Research and Publications
Publications and working papers by Vaibhav Lalwani, auto-updated from OpenAlex.
Below, you’ll find details of my research work. For questions on any specific publication, feel free to send me an email.
Peer-reviewed publications
Factor timing with transaction costs
Times factor exposures using 50 net-of-cost smart-beta factors, driven by their past returns and covariances. The dynamic strategy beats a static 1/N benchmark on risk-adjusted returns even after 2000's fading premiums, with low turnover and results robust to specification choices.
Climate news betas and risk premia
Tests whether climate-news betas are priced in US and Chinese stocks, and shows the answer swings widely with innocuous modelling choices. After correcting for multiple testing, no climate-risk premium survives.
Shows that research-design choices move machine-learning portfolio returns so much that their nonstandard errors are up to five times the usual standard errors. Even so, ML still earns net-of-cost returns for about a third of portfolios.
Does economic complexity tame the stock markets? International evidence
Shows that countries producing more diverse and unique goods tend to have calmer stock markets. The effect is concentrated in emerging markets and only kicks in past a complexity threshold.
Finfluencer recommendations
Studies stock calls from Indian financial YouTubers. Finfluencers favour past winners with heavy trading, rich valuations, and high intraday activity, and the number of their recommendations predicts future returns.
Mean-variance optimization and the cross-section of stock returns
Builds an asset-pricing factor from Sharpe-ratio-maximising mean-variance weights, and finds it is priced in the cross-section of stocks and bonds, out of sample and across countries.
Forecasting equity returns with oil prices: addressing model choice uncertainty
Adapts extreme bounds analysis to out-of-sample forecasting, and finds oil prices carry incremental information for aggregate and sectoral stock returns once combined with other oil variables.
Inflation hedging via tracking portfolios in the BRICS markets
Builds portfolios that track unexpected CPI inflation in the BRICS markets. Statistical tracking beats the benchmarks, especially when inflation uncertainty is low.
Climate risks, corporate bonds, and economic uncertainty
Shows corporate bonds that move with global-warming news earn lower returns. The gap shows up mainly in periods of high economic policy uncertainty, when investors pay up for climate-resilient bonds.
Incorporating green assets in equity portfolios
Adds green-asset ETFs to mean-variance portfolios. Mixing them with broad market indices lifts returns and Sharpe ratios, survives transaction costs, and long-horizon investors are more likely to beat the benchmark.
Shows that most NSE factor indices stop earning their past returns once they go live, and none deliver alpha over size, value, and momentum.
The cross-section of Indian stock returns: evidence using machine learning
Tests 35 characteristics on every listed Indian firm and finds machine learning forecasts beat OLS, with the best portfolios earning significant returns.
Predicting Intraday cryptocurrency returns – A Sparse Signals approach
Finds sparse, short-lived signals in minute-by-minute cryptocurrency returns, with LASSO forecasts beating the usual benchmarks.
Shows stock-return predictability rose in several industries after COVID-19 hit, suggesting markets became less informationally efficient.
Multi-factor asset pricing models in emerging and developed markets
Compares multi-factor models across ten markets. The Fama-French five-factor model prices stocks best in Australia, Canada, China, and the US, but not everywhere.
Aggregate earnings and gross domestic product: International evidence
Shows the link between aggregate earnings and real GDP growth holds across eight countries, and that forecasters underreact to aggregate earnings news.
Documents over- and under-reaction after extreme intraday moves in the ten largest markets, pointing to exploitable behavioural biases.
Asset pricing factors and future economic growth
Tests seven common asset-pricing factors against future GDP and industrial-production growth, and finds only the market factor predicts it. The predictive power reported in earlier studies looks to have faded.
Quality investing in the Indian stock market
Finds two of four quality screens beat the market on BSE-500 stocks, even after controlling for size, value, and momentum.
Working papers & preprints
YouTubers and Stock Returns
Uses a large language model to pull stock calls from YouTubers across nine countries. The calls predict one-month returns, but not longer-horizon moves or lasting profits.
The Value Relevance of Earnings for Factor Investors
Shows the aggregate earnings-returns link is stronger for large-cap and growth stocks than for small-cap and value stocks, with implications for factor investors.
Work in progress
- Narratives from YouTube videos.
- Anomalies and asset pricing factors database for India.
- AI for portfolio choice and financial stability.
Some of my working papers are available on my SSRN author page.