Texas Investment Network


Recent Blog


Pitching Help Desk


Testimonials

"We have already had one investor for $25K, and another who is very involved in the food business, who could be a funder on a much larger level. So we are very pleased, and offer our thanks."
Bruce J.

 BLOG >> Definitions

Business Terminology [Definitions
Posted on March 29, 2021 @ 03:37:00 PM by Paul Meagher

In today's blog I want to define some terms used in finance and investing that I think are worth knowing. I hope to make a habit of devoting future blogs to defining useful business terms. Some terms in finance and investing are "mind tools" that can help us think more clearly about certain business problems. Just like farmers have invented tools to make farming easier, academic and practicing business people have created business terms that make thinking about business problems easier. Here are some terms to start with.

Loan To Value (LTV): Loan to value is a ratio (L / V). It is the ratio of the amount of loan L used to acquire an asset to the assessed value of an asset V. Lenders may specify an LTV of say 70% meaning they will only loan up to 70 percent of the value of the asset. So, for a house assessed at $100,000, the maximum loan the lender will provide is $70,000. The portion the buyer is expected to pay is sometimes called "the haircut" (in this example 30% or $30,000) . The higher the LTV value on a loan, the riskier the loan is. Different lenders may offer different LTV rates and some may originate riskier loans. One of the factors that led to the economic crisis of 2008 was that mortgage originators were offering loans with high LTV's. In Investopedia's article The Fuel That Fed The Subprime Meltdown they describe what happened to LTV rates:

As a result of this activity, it became very profitable to originate mortgages—even risky ones. It wasn't long before even basic requirements like proof of income and a down payment were being overlooked by mortgage lenders; 125% loan-to-value mortgages were being underwritten and given to prospective homeowners. The logic being that with real estate prices rising so fast (median home prices were rising as much as 14% annually by 2005), a 125% LTV mortgage would be above water in less than two years.

Time Under Water: Measures how long it takes for some measure of business performance to return after it goes down in value. If you made, say, 50,000 in February of 2020 but your revenues took a hit as a result of COVID, then you could measure how long it takes to get back to making 50k a month again. The time under water would be the number of months it takes to get back to making 50k a month again. The time under water could be measured in days or years depending on the context. Many small businesses are continuing to spend time under water as a result of the pandemic. If you were making, say, 50k per month before the pandemic and then your revenue dropped to 10k per month, that drop of 40k would be the drawdown amount. If it was the largest drop in revenue you have ever experienced, then it would be the maximum drawdown, and your recovery back to making 50k a month again would be time spent deep underwater. When assessing the risk associated with different stock market investments, you might measure the average time under water and maximum drawdown of different stocks to create a risk profile for them.


Source: Optimal Portfolios with Traditional and Alternative Investments: An Empirical Investigation

It might be worth noting that if you are in the situation of having a mortgage loan where the value of the loan is greater then the value of the house, then your loan is said to be under water.

Arbitrage: An arbitrage opportunity arises when there is the possibility of buying something for a low price in one market and selling it for a higher price in another market. A stock that is priced lower in one stock exchange, for example, can be exploited by quickly buying up stock on the lower priced exchange and selling it on the higher priced exchange. Hedge funds will often use leverage to buy large quantities of shares to make it worth their while to make these arbitrage trades. The difference in price between the two markets is the gross profit. There are transaction costs in executing a trade which may wipe out the profits if you are not careful. Retail arbitrage involves buying items in one retail environment at a low price and selling it in another retail environment at a higher price. Some Amazon sellers, for example, use retail arbitrage to make money on the items they buy on clearance at Walmart and sell on Amazon. An example of arbitrage in rural areas might involve a store owner buying retail items in a larger big box store and selling them at a higher price in a rural general store.

Permalink 

 Archive 
 

Archive


 November 2023 [1]
 June 2023 [1]
 May 2023 [1]
 April 2023 [1]
 March 2023 [6]
 February 2023 [1]
 November 2022 [2]
 October 2022 [2]
 August 2022 [2]
 May 2022 [2]
 April 2022 [4]
 March 2022 [1]
 February 2022 [1]
 January 2022 [2]
 December 2021 [1]
 November 2021 [2]
 October 2021 [1]
 July 2021 [1]
 June 2021 [1]
 May 2021 [3]
 April 2021 [3]
 March 2021 [4]
 February 2021 [1]
 January 2021 [1]
 December 2020 [2]
 November 2020 [1]
 August 2020 [1]
 June 2020 [4]
 May 2020 [1]
 April 2020 [2]
 March 2020 [2]
 February 2020 [1]
 January 2020 [2]
 December 2019 [1]
 November 2019 [2]
 October 2019 [2]
 September 2019 [1]
 July 2019 [1]
 June 2019 [2]
 May 2019 [3]
 April 2019 [5]
 March 2019 [4]
 February 2019 [3]
 January 2019 [3]
 December 2018 [4]
 November 2018 [2]
 September 2018 [2]
 August 2018 [1]
 July 2018 [1]
 June 2018 [1]
 May 2018 [5]
 April 2018 [4]
 March 2018 [2]
 February 2018 [4]
 January 2018 [4]
 December 2017 [2]
 November 2017 [6]
 October 2017 [6]
 September 2017 [6]
 August 2017 [2]
 July 2017 [2]
 June 2017 [5]
 May 2017 [7]
 April 2017 [6]
 March 2017 [8]
 February 2017 [7]
 January 2017 [9]
 December 2016 [7]
 November 2016 [7]
 October 2016 [5]
 September 2016 [5]
 August 2016 [4]
 July 2016 [6]
 June 2016 [5]
 May 2016 [10]
 April 2016 [12]
 March 2016 [10]
 February 2016 [11]
 January 2016 [12]
 December 2015 [6]
 November 2015 [8]
 October 2015 [12]
 September 2015 [10]
 August 2015 [14]
 July 2015 [9]
 June 2015 [9]
 May 2015 [10]
 April 2015 [9]
 March 2015 [8]
 February 2015 [8]
 January 2015 [5]
 December 2014 [11]
 November 2014 [10]
 October 2014 [10]
 September 2014 [8]
 August 2014 [7]
 July 2014 [5]
 June 2014 [7]
 May 2014 [6]
 April 2014 [3]
 March 2014 [8]
 February 2014 [6]
 January 2014 [5]
 December 2013 [5]
 November 2013 [3]
 October 2013 [4]
 September 2013 [11]
 August 2013 [4]
 July 2013 [8]
 June 2013 [10]
 May 2013 [14]
 April 2013 [12]
 March 2013 [11]
 February 2013 [19]
 January 2013 [20]
 December 2012 [5]
 November 2012 [1]
 October 2012 [3]
 September 2012 [1]
 August 2012 [1]
 July 2012 [1]
 June 2012 [2]


Categories


 Agriculture [77]
 Bayesian Inference [14]
 Books [18]
 Business Models [24]
 Causal Inference [2]
 Creativity [7]
 Decision Making [17]
 Decision Trees [8]
 Definitions [1]
 Design [38]
 Eco-Green [4]
 Economics [14]
 Education [10]
 Energy [0]
 Entrepreneurship [74]
 Events [7]
 Farming [21]
 Finance [30]
 Future [15]
 Growth [19]
 Investing [25]
 Lean Startup [10]
 Leisure [5]
 Lens Model [9]
 Making [1]
 Management [12]
 Motivation [3]
 Nature [22]
 Patents & Trademarks [1]
 Permaculture [36]
 Psychology [2]
 Real Estate [5]
 Robots [1]
 Selling [12]
 Site News [17]
 Startups [12]
 Statistics [3]
 Systems Thinking [3]
 Trends [11]
 Useful Links [3]
 Valuation [1]
 Venture Capital [5]
 Video [2]
 Writing [2]