Overall, our findings challenge the notion that returns evolve as a simple “random walk,” a critical pre-condition without which we must interpret the correlation coefficient distrustfully. To address these issues, we introduce the notion of co-occurrence and offer a new perspective on how investors should diversify portfolios.

 

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By William Kinlaw, Mark Kritzman, David Turkington