We propose the following structured approach to asset allocation: all assets and liabilities in any portfolio should be thought of as means contributing to the following four ends: • Liquidity maintenance: nominally safe and quickly accessible “cash-like” pool of assets, • Income generation: relatively regular, certain and near-term cash payments, • Preservation of (real) capital: assets expected to retain their value over time, • Growth: more volatile assets and strategies expected to generate future cash payments. We believe that all 4 areas should be “powered,” giving our approach its 4×4 name. Further, we suggest that investors should start their asset allocation process by explicitly setting a strategic investment horizon over which they seek to achieve their goals, and building strategic 4×4 portfolios. Investment portfolios should then be rebalanced with some regular tactical frequency in order to re-align with the strategic investment horizon goals, while also managing tactical risk, return, and cash flows.
{"title":"4×4 Asset Allocation","authors":"Maxim Golts","doi":"10.2139/ssrn.3949919","DOIUrl":"https://doi.org/10.2139/ssrn.3949919","url":null,"abstract":"We propose the following structured approach to asset allocation: all assets and liabilities in any portfolio should be thought of as means contributing to the following four ends: • Liquidity maintenance: nominally safe and quickly accessible “cash-like” pool of assets, • Income generation: relatively regular, certain and near-term cash payments, • Preservation of (real) capital: assets expected to retain their value over time, • Growth: more volatile assets and strategies expected to generate future cash payments. We believe that all 4 areas should be “powered,” giving our approach its 4×4 name. Further, we suggest that investors should start their asset allocation process by explicitly setting a strategic investment horizon over which they seek to achieve their goals, and building strategic 4×4 portfolios. Investment portfolios should then be rebalanced with some regular tactical frequency in order to re-align with the strategic investment horizon goals, while also managing tactical risk, return, and cash flows.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43116879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We introduce a theoretical tool for handling pure-jump processes taking values in complex spaces. We generalize the notion of rate kernels for the non-Markov case, being able to describe any pure-jump process in Borel space with absolutely continuous conditional distribution of jump times. We study the case of two simultaneously running processes where the evolution of the first is locally unaffected on the values of the second; we show that then the conditional distribution of the second can be evaluated as if the first were deterministic. Further we study pure-jump process of bounded atomic measures. We characterize rate kernels ruling processes of completely random atomic measures. Finally, we apply our theory to the model of call auction with the limit order process depending on a common driving factor called fair price; we give analytical formula for the conditional distribution of the order books given the trajectory of the fair price and semi-analytical formulas for both the conditional and unconditional distribution of the settlement price.
{"title":"Non-Markov rate kernels: Application to batch auction","authors":"M. Šmíd, A. Kuběna","doi":"10.2139/ssrn.3949374","DOIUrl":"https://doi.org/10.2139/ssrn.3949374","url":null,"abstract":"We introduce a theoretical tool for handling pure-jump processes taking values in complex spaces. We generalize the notion of rate kernels for the non-Markov case, being able to describe any pure-jump process in Borel space with absolutely continuous conditional distribution of jump times. We study the case of two simultaneously running processes where the evolution of the first is locally unaffected on the values of the second; we show that then the conditional distribution of the second can be evaluated as if the first were deterministic. Further we study pure-jump process of bounded atomic measures. We characterize rate kernels ruling processes of completely random atomic measures. Finally, we apply our theory to the model of call auction with the limit order process depending on a common driving factor called fair price; we give analytical formula for the conditional distribution of the order books given the trajectory of the fair price and semi-analytical formulas for both the conditional and unconditional distribution of the settlement price.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46958238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We formulate and solve a costly multi-unit search problem for the optimal selling of a stock of goods. Our showcase application is an inventory liquidation problem with fixed holding costs, such as warehousing, salaries or floor planning. A seller faces a stream of buyers periodically arriving with random capped demands. At each decision point, he decides how to price each unit and also whether to stop search or not. We set this as a dynamic programming problem and solve it inductively by characterizing optimal search rules and reservation prices. We show that combining multiple units with a fixed per period search cost might translate into non-monotone selling costs and reservation prices. This lack of monotonicity naturally leads to discontinuities of the pricing strategy. In particular, the seller optimally employs strategies such as bundling, and more sophisticated ones that endogenously combine purchase premiums, when inventory is large, with clearance sales and discounts, when inventory is low. Our model extends search theory by explicitly accounting for the effects of fixed costs on optimal multi-unit pricing strategies, pushing it into a richer class of problems and offering solutions that extend beyond optimal stopping rules.
{"title":"Costly Multi-Unit Search","authors":"José A. Carrasco, Rodrigo Harrison","doi":"10.2139/ssrn.3949785","DOIUrl":"https://doi.org/10.2139/ssrn.3949785","url":null,"abstract":"We formulate and solve a costly multi-unit search problem for the optimal selling of a stock of goods. Our showcase application is an inventory liquidation problem with fixed holding costs, such as warehousing, salaries or floor planning. A seller faces a stream of buyers periodically arriving with random capped demands. At each decision point, he decides how to price each unit and also whether to stop search or not. We set this as a dynamic programming problem and solve it inductively by characterizing optimal search rules and reservation prices. We show that combining multiple units with a fixed per period search cost might translate into non-monotone selling costs and reservation prices. This lack of monotonicity naturally leads to discontinuities of the pricing strategy. In particular, the seller optimally employs strategies such as bundling, and more sophisticated ones that endogenously combine purchase premiums, when inventory is large, with clearance sales and discounts, when inventory is low. Our model extends search theory by explicitly accounting for the effects of fixed costs on optimal multi-unit pricing strategies, pushing it into a richer class of problems and offering solutions that extend beyond optimal stopping rules.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45855572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the effect of competition on firm innovation at the project-level. We instrument shocks to competition in therapeutic areas with the FDA’s breakthrough therapy designation (BTD) event on a therapy. BTD events strongly associate with several indicators of competitive shocks, including announcement returns and increased likelihood of FDA approval to market the drug. BTD shocks discourage rivals’ innovation in that therapeutic area on average. However, the effect varies with ex-ante competitiveness of the therapeutic area, as well as with the rival’s position (leader vs. follower) in that space. We support Aghion et al. (2005) with direct causal evidence at the corporate-project-level.
{"title":"Competition and Innovation Revisited: A Product-Level View","authors":"Jon A. Garfinkel, Mosab Hammoudeh","doi":"10.2139/ssrn.3684095","DOIUrl":"https://doi.org/10.2139/ssrn.3684095","url":null,"abstract":"We study the effect of competition on firm innovation at the project-level. We instrument shocks to competition in therapeutic areas with the FDA’s breakthrough therapy designation (BTD) event on a therapy. BTD events strongly associate with several indicators of competitive shocks, including announcement returns and increased likelihood of FDA approval to market the drug. BTD shocks discourage rivals’ innovation in that therapeutic area on average. However, the effect varies with ex-ante competitiveness of the therapeutic area, as well as with the rival’s position (leader vs. follower) in that space. We support Aghion et al. (2005) with direct causal evidence at the corporate-project-level.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68622976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We decompose total disagreement about macro variables into the disagreement among optimists (i.e., forecasters whose forecast exceeds a certain threshold) and pessimists. Optimistic (pessimistic) forecasters tend to disagree more in good (bad) times. Pessimistic (optimistic) disagreement commands a negative and significant (positive, although often (insignificant) risk premium and total disagreement is often insignificant when included in the same regression. These results are robust across a variety of empirical specifications and sets of test assets. A theoretical model, in which the risk premia of optimistic and pessimistic disagreement depend in a non-trivial way on forecasters’ beliefs and on the joint impact of optimistic and pessimistic disagreement on the price of the assets used to speculate on individual beliefs, rationalizes the empirical findings.
{"title":"Optimistic and Pessimistic Disagreement and the Cross Section of Stock Returns","authors":"I. Dergunov, G. Curatola, Christian Schlag","doi":"10.2139/ssrn.3948908","DOIUrl":"https://doi.org/10.2139/ssrn.3948908","url":null,"abstract":"We decompose total disagreement about macro variables into the disagreement among optimists (i.e., forecasters whose forecast exceeds a certain threshold) and pessimists. Optimistic (pessimistic) forecasters tend to disagree more in good (bad) times. Pessimistic (optimistic) disagreement commands a negative and significant (positive, although often (insignificant) risk premium and total disagreement is often insignificant when included in the same regression. These results are robust across a variety of empirical specifications and sets of test assets. A theoretical model, in which the risk premia of optimistic and pessimistic disagreement depend in a non-trivial way on forecasters’ beliefs and on the joint impact of optimistic and pessimistic disagreement on the price of the assets used to speculate on individual beliefs, rationalizes the empirical findings.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48563824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blanka Horvath, Zacharia Issa, Aitor Muguruza Gonzalez
The problem of rapid and automated detection of distinct market regimes is a topic of great interest to financial mathematicians and practitioners alike. In this paper, we outline an unsupervised learning algorithm for clustering financial time-series into a suitable number of temporal segments (market regimes). As a special case of the above, we develop a robust algorithm that automates the process of classifying market regimes. The method is robust in the sense that it does not depend on modelling assumptions of the underlying time series as our experiments with real datasets show. This method -- dubbed the Wasserstein $k$-means algorithm -- frames such a problem as one on the space of probability measures with finite $p^text{th}$ moment, in terms of the $p$-Wasserstein distance between (empirical) distributions. We compare our WK-means approach with a more traditional clustering algorithms by studying the so-called maximum mean discrepancy scores between, and within clusters. In both cases it is shown that the WK-means algorithm vastly outperforms all considered competitor approaches. We demonstrate the performance of all approaches both in a controlled environment on synthetic data, and on real data.
{"title":"Clustering Market Regimes Using the Wasserstein Distance","authors":"Blanka Horvath, Zacharia Issa, Aitor Muguruza Gonzalez","doi":"10.2139/ssrn.3947905","DOIUrl":"https://doi.org/10.2139/ssrn.3947905","url":null,"abstract":"The problem of rapid and automated detection of distinct market regimes is a topic of great interest to financial mathematicians and practitioners alike. In this paper, we outline an unsupervised learning algorithm for clustering financial time-series into a suitable number of temporal segments (market regimes). As a special case of the above, we develop a robust algorithm that automates the process of classifying market regimes. The method is robust in the sense that it does not depend on modelling assumptions of the underlying time series as our experiments with real datasets show. This method -- dubbed the Wasserstein $k$-means algorithm -- frames such a problem as one on the space of probability measures with finite $p^text{th}$ moment, in terms of the $p$-Wasserstein distance between (empirical) distributions. We compare our WK-means approach with a more traditional clustering algorithms by studying the so-called maximum mean discrepancy scores between, and within clusters. In both cases it is shown that the WK-means algorithm vastly outperforms all considered competitor approaches. We demonstrate the performance of all approaches both in a controlled environment on synthetic data, and on real data.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48510598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a model of seller expertise, expressed in our setting as the accuracy of seller beliefs about buyers. Principally, both buyers and sellers are heterogeneous ex-ante, the former with respect to their marginal valuation for quality of a good and the latter with respect to expertise. Information asymmetries from both private buyer valuations and uncertainty regarding the number of competing sellers per buyer give rise to imperfectly competitive equilibria, in which sellers offer screening menus. We characterize equilibria generically through results concerning existence, uniqueness, a ranking property of menus with respect to the indirect utilities offered to each type of buyer, as well as link between the sellers' belief about being in a high valuation buyer match and the generosity of their bids. Using our analytic characterization, we explore variations in market structure to study the effects of expertise on trade. Expertise is uniformly efficiency enhancing but inherently redistributive. On the demand side, low valuation buyers benefit while high valuation buyers suffer. On the supply side, expertise not only benefits sellers who possess it, but even those who do not.
{"title":"The Invisible FAANG","authors":"Collum Freedman, J. Sagredo","doi":"10.2139/ssrn.3948210","DOIUrl":"https://doi.org/10.2139/ssrn.3948210","url":null,"abstract":"We present a model of seller expertise, expressed in our setting as the accuracy of seller beliefs about buyers. Principally, both buyers and sellers are heterogeneous ex-ante, the former with respect to their marginal valuation for quality of a good and the latter with respect to expertise. Information asymmetries from both private buyer valuations and uncertainty regarding the number of competing sellers per buyer give rise to imperfectly competitive equilibria, in which sellers offer screening menus. We characterize equilibria generically through results concerning existence, uniqueness, a ranking property of menus with respect to the indirect utilities offered to each type of buyer, as well as link between the sellers' belief about being in a high valuation buyer match and the generosity of their bids. Using our analytic characterization, we explore variations in market structure to study the effects of expertise on trade. Expertise is uniformly efficiency enhancing but inherently redistributive. On the demand side, low valuation buyers benefit while high valuation buyers suffer. On the supply side, expertise not only benefits sellers who possess it, but even those who do not.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49340707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we estimate an agent-based model (ABM) to investigate herding behaviors in the formation of investor sentiment. We formalize a simple opinion dynamics model in a social network framework and rely on a numerical method to estimate its parameters. We derive a sentiment proxy from the weekly aggregation of online messages concerning 15 US stocks and 5 cryptocurrencies. Our empirical results suggest a strong impact of herding behavior on the formation of sentiment toward highly volatile assets. For such assets, we simultaneously find limited impacts of financial returns and investor attention on the opinion formation process, suggesting that investor sentiment is explained by social interactions. On the other hand, we find a limited influence of social interactions on sentiment regarding less volatile assets, whose formation process is instead explained by the strong influence of financial returns and investors' attention. In particular, we find that herding behavior was significantly higher and played a major role in the sentiment formation process regarding cryptocurrencies when the bubble occurred.
{"title":"Estimating a model of herding behavior on social networks","authors":"M. L. Nicolas","doi":"10.2139/ssrn.3948170","DOIUrl":"https://doi.org/10.2139/ssrn.3948170","url":null,"abstract":"In this paper, we estimate an agent-based model (ABM) to investigate herding behaviors in the formation of investor sentiment. We formalize a simple opinion dynamics model in a social network framework and rely on a numerical method to estimate its parameters. We derive a sentiment proxy from the weekly aggregation of online messages concerning 15 US stocks and 5 cryptocurrencies. Our empirical results suggest a strong impact of herding behavior on the formation of sentiment toward highly volatile assets. For such assets, we simultaneously find limited impacts of financial returns and investor attention on the opinion formation process, suggesting that investor sentiment is explained by social interactions. On the other hand, we find a limited influence of social interactions on sentiment regarding less volatile assets, whose formation process is instead explained by the strong influence of financial returns and investors' attention. In particular, we find that herding behavior was significantly higher and played a major role in the sentiment formation process regarding cryptocurrencies when the bubble occurred.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42201192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is devoted to the theoretical and empirical study seeking to explain the choice of accounting strategies made by the Algerian companies in the framework of positive accounting theory (Watts and Zimmerman, 1978) and the institutional theory (DiMaggio and Powell, 1983). The empirical analysis, using multinomial logistic regression with some specification tests as Wald Test and Ramsey RESET Test, of 50 public and private Algerian companies on the data for year 2010, suggests that accounting strategy is determined by the company’ size, the system of managers’ compensation and legal status.
{"title":"The determinants of Accounting Strategy Choices: “A Theoretical and Empirical Study through Positive Accounting Theory and Institutional Theory”","authors":"F. Saci","doi":"10.2139/ssrn.3948221","DOIUrl":"https://doi.org/10.2139/ssrn.3948221","url":null,"abstract":"This paper is devoted to the theoretical and empirical study seeking to explain the choice of accounting strategies made by the Algerian companies in the framework of positive accounting theory (Watts and Zimmerman, 1978) and the institutional theory (DiMaggio and Powell, 1983). The empirical analysis, using multinomial logistic regression with some specification tests as Wald Test and Ramsey RESET Test, of 50 public and private Algerian companies on the data for year 2010, suggests that accounting strategy is determined by the company’ size, the system of managers’ compensation and legal status.","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46645919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We show theoretically that variable production costs reduce systematic risk of firms' cash flows if capital and variable inputs are complementary in firms' production and input prices are procyclical. In our dynamic model, this operating hedge effect is weaker for more profitable firms, giving rise to a gross profitability premium. Moreover, gross profitability and value factors are distinct and negatively correlated, and their premia are not captured by the CAPM. We estimate the model by simulated method of moments, and find that its main implications for stock returns and cash flow dynamics are quantitatively consistent with the data.This article is protected by copyright. All rights reserved
{"title":"Operating Hedge and Gross Profitability Premium","authors":"L. Kogan, Jun Li, Harold H. Zhang","doi":"10.2139/ssrn.3947165","DOIUrl":"https://doi.org/10.2139/ssrn.3947165","url":null,"abstract":"We show theoretically that variable production costs reduce systematic risk of firms' cash flows if capital and variable inputs are complementary in firms' production and input prices are procyclical. In our dynamic model, this operating hedge effect is weaker for more profitable firms, giving rise to a gross profitability premium. Moreover, gross profitability and value factors are distinct and negatively correlated, and their premia are not captured by the CAPM. We estimate the model by simulated method of moments, and find that its main implications for stock returns and cash flow dynamics are quantitatively consistent with the data.This article is protected by copyright. All rights reserved","PeriodicalId":74863,"journal":{"name":"SSRN","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42122591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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