https://www.ml-quant.com/topics/econometrics-forecasting/Forecasting, time series, econometrics and nowcasting. en https://www.ml-quant.com/papers/arxiv/2610.07430/https://www.ml-quant.com/papers/arxiv/2610.07430/Fri, 09 Oct 2026 07:00:00 +0000A convex method learns causal filters that balance stationarity and input preservation for financial time series, adapting filtering strength to persistence while preserving signal similarity. https://www.ml-quant.com/papers/repec/imf-imfsdn-2026-003/https://www.ml-quant.com/papers/repec/imf-imfsdn-2026-003/Fri, 09 Oct 2026 07:00:00 +0000A framework using deviations from interest-rate parity identifies when exchange-rate movements stem from financial shocks rather than fundamentals, aiding intervention decisions. https://www.ml-quant.com/papers/repec/onb-oenbwp-281/https://www.ml-quant.com/papers/repec/onb-oenbwp-281/Fri, 09 Oct 2026 07:00:00 +0000The sequencing and emphasis of sentiment within central bank statements predict rate decisions and inflation expectations beyond average tone alone. https://www.ml-quant.com/papers/repec/boa-wpaper-202648/https://www.ml-quant.com/papers/repec/boa-wpaper-202648/Fri, 09 Oct 2026 07:00:00 +0000Fractional processes outperform discrete models like HAR for forecasting realized volatility at longer horizons by better balancing recent levels against long-run persistence. https://www.ml-quant.com/papers/repec/bca-bocsap-26-7/https://www.ml-quant.com/papers/repec/bca-bocsap-26-7/Fri, 09 Oct 2026 07:00:00 +0000CLONE decomposes daily price moves into demand, productivity, inflation, and policy news using stocks, bonds, and inflation swaps; aggregate demand dominated until 2021. https://www.ml-quant.com/papers/repec/hal-journl-hal-05740995/https://www.ml-quant.com/papers/repec/hal-journl-hal-05740995/Fri, 09 Oct 2026 07:00:00 +0000Treasury yield curve slope volatility forecasts industrial production and employment growth at medium and long horizons, outperforming term spread alone after the 2008 crisis. https://www.ml-quant.com/papers/repec/adl-wpaper-2026-05/https://www.ml-quant.com/papers/repec/adl-wpaper-2026-05/Fri, 09 Oct 2026 07:00:00 +0000A Bayesian spike-and-slab method improves high-dimensional panel VAR forecasting and reveals heterogeneous spillover structures in sovereign bonds and macro data. https://www.ml-quant.com/papers/repec/pre-wpaper-202630/https://www.ml-quant.com/papers/repec/pre-wpaper-202630/Fri, 09 Oct 2026 07:00:00 +0000A time-varying VAR network reveals supply-inelastic coastal markets absorb largest regulatory shocks and spillovers persist to monetary conditions and inflation expectations. https://www.ml-quant.com/papers/repec/adl-wpaper-2026-02/https://www.ml-quant.com/papers/repec/adl-wpaper-2026-02/Fri, 09 Oct 2026 07:00:00 +0000Time-varying beliefs about the central bank's reaction function collapsed at the zero bound and rose only after observed tightening, not from guidance alone. https://www.ml-quant.com/papers/arxiv/2610.01955/https://www.ml-quant.com/papers/arxiv/2610.01955/Fri, 02 Oct 2026 07:00:00 +0000Training teaches a language model to improve event forecasting by learning which evidence to gather, beating frontier models on hard questions at lower cost. https://www.ml-quant.com/papers/arxiv/2609.38197/https://www.ml-quant.com/papers/arxiv/2609.38197/Fri, 02 Oct 2026 07:00:00 +0000Dual-path language model extended with financial tokens and news-conditioned revision achieves lowest error in 8 of 12 equity and energy forecasting settings across multiple horizons. https://www.ml-quant.com/papers/ssrn/7527762/https://www.ml-quant.com/papers/ssrn/7527762/Fri, 02 Oct 2026 07:00:00 +0000A new 234-year synthetic total-return dataset for equities and Treasuries reveals that permanent 3× leverage faces near-total loss in most reconstructions, ranking below 2× on risk-adjusted returns. https://www.ml-quant.com/papers/ssrn/7532698/https://www.ml-quant.com/papers/ssrn/7532698/Fri, 02 Oct 2026 07:00:00 +0000The research develops a compact Bayesian VAR for real-time forecasting of GDP growth, inflation, unemployment, and the federal funds rate, with evaluation emphasizing density scores and predictive-interval diagnostics. https://www.ml-quant.com/papers/repec/bdi-wptemi-td-1542-26/https://www.ml-quant.com/papers/repec/bdi-wptemi-td-1542-26/Fri, 02 Oct 2026 07:00:00 +0000AI-intensive patents generate delayed productivity and employment gains alongside falling consumer prices, with substantially larger aggregate effects than broader ICT shocks but reducing labor share and increasing wealth inequality. https://www.ml-quant.com/papers/repec/tse-wpaper-132139/https://www.ml-quant.com/papers/repec/tse-wpaper-132139/Fri, 02 Oct 2026 07:00:00 +0000The study shows that increased Federal Reserve communication lowers monetary policy uncertainty and generates substantial real effects: industrial production rises 0.3 percent and unemployment falls 0.2 percentage points within two months. https://www.ml-quant.com/papers/repec/cbi-wpaper-09-rt-26/https://www.ml-quant.com/papers/repec/cbi-wpaper-09-rt-26/Fri, 02 Oct 2026 07:00:00 +0000Analysis of a large macro-financial dataset ranks non-linear monetary transmission channels, finding transmission to long-term rates weakens at high interest rates and high credit growth, with sovereign risk mattering in the euro area. https://www.ml-quant.com/papers/repec/pre-wpaper-202620/https://www.ml-quant.com/papers/repec/pre-wpaper-202620/Fri, 02 Oct 2026 07:00:00 +0000The GARCH-MIDAS model incorporating a quarterly news-based Price Conflict Index outperforms benchmarks for forecasting US stock volatility over 150 years of monthly and daily data. https://www.ml-quant.com/papers/repec/ces-ceswps-12972/https://www.ml-quant.com/papers/repec/ces-ceswps-12972/Fri, 02 Oct 2026 07:00:00 +0000A pre-trained time-series model reading central bank published paths cuts forecast errors better than the banks themselves and hard-conditioned VARs, revealing exploitable institutional differences. https://www.ml-quant.com/papers/arxiv/2609.29530/https://www.ml-quant.com/papers/arxiv/2609.29530/Fri, 25 Sep 2026 07:00:00 +0000Proves that training sufficiency, test coverage, and temporal causality cannot be maximized simultaneously in time-series validation, pricing each constraint explicitly. https://www.ml-quant.com/papers/arxiv/2609.25617/https://www.ml-quant.com/papers/arxiv/2609.25617/Fri, 25 Sep 2026 07:00:00 +0000A hierarchical multi-task framework jointly predicts price movement, volatility and volume using liquidity-aware signals, outperforming neural and tree-based baselines on Chinese equity indices. https://www.ml-quant.com/papers/arxiv/2609.23223/https://www.ml-quant.com/papers/arxiv/2609.23223/Fri, 25 Sep 2026 07:00:00 +0000Jointly reconciling hourly price and spread forecasts improves intraday electricity price prediction accuracy by up to 19.7% and battery-arbitrage profits by up to 10.4%. https://www.ml-quant.com/papers/arxiv/2609.26994/https://www.ml-quant.com/papers/arxiv/2609.26994/Fri, 25 Sep 2026 07:00:00 +0000A regime-switching volatility-in-mean VAR reveals that the drivers of growth and inflation tails differ from median dynamics, with macroeconomic uncertainty playing a larger role in downside risk. https://www.ml-quant.com/papers/arxiv/2609.23998/https://www.ml-quant.com/papers/arxiv/2609.23998/Fri, 25 Sep 2026 07:00:00 +0000A stochastic nested fixed-point estimator reduces memory and computational cost for random-coefficients logit demand models, enabling estimation on 100 million markets in hours. https://www.ml-quant.com/papers/arxiv/2609.21587/https://www.ml-quant.com/papers/arxiv/2609.21587/Fri, 25 Sep 2026 07:00:00 +0000Augmenting HAR with a negative moving-average component approximates rough dynamics, outperforming classical models out-of-sample and matching continuous-time rough model accuracy. https://www.ml-quant.com/papers/arxiv/2609.29515/https://www.ml-quant.com/papers/arxiv/2609.29515/Fri, 25 Sep 2026 07:00:00 +0000Introduces a network realized GARCH-Itô model that identifies dynamic volatility transmission among assets using high-frequency data, outperforming recursive forecasts on sector ETFs. https://www.ml-quant.com/papers/ssrn/7486138/https://www.ml-quant.com/papers/ssrn/7486138/Fri, 25 Sep 2026 07:00:00 +0000Using production, employment, and sales data across 426 industries, the research shows that upstream industry signals predict aggregate monthly stock returns with 23.8% out-of-sample R-squared. https://www.ml-quant.com/papers/arxiv/2602.04464/https://www.ml-quant.com/papers/arxiv/2602.04464/Thu, 12 Feb 2026 07:00:00 +0000Including discounted sales of soon-to-expire perishables in demand forecasts leads to underestimating demand, highlighting the need for better forecasting to reduce inventory waste in grocery stores. https://www.ml-quant.com/papers/arxiv/2601.16821/https://www.ml-quant.com/papers/arxiv/2601.16821/Mon, 02 Feb 2026 07:00:00 +0000The article introduces a new Bayesian model that analyzes compositional time series data, effectively handling structural breaks and enhancing forecasting accuracy during these changes. https://www.ml-quant.com/papers/arxiv/2601.10143/https://www.ml-quant.com/papers/arxiv/2601.10143/Fri, 16 Jan 2026 07:00:00 +0000A new adaptive data management system enhances model performance in quantitative finance by constantly updating to reflect market changes, addressing the shortcomings of relying solely on historical data. https://www.ml-quant.com/papers/ssrn/4463148/https://www.ml-quant.com/papers/ssrn/4463148/Sun, 28 Dec 2025 07:00:00 +0000The study promotes the use of Bayesian statistics in finance to better analyze large AI-generated datasets and mitigate misleading significance from traditional methods.