Oxford Lane Capital Stock Alpha and Beta Analysis
| OXLCN Stock | USD 24.02 0.07 0.29% |
This module allows you to check different measures of market premium (i.e., alpha and beta) for all equities such as Oxford Lane Capital. It also helps investors analyze the systematic and unsystematic risks associated with investing in Oxford Lane over a specified time horizon. Remember, high Oxford Lane's alpha is almost always a sign of good performance; however, a high beta will depend on investors' risk tolerance level and may signal increased volatility and potential future overvaluation. Key technical indicators related to Oxford Lane's market risk premium analysis include:
Beta 0.16 | Alpha (0.01) | Risk 0.59 | Sharpe Ratio 0.0162 | Expected Return 0.0095 |
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Alpha is a measure of relative performance on a risk-adjusted basis, while beta measures volatility against the benchmark. The goal is to know if an investor is being compensated for the volatility risk taken. The return on investment might be better than its reference but still not compensate for the assumption of the risk.
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Oxford Lane Market Premiums
Investors always prefer to have the highest possible return on investment, coupled with the lowest possible volatility. Oxford Lane market risk premium is the additional return an investor will receive from holding Oxford Lane long position in a well-diversified portfolio. The market premium is part of the Capital Asset Pricing Model (CAPM), which most analysts and investors use to calculate the acceptable rate of return on investment in Oxford Lane. At the center of the CAPM is the concept of risk and reward, which is usually communicated by investors using alpha and beta measures. Alpha and beta are two of the key measurements used to evaluate Oxford Lane's performance over market.| α | -0.0093 | β | 0.16 |
Oxford Lane expected buy-and-hold returns
Although buy-and-hold investment strategy may not appeal to all investors, it may be used as a good measure of Oxford Lane's Buy-and-hold return. Our buy-and-hold chart shows how Oxford Lane performed over your current time horizon against a typical interest-earning bank account and a selected benchmark.Oxford Lane Market Price Analysis
Market price analysis indicators help investors to evaluate how Oxford Lane stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Oxford Lane shares will generate the highest return on investment. By understating and applying Oxford Lane stock market price indicators, traders can identify Oxford Lane position entry and exit signals to maximize returns.
Oxford Lane Return and Market Media
The median price of Oxford Lane for the period between Tue, Sep 24, 2024 and Mon, Dec 23, 2024 is 23.92 with a coefficient of variation of 0.58. The daily time series for the period is distributed with a sample standard deviation of 0.14, arithmetic mean of 23.93, and mean deviation of 0.11. The Stock received substential amount of media coverage during this period. Price Growth (%) |
| Timeline |
| Oxford Lane dividend paid on 30th of September 2024 | 09/30/2024 |
1 | Acquisition by Conroy Patrick of 10000 shares of Oxford Lane at 22.5 subject to Rule 16b-3 | 10/16/2024 |
2 | Oxford Lane Capital Corp. Sees Large Growth in Short Interest - MarketBeat | 10/28/2024 |
3 | Acquisition by Rosenthal Saul B of 4000 shares of Oxford Lane at 15.0 subject to Rule 16b-3 | 10/30/2024 |
| Oxford Lane dividend paid on 31st of October 2024 | 10/31/2024 |
4 | Oxford Lane Capital reports Q3 results | 11/01/2024 |
5 | Q2 2025 Oxford Lane Capital Corp Earnings Call Transcript | 11/04/2024 |
6 | Oxford Lane Capital Corp. Short Interest Down 47.1 percent in October | 11/14/2024 |
7 | Oxford Lane Capital Corp. to Issue Monthly Dividend of 0.13 on January 31st | 11/15/2024 |
| Oxford Lane dividend paid on 29th of November 2024 | 11/29/2024 |
8 | Oxford Lane Capital estimates November NAV per share rose 0.4 percent MM | 12/10/2024 |
About Oxford Lane Beta and Alpha
For many years both, Alpha and Beta indicators are used by professional money managers as critical performance measurement tools across virtually all financial instruments including Oxford or other stocks. Alpha measures the amount that position in Oxford Lane Capital has returned in comparison to a selected market index or another relevant benchmark. In other words, Alpha is the excess return on an investment relative to the performance of your selected benchmark. Beta, on the other hand, measures the relative risk of your investment.
| 2021 | 2024 (projected) | PTB Ratio | 0.8 | 0.86 | Dividend Yield | 0.11 | 0.12 |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Oxford Lane in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Oxford Lane's short interest history, or implied volatility extrapolated from Oxford Lane options trading.
Build Portfolio with Oxford Lane
Your optimized portfolios are the building block of your wealth. We provide an intuitive interface to determine which securities in a portfolio should be removed or rebalanced to achieve better diversification, find the right mix of securities that minimizes portfolio risk for a given return, or maximize portfolio expected return for a given risk level.Build Diversified Portfolios
Align your risk with return expectations
Check out Oxford Lane Backtesting, Oxford Lane Valuation, Oxford Lane Correlation, Oxford Lane Hype Analysis, Oxford Lane Volatility, Oxford Lane History and analyze Oxford Lane Performance. You can also try the Fundamentals Comparison module to compare fundamentals across multiple equities to find investing opportunities.
Oxford Lane technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.