How Much Is Financial Advice Worth? The Transparency-Revenue Tension in Social Trading
Autor: | Zhiqiang (Eric) Zheng, Vijay Mookerjee, Mingwen Yang |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Management Science. 68:5252-5268 |
ISSN: | 1526-5501 0025-1909 |
DOI: | 10.1287/mnsc.2021.4147 |
Popis: | In social trading, less experienced investors (followers) are allowed to copy the trades of experts (traders) in real time after paying a fee. Such a copy-trading mechanism often runs into a transparency-revenue tension. On the one hand, social trading platforms need to release traders’ trades as transparently as possible to allow followers to evaluate traders accurately. On the other hand, complete transparency may undercut the platform’s revenue because followers can free ride. That is, followers can manually copy the trades of a trader to avoid paying the following fees. This study addresses this critical tension by optimizing the level of transparency through delaying the release of trading information pertaining to the trades executed by traders. We capture the economic impact of the delay using the notions of profit-gap and delayed-profit. We propose a mechanism that elucidates the economic effects of the profit-gap and delayed-profit on followers and, consequently, the amount of money following a trader: protection effect and evaluation effect. Empirical investigations find support for these two effects. We then develop a stochastic control formulation that optimizes platform revenue, where the control is the optimal delay customized at the trader level and calculated as a function of the current amount of money following a trader and the number of views on the trader’s profile page. The optimized revenue can be incorporated into an algorithm to provide a systematic way to infuse the platform’s goals into the ranking of the traders. A counterfactual study is conducted to demonstrate the performance of the optimal delay policy (versus a constant-delay policy) using data from a leading social trading platform operating in the foreign exchange market. This paper was accepted by Chris Forman, information systems. |
Databáze: | OpenAIRE |
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