-- Luca Regis Associate Professor Department of Economics and Statistics (ESOMAS) University of Torino sites.google.com/view/lucaregis http://sites.google.com/view/lucaregis Office: +39 011 670 6065 www.carloalberto.org/lti http://www.carloalberto.org/lti <#> https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/dxQszhXdTYSeK8TgXWVwPdgch-yVozm308uWxeg02CAeRgCXbxXMzGg0Afvlvvj-dMKNlzkSEuKcRdARWz4xB8ORasq7ZEsLK7H8it5uSxv1YQA41LEkDrUoFgv043G6EgQaODBV54pSvEw6G-VhdHv4-izZnrqz9U8DPjGJxvmBftACZhIuFnX9KhROIHfsZxBAmln1HQ <#> LTI@UniTO and Fondazione Collegio Carlo Alberto are pleased to invite you to the following seminars: <#> *May 24, 2022 | 12:00-13:15* *Predicting Corporate Bond Returns: Merton Meets Machine Learning* *Amit Goyal (University of Lausanne)* <#> *Abstract.* We investigate the return predictability of corporate bonds using big data and machine learning. We find that machine learning models substantially improve the out-of-sample performance of stock and bond characteristics in predicting future bond returns. We also find a significant improvement in the performance of machine learning models when imposing a theoretically motivated economic structure from the Merton model, compared to the reduced-form approach without restrictions. Overall, our work highlights the importance of explicitly imposing the dependence between expected bond and stock returns via machine learning and Merton model when investigating expected bond returns. <#> *To attend in person, register here* https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/hfP4I4mUbx241x0z60A6739Y-00wYiECykBv8JEkIfoxDOPstOzun3OdgA9xxckWeA4IDkIikAeIuK1NrbDMOG-n2IKVWZFfFuzppykcNLz3DyBF81r6aD2JooS8N7kCAnxdJuOPTnxMw8bDd4cqvQWm_fURgLGfRlG2JNbOS7kVivIyXIdmg0qqpU8rBfOuAkoh5aWjXDU87BjHQw <#> *To attend online, join Zoom Meeting* https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/H7wKsG1vuV3OD31wQ_0E5gOGft1OURjriGpy4l2HBnbGy5-RIpKtNE24in74xl9qdi71_G-lNdxn3MOWKy1jqexRCget7fl3q0pEXzGTbyAj8S6Z9TzvrPDfzKAx82f67Ki7496qWeYia5GiENxXAlY90ZmgY3xJN7LTZHHy-JpEuaeW5a9IqrVgMIO-Ltcxx1Rvm6rU0087cWu9rtjDAZZCBEGY1r5AEYwVv7sF-2g8rREQF1S4zYdYXhSzm5tvTP90nrFrpiKkYQ <#> <#> *May 25, 2022 | 12:00 - 13:15* *JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality* *Marco Pagano (University of Naples Federico II)* <#> *Abstract.* Does the matching between workers and jobs help explain productivity differentials across firms? To address this question we develop a job-worker allocation quality measure JAQ by combining employer-employee administrative data with machine learning techniques. The proposed measure is positively and significantly associated with labor earnings over workers’ careers. At firm level, it features a robust positive correlation with firm productivity, and with managerial turnover leading to an improvement in the quality and experience of management. JAQ can be constructed for any employer-employee data including workers’ occupations, and used to explore the effect of corporate restructuring on workers’ allocation and careers. <#> *To attend in person, register here* https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/ykATFHYX2laIzxQ_xgRrxeAEz3ksTLnNgK53pCdxL7LUg6LRR-g_XnvkXX3DzRr8VvfauqJQP-xf0q0Yiafv3_c3MFrohM-bHRhHTlbCH72Bqt8h5ji5DtJxhaw7VPQUmSLRzwlKySzKj3acAA0bBh_ckzdM6ByZ_zJ3taHUIkFLQEIkwUZsTXsUHFYZGrxwbPV8RRpQ4bX5m2a24g <#> *To attend online, join Zoom Meeting* https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/Qu65mxHMOuyATkYSpHoaTbGG4jZwv1_-MWx7ot4VbxeAIke9unypHJeH4F4osqR_7VF__gPicGS2Axw93Gx_S1kkj5Wq5DXhOwyEgKa6JK5M25akIQLx0MeG4hyMVIq2v12-yIpXar7aPUVNlH44RNaXv7JipcRs-B2UqfxBWvcksZNlGXA56m1DBv9F_Jy2wULVljU6LzEIQk8-CKcyVcxk8vnRpNgqBYE9_dxIQRzWUOTmcdtZlsoqnYIRggMELWTkR82CnTw1Yg <#> <#> <#> <#> https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/IfoXGKh5By8LrSGugLNRNVSXyH2VOsaTTdhsYfHWJYm7Npe6AIZy83XspgK0JMedxT1YYB-0VnuIqcP7-gtaE1X1cKcUPkgvAW2OrzavHj2JeGnyiMiPwxc5ubQnJunuhTw9KJ_-MgTfugMZH7ra3kfK9dJLeHd67p3l2o7GmnLdzo8-LSll22n_FkbDbpTgwo1JxphcWZmH9AP10g https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/8usPEOcCcpYYly0bCauwMS_rfjHMGgHJVtnSVNd_t5WugxAql95e1Z_u3zqR75EOApj9z8VZEaTpZt8hlnJkrzJTJL6CCCCgdWo8tIF4VN6Be_Nsw4c88Q_Yj_q7Z7D3ttEQEp_FpvOHbwt9Itxf7AkRd0RfLMhGjUJ1olIJt2cG32e_ZfT8-ZQm7kcJFGE <#> FONDAZIONE COLLEGIO CARLO ALBERTO Piazza Arbarello 8 - 10122 Torino, Italy phone: +39011 15630 800 segreteria@carloalberto.org - www.carloalberto.org Facebook https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/96qDEBjI389G7GVS3NgHy4QU5ODhiSBUXH5afGHo0BT7bEoh5-TMpqq1iYgWi-EP5Z83IPepZNgUcrNPf-YGTNJ5QpXpbzGzeIN-qn-QWe73g_gLYjN0JmRYXP3J_r8EZxTGj-ygNmU-ExuDPZVHDlJP8Bra6Uz8QIzpsXAMW93hIvA092anBRWxARoLCttIWhmFjqlv2VvCf6HILUGteWZHap5K2B4 Twitter https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/NblUBI8B5HmNemhQAOs_hH9Lb0xHqj4qYn-UKTGURkPIU6e_-qH6R8J6594sN0oHsCa2ZBd8vSvQwmvScm9WyaCG4Pd1o5gUsuUzWPPPurJmNrbImAb06pc5EWCmNtRiVnKsLWUc8IBbWlXwOuvM6R5y-_JK2xL_o_ctpmCcp5QpvedNbG6Pbj_ZAOz_cEykcEcDhSJ8Gns LinkedIn https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/rMMfajyr067kRoDawTi2FFsw8dBZwyxWPWTJGg5_Y9x5xN9F55ryYsdDlCjmIvPFA-zNxbJEUjraTy3fdb9RyBRBuvvKTM8hfF0h23fn-1UxQttVEUbVyo_P1AifM2qCQ2DxeNlyyNk6eTJ1NzdXF6JKrGR-EN0uxXe6M21R-uq59V88tfOY5V39jgI3LYtUQxydCZmk15wXfoviz6OgAKGNVLZpvr11-xr_ORHNmfaUP3YI9A Instagram https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/0wIj1P36GYdj7O34J7nWI5VyNMMLDGzqBJzFyPAGjypZg9WZatShgLWVEgRnsFPwLSyxe-AjPRZFVfNhUQiBETYNuJxMcTRB19qCVjmPg4kMfx_W9sdLBlEdN732Z-EfW2ZDGeLMLEYIuevXgfbNnj-yDQOZHaVBwaiLF5bE5kwyhR2q9LNCVdhc7zGInsbWhdGksuC_Y9BcnRWAWEG0YhIe2dfmW12uRQmLvQ Youtube https://4z5y5.r.a.d.sendibm1.com/mk/cl/f/-09AvrjEn7eE8yYbc-ZCF8ERm7rdddPHtichcaktDRlmpA_fs0icTkFwHfzgez4COqndBoAHOq92s0mPZJKTuuBdwSfej36SlNzI-sgc3mfVF7Kpquv9crE0iYaN_26hmBjcg8jXICqa6eOA15pB2LUBTK-Vq56R-WLzIBXX6obSWOW2Hq4vsCNU9lvc9wIvHfewTTVSC3nxI1KPicTxkkSUyQMfo_JrfjJzMqUBddmB8MRYKQ <#> *INFORMATION UNDER THE NEW GENERAL DATA PROTECTION REGULATION (GDPR)* Your personal information has been gathered for the exclusive purpose of informing you about the Collegio's initiatives, considering our and your legitimate interest or your consent. 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