Earlier this month Metonymy Labs’ announced their alliance with Fulbrook Capital Management, a global leader in Dispute Finance. It is a major step and of course surely the sign of things to come. With the rise of big data and AI in other industries especially financial sectors, it is the logical weapon of choice for these large firms.
Many feel that the industry is lagging behind in its adoption of technology and data analytics.
‘The litigation finance market is presently making very limited use of data analytics. The industry is at the same stage of sophistication that banks were at in the 1950s — data is gathered, but it is rarely used effectively.’ – Michael McDonald PHD
Michael goes on to elaborate on this point. He feels that regression analysis for pricing is non-existent, risk management tools like VAR or modified convexity don’t exist and there is no Black-Scholes equivalent. He also feels staff awareness of these tools is insufficient.
If those terms are unfamiliar here is a breakdown of what they mean.
1. Regression analysis for pricing. An explanation:
Imagine you’re a sales manager being asked to predict next month’s sales. There are dozens, perhaps even hundreds of factors from the weather to a competitor’s promotion that could impact your sales. Regression analysis is a way of mathematically deciding which of those variables does indeed have an impact. It answers the questions: Which factors matter most? Which can we ignore? How do those factors interact with each other? And, perhaps most importantly, how certain are we about all of these factors?
In regression analysis, these factors are called variables. In regression analysis, you always have a dependent variable and independent variables. Continuing the example above your dependent variable is sales. The independent variable are the factors you suspect have an impact on your dependent variable.
Harvard have an excellent piece that goes into more depth. The explanation above is just to provide some context.
2. Risk management tools like VAR or modified convexity.
VAR: stands for Value At Risk. It estimates how much a set of investments might lose, given normal market conditions, in a set time period such as a day. VAR is typically used by firms and regulators in the financial industry to gauge the amount of assets needed to cover possible losses.
Modified Convexity: Measures the curvature of an instrument’s or a portfolio’s price function, as yields change – from a given starting point – by a small amount. More strictly, it is the rate of change of modified duration with respect to yield – at the given starting yield.
3. Black-Scholes model.
The Black-Scholes model, also known as the Black-Scholes-Merton model, is a model of price variation over time of financial instruments such as stocks that can, among other things, be used to determine the price of a call option. The model assumes the price of heavily traded assets follows a geometric Brownian motion with constant drift and volatility. When applied to a stock option, the model incorporates the constant price variation of the stock, the time value of money, the option’s strike price and the time to the option’s expiry.
The point being that the more data and analytics are deployed against this asset the more predictable returns will become.
Michael McDonald PhD uses the example of investing in startup businesses. Angel investing has been around for years and was very simple. High net worth individuals would deploy capital against a fledgeling firm in the hope it succeeds and delivers a big return. The venture capital ate this market but approaching it in an analytical manner.
This is something Eva Shang of LegalList has been exploring for some time. This algorithmic approach stems from the startup’s original idea. Shang and her co-founder Christian Haigh, both undergraduates at Harvard, were building a database and analytical service for lawyers. TechCrunch dubbed Legalist, “Google for state court records.”
Now LegalList are leveraging this data to make investment decisions. LegalList are also backed by YCombinator and have received a fellowship grant from Peter Thiel. Thiel backed Hulk Hogan in his suit against Gawker Media
More interesting developments to come.
 http://abovethelaw.com/2017/02/fulbrook-using-big-data-to-get-ahead-in-litigation-finance/?rf=1  https://www.linkedin.com/pulse/metonymy-labs-alliance-leader-dispute-finance-kripa-rajshekhar  https://hbr.org/2015/11/a-refresher-on-regression-analysis  https://wiki.treasurers.org/wiki/Modified_convexity  https://en.wikipedia.org/wiki/Value_at_risk  http://www.investopedia.com/terms/b/blackscholes.asp#ixzz4ZPxLEPRb  http://mashable.com/2016/08/24/legalist-startup-lawsuit/#oEDH8.2t9qq6