Diligent portfolio management is critical to successful investment, but in an era of high-frequency trading and information overload, retail investors risk missing out on many opportunities to trade if they have to analyze their portfolios manually. In fact, retail investors who make more than 500 trades a year would do so more often if they could better manage their time, according to a 2014 Aite report.
In response to the need for speed, a range of automated software suites have emerged in recent years to streamline the portfolio analytics process for retail investors. Analytics suites save traders time, encouraging them to trade more often. As a result, a sophisticated analytics suite can drive up DARTs and increase a brokerage’s total revenue.
Fundamentally, analytic suites automate various calculations recommended for measuring the performance of all an investors’ securities over time. These calculations measure three key variables that illustrate how each security contributes to the portfolio’s performance and that assess the risk-reward profile of each investment:
- Performance Measurement – How do the returns on the securities in the portfolio compare to a benchmark index? For example, if an investor’s portfolio takes the S&P 500 to be its benchmark, then analytics will measure the return on investments vs the returns on the S&P 500 over the same period of time.
- Asset Allocation and Attribution – After determining the discrepancy between a portfolio’s return and the benchmark, analytics can assess returns based on sector or asset weighting, as well as returns based on individual security selection decisions. This insight explains if you allocated investments to the appropriate sectors, chose the right stocks within each sector, or luckily timed the market just right.
- Risk Analysis – An investor’s current level of risk is compared to other users with a similar trading profile to see how the investment community views the current market conditions. Are allocations too skewed toward riskier assets, jeopardizing the overall health of the portfolio in the event of a market downturn? Conversely, are investors missing out on possible gains by not having enough “risky” assets in their portfolio?
When an investor reviews these calculations, he or she can determine if they have over-allocated their investments in a certain security, or if they own too many low-risk assets to realize the return they want by their desired deadline.
A truly comprehensive portfolio analytics solution looks for insight from outside the portfolio as well. New analytics suites are emerging that complement traditional portfolio analysis capabilities with cutting-edge insights drawn from big data analytics and crowdsourcing. These functionalities add two additional assessment variables to the core three above:
- Social Analysis – How are other investors (with similar Age, Income, Risk Tolerance, Favorite Sectors and Trading Frequency risk-reward profiles) trading?
- Data Insights – What does an analysis of an investor’s holdings and the market data indicate about the future direction of securities that investor may be interested in?
With these added capabilities, analytics suites can consolidate intelligence from inside and outside an investor’s portfolio. Incorporating social analysis into the analytics suite also helps brokerages meet another key demand of the retail investor: a socially integrated experience.
According to Celent’s 2015 report, The State of Online Brokerage Platforms:
“The digital revolution both within and outside the financial services industry has had a significant impact on consumers’ expectations. As a result, brokerage firms are dedicating considerable resources to the development of their digital strategies. Firms are using Facebook, Twitter, LinkedIn, and YouTube, among other social media sites, to inform and educate their online audience. Additionally, firms are building out robust online client communities where traders can connect and discuss a wide variety of topics relevant to trading. Social trading and social investing sites, where traders can connect with each other and mirror trades, are growing in popularity.”
All signs are pointing brokerages toward the need for comprehensive portfolio analytics, but in many cases, the cost of building and implementing a proprietary solution is a significant barrier to entry. With Scivantage’s Sqope solution, brokerages can deliver performance reporting, asset allocation and attribution, risk analysis, social analysis and data insights under the protection of their own brands. Sqope is a proven turnkey solution that taps into a range of key market trends and amplifies brokerages’ reinvention for the digital era.
For a demonstration of Sqope, see here.