How Much is Financial Advice Worth? The Transparency-Revenue Tension in Social Trading
by
Zhiqiang (Eric) Zheng
Ashbel Smith Professor
Department of Information Systems and Operations Management
Naveen Jindal School of Management
University of Texas at Dallas
Friday, February 7
10:30 – 12:00 pm | Speakman 200
Abstact:
Social trading — an emerging paradigm in the spirit of the sharing economy — enables a trader to share her trading wisdom with other investors. A special type of social trading is copy trading, where 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. On the other hand, complete transparency may undercut the platform’s revenue since followers could free ride. That is, followers could manually copy the trades of a trader to avoid paying following fees.
This study addresses the tension by optimizing the level of transparency by delaying the release of the information pertaining to the trades executed by traders on the platform. We capture the economic impact of the delay using the notions of profit-gap and delayed-profit. Profit-gap is calculated as the difference between the profit of the real-time trade and the delayed-profit of the trade (i.e., the profit of the same trade executed after adding some time delay). First, we propose stochastic differential models that capture the impact of delay on profit-gap and delayed-profit. Next, we propose a mechanism that elucidates the economic effects of profit-gap and delayed-profit on followers, and consequently, the amount following a trader: (1) Protection Effect and (2) Evaluation Effect. The protection effect becomes stronger as the profit-gap increases. The evaluation effect becomes stronger when the delayed-profit increases or when a trader attracts more evaluation activities (views) on her profile page. Empirical investigations find support for the above mentioned effects of profit-gap and delayed-profit on the amount of money following a trader.
We then develop a stochastic control formulation that optimizes platform revenue. The control is the optimal delay that is 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.