Serious Algorithmic Trading Series – Part 1
Can individual traders really compete with large institutions?
This post is the first of a four-part “Serious Algorithmic Trading” series, introduced here.
A trader will at one point or another, question how practical it is to compete with large institutions in the same markets.
After all, it is “big money” at the end of the day that moves these markets.
The reality is that institutions face several regulatory, technological, structural and capital constraints that individual traders don’t.
It’s these very constraints that also lead to institutional funds often exhibiting a degree of predictability that is visible to – and can potentially be exploited by – individual traders. This phenomenon will be discussed in more detail in post #3, “The Quantitative Approach to Algorithmic R&D”.
The answer to the question is therefore YES.
Let’s examine why in the contexts of Scalability & Market Impact, Risk Management, and Trading Technology.
Scalability & Market Impact
Individual traders can design and execute trading strategies that target small inefficiencies in the market.
Such inefficiencies often have capacities up to a fairly limited amount of capital before they lose their profitability.
This limited capital support usually ranges from a few hundred thousand to a few million dollars, and is therefore of little to no interest to institutional funds trading with a substantially larger capital base.
Note: For the benefit of the Darwinex community, a Scalability/Capacity investment attribute is displayed on each DARWIN asset listed on the Darwin Exchange. It is a score ranging from 1 to 10 that indicates how invest-able the underlying strategy is. The higher the score, the more assets under management (AuM) the strategy can support.
Furthermore, individual trader capitalization is much lower than that of institutions. This is an advantage as retail trading activity in highly liquid markets cannot therefore create any substantial market impact.
Without middle or compliance offices enforcing industry standards and regulatory oversight, individual traders have the option to model their own risk management techniques as they deem fit, promoting flexibility that can indeed contribute to generating excess returns.
While this may certainly be an advantage for some experienced traders, it is a double-edged sword.
At no risk of being “overruled”, individual traders are at greater risk of exercising “nonoptimal” risk management decisions, often leading to negative outcomes, e.g. accounts blowing up due to excessive use of leverage or aggressive risk management that wouldn’t otherwise have been permitted in an institutional setting.
Note: The Darwin Exchange solves this problem for investors in DARWINs. Traders listing strategies on the Darwin Exchange never manage investor capital themselves.
Darwinex manages all DARWIN assets, and enforces its own risk management to deliver a fixed Value-at-Risk to investors, thereby insulating them from the underlying strategy’s specific risk profile. Traders simply license their intellectual property to Darwinex in exchange for 20% performance fees on any profits generated for investors.
In addition, a Risk Management investment attribute is displayed on all listed DARWIN assets. It is a score ranging from 1 to 10, indicating the ability of the underlying strategy to yield stable risk with consistent use of leverage. The higher the score, the more invest-able the strategy is.
Furthermore, with no enforcement of industry best practices and risk management oversight, individual traders often find themselves modeling risk at the execution level (e.g. stop losses and take profits), without much consideration given to risk at the portfolio level (e.g. mixture of assets or strategies deployed on the same account).
Note: Darwinex addresses this problem for investors in DARWINs. Our Investor Platform enables investors to see the correlation and diversification benefit of selecting any mix of DARWIN assets, before making any investment decisions.
Institutional traders do not enjoy the same flexibility as retail traders, in terms of their choice of technology for trading and strategy development.
Retail traders can choose from a large selection of servers, hardware, trading platforms, programming languages and toolkits, without corporate IT policy or a predetermined list of “permitted systems” affecting their technology preferences.
The only disadvantage that accompanies this flexibility though, is that it can get quite expensive (relative to a retail trader’s available funding) to purchase hardware, software and server subscriptions. These costs must therefore be paid for by traders themselves, whereas in institutions they would most likely be mitigated by management fees charged.
In the next post, we will discuss the core advantages and disadvantages of algorithmic/quantitative trading.
The Darwinex Team
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