{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T14:41:57Z","timestamp":1792248117655,"version":"4.4.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":10,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.uspto.gov\/ip-policy\/copyright-policy\/copyright-basics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<p>Many asset-allocation processes begin with an economic view and then translate it into positions. This paper asks a narrower question: once price information is used systematically, does adding historical-vintage macroeconomic information improve allocation decisions? We study 112 monthly out-of-sample decisions from March 2017 to June 2026 across 11 U.S.-listed ETFs and organize the analysis around three comparisons: active ranking versus the same-universe equal-weight benchmark (EW11), incremental macro value versus Price-only, and economic trade-offs versus 60\/40.<span><\/span><\/p>\n<p>Price-only earns a 15.3% CAGR versus 10.2% for EW11, with 5.0% annualized active return and an information ratio of 0.71; simple momentum rules also outperform EW11. Macro+Price has a net Sharpe ratio of 0.798 versus 0.821 for Price-only. The difference is -0.023, with a 95% moving-block interval of [-0.351, 0.235]. The conclusion on incremental macro value is unchanged in the raw-series and conservative timing checks. Under the conservative convention, the difference is -0.192 with a 95% interval of [-0.659, 0.175], although Macro+Price selections change in about 53% of months.<\/p>\n<p>Macro-only retains positive standalone performance. The evidence is not a case against macro research. It shows that richer information should be credited with incremental value only when it improves an active process that already adds value after portfolio construction, turnover, and costs.<\/p><\/jats:p>","DOI":"10.2139\/ssrn.7340100","type":"posted-content","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T13:30:17Z","timestamp":1787664617000},"source":"Crossref","is-referenced-by-count":0,"title":["The Decision Value of Price and Macro Information: Benchmark-Relative Evidence in Multi-asset Allocation using Historical-Vintage FRED-MD Data"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5598-3346","authenticated-orcid":true,"given":"Sungkyu","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"ref1","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1111\/jofi.12021","article-title":"Value and Momentum Everywhere","volume":"68","author":"Clifford S Asness","year":"2013","journal-title":"The Journal of Finance"},{"issue":"3","key":"ref2","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1287\/mnsc.2018.3253","article-title":"From Predictive to Prescriptive Analytics","volume":"66","author":"Dimitris Bertsimas","year":"2020","journal-title":"Management Science"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/S0304-4076(01)00072-0","article-title":"A Real-Time Data Set for Macroeconomists","volume":"105","author":"Dean Croushore","year":"2001","journal-title":"Journal of Econometrics"},{"issue":"1","key":"ref4","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1287\/mnsc.2020.3922","article-title":"Smart \"Predict, then Optimize","volume":"68","author":"Adam N Elmachtoub","year":"2022","journal-title":"Management Science"},{"issue":"11","key":"ref5","doi-asserted-by":"crossref","first-page":"3490","DOI":"10.1093\/rfs\/hhae044","article-title":"A Comprehensive 2022 Look at the Empirical Performance of Equity Premium Prediction","volume":"37","author":"Amit Goyal","year":"2024","journal-title":"The Review of Financial Studies"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1111\/j.1540-6261.1993.tb04702.x","article-title":"Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency","volume":"48","author":"Narasimhan Jegadeesh","year":"1993","journal-title":"The Journal of Finance"},{"key":"ref7","first-page":"3035","volume":"39","author":"Theis Jensen","year":"2026","journal-title":"Machine Learning and the Implementable Efficient Frontier"},{"issue":"4","key":"ref8","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1080\/07350015.2015.1086655","article-title":"FRED-MD: A Monthly Database for Macroeconomic Research","volume":"34","author":"Michael W Mccracken","year":"2016","journal-title":"Journal of Business & Economic Statistics"},{"issue":"2","key":"ref9","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.jfineco.2011.11.003","article-title":"Time Series Momentum","volume":"104","author":"Tobias J Moskowitz","year":"2012","journal-title":"Journal of Financial Economics"},{"issue":"4","key":"ref10","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1093\/rfs\/hhm014","article-title":"A Comprehensive Look at The Empirical Performance of Equity Premium Prediction","volume":"21","author":"Ivo Welch","year":"2008","journal-title":"The Review of Financial Studies"}],"container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T14:05:00Z","timestamp":1792245900000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7340100"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":10,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7340100","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}